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1.  Subtyping of Breast Cancer by Immunohistochemistry to Investigate a Relationship between Subtype and Short and Long Term Survival: A Collaborative Analysis of Data for 10,159 Cases from 12 Studies 
PLoS Medicine  2010;7(5):e1000279.
Paul Pharoah and colleagues evaluate the prognostic significance of immunohistochemical subtype classification in more than 10,000 breast cancer cases with early disease, and examine the influence of a patient's survival time on the prediction of future survival.
Background
Immunohistochemical markers are often used to classify breast cancer into subtypes that are biologically distinct and behave differently. The aim of this study was to estimate mortality for patients with the major subtypes of breast cancer as classified using five immunohistochemical markers, to investigate patterns of mortality over time, and to test for heterogeneity by subtype.
Methods and Findings
We pooled data from more than 10,000 cases of invasive breast cancer from 12 studies that had collected information on hormone receptor status, human epidermal growth factor receptor-2 (HER2) status, and at least one basal marker (cytokeratin [CK]5/6 or epidermal growth factor receptor [EGFR]) together with survival time data. Tumours were classified as luminal and nonluminal tumours according to hormone receptor expression. These two groups were further subdivided according to expression of HER2, and finally, the luminal and nonluminal HER2-negative tumours were categorised according to expression of basal markers. Changes in mortality rates over time differed by subtype. In women with luminal HER2-negative subtypes, mortality rates were constant over time, whereas mortality rates associated with the luminal HER2-positive and nonluminal subtypes tended to peak within 5 y of diagnosis and then decline over time. In the first 5 y after diagnosis the nonluminal tumours were associated with a poorer prognosis, but over longer follow-up times the prognosis was poorer in the luminal subtypes, with the worst prognosis at 15 y being in the luminal HER2-positive tumours. Basal marker expression distinguished the HER2-negative luminal and nonluminal tumours into different subtypes. These patterns were independent of any systemic adjuvant therapy.
Conclusions
The six subtypes of breast cancer defined by expression of five markers show distinct behaviours with important differences in short term and long term prognosis. Application of these markers in the clinical setting could have the potential to improve the targeting of adjuvant chemotherapy to those most likely to benefit. The different patterns of mortality over time also suggest important biological differences between the subtypes that may result in differences in response to specific therapies, and that stratification of breast cancers by clinically relevant subtypes in clinical trials is urgently required.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Each year, more than one million women discover they have breast cancer. Breast cancer begins when cells in the breast's milk-producing glands or in the tubes (ducts) that take milk to the nipples acquire genetic changes that allow them to divide uncontrollably and to move around the body (metastasize). The uncontrolled cell division leads to the formation of a lump that can be detected by mammography (a breast X-ray) or by manual breast examination. Breast cancer is treated by surgical removal of the lump or, if the cancer has started to spread, by removal of the whole breast (mastectomy). Surgery is usually followed by radiotherapy or chemotherapy. These “adjuvant” therapies are designed to kill any remaining cancer cells but can make women very ill. Generally speaking, the outlook (prognosis) for women with breast cancer is good. In the United States, for example, nearly 90% of affected women are still alive five years after their diagnosis.
Why Was This Study Done?
Because there are several types of cells in the milk ducts and glands, there are several subtypes of breast cancer. Luminal tumors, for example, begin in the cells that line the ducts and glands and usually grow slowly; basal-type tumors arise in deeper layers of the ducts and glands and tend to grow quickly. Clinicians need to distinguish between different breast cancer subtypes so that they can give women a realistic prognosis and can give adjuvant treatments to those women who are most likely to benefit. One way to distinguish between different subtypes is to stain breast cancer samples using antibodies (immune system proteins) that recognize particular proteins (antigens). This “immunohistochemical” approach can identify several breast cancer subtypes but its prognostic value and the best way to classify breast tumors remains unclear. In this study, the researchers investigate the survival over time of women with six major subtypes of breast cancer classified using five immunohistochemical markers: the estrogen receptor and the progesterone receptor (two hormone receptors expressed by luminal cells), the human epidermal growth factors receptor-2 (HER2, a protein marker used to select specific adjuvant therapies), and CK5/6 and EGFR (proteins expressed by basal cells).
What Did the Researchers Do and Find?
The researchers pooled data on survival time and on the expression of the five immunohistochemical markers from more than 10,000 cases of breast cancer from 12 studies. They then divided the tumors into six subtypes on the basis of their marker expression: luminal (hormone receptor-positive), HER2-positive tumors; luminal, HER2-negative, basal marker-positive tumors; luminal, HER2-negative, basal marker-negative tumors; nonluminal (hormone receptor-negative), HER2-positive tumors; nonluminal, HER2-negative, basal marker-positive tumors; and nonluminal, HER2-negative, basal marker-negative tumors. In the first five years after diagnosis, women with nonluminal tumor subtypes had the worst prognosis but at 15 years after diagnosis, women with luminal HER2-positive tumors had the worst prognosis. Furthermore, death rates (the percentage of affected women dying each year) differed by subtype over time. Thus, women with the two luminal HER2-negative subtypes were as likely to die soon after diagnosis as at later times whereas the death rates associated with nonluminal subtypes peaked within five years of diagnosis and then declined.
What Do These Findings Mean?
These and other findings indicate that the six subtypes of breast cancer defined by the expression of five immunohistochemical markers have distinct biological characteristics that are associated with important differences in short-term and long-term outcomes. Because different laboratories measured the immunohistochemical markers using different methods, it is possible that some of the tumors included in this study were misclassified. However, the finding of clear differences in the behavior of the immunochemically classified subtypes suggests that the use of the five markers for tumor classification might be robust enough for routine clinical practice. The application of these markers in the clinical setting, suggest the researchers, could improve the targeting of adjuvant therapies to those women most likely to benefit. Furthermore, note the researchers, these findings strongly suggest that subtype-specific responses should be evaluated in future clinical trials of treatments for breast cancer.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000279.
This study is further discussed in a PLoS Medicine Perspective by Stefan Ambs
The US National Cancer Institute provides detailed information for patients and health professionals on all aspects of breast cancer (in English and Spanish)
The American Cancer Society has a detailed guide to breast cancer, which includes information on the immunochemical classification of breast cancer subtypes
The UK charities MacMillan Cancer Support and Cancer Research UK also provide detailed information about breast cancer
The MedlinePlus Encyclopedia provides information for patients about breast cancer; Medline Plus provides links to many other breast cancer resources (in English and Spanish)
doi:10.1371/journal.pmed.1000279
PMCID: PMC2876119  PMID: 20520800
2.  DEAR1 Is a Dominant Regulator of Acinar Morphogenesis and an Independent Predictor of Local Recurrence-Free Survival in Early-Onset Breast Cancer 
PLoS Medicine  2009;6(5):e1000068.
Ann Killary and colleagues describe a new gene that is genetically altered in breast tumors, and that may provide a new breast cancer prognostic marker.
Background
Breast cancer in young women tends to have a natural history of aggressive disease for which rates of recurrence are higher than in breast cancers detected later in life. Little is known about the genetic pathways that underlie early-onset breast cancer. Here we report the discovery of DEAR1 (ductal epithelium–associated RING Chromosome 1), a novel gene encoding a member of the TRIM (tripartite motif) subfamily of RING finger proteins, and provide evidence for its role as a dominant regulator of acinar morphogenesis in the mammary gland and as an independent predictor of local recurrence-free survival in early-onset breast cancer.
Methods and Findings
Suppression subtractive hybridization identified DEAR1 as a novel gene mapping to a region of high-frequency loss of heterozygosity (LOH) in a number of histologically diverse human cancers within Chromosome 1p35.1. In the breast epithelium, DEAR1 expression is limited to the ductal and glandular epithelium and is down-regulated in transition to ductal carcinoma in situ (DCIS), an early histologic stage in breast tumorigenesis. DEAR1 missense mutations and homozygous deletion (HD) were discovered in breast cancer cell lines and tumor samples. Introduction of the DEAR1 wild type and not the missense mutant alleles to complement a mutation in a breast cancer cell line, derived from a 36-year-old female with invasive breast cancer, initiated acinar morphogenesis in three-dimensional (3D) basement membrane culture and restored tissue architecture reminiscent of normal acinar structures in the mammary gland in vivo. Stable knockdown of DEAR1 in immortalized human mammary epithelial cells (HMECs) recapitulated the growth in 3D culture of breast cancer cell lines containing mutated DEAR1, in that shDEAR1 clones demonstrated disruption of tissue architecture, loss of apical basal polarity, diffuse apoptosis, and failure of lumen formation. Furthermore, immunohistochemical staining of a tissue microarray from a cohort of 123 young female breast cancer patients with a 20-year follow-up indicated that in early-onset breast cancer, DEAR1 expression serves as an independent predictor of local recurrence-free survival and correlates significantly with strong family history of breast cancer and the triple-negative phenotype (ER−, PR−, HER-2−) of breast cancers with poor prognosis.
Conclusions
Our data provide compelling evidence for the genetic alteration and loss of expression of DEAR1 in breast cancer, for the functional role of DEAR1 in the dominant regulation of acinar morphogenesis in 3D culture, and for the potential utility of an immunohistochemical assay for DEAR1 expression as an independent prognostic marker for stratification of early-onset disease.
Editors' Summary
Background
Each year, more than one million women discover that they have breast cancer. This type of cancer begins when cells in the breast that line the milk-producing glands or the tubes that take the milk to the nipples (glandular and ductal epithelial cells, respectively) acquire genetic changes that allow them to grow uncontrollably and to move around the body (metastasize). The uncontrolled division leads to the formation of a lump that can be detected by mammography (a breast X-ray) or by manual breast examination. Breast cancer is treated by surgical removal of the lump or, if the cancer has started to spread, by removal of the whole breast (mastectomy). Surgery is usually followed by radiotherapy or chemotherapy. These “adjuvant” therapies are designed to kill any remaining cancer cells but can make patients very ill. Generally speaking, the outlook for women with breast cancer is good. In the US, for example, nearly 90% of affected women are still alive five years after their diagnosis.
Why Was This Study Done?
Although breast cancer is usually diagnosed in women in their 50s or 60s, some women develop breast cancer much earlier. In these women, the disease is often very aggressive. Compared to older women, young women with breast cancer have a lower overall survival rate and their cancer is more likely to recur locally or to metastasize. It would be useful to be able to recognize those younger women at the greatest risk of cancer recurrence so that they could be offered intensive surveillance and adjuvant therapy; those women at a lower risk could have gentler treatments. To achieve this type of “stratification,” the genetic changes that underlie breast cancer in young women need to be identified. In this study, the researchers discover a gene that is genetically altered (by mutations or deletion) in early-onset breast cancer and then investigate whether its expression can predict outcomes in women with this disease.
What Did the Researchers Do and Find?
The researchers used “suppression subtractive hybridization” to identify a new gene in a region of human Chromosome 1 where loss of heterozygosity (LOH; a genetic alteration associated with cancer development) frequently occurs. They called the gene DEAR1 (ductal epithelium-associated RING Chromosome 1) to indicate that it is expressed in ductal and glandular epithelial cells and encodes a “RING finger” protein (specifically, a subtype called a TRIM protein; RING finger proteins such as BRCA1 and BRCA2 have been implicated in early cancer development and in a large fraction of inherited breast cancers). DEAR1 expression was reduced or lost in several ductal carcinomas in situ (a local abnormality that can develop into breast cancer) and advanced breast cancers, the researchers report. Furthermore, many breast tumors carried DEAR1 missense mutations (genetic changes that interfere with the normal function of the DEAR1 protein) or had lost both copies of DEAR1 (the human genome contains two copies of most genes). To determine the function of DEAR1, the researchers replaced a normal copy of DEAR1 into a breast cancer cell that had a mutation in DEAR1. They then examined the growth of these genetically manipulated cells in special three-dimensional cultures. The breast cancer cells without DEAR1 grew rapidly without an organized structure while the breast cancer cells containing the introduced copy of DEAR1 formed structures that resembled normal breast acini (sac-like structures that secrete milk). In normal human mammary epithelial cells, the researchers silenced DEAR1 expression and also showed that without DEAR1, the normal mammary cells lost their ability to form proper acini. Finally, the researchers report that DEAR1 expression (detected “immunohistochemically”) was frequently lost in women who had had early-onset breast cancer and that the loss of DEAR1 expression correlated with reduced local recurrence-free survival, a strong family history of breast cancer and with a breast cancer subtype that has a poor outcome.
What Do These Findings Mean?
These findings indicate that genetic alteration and loss of expression of DEAR1 are common in breast cancer. Although laboratory experiments may not necessarily reflect what happens in people, the results from the three-dimensional culture of breast epithelial cells suggest that DEAR1 may regulate the normal acinar structure of the breast. Consequently, loss of DEAR1 expression could be an early event in breast cancer development. Most importantly, the correlation between DEAR1 expression and both local recurrence in early-onset breast cancer and a breast cancer subtype with a poor outcome suggests that it might be possible to use DEAR1 expression to identify women with early-onset breast cancer who have an increased risk of local recurrence so that they get the most appropriate treatment for their cancer.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000068.
This study is further discussed in a PLoS Medicine Perspective by Senthil Muthuswamy
The US National Cancer Institute provides detailed information for patients and health professionals on all aspects of breast cancer, including information on genetic alterations in breast cancer (in English and Spanish)
The MedlinePlus Encyclopedia provides information for patients about breast cancer; MedlinePlus also provides links to many other breast cancer resources (in English and Spanish)
The UK charities Cancerbackup (now merged with MacMillan Cancer Support) and Cancer Research UK also provide detailed information about breast cancer
doi:10.1371/journal.pmed.1000068
PMCID: PMC2673042  PMID: 19536326
3.  Risk Prediction for Breast, Endometrial, and Ovarian Cancer in White Women Aged 50 y or Older: Derivation and Validation from Population-Based Cohort Studies 
PLoS Medicine  2013;10(7):e1001492.
Ruth Pfeiffer and colleagues describe models to calculate absolute risks for breast, endometrial, and ovarian cancers for white, non-Hispanic women over 50 years old using easily obtainable risk factors.
Please see later in the article for the Editors' Summary
Background
Breast, endometrial, and ovarian cancers share some hormonal and epidemiologic risk factors. While several models predict absolute risk of breast cancer, there are few models for ovarian cancer in the general population, and none for endometrial cancer.
Methods and Findings
Using data on white, non-Hispanic women aged 50+ y from two large population-based cohorts (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial [PLCO] and the National Institutes of Health–AARP Diet and Health Study [NIH-AARP]), we estimated relative and attributable risks and combined them with age-specific US-population incidence and competing mortality rates. All models included parity. The breast cancer model additionally included estrogen and progestin menopausal hormone therapy (MHT) use, other MHT use, age at first live birth, menopausal status, age at menopause, family history of breast or ovarian cancer, benign breast disease/biopsies, alcohol consumption, and body mass index (BMI); the endometrial model included menopausal status, age at menopause, BMI, smoking, oral contraceptive use, MHT use, and an interaction term between BMI and MHT use; the ovarian model included oral contraceptive use, MHT use, and family history or breast or ovarian cancer. In independent validation data (Nurses' Health Study cohort) the breast and ovarian cancer models were well calibrated; expected to observed cancer ratios were 1.00 (95% confidence interval [CI]: 0.96–1.04) for breast cancer and 1.08 (95% CI: 0.97–1.19) for ovarian cancer. The number of endometrial cancers was significantly overestimated, expected/observed = 1.20 (95% CI: 1.11–1.29). The areas under the receiver operating characteristic curves (AUCs; discriminatory power) were 0.58 (95% CI: 0.57–0.59), 0.59 (95% CI: 0.56–0.63), and 0.68 (95% CI: 0.66–0.70) for the breast, ovarian, and endometrial models, respectively.
Conclusions
These models predict absolute risks for breast, endometrial, and ovarian cancers from easily obtainable risk factors and may assist in clinical decision-making. Limitations are the modest discriminatory ability of the breast and ovarian models and that these models may not generalize to women of other races.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In 2008, just three types of cancer accounted for 10% of global cancer-related deaths. That year, about 460,000 women died from breast cancer (the most frequently diagnosed cancer among women and the fifth most common cause of cancer-related death). Another 140,000 women died from ovarian cancer, and 74,000 died from endometrial (womb) cancer (the 14th and 20th most common causes of cancer-related death, respectively). Although these three cancers originate in different tissues, they nevertheless share many risk factors. For example, current age, age at menarche (first period), and parity (the number of children a woman has had) are all strongly associated with breast, ovarian, and endometrial cancer risk. Because these cancers share many hormonal and epidemiological risk factors, a woman with a high breast cancer risk is also likely to have an above-average risk of developing ovarian or endometrial cancer.
Why Was This Study Done?
Several statistical models (for example, the Breast Cancer Risk Assessment Tool) have been developed that estimate a woman's absolute risk (probability) of developing breast cancer over the next few years or over her lifetime. Absolute risk prediction models are useful in the design of cancer prevention trials and can also help women make informed decisions about cancer prevention and treatment options. For example, a woman at high risk of breast cancer might decide to take tamoxifen for breast cancer prevention, but ideally she needs to know her absolute endometrial cancer risk before doing so because tamoxifen increases the risk of this cancer. Similarly, knowledge of her ovarian cancer risk might influence a woman's decision regarding prophylactic removal of her ovaries to reduce her breast cancer risk. There are few absolute risk prediction models for ovarian cancer, and none for endometrial cancer, so here the researchers develop models to predict the risk of these cancers and of breast cancer.
What Did the Researchers Do and Find?
Absolute risk prediction models are constructed by combining estimates for risk factors from cohorts with population-based incidence rates from cancer registries. Models are validated in an independent cohort by testing their ability to identify people with the disease in an independent cohort and their ability to predict the observed numbers of incident cases. The researchers used data on white, non-Hispanic women aged 50 years or older that were collected during two large prospective US cohort studies of cancer screening and of diet and health, and US cancer incidence and mortality rates provided by the Surveillance, Epidemiology, and End Results Program to build their models. The models all included parity as a risk factor, as well as other factors. The model for endometrial cancer, for example, also included menopausal status, age at menopause, body mass index (an indicator of the amount of body fat), oral contraceptive use, menopausal hormone therapy use, and an interaction term between menopausal hormone therapy use and body mass index. Individual women's risk for endometrial cancer calculated using this model ranged from 1.22% to 17.8% over the next 20 years depending on their exposure to various risk factors. Validation of the models using data from the US Nurses' Health Study indicated that the endometrial cancer model overestimated the risk of endometrial cancer but that the breast and ovarian cancer models were well calibrated—the predicted and observed risks for these cancers in the validation cohort agreed closely. Finally, the discriminatory power of the models (a measure of how well a model separates people who have a disease from people who do not have the disease) was modest for the breast and ovarian cancer models but somewhat better for the endometrial cancer model.
What Do These Findings Mean?
These findings show that breast, ovarian, and endometrial cancer can all be predicted using information on known risk factors for these cancers that is easily obtainable. Because these models were constructed and validated using data from white, non-Hispanic women aged 50 years or older, they may not accurately predict absolute risk for these cancers for women of other races or ethnicities. Moreover, the modest discriminatory power of the breast and ovarian cancer models means they cannot be used to decide which women should be routinely screened for these cancers. Importantly, however, these well-calibrated models should provide realistic information about an individual's risk of developing breast, ovarian, or endometrial cancer that can be used in clinical decision-making and that may assist in the identification of potential participants for research studies.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001492.
This study is further discussed in a PLOS Medicine Perspective by Lars Holmberg and Andrew Vickers
The US National Cancer Institute provides comprehensive information about cancer (in English and Spanish), including detailed information about breast cancer, ovarian cancer, and endometrial cancer;
Information on the Breast Cancer Risk Assessment Tool, the Surveillance, Epidemiology, and End Results Program, and on the prospective cohort study of screening and the diet and health study that provided the data used to build the models is also available on the NCI site
Cancer Research UK, a not-for-profit organization, provides information about cancer, including detailed information on breast cancer, ovarian cancer, and endometrial cancer
The UK National Health Service Choices website has information and personal stories about breast cancer, ovarian cancer, and endometrial cancer; the not-for-profit organization Healthtalkonline also provides personal stories about dealing with breast cancer and ovarian cancer
doi:10.1371/journal.pmed.1001492
PMCID: PMC3728034  PMID: 23935463
4.  Breast Cancer DNA Methylation Profiles Are Associated with Tumor Size and Alcohol and Folate Intake 
PLoS Genetics  2010;6(7):e1001043.
Although tumor size and lymph node involvement are the current cornerstones of breast cancer prognosis, they have not been extensively explored in relation to tumor methylation attributes in conjunction with other tumor and patient dietary and hormonal characteristics. Using primary breast tumors from 162 (AJCC stage I–IV) women from the Kaiser Division of Research Pathways Study and the Illumina GoldenGate methylation bead-array platform, we measured 1,413 autosomal CpG loci associated with 773 cancer-related genes and validated select CpG loci with Sequenom EpiTYPER. Tumor grade, size, estrogen and progesterone receptor status, and triple negative status were significantly (Q-values <0.05) associated with altered methylation of 209, 74, 183, 69, and 130 loci, respectively. Unsupervised clustering, using a recursively partitioned mixture model (RPMM), of all autosomal CpG loci revealed eight distinct methylation classes. Methylation class membership was significantly associated with patient race (P<0.02) and tumor size (P<0.001) in univariate tests. Using multinomial logistic regression to adjust for potential confounders, patient age and tumor size, as well as known disease risk factors of alcohol intake and total dietary folate, were all significantly (P<0.0001) associated with methylation class membership. Breast cancer prognostic characteristics and risk-related exposures appear to be associated with gene-specific tumor methylation, as well as overall methylation patterns.
Author Summary
The current standard prognostic indicator for breast cancer is tumor-node-metastasis staging; though, as population-based studies and clinical trials are conducted, molecular characterization of disease is beginning to allow improved markers of prognosis and assist clinicians in choosing the most appropriate therapies. We investigated DNA methylation profiles in over 160 well annotated breast tumor samples and found significant relationships with standard and other known predictors of prognosis, as well as established risk factors for disease: alcohol intake and dietary folate. Recently the United States National Cancer Institute Cancer Biomarkers Research Group articulated a need for a “Strategic Approach to Validating Methylated Genes as Biomarkers for Breast Cancer,” and our work is extremely responsive to this call for a national strategy. Recognizing the increasing use of pre-operative chemotherapy for patients with operable, early-stage disease, there is added complexity in breast cancer staging. Since chemotherapy can considerably decrease tumor size, it is still unclear whether pre-operative or post-operative stage best informs prognosis and treatment decisions for patients electing pre-operative chemotherapy. However, our data clearly illustrate the promise of tumor DNA methylation for augmenting tumor staging and can be attained with minimal tissue in a pre-operative context.
doi:10.1371/journal.pgen.1001043
PMCID: PMC2912395  PMID: 20686660
5.  WSG ADAPT – adjuvant dynamic marker-adjusted personalized therapy trial optimizing risk assessment and therapy response prediction in early breast cancer: study protocol for a prospective, multi-center, controlled, non-blinded, randomized, investigator initiated phase II/III trial 
Trials  2013;14:261.
Background
Adjuvant treatment decision-making based on conventional clinical/pathological and prognostic single molecular markers or genomic signatures is a therapeutic area in which over-/under-treatment are still key clinical problems even though substantial and continuous improvement of outcome has been achieved over the past decades. Response to therapy is currently not considered in the decision-making procedure.
ADAPT is one of the first new generation (neo)adjuvant trials dealing with individualization of (neo)adjuvant decision-making in early breast cancer and aims to establish early predictive surrogate markers, e.g., Ki-67, for therapy response under a short induction treatment in order to maximally individualize therapy and avoid unnecessary toxicity by ineffective treatment.
Methods/design
The prospective, multi-center, controlled, non-blinded, randomized, investigator initiated phase II/III ADAPT trial has an innovative “umbrella” protocol design. The “umbrella” is common for all patients, consisting of dynamic testing of early therapy response. ADAPT will recruit 4,936 patients according to their respective breast cancer subtype in four distinct sub-trials at 80 trial sites in Germany; 4,000 patients with hormone receptor positive (HR+) and HER2 negative disease will be included in the ADAPT HR+/HER2- sub-trial, where treatment decision is based on risk assessment and therapy response to induction therapy, and 380 patients will be included in ADAPT HER2+/HR+. A further 220 patients will be included in ADAPT HER2+/HR- and 336 patients will be recruited for ADAPT Triple Negative. These three sub-trials focus on identification of early surrogate markers for therapy success in the neoadjuvant setting. Patients will be allocated to the respective sub-trial according to the result of their diagnostic core biopsy, as reported by local/central pathology for HR and HER2 status.
Discussion
Recent trials, such as the GeparTrio, have shown that response-guided therapy using clinical response may improve outcome. For chemotherapy or HER2-targeted treatment, pathologic complete response in a neoadjuvant setting is an excellent predictor of outcome. For endocrine therapy, response to short induction treatment – as defined by decrease in tumor cell proliferation – strongly correlates with outcome. ADAPT now aims to combine static prognostic and dynamic predictive markers, focusing not just on single therapeutic targets, but also on general markers of proliferation and cell death. Biomarker analysis will help to optimize selection of subtype-specific treatment.
Trial registration
ClinicalTrials.gov: ADAPT Umbrella: NCT01781338; ADAPT HR+/HER2-: NCT01779206; ADAPT HER2+/HR+: NCT01745965; ADAPT HER2+/HR-: NCT01817452; ADAPT TN:NCT01815242.
doi:10.1186/1745-6215-14-261
PMCID: PMC3765940  PMID: 23958221
ADAPT; Biomarker; Early breast cancer; Investigator initiated trial
6.  P53 autoantibodies in 1006 patients followed up for breast cancer 
Breast Cancer Research : BCR  2000;2(6):438-443.
Serial plasma samples from 1006 patients with breast cancer revealed: (i) no correlation of p53 autoantibody status with disease status at the time of sample collection, or with menopausal status at time of primary diagnosis of breast cancer; (ii) 155 out of 1006 (15%) of patients were positive for p53 autoantibodies, and these patients tended to have a persistent autoantibody status throughout follow up, irrespective of disease behaviour; and (iii) where a negative autoantibody status was found at primary diagnosis of breast cancer, this negative status persisted throughout follow up, irrespective of later disease behaviour. We conclude that screening for p53 autoantibody status is not informative on residual tumour activity nor on therapeutic responsiveness.
Introduction:
Dysfunction of the tumour-suppressor protein, p53, may be due to either mutational or epigenetic factors, each of which may lead to accumulation of cytoplasmic p53. Abnormal accumulation of p53 in breast cancer tissue is predictive of poor prognosis [1,2]. Humoral studies [3,4] have shown that cancer patients may develop immunity to abnormally expressed p53, as revealed by p53 autoantibodies in the blood. Again, prognostic correlates have been noted, with presence of circulating p53 autoantibodies at diagnosis of breast cancer being associated with reduced overall survival [5,6] and with poor prognostic factors such as high histological grade and the absence of hormone receptors [5,7,8].
Little is known of the potential value of p53 autoantibody in follow up of cancer. In lung cancer there is evidence that autoantibodies to p53 may provide a useful tool to monitor response to therapy [9,10], whereas serial measurements of autoantibodies to p53 in 40 patients with advanced ovarian cancer were not found to be clinically useful [11]. In breast cancer some 30% of node-negative patients will relapse within 5 years, but there is no current means to predict those who are at risk.
We performed the present study to ask if the presence of autoantibodies to p53 has any association with breast cancer progression.
Materials and method:
A library of plasma samples were collected from all patients attending one general oncology clinic for postoperative follow up of breast cancer. The clinical status of each patient at the time of sampling was summarized. An average of eight plasma samples were cryopreserved for each patient over a period of 15 years.
The enzyme-linked immusorbent assay (ELISA) for p53 autoantibodies was developed in-house, based on the ELISA procedure of Lubin et al [3]. Our in-house method is detailed in the full text of this article. In one assay series we compared a commercial ELISA kit for p53 autoantibodies with our in-house ELISA. A total of 20 patients' samples were tested, representing a range of positive and negative readings. Two samples scored as strongly positive with the in-house assay, but only one of these two scored positive with the commercial assay. Having established sensitivity, specificity and reproducibility of the in-house assay, we judged that this was superior to the commercial assay both in terms of sensitivity and of cost (£1 per test compared with £23 per test). The in-house assay was thus used throughout the present study.
Results:
Serial plasma samples from 1006 patients with breast cancer revealed the following: (i) no correlation of p53 autoantibody status with disease status at the time of sample collection (Table 1), or with menopausal status at time of primary diagnosis of breast cancer (Table 2); (ii) 155 out of 1006 (15%) of patients were positive for p53 autoantibodies, and these patients tended to have a persistent autoantibody status throughout follow up, irrespective of disease behaviour; and (iii) where a negative autoantibody status was found at primary diagnosis of breast cancer, this negative status persisted throughout follow up, irrespective of later disease behaviour (Table 3).
Discussion:
As a working hypothesis, we proposed that levels of autoantibodies to p53 would reflect tumour behaviour. However, we found that the presence or absence of p53 autoantibodies was not predictive of presence or absence of recurrent disease. There was an equivalent incidence of active disease at the time of sampling in both the autoantibody-negative and autoantibody-positive groups, these being 25.2 and 28.7%, respectively. Thus, humoral immune activity against p53 appeared to be relatively restricted to a subgroup of patients in whom, once an autoantibody response had been generated, antibody was likely to persist regardless of tumour behaviour. Conversely, where no detectable p53 autoantibody was present at the time of primary diagnosis, these patients remained similarly negative for antibody, irrespective of subsequent disease activity (Table 3).
In contrast to shed markers that correlate with tumour mass, such as CA15.3 for cancer of the breast, any tumour-related immune response will be subject to complex regulation. Autoantibody responses to p53 will require appropriate primary immunization; initial low-dose antigen exposure may induce immune tolerance and lack of response. Higher antigen doses may activate either antibody-mediated immunity, or cellular immunity.
In breast cancer patients, our results suggest that, once an active humoral response against p53 is established, then this remains active. This persistent humoral reaction may be driven by persistent antigenic stimulation by p53 protein derived from overexpression of p53 at distant metastatic sites; alternatively, irradiated normal tissue may be a source of continued antigenic stimulation, because a long-term side effect of radiation therapy is an increased expression of p53 in normal breast tissue that persists for several years [12]. Since the great majority of our total patient cohort had received radiotherapy, humoral immunity to p53 associated with primary disease might persist, even in those patients who enter remission, due to tumour-independent antigenic stimulation.
Loss of p53 function is known to correlate with loss of efficacy of cancer therapy in vivo [13,14]. This raised the possibility that autoantibodies to p53 that develop during follow up might indicate those patients whose tumor has become resistant to therapy. However, the present results show that, if no immunity has been generated at the time of primary diagnosis, then later immunity is unlikely to occur. This corresponds to the finding that expression of p53 antigen in biopies of locally advanced breast cancer did not correlate with drug resistance [15,16]. Overall, the present observations show that screening for p53 autoantibody status is not informative on residual tumour activity, or on therapeutic responsiveness. We conclude that the potential value of p53 autoantibody screening in patients with breast cancer is limited to the prognostic information obtained at diagnosis.
PMCID: PMC13921  PMID: 11056691
breast; cancer; monitoring; p53 autoantibodies
7.  Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer 
Executive Summary
In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of published literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.
Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenomics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.
The following reports can be publicly accessed at the MAS website at: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.html
Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer: An Evidence-Based and Economic Analysis
Epidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: An Evidence-Based and Ecopnomic Analysis
K-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based and Economic Analysis
Objective
To review and synthesize the available evidence regarding the laboratory performance, prognostic value, and predictive value of Oncotype-DX for the target population.
Clinical Need: Condition and Target Population
The target population of this review is women with newly diagnosed early stage (stage I–IIIa) invasive breast cancer that is estrogen-receptor (ER) positive and/or progesterone-receptor (PR) positive. Much of this review, however, is relevant for women with early stage (I and II) invasive breast cancer that is specifically ER positive, lymph node (LN) negative and human epidermal growth factor receptor 2 (HER-2/neu) negative. This refined population represents an estimated incident population of 3,315 new breast cancers in Ontario (according to 2007 data). Currently it is estimated that only 15% of these women will develop a distant metastasis at 10 years; however, a far great proportion currently receive adjuvant chemotherapy, suggesting that more women are being treated with chemotherapy than can benefit. There is therefore a need to develop better prognostic and predictive tools to improve the selection of women that may benefit from adjuvant chemotherapy.
Technology of Concern
The Oncotype-DX Breast Cancer Assay (Genomic Health, Redwood City, CA) quantifies gene expression for 21 genes in breast cancer tissue by performing reverse transcription polymerase chain reaction (RT-PCR) on formalin-fixed paraffin-embedded (FFPE) tumour blocks that are obtained during initial surgery (lumpectomy, mastectomy, or core biopsy) of women with early breast cancer that is newly diagnosed. The panel of 21 genes include genes associated with tumour proliferation and invasion, as well as other genes related to HER-2/neu expression, ER expression, and progesterone receptor (PR) expression.
Research Questions
What is the laboratory performance of Oncotype-DX?
How reliable is Oncotype-DX (i.e., how repeatable and reproducible is Oncotype-DX)?
How often does Oncotype-DX fail to give a useable result?
What is the prognostic value of Oncotype-DX?*
Is Oncotype-DX recurrence score associated with the risk of distant recurrence or death due to any cause in women with early breast cancer receiving tamoxifen?
What is the predictive value of Oncotype-DX?*
Does Oncoytpe-DX recurrence score predict significant benefit in terms of improvements in 10-year distant recurrence or death due to any cause for women receiving tamoxifen plus chemotherapy in comparison to women receiving tamoxifen alone?
How does Oncotype-DX compare to other known predictors of risk such as Adjuvant! Online?
How does Oncotype-DX impact patient quality of life and clinical/patient decision-making?
Research Methods
Literature Search
Search Strategy
A literature search was performed on March 19th, 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1st, 2006 to March 19th, 2010. A starting search date of January 1st, 2006 was because a comprehensive systematic review of Oncotype-DX was identified in preliminary literature searching. This systematic review, by Marchionni et al. (2008), included literature up to January 1st, 2007. All studies identified in the review by Marchionni et al. as well as those identified in updated literature searching were used to form the evidentiary base of this review. The quality of the overall body of evidence was identified as high, moderate, low or very low according to GRADE methodology.
Inclusion Criteria
Any observational trial, controlled clinical trial, randomized controlled trial (RCT), meta-analysis or systematic review that reported on the laboratory performance, prognostic value and/or predictive value of Oncotype-DX testing, or other outcome relevant to the Key Questions, specific to the target population was included.
Exclusion Criteria
Studies that did not report original data or original data analysis,
Studies published in a language other than English,
Studies reported only in abstract or as poster presentations (such publications were not sought nor included in this review since the MAS does not generally consider evidence that is not subject to peer review nor does the MAS consider evidence that lacks detailed description of methodology).
Outcomes of Interest
Outcomes of interest varied depending on the Key Question. For the Key Questions of prognostic and predictive value (Key Questions #2 and #3), the prospectively defined primary outcome was risk of 10-year distant recurrence. The prospectively defined secondary outcome was 10-year death due to any cause (i.e., overall survival). All additional outcomes such as risk of locoregional recurrence or disease-free survival (DFS) were not prospectively determined for this review but were reported as presented in included trials; these outcomes are referenced as tertiary outcomes in this review. Outcomes for other Key Questions (i.e., Key Questions #1, #4 and #5) were not prospectively defined due to the variability in endpoints relevant for these questions.
Summary of Findings
A total of 26 studies were included. Of these 26 studies, only five studies were relevant to the primary questions of this review (Key Questions #2 and #3). The following conclusions were drawn from the entire body of evidence:
There is a lack of external validation to support the reliability of Oncotype-DX; however, the current available evidence derived from internal industry validation studies suggests that Oncotype-DX is reliable (i.e., Oncotype-DX is repeatable and reproducible).
Current available evidence suggests a moderate failure rate of Oncotype-DX testing; however, the failure rate observed across clinical trials included in this review is likely inflated; the current Ontario experience suggests an acceptably lower rate of test failure.
In women with newly diagnosed early breast cancer (stage I–II) that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node negative:
There is low quality evidence that Oncotype-DX has prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole (the latter for postmenopausal women only),
There is very low quality evidence that Oncotype-DX can predict which women will benefit from adjuvant CMF/MF chemotherapy in women being treated with adjuvant tamoxifen.
In postmenopausal women with newly diagnosed early breast cancer that is estrogen-receptor positive and/or progesterone-receptor positive and lymph-node positive:
There is low quality evidence that Oncotype-DX has limited prognostic value in women who are being treated with adjuvant tamoxifen or anastrozole,
There is very low quality evidence that Oncotype-DX has limited predictive value for predicting which women will benefit from adjuvant CAF chemotherapy in women who are being treated with adjuvant tamoxifen.
There are methodological and statistical limitations that affect both the generalizability of the current available evidence, as well as the magnitude and statistical strength of the observed effect sizes; in particular:
Of the major predictive trials, Oncotype-DX scores were only produced for a small subset of women (<40% of the original randomized population) potentially disabling the effects of treatment randomization and opening the possibility of selection bias;
Data is not specific to HER-2/neu-negative women;
There were limitations with multivariate statistical analyses.
Additional trials of observational design may provide further validation of the prognostic and predictive value of Oncotype-DX; however, it is unlikely that prospective or randomized data will become available in the near future due to ethical, time and resource considerations.
There is currently insufficient evidence investigating how Oncoytpe-DX compares to other known prognostic estimators of risk, such as Adjuvant! Online, and there is insufficient evidence investigating how Oncotype-DX would impact clinician/patient decision-making in a setting generalizable to Ontario.
PMCID: PMC3382301  PMID: 23074401
8.  Growth Factor Receptors and Apoptosis Regulators: Signaling Pathways, Prognosis, Chemosensitivity and Treatment Outcomes of Breast Cancer 
Biomarkers of breast cancer are necessary for prognosis and prediction to chemotherapy. Prognostic biomarkers provide information regarding outcome irrespective of therapy, while predictive biomarkers provide information regarding response to therapy. Candidate prognostic biomarkers for breast cancers are growth factor receptors, steroid receptors, Ki-67, cyclins, urokinase plasminogen activator, p53, p21, pro- and anti-apoptotic factors, BRCA1 and BRCA2. But currently, the predictive markers are Estrogen and Progesterone receptors responding to endocrine therapy, and HER-2 responding to herceptin. But there are numerous breast cancer cases, where tamoxifen is ineffective even after estrogen receptor positivity. This lead to search of new prognostic and predictive markers and the number of potential markers is constantly increasing due to proteomics and genomics studies. However, most biomarkers individually have poor sensitivity or specificity, or other clinical value. It can be resolved by studying various biomarkers simultaneously, which will help in better prognosis and increasing sensitivity for chemotherapeutic agents. This review is focusing on growth factor receptors, apoptosis markers, signaling cascades, and their correlation with other associated biomarkers in breast cancers. As our knowledge regarding molecular biomarkers for breast cancer increases, prognostic indices will be developed that combine the predictive power of individual molecular biomarkers with specific clinical and pathologic factors. Rigorous comparison of these existing as well as emerging markers with current treatment selection is likely to see an escalation in an era of personalized medicines to ensure the breast cancer patients receive optimal treatment. This will also solve the treatment modalities and complications related to chemotherapeutic regimens.
PMCID: PMC3086304  PMID: 21556249
prognostic markers; estrogen; growth factor receptor; apoptosis; chemotherapy; mitogen-activated protein kinase
9.  Exquisite Sensitivity of TP53 Mutant and Basal Breast Cancers to a Dose-Dense Epirubicin−Cyclophosphamide Regimen 
PLoS Medicine  2007;4(3):e90.
Background
In breast cancers, only a minority of patients fully benefit from the different chemotherapy regimens currently in use. Identification of markers that could predict the response to a particular regimen would thus be critically important for patient care. In cell lines or animal models, tumor protein p53 (TP53) plays a critical role in modulating the response to genotoxic drugs. TP53 is activated in response to DNA damage and triggers either apoptosis or cell-cycle arrest, which have opposite effects on cell fate. Yet, studies linking TP53 status and chemotherapy response have so far failed to unambiguously establish this paradigm in patients. Breast cancers with a TP53 mutation were repeatedly shown to have a poor outcome, but whether this reflects poor response to treatment or greater intrinsic aggressiveness of the tumor is unknown.
Methods and Findings
In this study we analyzed 80 noninflammatory breast cancers treated by frontline (neoadjuvant) chemotherapy. Tumor diagnoses were performed on pretreatment biopsies, and the patients then received six cycles of a dose-dense regimen of 75 mg/m2 epirubicin and 1,200 mg/m2 cyclophosphamide, given every 14 days. After completion of chemotherapy, all patients underwent mastectomies, thus allowing for a reliable assessment of chemotherapy response. The pretreatment biopsy samples were used to determine the TP53 status through a highly efficient yeast functional assay and to perform RNA profiling. All 15 complete responses occurred among the 28 TP53-mutant tumors. Furthermore, among the TP53-mutant tumors, nine out of ten of the highly aggressive basal subtypes (defined by basal cytokeratin [KRT] immunohistochemical staining) experienced complete pathological responses, and only TP53 status and basal subtype were independent predictors of a complete response. Expression analysis identified many mutant TP53-associated genes, including CDC20, TTK, CDKN2A, and the stem cell gene PROM1, but failed to identify a transcriptional profile associated with complete responses among TP53 mutant tumors. In patients with unresponsive tumors, mutant TP53 status predicted significantly shorter overall survival. The 15 patients with responsive TP53-mutant tumors, however, had a favorable outcome, suggesting that this chemotherapy regimen can overcome the poor prognosis generally associated with mutant TP53 status.
Conclusions
This study demonstrates that, in noninflammatory breast cancers, TP53 status is a key predictive factor for response to this dose-dense epirubicin–cyclophosphamide regimen and further suggests that the basal subtype is exquisitely sensitive to this association. Given the well-established predictive value of complete responses for long-term survival and the poor prognosis of basal and TP53-mutant tumors treated with other regimens, this chemotherapy could be particularly suited for breast cancer patients with a mutant TP53, particularly those with basal features.
Hugues de The and colleagues report thatTP53 status is a predictive factor for responsiveness in breast cancers to a dose-dense epirubicin-cyclophosphamide chemotherapy regimen, and suggests that this regimen might be well suited for patientsTP53 mutant tumors.
Editors' Summary
Background.
One woman in eight will develop breast cancer during her life. As with other cancers, breast cancer arises when cells accumulate genetic changes (mutations) that allow them to grow uncontrollably and to move around the body. These altered cells are called malignant cells. The normal human breast contains several types of cell, any of which can become malignant. In addition, there is more than one route to malignancy—different sets of genes can be mutated. As a result, breast cancer is a heterogeneous disease that cannot be cured with a single type of treatment. Ideally, oncologists would like to know before they start treating a patient which therapeutic approach is going to be successful for that individual. Recently, researchers have begun to identify molecular changes that might eventually allow oncologists to make such rational treatment decisions. For example, laboratory studies in cell lines or animals indicate that the status of a gene called TP53 determines the chemotherapy agents (drugs that preferentially kill rapidly dividing cancer cells) to which cells respond. p53, the protein encoded by TP53, is a tumor suppressor. That is, in normal cells it prevents unregulated growth by controlling the expression of proteins involved in cell division and cell death. Consequently, p53 is often inactivated during cancer development.
Why Was This Study Done?
Although laboratory studies have linked TP53 status to chemotherapy responses, little is known about this relationship in human breast cancers. The clinical studies that have investigated whether TP53 status affects chemotherapy responses have generally found that patients whose tumors contain mutant TP53 have a poorer response to therapy and/or a shorter survival time than those whose tumors contain normal TP53. In this study, the researchers have asked whether TP53 status affects tumor responses to a dose-intense chemotherapy regimen (frequent, high doses of drugs) given to women with advanced noninflammatory breast cancer before surgery. This type of treatment is called neoadjuvant chemotherapy and is used to shrink tumors before surgery.
What Did the Researchers Do and Find?
The researchers collected breast tumor samples from 80 women before starting six fortnightly cycles of chemotherapy with epirubicin and cyclophosphamide. After this, each woman had her affected breast removed and examined to see whether the chemotherapy had killed the tumor cells. The researchers determined which original tumor samples contained mutated TP53 and used a technique called microarray expression profiling to document gene expression patterns in them. Overall, 28 tumors contained mutated TP53. Strikingly, all 15 tumors that responded completely to neoadjuvant chemotherapy (no tumor cells detectable in the breast tissue after chemotherapy) contained mutated TP53. Nine of these responsive tumors were basal-cell–like breast tumors, a particularly aggressive type of breast cancer; only one basal-cell–like, TP53-mutated tumor did not respond to chemotherapy. Patients whose tumors were unresponsive to the neoadjuvant chemotherapy but contained mutated TP53 tended to die sooner than those whose tumors contained normal TP53 or those with chemotherapy-responsive TP53-mutated tumors. Finally, expression profiling identified changes in the expression of many p53-regulated genes, but did not identify an expression profile in the TP53-mutated tumors unique to those that responded to chemotherapy.
What Do These Findings Mean?
These findings indicate that noninflammatory breast tumors containing mutant TP53—in particular, basal-cell–like tumors—are very sensitive to dose-dense epirubicin and cyclophosphamide chemotherapy. Intensive regimens of this type have rarely been used in previous studies, which might explain the apparent contradiction between these results and the generally poor response to chemotherapy of TP53-mutated breast tumors. More tumors now need to be examined to confirm the association between complete response, TP53 status and basal-cell–like tumors. In addition, although complete tumor responses generally predict good overall survival, longer survival studies than those reported here are needed to show that the tumor response to this particular neoadjuvant chemotherapy regimen translates into improved overall survival. If the present results can be confirmed and extended, dose-dense neoadjuvant chemotherapy with epirubicin and cyclophosphamide could considerably improve the outlook for patients with aggressive TP53-mutant, basal-cell–like breast tumors.
Additional Information.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040090.
The US National Cancer Institute provides patient and physician information on breast cancer and general information on understanding cancer
Cancer Research UK offers patient information on cancer and breast cancer
The MedlinePlus encyclopedia has pages on breast cancer
Emory University's CancerQuest discusses the biology of cancer, including the role of tumor suppressor proteins
Wikipedia has pages on p53 (note that Wikipedia is a free online encyclopedia that anyone can edit)
doi:10.1371/journal.pmed.0040090
PMCID: PMC1831731  PMID: 17388661
10.  Effect of PREDICT on chemotherapy/trastuzumab recommendations in HER2-positive patients with early-stage breast cancer 
Oncology Letters  2014;8(6):2757-2761.
PREDICT is an online prognostication tool for early-stage breast cancer, which incorporates human epidermal growth factor 2 (HER2) status and stratifies absolute treatment benefits for hormone therapy, chemotherapy and trastuzumab. The present study compared historical multidisciplinary team (MDT) decisions regarding adjuvant treatment with PREDICT estimates, to determine whether certain patients are being over- or undertreated, particularly when stratified by age and oestrogen-receptor (ER) status. HER2-positive early-stage breast cancer cases over a five-year period at the Cambridge Breast Unit (Addenbrooke’s Hospital, Cambridge, UK) were retrospectively reviewed. Patients receiving neo-adjuvant therapy were excluded. Adjuvant chemotherapy/trastuzumab recommendations based on PREDICT (<3%, no benefit; 3–5%, discuss treatment; and >5%, recommend treatment) were compared with actual MDT decisions. In total, 109 eligible patients were identified. The average age at diagnosis was 59.6 years, with 21 patients older than 70 years (19%). Four patients were predicted to gain an absolute benefit of >5% from chemotherapy/ trastuzumab, but were not offered treatment (all >70 years). Amongst the 19 patients aged >70 years predicted to benefit >3%, six were not offered treatment (32%). In the patients aged <69 years, there was evidence of overtreatment with adjuvant chemotherapy/trastuzumab in 8 out of 12 cases with <3% benefit using PREDICT. For all 20 patients with ER-negative tumours, the MDT and PREDICT decisions correlated, whilst for ER-positive cases, more than half (8 out of 14) were offered treatment despite a <3% predicted benefit. PREDICT can aid decision-making in HER2-positive early-stage breast cancer by identifying older patients at risk of undertreatment with chemotherapy/trastuzumab, and by reducing the overtreatment of patients with little predicted benefit, particularly in ER-positive disease.
doi:10.3892/ol.2014.2589
PMCID: PMC4214477  PMID: 25364461
breast cancer; management; prognostic factors; erbB-2 receptor; online predictive tools; age
11.  Association between Cutaneous Nevi and Breast Cancer in the Nurses' Health Study: A Prospective Cohort Study 
PLoS Medicine  2014;11(6):e1001659.
Using data from the Nurses' Health Study, Jiali Han and colleagues examine the association between number of cutaneous nevi and the risk for breast cancer.
Please see later in the article for the Editors' Summary
Background
Cutaneous nevi are suggested to be hormone-related. We hypothesized that the number of cutaneous nevi might be a phenotypic marker of plasma hormone levels and predict subsequent breast cancer risk.
Methods and Findings
We followed 74,523 female nurses for 24 y (1986–2010) in the Nurses' Health Study and estimate the relative risk of breast cancer according to the number of cutaneous nevi. We adjusted for the known breast cancer risk factors in the models. During follow-up, a total of 5,483 invasive breast cancer cases were diagnosed. Compared to women with no nevi, women with more cutaneous nevi had higher risks of breast cancer (multivariable-adjusted hazard ratio, 1.04, 95% confidence interval [CI], 0.98–1.10 for 1–5 nevi; 1.15, 95% CI, 1.00–1.31 for 6–14 nevi, and 1.35, 95% CI, 1.04–1.74 for 15 or more nevi; p for continuous trend = 0.003). Over 24 y of follow-up, the absolute risk of developing breast cancer increased from 8.48% for women without cutaneous nevi to 8.82% (95% CI, 8.31%–9.33%) for women with 1–5 nevi, 9.75% (95% CI, 8.48%–11.11%) for women with 6–14 nevi, and 11.4% (95% CI, 8.82%–14.76%) for women with 15 or more nevi. The number of cutaneous nevi was associated with increased risk of breast cancer only among estrogen receptor (ER)–positive tumors (multivariable-adjusted hazard ratio per five nevi, 1.09, 95% CI, 1.02–1.16 for ER+/progesterone receptor [PR]–positive tumors; 1.08, 95% CI, 0.94–1.24 for ER+/PR− tumors; and 0.99, 95% CI, 0.86–1.15 for ER−/PR− tumors). Additionally, we tested plasma hormone levels according to the number of cutaneous nevi among a subgroup of postmenopausal women without postmenopausal hormone use (n = 611). Postmenopausal women with six or more nevi had a 45.5% higher level of free estradiol and a 47.4% higher level of free testosterone compared to those with no nevi (p for trend = 0.001 for both). Among a subgroup of 362 breast cancer cases and 611 matched controls with plasma hormone measurements, the multivariable-adjusted odds ratio for every five nevi attenuated from 1.25 (95% CI, 0.89–1.74) to 1.16 (95% CI, 0.83–1.64) after adjusting for plasma hormone levels. Key limitations in this study are that cutaneous nevi were self-counted in our cohort and that the study was conducted in white individuals, and thus the findings do not necessarily apply to other populations.
Conclusions
Our results suggest that the number of cutaneous nevi may reflect plasma hormone levels and predict breast cancer risk independently of previously known factors.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
One woman in eight will develop breast cancer during her lifetime. Breast cancer begins when cells in the breast acquire genetic changes that allow them to divide uncontrollably (which leads to the formation of a lump in the breast) and to move around the body (metastasize). The treatment of breast cancer, which is diagnosed using mammography (a breast X-ray) or manual breast examination and biopsy, usually involves surgery to remove the lump, or the whole breast (mastectomy) if the cancer has started to metastasize. After surgery, women often receive chemotherapy or radiotherapy to kill any remaining cancer cells and may also be given drugs that block the action of estrogen and progesterone, female sex hormones that stimulate the growth of some breast cancer cells. Globally, half a million women die from breast cancer each year. However, in developed countries, nearly 90% of women affected by breast cancer are still alive five years after diagnosis.
Why Was This Study Done?
Several sex hormone–related factors affect breast cancer risk, including at what age a woman has her first child (pregnancy alters sex hormone levels) and her age at menopause, when estrogen levels normally drop. Moreover, postmenopausal women with high circulating levels of estrogen and testosterone (a male sex hormone) have an increased breast cancer risk. Interestingly, moles (nevi)—dark skin blemishes that are a risk factor for the development of melanoma, a type of skin cancer—often darken or enlarge during pregnancy. Might the number of nevi be a marker of hormone levels, and could nevi counts therefore be used to predict an individual's risk of breast cancer? In this prospective cohort study, the researchers look for an association between number of nevi and breast cancer risk among participants in the US Nurses' Health Study (NHS). A prospective cohort study enrolls a group of people, determines their baseline characteristics, and follows them over time to see which characteristics are associated with the development of certain diseases. The NHS, which enrolled 121,700 female nurses aged 30–55 years in 1976, is studying risk factors for cancer and other chronic diseases in women.
What Did the Researchers Do and Find?
In 1986, nearly 75,000 NHS participants (all of whom were white) reported how many nevi they had on their left arm. Over the next 24 years, 5,483 invasive breast cancers were diagnosed in these women. Compared to women with no nevi, women with increasing numbers of nevi had a higher risk of breast cancer after adjustment for known breast cancer risk factors. Specifically, among women with 1–5 nevi, the hazard ratio (HR) for breast cancer was 1.04, whereas among women with 15 or more nevi the HR was 1.35. An HR compares how often a particular event occurs in two groups with different characteristics; an HR greater than one indicates that a specific characteristic is associated with an increased risk of the event. Over 24 years of follow-up, the absolute risk of developing breast cancer was 8.48% in women with no nevi but 11.4% for women with 15 or more nevi. Notably, postmenopausal women with six or more nevi had higher blood levels of estrogen and testosterone than women with no nevi. Finally, in a subgroup analysis, the association between number of nevi and breast cancer risk disappeared after adjustment for hormone levels.
What Do These Findings Mean?
These findings support the hypothesis that the number of nevi reflects sex hormone levels in women and may predict breast cancer risk. Notably, they show that the association between breast cancer risk and nevus number was independent of known risk factors for breast cancer, and that the risk of breast cancer increased with the number of nevi in a dose-dependent manner. These findings also suggest that a hormonal mechanism underlies the association between nevus number and breast cancer risk. Because this study involved only white participants, these findings may not apply to non-white women. Moreover, the use of self-reported data on nevus numbers may affect the accuracy of these findings. Finally, because this study is observational, these findings are insufficient to support any changes in clinical recommendations for breast cancer screening or diagnosis. Nevertheless, these data and those in an independent PLOS Medicine Research Article by Kvaskoff et al. support the need for further investigation of the association between nevi and breast cancer risk and of the mechanisms underlying this relationship.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001659.
An independent PLOS Medicine Research Article by Kvaskoff et al. also investigates the relationship between nevi and breast cancer risk
The US National Cancer Institute provides comprehensive information about cancer (in English and Spanish), including detailed information for patients and professionals about breast cancer; it also has a fact sheet on moles
Cancer Research UK, a not-for profit organization, provides information about cancer, including detailed information on breast cancer
The UK National Health Service Choices website has information and personal stories about breast cancer; the not-for profit organization Healthtalkonline also provides personal stories about dealing with breast cancer
More information about the Nurses' Health Study is available
doi:10.1371/journal.pmed.1001659
PMCID: PMC4051600  PMID: 24915186
12.  Novel diagnostic biomarkers for prostate cancer 
Journal of Cancer  2010;1:150-177.
Prostate cancer is the most frequently diagnosed malignancy in American men, and a more aggressive form of the disease is particularly prevalent among African Americans. The therapeutic success rate for prostate cancer can be tremendously improved if the disease is diagnosed early. Thus, a successful therapy for this disease depends heavily on the clinical indicators (biomarkers) for early detection of the presence and progression of the disease, as well as the prediction after the clinical intervention. However, the current clinical biomarkers for prostate cancer are not ideal as there remains a lack of reliable biomarkers that can specifically distinguish between those patients who should be treated adequately to stop the aggressive form of the disease and those who should avoid overtreatment of the indolent form.
A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. A biomarker reveals further information to presently existing clinical and pathological analysis. It facilitates screening and detecting the cancer, monitoring the progression of the disease, and predicting the prognosis and survival after clinical intervention. A biomarker can also be used to evaluate the process of drug development, and, optimally, to improve the efficacy and safety of cancer treatment by enabling physicians to tailor treatment for individual patients. The form of the prostate cancer biomarkers can vary from metabolites and chemical products present in body fluid to genes and proteins in the prostate tissues.
Current advances in molecular techniques have provided new tools facilitating the discovery of new biomarkers for prostate cancer. These emerging biomarkers will be beneficial and critical in developing new and clinically reliable indicators that will have a high specificity for the diagnosis and prognosis of prostate cancer. The purpose of this review is to examine the current status of prostate cancer biomarkers, with special emphasis on emerging markers, by evaluating their diagnostic and prognostic potentials. Both genes and proteins that reveal loss, mutation, or variation in expression between normal prostate and cancerous prostate tissues will be covered in this article. Along with the discovery of prostate cancer biomarkers, we will describe the criteria used when selecting potential biomarkers for further development towards clinical use. In addition, we will address how to appraise and validate candidate markers for prostate cancer and some relevant issues involved in these processes. We will also discuss the new concept of the biomarkers, existing challenges, and perspectives of biomarker development.
PMCID: PMC2962426  PMID: 20975847
diagnostic biomarkers; prostate cancer
13.  Nuclear Receptor Expression Defines a Set of Prognostic Biomarkers for Lung Cancer 
PLoS Medicine  2010;7(12):e1000378.
David Mangelsdorf and colleagues show that nuclear receptor expression is strongly associated with clinical outcomes of lung cancer patients, and this expression profile is a potential prognostic signature for lung cancer patient survival time, particularly for individuals with early stage disease.
Background
The identification of prognostic tumor biomarkers that also would have potential as therapeutic targets, particularly in patients with early stage disease, has been a long sought-after goal in the management and treatment of lung cancer. The nuclear receptor (NR) superfamily, which is composed of 48 transcription factors that govern complex physiologic and pathophysiologic processes, could represent a unique subset of these biomarkers. In fact, many members of this family are the targets of already identified selective receptor modulators, providing a direct link between individual tumor NR quantitation and selection of therapy. The goal of this study, which begins this overall strategy, was to investigate the association between mRNA expression of the NR superfamily and the clinical outcome for patients with lung cancer, and to test whether a tumor NR gene signature provided useful information (over available clinical data) for patients with lung cancer.
Methods and Findings
Using quantitative real-time PCR to study NR expression in 30 microdissected non-small-cell lung cancers (NSCLCs) and their pair-matched normal lung epithelium, we found great variability in NR expression among patients' tumor and non-involved lung epithelium, found a strong association between NR expression and clinical outcome, and identified an NR gene signature from both normal and tumor tissues that predicted patient survival time and disease recurrence. The NR signature derived from the initial 30 NSCLC samples was validated in two independent microarray datasets derived from 442 and 117 resected lung adenocarcinomas. The NR gene signature was also validated in 130 squamous cell carcinomas. The prognostic signature in tumors could be distilled to expression of two NRs, short heterodimer partner and progesterone receptor, as single gene predictors of NSCLC patient survival time, including for patients with stage I disease. Of equal interest, the studies of microdissected histologically normal epithelium and matched tumors identified expression in normal (but not tumor) epithelium of NGFIB3 and mineralocorticoid receptor as single gene predictors of good prognosis.
Conclusions
NR expression is strongly associated with clinical outcomes for patients with lung cancer, and this expression profile provides a unique prognostic signature for lung cancer patient survival time, particularly for those with early stage disease. This study highlights the potential use of NRs as a rational set of therapeutically tractable genes as theragnostic biomarkers, and specifically identifies short heterodimer partner and progesterone receptor in tumors, and NGFIB3 and MR in non-neoplastic lung epithelium, for future detailed translational study in lung cancer.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Lung cancer, the most common cause of cancer-related death, kills 1.3 million people annually. Most lung cancers are “non-small-cell lung cancers” (NSCLCs), and most are caused by smoking. Exposure to chemicals in smoke causes changes in the genes of the cells lining the lungs that allow the cells to grow uncontrollably and to move around the body. How NSCLC is treated and responds to treatment depends on its “stage.” Stage I tumors, which are small and confined to the lung, are removed surgically, although chemotherapy is also sometimes given. Stage II tumors have spread to nearby lymph nodes and are treated with surgery and chemotherapy, as are some stage III tumors. However, because cancer cells in stage III tumors can be present throughout the chest, surgery is not always possible. For such cases, and for stage IV NSCLC, where the tumor has spread around the body, patients are treated with chemotherapy alone. About 70% of patients with stage I and II NSCLC but only 2% of patients with stage IV NSCLC survive for five years after diagnosis; more than 50% of patients have stage IV NSCLC at diagnosis.
Why Was This Study Done?
Patient responses to treatment vary considerably. Oncologists (doctors who treat cancer) would like to know which patients have a good prognosis (are likely to do well) to help them individualize their treatment. Consequently, the search is on for “prognostic tumor biomarkers,” molecules made by cancer cells that can be used to predict likely clinical outcomes. Such biomarkers, which may also be potential therapeutic targets, can be identified by analyzing the overall pattern of gene expression in a panel of tumors using a technique called microarray analysis and looking for associations between the expression of sets of genes and clinical outcomes. In this study, the researchers take a more directed approach to identifying prognostic biomarkers by investigating the association between the expression of the genes encoding nuclear receptors (NRs) and clinical outcome in patients with lung cancer. The NR superfamily contains 48 transcription factors (proteins that control the expression of other genes) that respond to several hormones and to diet-derived fats. NRs control many biological processes and are targets for several successful drugs, including some used to treat cancer.
What Did the Researchers Do and Find?
The researchers analyzed the expression of NR mRNAs using “quantitative real-time PCR” in 30 microdissected NSCLCs and in matched normal lung tissue samples (mRNA is the blueprint for protein production). They then used an approach called standard classification and regression tree analysis to build a prognostic model for NSCLC based on the expression data. This model predicted both survival time and disease recurrence among the patients from whom the tumors had been taken. The researchers validated their prognostic model in two large independent lung adenocarcinoma microarray datasets and in a squamous cell carcinoma dataset (adenocarcinomas and squamous cell carcinomas are two major NSCLC subtypes). Finally, they explored the roles of specific NRs in the prediction model. This analysis revealed that the ability of the NR signature in tumors to predict outcomes was mainly due to the expression of two NRs—the short heterodimer partner (SHP) and the progesterone receptor (PR). Expression of either gene could be used as a single gene predictor of the survival time of patients, including those with stage I disease. Similarly, the expression of either nerve growth factor induced gene B3 (NGFIB3) or mineralocorticoid receptor (MR) in normal tissue was a single gene predictor of a good prognosis.
What Do These Findings Mean?
These findings indicate that the expression of NR mRNA is strongly associated with clinical outcomes in patients with NSCLC. Furthermore, they identify a prognostic NR expression signature that provides information on the survival time of patients, including those with early stage disease. The signature needs to be confirmed in more patients before it can be used clinically, and researchers would like to establish whether changes in mRNA expression are reflected in changes in protein expression if NRs are to be targeted therapeutically. Nevertheless, these findings highlight the potential use of NRs as prognostic tumor biomarkers. Furthermore, they identify SHP and PR in tumors and two NRs in normal lung tissue as molecules that might provide new targets for the treatment of lung cancer and new insights into the early diagnosis, pathogenesis, and chemoprevention of lung cancer.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000378.
The Nuclear Receptor Signaling Atlas (NURSA) is consortium of scientists sponsored by the US National Institutes of Health that provides scientific reagents, datasets, and educational material on nuclear receptors and their co-regulators to the scientific community through a Web-based portal
The Cancer Prevention and Research Institute of Texas (CPRIT) provides information and resources to anyone interested in the prevention and treatment of lung and other cancers
The US National Cancer Institute provides detailed information for patients and professionals about all aspects of lung cancer, including information on non-small-cell carcinoma and on tumor markers (in English and Spanish)
Cancer Research UK also provides information about lung cancer and information on how cancer starts
MedlinePlus has links to other resources about lung cancer (in English and Spanish)
Wikipedia has a page on nuclear receptors (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1000378
PMCID: PMC3001894  PMID: 21179495
14.  Health-related quality of life in breast cancer patients: A bibliographic review of the literature from 1974 to 2007 
Background
Quality of life in patients with breast cancer is an important outcome. This paper presents an extensive overview on the topic ranging from descriptive findings to clinical trials.
Methods
This was a bibliographic review of the literature covering all full publications that appeared in English language biomedical journals between 1974 and 2007. The search strategy included a combination of key words 'quality of life' and 'breast cancer' or 'breast carcinoma' in titles. A total of 971 citations were identified and after exclusion of duplicates, the abstracts of 606 citations were reviewed. Of these, meetings abstracts, editorials, brief commentaries, letters, errata and dissertation abstracts and papers that appeared online and were indexed ahead of publication were also excluded. The remaining 477 papers were examined. The major findings are summarized and presented under several headings: instruments used, validation studies, measurement issues, surgical treatment, systemic therapies, quality of life as predictor of survival, psychological distress, supportive care, symptoms and sexual functioning.
Results
Instruments-Several valid instruments were used to measure quality of life in breast cancer patients. The European Organization for Research and Treatment of Cancer Core Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and its breast cancer specific complementary measure (EORTC QLQ-BR23) and the Functional Assessment Chronic Illness Therapy General questionnaire (FACIT-G) and its breast cancer module (FACIT-B) were found to be the most common and well developed instruments to measure quality of life in breast cancer patients. Surgery-different surgical procedures led to relatively similar results in terms of quality of life assessments, although mastectomy patients compared to conserving surgery patients usually reported a lower body image and sexual functioning. Systemic therapies-almost all studies indicated that breast cancer patients receiving chemotherapy might experience several side-effects and symptoms that negatively affect their quality of life. Adjuvant hormonal therapies also were found to have similar negative impact on quality of life, although in general they were associated with improved survival. Quality of life as predictor of survival-similar to known medical factors, quality of life data in metastatic breast cancer patients was found to be prognostic and predictive of survival time. Psychological distress-anxiety and depression were found to be common among breast cancer patients even years after the disease diagnosis and treatment. Psychological factors also were found to predict subsequent quality of life or even overall survival in breast cancer patients. Supportive care-clinical treatments to control emesis, or interventions such as counseling, providing social support and exercise could improve quality of life. Symptoms-Pain, fatigue, arm morbidity and postmenopausal symptoms were among the most common symptoms reported by breast cancer patients. As recommended, recognition and management of these symptoms is an important issue since such symptoms impair health-related quality of life. Sexual functioning-breast cancer patients especially younger patients suffer from poor sexual functioning that negatively affect quality of life.
Conclusion
There was quite an extensive body of the literature on quality of life in breast cancer patients. These papers have made a considerable contribution to improving breast cancer care, although their exact benefit was hard to define. However, quality of life data provided scientific evidence for clinical decision-making and conveyed helpful information concerning breast cancer patients' experiences during the course of the disease diagnosis, treatment, disease-free survival time, and recurrences; otherwise finding patient-centered solutions for evidence-based selection of optimal treatments, psychosocial interventions, patient-physician communications, allocation of resources, and indicating research priorities were impossible. It seems that more qualitative research is needed for a better understanding of the topic. In addition, issues related to the disease, its treatment side effects and symptoms, and sexual functioning should receive more attention when studying quality of life in breast cancer patients.
doi:10.1186/1756-9966-27-32
PMCID: PMC2543010  PMID: 18759983
15.  E2F4 regulatory program predicts patient survival prognosis in breast cancer 
Introduction
Genetic and molecular signatures have been incorporated into cancer prognosis prediction and treatment decisions with good success over the past decade. Clinically, these signatures are usually used in early-stage cancers to evaluate whether they require adjuvant therapy following surgical resection. A molecular signature that is prognostic across more clinical contexts would be a useful addition to current signatures.
Methods
We defined a signature for the ubiquitous tissue factor, E2F4, based on its shared target genes in multiple tissues. These target genes were identified by chromatin immunoprecipitation sequencing (ChIP-seq) experiments using a probabilistic method. We then computationally calculated the regulatory activity score (RAS) of E2F4 in cancer tissues, and examined how E2F4 RAS correlates with patient survival.
Results
Genes in our E2F4 signature were 21-fold more likely to be correlated with breast cancer patient survival time compared to randomly selected genes. Using eight independent breast cancer datasets containing over 1,900 unique samples, we stratified patients into low and high E2F4 RAS groups. E2F4 activity stratification was highly predictive of patient outcome, and our results remained robust even when controlling for many factors including patient age, tumor size, grade, estrogen receptor (ER) status, lymph node (LN) status, whether the patient received adjuvant therapy, and the patient’s other prognostic indices such as Adjuvant! and the Nottingham Prognostic Index scores. Furthermore, the fractions of samples with positive E2F4 RAS vary in different intrinsic breast cancer subtypes, consistent with the different survival profiles of these subtypes.
Conclusions
We defined a prognostic signature, the E2F4 regulatory activity score, and showed it to be significantly predictive of patient outcome in breast cancer regardless of treatment status and the states of many other clinicopathological variables. It can be used in conjunction with other breast cancer classification methods such as Oncotype DX to improve clinical outcome prediction.
Electronic supplementary material
The online version of this article (doi:10.1186/s13058-014-0486-7) contains supplementary material, which is available to authorized users.
doi:10.1186/s13058-014-0486-7
PMCID: PMC4303196  PMID: 25440089
16.  Redefining prognostic factors for breast cancer: YB-1 is a stronger predictor of relapse and disease-specific survival than estrogen receptor or HER-2 across all tumor subtypes 
Introduction
Gene expression analysis is used to subtype breast cancers such that the most aggressive tumors are identified, but translating this into clinical practice can be cumbersome. Our goal is to develop a universal biomarker that distinguishes patients at high risk across all breast cancer subtypes. We previously reported that Y-box binding protein-1 (YB-1), a transcription/translation factor, was a marker of poor prognosis in a cohort of 490 patients with breast cancer, but the study was not large enough to subtype the cancers. We therefore investigated whether YB-1 identifies patients at risk for either reduced relapse free survival or decreased r breast cancer specific survival (BCSS) across all tumor subtypes by evaluating 4,049 cases.
Methods
Tumor tissue microarrays, representing 4,049 cases of invasive breast cancers with 20 years of follow up, were subtyped by the expression profiles of estrogen receptor, progesterone receptor, or HER-2. We then addressed whether YB-1 expression identified patients at higher risk for relapse and/or lower BCSS.
Results
We found YB-1 to be a highly predictive biomarker of relapse (P < 2.5 × 10-20) and poor survival (P < 7.3 × 10-26) in the entire cohort and across all breast cancer subtypes. Patients with node-positive or node-negative cancer were more likely to die from the disease if YB-1 was expressed. This was further substantiated using a Cox regression model, which revealed that it was significantly associated with relapse and poor survival in a subtype independent manner (relapse patients, hazard ratio = 1.28, P < 8 × 10-3; all patients, hazard ratio = 1.45, P < 6.7 × 10-7). Moreover, YB-1 was superior to estrogen receptor and HER-2 as a prognostic marker for relapse and survival. For a subset of patients who were originally considered low risk and were therefore not given chemotherapy, YB-1 was indicative of poor survival (P < 7.1 × 10 -17). Likewise, YB-1 was predictive of decreased BCSS in tamoxifen-treated patients (P = 0.001); in this setting a Cox regression model once again demonstrated it to be an independent biomarker indicating poor survival (hazard ratio = 1.70, P = 0.022).
Conclusions
Expression of YB-1 universally identifies patients at high risk across all breast cancer subtypes and in situations where more aggressive treatment may be needed. We therefore propose that YB-1 may re-define high-risk breast cancer and thereby create opportunities for individualized therapy.
doi:10.1186/bcr2156
PMCID: PMC2614522  PMID: 18925950
17.  Classical and Novel Prognostic Markers for Breast Cancer and their Clinical Significance 
The use of biomarkers ensures breast cancer patients receive optimal treatment. Established biomarkers such as estrogen receptor (ER) and progesterone receptor (PR) have been playing significant roles in the selection and management of patients for endocrine therapy. HER2 is a strong predictor of response to trastuzumab. Recently, the roles of ER as a negative and HER2 as a positive indicator for chemotherapy have been established. Ki67 has traditionally been recognized as a poor prognostic factor, but recent studies suggest that measurement of Ki67-positive cells during treatment will more effectively predict treatment efficacy for both anti-hormonal and chemotherapy. p53 mutations are found in 20–35% of human breast cancers and are associated with aggressive disease with poor clinical outcome when the DNA-binding domain is mutated. The utility of cyclin D1 as a predictor of breast cancer prognosis is controversial, but cyclin D1b overexpression is associated with poor prognosis. Likewise, overexpression of the low molecular weight form of cyclin E1 protein predicts poor prognosis. Breast cancers from BRCA1/2 carriers often show high nuclear grades, negativity to ER/PR/HER2, and p53 mutations, and thus, are associated with poor prognosis. The prognostic values of other molecular markers, such as p14ARF, TBX2/3, VEGF in breast cancer are also discussed. Careful evaluation of these biomarkers with current treatment modality is required to determine whether their measurement or monitoring offer significant clinical benefits.
PMCID: PMC2883240  PMID: 20567632
breast cancer; prognosis; molecular marker; Ki67; ER; PR; HER2; cyclin D1; cyclin E; p53; ARF; TBX2/3; BRCA1/2; VEGF
18.  Association between Melanocytic Nevi and Risk of Breast Diseases: The French E3N Prospective Cohort 
PLoS Medicine  2014;11(6):e1001660.
Using data from the French E3N prospective cohort, Marina Kvaskoff and colleagues examine the association between number of cutaneous nevi and the risk for breast cancer.
Please see later in the article for the Editors' Summary
Background
While melanocytic nevi have been associated with genetic factors and childhood sun exposure, several observations also suggest a potential hormonal influence on nevi. To test the hypothesis that nevi are associated with breast tumor risk, we explored the relationships between number of nevi and benign and malignant breast disease risk.
Methods and Findings
We prospectively analyzed data from E3N, a cohort of French women aged 40–65 y at inclusion in 1990. Number of nevi was collected at inclusion. Hazard ratios (HRs) for breast cancer and 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression models. Associations of number of nevi with personal history of benign breast disease (BBD) and family history of breast cancer were estimated using logistic regression. Over the period 15 June 1990–15 June 2008, 5,956 incident breast cancer cases (including 5,245 invasive tumors) were ascertained among 89,902 women. In models adjusted for age, education, and known breast cancer risk factors, women with “very many” nevi had a significantly higher breast cancer risk (HR = 1.13, 95% CI = 1.01–1.27 versus “none”; ptrend = 0.04), although significance was lost after adjustment for personal history of BBD or family history of breast cancer. The 10-y absolute risk of invasive breast cancer increased from 3,749 per 100,000 women without nevi to 4,124 (95% CI = 3,674–4,649) per 100,000 women with “very many” nevi. The association was restricted to premenopausal women (HR = 1.40, ptrend = 0.01), even after full adjustment (HR = 1.34, ptrend = 0.03; phomogeneity = 0.04), but did not differ according to breast cancer type or hormone receptor status. In addition, we observed significantly positive dose–response relationships between number of nevi and history of biopsy-confirmed BBD (n = 5,169; ptrend<0.0001) and family history of breast cancer in first-degree relatives (n = 7,472; ptrend = 0.0003). The main limitations of our study include self-report of number of nevi using a qualitative scale, and self-reported history of biopsied BBD.
Conclusions
Our findings suggest associations between number of nevi and the risk of premenopausal breast cancer, BBD, and family history of breast cancer. More research is warranted to elucidate these relationships and to understand their underlying mechanisms.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
In 2012, nearly 1.7 million women worldwide discovered they had breast cancer, and about half a million women died from the disease. Breast cancer begins when cells in the breast acquire genetic changes that allow them to divide uncontrollably and to move around the body (metastasize). Uncontrolled cell division leads to the formation of a lump that can be detected by mammography (a breast X-ray) or by manual breast examination. Breast cancer is treated by surgical removal of the lump, or, if the cancer has started to spread, by removal of the whole breast (mastectomy). Surgery is usually followed by radiotherapy or chemotherapy to kill any remaining cancer cells. Because the female sex hormones estrogen and progesterone stimulate the growth of some tumors, drugs that block hormone receptors are also used to treat receptor-positive breast cancer. Nowadays, the prognosis (outlook) for women with breast cancer is good, and in developed countries, nearly 90% of affected women are still alive five years after diagnosis.
Why Was This Study Done?
Several hormone-related factors affect a woman's chances of developing breast cancer. For example, women who have no children or who have them late in life have a higher breast cancer risk than women who have several children when they are young because pregnancy alters sex hormone levels. Interestingly, the development of moles (nevi)—dark skin blemishes that are risk factors for the development of melanoma, a type of skin cancer—may also be affected by estrogen and progesterone. Thus, the number of nevi might be a marker of blood hormone levels and might predict breast cancer risk. In this prospective cohort study, the researchers test this hypothesis by investigating the association between how many moles a woman has and her breast cancer risk. A prospective cohort study enrolls a group (cohort) of people, determines their baseline characteristics, and follows them over time to see which characteristics are associated with the development of specific diseases.
What Did the Researchers Do and Find?
In 1990, the E3N prospective cohort study enrolled nearly 100,000 French women (mainly school teachers) aged 40–65 years to investigate cancer risk factors. The women completed a baseline questionnaire about their lifestyle and medical history, and regular follow-up questionnaires that asked about cancer occurrence. In the initial questionnaire, the women indicated whether they had no, a few, many, or very many moles. Between 1990 and 2008, nearly 6,000 women in the cohort developed breast cancer. Using statistical methods to calculate hazard ratios (an “HR” compares how often a particular event happens in two groups with different characteristics; an HR greater than one indicates that a specific characteristic is associated with an increased risk of the event), the researchers report that women with “very many” nevi had a significantly higher breast cancer risk (a higher risk that was unlikely to have occurred by chance) than women with no nevi. Specifically, the age-adjusted HR for breast cancer among women with “very many” nevi compared to women with no nevi was 1.17. After adjustment for a personal history of benign (noncancerous) breast disease and a family history of breast cancer (two established risk factors for breast cancer), the association between nevi and breast cancer risk among the whole cohort became nonsignificant. Notably, however, the association among only premenopausal women remained significant after full adjustment (HR = 1.34), which corresponded to an increase in ten-year absolute risk of invasive breast cancer from 2,515 per 100,000 women with no nevi to 3,370 per 100,000 women with “very many” nevi.
What Do These Findings Mean?
These findings suggest that among premenopausal women there is a modest association between nevi number and breast cancer risk. This noncausal relationship may indicate that nevi and breast diseases are affected in similar ways by hormones or share common genetic factors, but the accuracy of these findings may be limited by aspects of the study design. For example, self-report of nevi numbers using a qualitative scale may have introduced some inaccuracies into the estimates of the association between nevi number and breast cancer risk. Most importantly, these findings are insufficient to support the use of nevi counts in breast cancer screening or diagnosis. Rather, together with the findings reported by Zhang et al. in an independent PLOS Medicine Research Article, they suggest that further studies into the biological mechanisms underlying the relationship between nevi and breast cancer and the association itself should be undertaken.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001660.
This study is further discussed in a PLOS Medicine Perspective by Fuhrman and Cardenas
An independent PLOS Medicine Research Article by Zhang et al. also investigates the relationship between nevi number and breast cancer risk
The US National Cancer Institute provides comprehensive information about cancer (in English and Spanish), including detailed information for patients and professionals about breast cancer; it also has a fact sheet on moles
Cancer Research UK, a not-for profit organization, provides information about cancer, including detailed information on breast cancer
The UK National Health Service Choices website has information and personal stories about breast cancer; the not-for profit organization Healthtalkonline also provides personal stories about dealing with breast cancer
More information about the E3N prospective cohort study is available; detailed information is available in French
doi:10.1371/journal.pmed.1001660
PMCID: PMC4051602  PMID: 24915306
19.  DACH1: Its Role as a Classifier of Long Term Good Prognosis in Luminal Breast Cancer 
PLoS ONE  2014;9(1):e84428.
Background
Oestrogen receptor (ER) positive (luminal) tumours account for the largest proportion of females with breast cancer. Theirs is a heterogeneous disease presenting clinical challenges in managing their treatment. Three main biological luminal groups have been identified but clinically these can be distilled into two prognostic groups in which Luminal A are accorded good prognosis and Luminal B correlate with poor prognosis. Further biomarkers are needed to attain classification consensus. Machine learning approaches like Artificial Neural Networks (ANNs) have been used for classification and identification of biomarkers in breast cancer using high throughput data. In this study, we have used an artificial neural network (ANN) approach to identify DACH1 as a candidate luminal marker and its role in predicting clinical outcome in breast cancer is assessed.
Materials and methods
A reiterative ANN approach incorporating a network inferencing algorithm was used to identify ER-associated biomarkers in a publically available cDNA microarray dataset. DACH1 was identified in having a strong influence on ER associated markers and a positive association with ER. Its clinical relevance in predicting breast cancer specific survival was investigated by statistically assessing protein expression levels after immunohistochemistry in a series of unselected breast cancers, formatted as a tissue microarray.
Results
Strong nuclear DACH1 staining is more prevalent in tubular and lobular breast cancer. Its expression correlated with ER-alpha positive tumours expressing PgR, epithelial cytokeratins (CK)18/19 and ‘luminal-like’ markers of good prognosis including FOXA1 and RERG (p<0.05). DACH1 is increased in patients showing longer cancer specific survival and disease free interval and reduced metastasis formation (p<0.001). Nuclear DACH1 showed a negative association with markers of aggressive growth and poor prognosis.
Conclusion
Nuclear DACH1 expression appears to be a Luminal A biomarker predictive of good prognosis, but is not independent of clinical stage, tumour size, NPI status or systemic therapy.
doi:10.1371/journal.pone.0084428
PMCID: PMC3879319  PMID: 24392136
20.  Current treatment of early breast cancer: adjuvant and neoadjuvant therapy 
F1000Research  2014;3:198.
Breast cancer is the most commonly diagnosed cancer in women. The latest world cancer statistics calculated by the International Agency for Research on Cancer (IARC) revealed that 1,677,000 women were diagnosed with breast cancer in 2012 and 577,000 died. The TNM classification of malignant tumor (TNM) is the most commonly used staging system for breast cancer. Breast cancer is a group of very heterogeneous diseases. The molecular subtype of breast cancer carries important predictive and prognostic values, and thus has been incorporated in the basic initial process of breast cancer assessment/diagnosis. Molecular subtypes of breast cancers are divided into human epidermal growth factor receptor 2 positive (HER2 +), hormone receptor positive (estrogen or progesterone +), both positive, and triple negative breast cancer. By virtue of early detection via mammogram, the majority of breast cancers in developed parts of world are diagnosed in the early stage of the disease. Early stage breast cancers can be completely resected by surgery. Over time however, the disease may come back even after complete resection, which has prompted the development of an adjuvant therapy. Surgery followed by adjuvant treatment has been the gold standard for breast cancer treatment for a long time. More recently, neoadjuvant treatment has been recognized as an important strategy in biomarker and target evaluation. It is clinically indicated for patients with large tumor size, high nodal involvement, an inflammatory component, or for those wish to preserve remnant breast tissue. Here we review the most up to date conventional and developing treatments for different subtypes of early stage breast cancer.
doi:10.12688/f1000research.4340.1
PMCID: PMC4224200  PMID: 25400908
21.  Advantages of adjuvant chemotherapy for patients with triple-negative breast cancer at Stage II: usefulness of prognostic markers E-cadherin and Ki67 
Breast Cancer Research : BCR  2011;13(6):R122.
Introduction
Triple-negative breast cancer (TNBC), which is characterized by negativity for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 (HER2), is a high risk breast cancer that lacks specific targets for treatment selection. Chemotherapy is, therefore, the primary systemic modality used in the treatment of this disease, but reliable parameters to predict the chemosensitivity of TNBC have not been clinically available.
Methods
A total of 190 TNBC patients who had undergone a curative resection of a primary breast cancer were enrolled. The adjuvant chemotherapy was performed for 138 (73%) of 190 TNBC cases; 60 cases had an anthracyclin-based regimen and 78 a 5-fluorouracil-based regimen. The prognostic value of E-cadherin, Ki67 and p53 expression in the outcome of TNBC patients with adjuvant chemotherapy was evaluated by immunohistochemistry.
Results
The adjuvant therapy group, especially those with Stage II TNBC, had a more favorable prognosis than the surgery only group (P = 0.0043), while there was no significant difference in prognosis between the anthracyclin-based regimen and 5-fluorouracil-based regimen. Patients with E-cadherin-negative and Ki67-positive expression showed significantly worse overall survival time than those with either E-cadherin-positive or Ki67-negative expression (P < 0.001). Multivariate analysis showed that the combination of E-cadherin-negative and Ki67-positive expression was strongly predictive of poor overall survival (P = 0.004) in TNBC patients receiving adjuvant chemotherapy. In contrast, p53 status was not a specific prognostic factor.
Conclusions
Adjuvant therapy is beneficial for Stage II TNBC patients. The combination of E-cadherin and Ki67 status might be a useful prognostic marker indicating the need for adjuvant chemotherapy in Stage II TNBC patients.
doi:10.1186/bcr3068
PMCID: PMC3326564  PMID: 22126395
chemosensitivity; E-cadherin; Ki67; predictive marker; triple-negative breast cancer
22.  Older patients with breast cancer: is there bias in the treatment they receive? 
Breast cancer is the most frequent malignant tumor in women worldwide and as breast cancer incidence increases with increasing age, over 40% of new cases are diagnosed in women older than 65 years of age. However, older patients are not treated to the same extent as younger patients and increasing age at diagnosis predicts deviation from guidelines for all treatment modalities. Evidence-based medicine in older patients is lacking as they are usually excluded from clinical trials often because of existing comorbidities and limited life expectancy. Accordingly, there is a higher competing risk of death from other causes than breast cancer compared with younger patients and this may have led to the false interpretation that prognosis of breast cancer in older patients is relatively good. However, every treatment modality should be evaluated during treatment decision making. Multimodal therapy should not be routinely withheld as data show that disease-specific mortality increases with age, probably due to undertreatment. Prognostic markers, fitness and comorbidities rather than chronological age should determine optimal, individualized therapy. It is recommended that treatment decisions should be discussed in a multidisciplinary setting, ideally in combination with any form of geriatric assessment, to improve breast cancer outcome in the older population.
doi:10.1177/1758834012455684
PMCID: PMC3481560  PMID: 23118807
breast cancer; evidence-based medicine; older people; prognosis; treatment
23.  Intra-tumor Genetic Heterogeneity and Mortality in Head and Neck Cancer: Analysis of Data from The Cancer Genome Atlas 
PLoS Medicine  2015;12(2):e1001786.
Background
Although the involvement of intra-tumor genetic heterogeneity in tumor progression, treatment resistance, and metastasis is established, genetic heterogeneity is seldom examined in clinical trials or practice. Many studies of heterogeneity have had prespecified markers for tumor subpopulations, limiting their generalizability, or have involved massive efforts such as separate analysis of hundreds of individual cells, limiting their clinical use. We recently developed a general measure of intra-tumor genetic heterogeneity based on whole-exome sequencing (WES) of bulk tumor DNA, called mutant-allele tumor heterogeneity (MATH). Here, we examine data collected as part of a large, multi-institutional study to validate this measure and determine whether intra-tumor heterogeneity is itself related to mortality.
Methods and Findings
Clinical and WES data were obtained from The Cancer Genome Atlas in October 2013 for 305 patients with head and neck squamous cell carcinoma (HNSCC), from 14 institutions. Initial pathologic diagnoses were between 1992 and 2011 (median, 2008). Median time to death for 131 deceased patients was 14 mo; median follow-up of living patients was 22 mo. Tumor MATH values were calculated from WES results. Despite the multiple head and neck tumor subsites and the variety of treatments, we found in this retrospective analysis a substantial relation of high MATH values to decreased overall survival (Cox proportional hazards analysis: hazard ratio for high/low heterogeneity, 2.2; 95% CI 1.4 to 3.3). This relation of intra-tumor heterogeneity to survival was not due to intra-tumor heterogeneity’s associations with other clinical or molecular characteristics, including age, human papillomavirus status, tumor grade and TP53 mutation, and N classification. MATH improved prognostication over that provided by traditional clinical and molecular characteristics, maintained a significant relation to survival in multivariate analyses, and distinguished outcomes among patients having oral-cavity or laryngeal cancers even when standard disease staging was taken into account. Prospective studies, however, will be required before MATH can be used prognostically in clinical trials or practice. Such studies will need to examine homogeneously treated HNSCC at specific head and neck subsites, and determine the influence of cancer therapy on MATH values. Analysis of MATH and outcome in human-papillomavirus-positive oropharyngeal squamous cell carcinoma is particularly needed.
Conclusions
To our knowledge this study is the first to combine data from hundreds of patients, treated at multiple institutions, to document a relation between intra-tumor heterogeneity and overall survival in any type of cancer. We suggest applying the simply calculated MATH metric of heterogeneity to prospective studies of HNSCC and other tumor types.
In this study, Rocco and colleagues examine data collected as part of a large, multi-institutional study, to validate a measure of tumor heterogeneity called MATH and determine whether intra-tumor heterogeneity is itself related to mortality.
Editors’ Summary
Background
Normally, the cells in human tissues and organs only reproduce (a process called cell division) when new cells are needed for growth or to repair damaged tissues. But sometimes a cell somewhere in the body acquires a genetic change (mutation) that disrupts the control of cell division and allows the cell to grow continuously. As the mutated cell grows and divides, it accumulates additional mutations that allow it to grow even faster and eventually from a lump, or tumor (cancer). Other mutations subsequently allow the tumor to spread around the body (metastasize) and destroy healthy tissues. Tumors can arise anywhere in the body—there are more than 200 different types of cancer—and about one in three people will develop some form of cancer during their lifetime. Many cancers can now be successfully treated, however, and people often survive for years after a diagnosis of cancer before, eventually, dying from another disease.
Why Was This Study Done?
The gradual acquisition of mutations by tumor cells leads to the formation of subpopulations of cells, each carrying a different set of mutations. This “intra-tumor heterogeneity” can produce tumor subclones that grow particularly quickly, that metastasize aggressively, or that are resistant to cancer treatments. Consequently, researchers have hypothesized that high intra-tumor heterogeneity leads to worse clinical outcomes and have suggested that a simple measure of this heterogeneity would be a useful addition to the cancer staging system currently used by clinicians for predicting the likely outcome (prognosis) of patients with cancer. Here, the researchers investigate whether a measure of intra-tumor heterogeneity called “mutant-allele tumor heterogeneity” (MATH) is related to mortality (death) among patients with head and neck squamous cell carcinoma (HNSCC)—cancers that begin in the cells that line the moist surfaces inside the head and neck, such as cancers of the mouth and the larynx (voice box). MATH is based on whole-exome sequencing (WES) of tumor and matched normal DNA. WES uses powerful DNA-sequencing systems to determine the variations of all the coding regions (exons) of the known genes in the human genome (genetic blueprint).
What Did the Researchers Do and Find?
The researchers obtained clinical and WES data for 305 patients who were treated in 14 institutions, primarily in the US, after diagnosis of HNSCC from The Cancer Genome Atlas, a catalog established by the US National Institutes of Health to map the key genomic changes in major types and subtypes of cancer. They calculated tumor MATH values for the patients from their WES results and retrospectively analyzed whether there was an association between the MATH values and patient survival. Despite the patients having tumors at various subsites and being given different treatments, every 10% increase in MATH value corresponded to an 8.8% increased risk (hazard) of death. Using a previously defined MATH-value cutoff to distinguish high- from low-heterogeneity tumors, compared to patients with low-heterogeneity tumors, patients with high-heterogeneity tumors were more than twice as likely to die (a hazard ratio of 2.2). Other statistical analyses indicated that MATH provided improved prognostic information compared to that provided by established clinical and molecular characteristics and human papillomavirus (HPV) status (HPV-positive HNSCC at some subsites has a better prognosis than HPV-negative HNSCC). In particular, MATH provided prognostic information beyond that provided by standard disease staging among patients with mouth or laryngeal cancers.
What Do These Findings Mean?
By using data from more than 300 patients treated at multiple institutions, these findings validate the use of MATH as a measure of intra-tumor heterogeneity in HNSCC. Moreover, they provide one of the first large-scale demonstrations that intra-tumor heterogeneity is clinically important in the prognosis of any type of cancer. Before the MATH metric can be used in clinical trials or in clinical practice as a prognostic tool, its ability to predict outcomes needs to be tested in prospective studies that examine the relation between MATH and the outcomes of patients with identically treated HNSCC at specific head and neck subsites, that evaluate the use of MATH for prognostication in other tumor types, and that determine the influence of cancer treatments on MATH values. Nevertheless, these findings suggest that MATH should be considered as a biomarker for survival in HNSCC and other tumor types, and raise the possibility that clinicians could use MATH values to decide on the best treatment for individual patients and to choose patients for inclusion in clinical trials.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001786.
The US National Cancer Institute (NCI) provides information about cancer and how it develops and about head and neck cancer (in English and Spanish)
Cancer Research UK, a not-for-profit organization, provides general information about cancer and how it develops, and detailed information about head and neck cancer; the Merseyside Regional Head and Neck Cancer Centre provides patient stories about HNSCC
Wikipedia provides information about tumor heterogeneity, and about whole-exome sequencing (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Information about The Cancer Genome Atlas is available
A PLOS Blog entry by Jessica Wapner explains more about MATH
doi:10.1371/journal.pmed.1001786
PMCID: PMC4323109  PMID: 25668320
24.  ELF5 Suppresses Estrogen Sensitivity and Underpins the Acquisition of Antiestrogen Resistance in Luminal Breast Cancer 
PLoS Biology  2012;10(12):e1001461.
The transcription factor ELF5 is responsible for gene expression patterning underlying molecular subtypes of breast cancer and may mediate acquired resistance to anti-estrogen therapy.
We have previously shown that during pregnancy the E-twenty-six (ETS) transcription factor ELF5 directs the differentiation of mammary progenitor cells toward the estrogen receptor (ER)-negative and milk producing cell lineage, raising the possibility that ELF5 may suppress the estrogen sensitivity of breast cancers. To test this we constructed inducible models of ELF5 expression in ER positive luminal breast cancer cells and interrogated them using transcript profiling and chromatin immunoprecipitation of DNA followed by DNA sequencing (ChIP-Seq). ELF5 suppressed ER and FOXA1 expression and broadly suppressed ER-driven patterns of gene expression including sets of genes distinguishing the luminal molecular subtype. Direct transcriptional targets of ELF5, which included FOXA1, EGFR, and MYC, accurately classified a large cohort of breast cancers into their intrinsic molecular subtypes, predicted ER status with high precision, and defined groups with differential prognosis. Knockdown of ELF5 in basal breast cancer cell lines suppressed basal patterns of gene expression and produced a shift in molecular subtype toward the claudin-low and normal-like groups. Luminal breast cancer cells that acquired resistance to the antiestrogen Tamoxifen showed greatly elevated levels of ELF5 and its transcriptional signature, and became dependent on ELF5 for proliferation, compared to the parental cells. Thus ELF5 provides a key transcriptional determinant of breast cancer molecular subtype by suppression of estrogen sensitivity in luminal breast cancer cells and promotion of basal characteristics in basal breast cancer cells, an action that may be utilised to acquire antiestrogen resistance.
Author Summary
The molecular subtypes of breast cancer are distinguished by their intrinsic patterns of gene expression and can be used to group patients with different prognoses and treatment options. Although molecular subtyping tests are currently under evaluation, some of them are already in use to better tailor therapy for patients; however, the molecular events that are responsible for these different patterns of gene expression in breast cancer are largely undefined. The elucidation of their mechanistic basis would improve our understanding of the disease process and enhance the chances of developing better predictive and prognostic markers, new therapies, and interventions to overcome resistance to existing therapies. Here, we show that the transcription factor ELF5 is responsible for much of the patterning of gene expression that distinguishes the breast cancer subtypes. Additionally, our data suggest that ELF5 may also be involved in the development of resistance to therapies designed to stop estrogen stimulation of breast cancer. These effects of ELF5 appear to represent a partial carryover into breast cancer of its normal role in the mammary gland, where it is responsible for the development of milk-producing structures during pregnancy.
doi:10.1371/journal.pbio.1001461
PMCID: PMC3531499  PMID: 23300383
25.  Epidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer 
Executive Summary
In February 2010, the Medical Advisory Secretariat (MAS) began work on evidence-based reviews of the literature surrounding three pharmacogenomic tests. This project came about when Cancer Care Ontario (CCO) asked MAS to provide evidence-based analyses on the effectiveness and cost-effectiveness of three oncology pharmacogenomic tests currently in use in Ontario.
Evidence-based analyses have been prepared for each of these technologies. These have been completed in conjunction with internal and external stakeholders, including a Provincial Expert Panel on Pharmacogenetics (PEPP). Within the PEPP, subgroup committees were developed for each disease area. For each technology, an economic analysis was also completed by the Toronto Health Economics and Technology Assessment Collaborative (THETA) and is summarized within the reports.
The following reports can be publicly accessed at the MAS website at: http://www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.html
Gene Expression Profiling for Guiding Adjuvant Chemotherapy Decisions in Women with Early Breast Cancer: An Evidence-Based Analysis
Epidermal Growth Factor Receptor Mutation (EGFR) Testing for Prediction of Response to EGFR-Targeting Tyrosine Kinase Inhibitor (TKI) Drugs in Patients with Advanced Non-Small-Cell Lung Cancer: an Evidence-Based Analysis
K-RAS testing in Treatment Decisions for Advanced Colorectal Cancer: an Evidence-Based Analysis
Objective
The Medical Advisory Secretariat undertook a systematic review of the evidence on the clinical effectiveness and cost-effectiveness of epidermal growth factor receptor (EGFR) mutation testing compared with no EGFR mutation testing to predict response to tyrosine kinase inhibitors (TKIs), gefitinib (Iressa®) or erlotinib (Tarceva®) in patients with advanced non-small cell lung cancer (NSCLC).
Clinical Need: Target Population and Condition
With an estimated 7,800 new cases and 7,000 deaths last year, lung cancer is the leading cause of cancer deaths in Ontario. Those with unresectable or advanced disease are commonly treated with concurrent chemoradiation or platinum-based combination chemotherapy. Although response rates to cytotoxic chemotherapy for advanced NSCLC are approximately 30 to 40%, all patients eventually develop resistance and have a median survival of only 8 to 10 months. Treatment for refractory or relapsed disease includes single-agent treatment with docetaxel, pemetrexed or EGFR-targeting TKIs (gefitinib, erlotinib). TKIs disrupt EGFR signaling by competing with adenosine triphosphate (ATP) for the binding sites at the tyrosine kinase (TK) domain, thus inhibiting the phosphorylation and activation of EGFRs and the downstream signaling network. Gefitinib and erlotinib have been shown to be either non-inferior or superior to chemotherapy in the first- or second-line setting (gefitinib), or superior to placebo in the second- or third-line setting (erlotinib).
Certain patient characteristics (adenocarcinoma, non-smoking history, Asian ethnicity, female gender) predict for better survival benefit and response to therapy with TKIs. In addition, the current body of evidence shows that somatic mutations in the EGFR gene are the most robust biomarkers for EGFR-targeting therapy selection. Drugs used in this therapy, however, can be costly, up to C$ 2000 to C$ 3000 per month, and they have only approximately a 10% chance of benefiting unselected patients. For these reasons, the predictive value of EGFR mutation testing for TKIs in patients with advanced NSCLC needs to be determined.
The Technology: EGFR mutation testing
The EGFR gene sequencing by polymerase chain reaction (PCR) assays is the most widely used method for EGFR mutation testing. PCR assays can be performed at pathology laboratories across Ontario. According to experts in the province, sequencing is not currently done in Ontario due to lack of adequate measurement sensitivity. A variety of new methods have been introduced to increase the measurement sensitivity of the mutation assay. Some technologies such as single-stranded conformational polymorphism, denaturing high-performance liquid chromatography, and high-resolution melting analysis have the advantage of facilitating rapid mutation screening of large numbers of samples with high measurement sensitivity but require direct sequencing to confirm the identity of the detected mutations. Other techniques have been developed for the simple, but highly sensitive detection of specific EGFR mutations, such as the amplification refractory mutations system (ARMS) and the peptide nucleic acid-locked PCR clamping. Others selectively digest wild-type DNA templates with restriction endonucleases to enrich mutant alleles by PCR. Experts in the province of Ontario have commented that currently PCR fragment analysis for deletion and point mutation conducts in Ontario, with measurement sensitivity of 1% to 5%.
Research Questions
In patients with locally-advanced or metastatic NSCLC, what is the clinical effectiveness of EGFR mutation testing for prediction of response to treatment with TKIs (gefitinib, erlotinib) in terms of progression-free survival (PFS), objective response rates (ORR), overall survival (OS), and quality of life (QoL)?
What is the impact of EGFR mutation testing on overall clinical decision-making for patients with advanced or metastatic NSCLC?
What is the cost-effectiveness of EGFR mutation testing in selecting patients with advanced NSCLC for treatment with gefitinib or erlotinib in the first-line setting?
What is the budget impact of EGFR mutation testing in selecting patients with advanced NSCLC for treatment with gefitinib or erlotinib in the second- or third-line setting?
Methods
A literature search was performed on March 9, 2010 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, Wiley Cochrane, CINAHL, Centre for Reviews and Dissemination/International Agency for Health Technology Assessment for studies published from January 1, 2004 until February 28, 2010 using the following terms:
Non-Small-Cell Lung Carcinoma
Epidermal Growth Factor Receptor
An automatic literature update program also extracted all papers published from February 2010 until August 2010. Abstracts were reviewed by a single reviewer and for those studies meeting the eligibility criteria full-text articles were obtained. Reference lists were also examined for any additional relevant studies not identified through the search. Articles with unknown eligibility were reviewed with a second clinical epidemiologist, and then a group of epidemiologists, until consensus was established. The quality of evidence was assessed as high, moderate, low or very low according to GRADE methodology.
The inclusion criteria were as follows:
Population: patients with locally advanced or metastatic NSCLC (stage IIIB or IV)
Procedure: EGFR mutation testing before treatment with gefitinib or erlotinib
Language: publication in English
Published health technology assessments, guidelines, and peer-reviewed literature (abstracts, full text, conference abstract)
Outcomes: progression-free survival (PFS), Objective response rate (ORR), overall survival (OS), quality of life (QoL).
The exclusion criteria were as follows:
Studies lacking outcomes specific to those of interest
Studies focused on erlotinib maintenance therapy
Studies focused on gefitinib or erlotinib use in combination with cytotoxic agents or any other drug
Grey literature, where relevant, was also reviewed.
Outcomes of Interest
PFS
ORR determined by means of the Response Evaluation Criteria in Solid Tumours (RECIST)
OS
QoL
Quality of Evidence
The quality of the Phase II trials and observational studies was based on the method of subject recruitment and sampling, possibility of selection bias, and generalizability to the source population. The overall quality of evidence was assessed as high, moderate, low or very low according to the GRADE Working Group criteria.
Summary of Findings
Since the last published health technology assessment by Blue Cross Blue Shield Association in 2007 there have been a number of phase III trials which provide evidence of predictive value of EGFR mutation testing in patients who were treated with gefitinib compared to chemotherapy in the first- or second-line setting. The Iressa Pan Asian Study (IPASS) trial showed the superiority of gefitinib in terms of PFS in patients with EGFR mutations versus patients with wild-type EGFR (Hazard ratio [HR], 0.48, 95%CI; 0.36-0.64 versus HR, 2.85; 95%CI, 2.05-3.98). Moreover, there was a statistically significant increased ORR in patients who received gefitinib and had EGFR mutations compared to patients with wild-type EGFR (71% versus 1%). The First-SIGNAL trial in patients with similar clinical characteristics as IPASS as well as the NEJ002 and WJTOG3405 trials that included only patients with EGFR mutations, provide confirmation that gefitinib is superior to chemotherapy in terms of improved PFS or higher ORR in patients with EGFR mutations. The INTEREST trial further indicated that patients with EGFR mutations had prolonged PFS and higher ORR when treated with gefitinib compared with docetaxel.
In contrast, there is still a paucity of strong evidence regarding the predictive value of EGFR mutation testing for response to erlotinib in the second- or third-line setting. The BR.21 trial randomized 731 patients with NSCLC who were refractory or intolerant to prior first- or second-line chemotherapy to receive erlotinib or placebo. While the HR of 0.61 (95%CI, 0.51-0.74) favored erlotinib in the overall population, this was not a significant in the subsequent retrospective subgroup analysis. A retrospective evaluation of 116 of the BR.21 tumor samples demonstrated that patients with EGFR mutations had significantly higher ORRs when treated with erlotinib compared with placebo (27% versus 7%; P=0.03). However, erlotinib did not confer a significant survival benefit compared with placebo in patients with EGFR mutations (HR, 0.55; 95%CI, 0.25-1.19) versus wild-type (HR, 0.74; 95%CI, 0.52-1.05). The interaction between EGFR mutation status and erlotinib use was not significant (P=0.47). The lack of significance could be attributable to a type II error since there was a low sample size that was available for subgroup analysis.
A series of phase II studies have examined the clinical effectiveness of erlotinib in patients known to have EGFR mutations. Evidence from these studies has consistently shown that erlotinib yields a very high ORR (typically 70% vs. 4%) and a prolonged PFS (9 months vs. 2 months) in patients with EGFR mutations compared with patients with wild-type EGFR. Although having a prolonged PFS and higher respond in EGFR mutated patients might be due to a better prognostic profile regardless of the treatment received. In the absence of a comparative treatment or placebo control group, it is difficult to determine if the observed differences in survival benefit in patients with EGFR mutation is attributed to prognostic or predictive value of EGFR mutation status.
Conclusions
Based on moderate quality of evidence, patients with locally advanced or metastatic NSCLC with adenocarcinoma histology being treated with gefitinib in the first-line setting are highly likely to benefit from gefitinib if they have EGFR mutations compared to those with wild-type EGFR. This advantage is reflected in improved PFS, ORR and QoL in patients with EGFR mutation who are being treated with gefitinib relative to patients treated with chemotherapy.
Based on low quality of evidence, in patients with locally advanced or metastatic NSCLC who are being treated with erlotinib, the identification of EGFR mutation status selects those who are most likely to benefit from erlotinib relative to patients treated with placebo in the second or third-line setting.
PMCID: PMC3377519  PMID: 23074402

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