Previously, we developed a radiosensitivity molecular signature (RSI) that was clinically-validated in three independent datasets (rectal, esophageal, head and neck) in 118 patients. Here, we test RSI in radiotherapy (RT) treated breast cancer patients.
RSI was tested in two previously published breast cancer datasets. Patients were treated at the Karolinska University Hospital (n=159) and Erasmus Medical Center (n=344). RSI was applied as previously described.
We tested RSI in RT-treated patients (Karolinska). Patients predicted to be radiosensitive (RS) had an improved 5 yr relapse-free survival when compared with radioresistant (RR) patients (95% vs. 75%, p=0.0212) but there was no difference between RS/RR patients treated without RT (71% vs. 77%, p=0.6744), consistent with RSI being RT-specific (interaction term RSIxRT, p=0.05). Similarly, in the Erasmus dataset RT-treated RS patients had an improved 5-year distant-metastasis-free survival over RR patients (77% vs. 64%, p=0.0409) but no difference was observed in patients treated without RT (RS vs. RR, 80% vs. 81%, p=0.9425). Multivariable analysis showed RSI is the strongest variable in RT-treated patients (Karolinska, HR=5.53, p=0.0987, Erasmus, HR=1.64, p=0.0758) and in backward selection (removal alpha of 0.10) RSI was the only variable remaining in the final model. Finally, RSI is an independent predictor of outcome in RT-treated ER+ patients (Erasmus, multivariable analysis, HR=2.64, p=0.0085).
RSI is validated in two independent breast cancer datasets totaling 503 patients. Including prior data, RSI is validated in five independent cohorts (621 patients) and represents, to our knowledge, the most extensively validated molecular signature in radiation oncology.
radiosensitivity; predictive biomarkers; gene expression; molecular signature; breast cancer
The European Cancer Concord is a unique patient-centered partnership that will act as a catalyst to achieve improved access to an optimal standard of cancer care and research for European citizens. In order to provide tangible benefits for European cancer patients, the partnership proposes the creation of a “European Cancer Patient’s Bill of Rights,” a patient charter that will underpin equitable access to an optimal standard of care for Europe’s citizens.
Long-term estrogen deprivation models are widely employed in an in vitro setting to recapitulate the hormonal milieu of breast cancer patients treated with endocrine therapy. Despite the wealth information we have garnered from these models thus far, a comprehensive time-course analysis of the estrogen (ER), progesterone (PR), and human epidermal growth factor 2 (HER-2/neu) receptors on the gene and protein level, coupled with expression array data is currently lacking. We aimed to address this knowledge gap in order to enhance our understanding of endocrine therapy resistance in breast cancer patients.
ER positive MCF7 and BT474 breast cancer cells were grown in estrogen depleted medium for 10 months with the ER negative MDA-MB-231 cell line employed as control. ER, PR and HER-2/neu expression were analysed at defined short and long-term time points by immunocytochemistry (ICC), and quantitative real-time RT-PCR (qRT-PCR). Microarray analysis was performed on representative samples.
MCF7 cells cultured in estrogen depleted medium displayed decreasing expression of ER up to 8 weeks, which was then re-expressed at 10 months. PR was also down-regulated at early time points and remained so for the duration of the study. BT474 cells generally displayed no changes in ER during the first 8 weeks of deprivation, however its expression was significantly decreased at 10 months. PR expression was also down-regulated early in BT474 samples and was absent at later time points. Finally, microarray data revealed that genes and cell processes down-regulated in both cell lines at 6 weeks overlapped with those down-regulated in aromatase inhibitor treated breast cancer patients.
Our data demonstrate that expression of ER, PR, and cell metabolic/proliferative processes are unstable in response to long-term estrogen deprivation in breast cancer cell lines. These results mirror recent clinical findings and again emphasize the utility of LTED models in translational research.
The 13th St Gallen International Breast Cancer Conference (2013) Expert Panel reviewed and endorsed substantial new evidence on aspects of the local and regional therapies for early breast cancer, supporting less extensive surgery to the axilla and shorter durations of radiation therapy. It refined its earlier approach to the classification and management of luminal disease in the absence of amplification or overexpression of the Human Epidermal growth factor Receptor 2 (HER2) oncogene, while retaining essentially unchanged recommendations for the systemic adjuvant therapy of HER2-positive and ‘triple-negative’ disease. The Panel again accepted that conventional clinico-pathological factors provided a surrogate subtype classification, while noting that in those areas of the world where multi-gene molecular assays are readily available many clinicians prefer to base chemotherapy decisions for patients with luminal disease on these genomic results rather than the surrogate subtype definitions. Several multi-gene molecular assays were recognized as providing accurate and reproducible prognostic information, and in some cases prediction of response to chemotherapy. Cost and availability preclude their application in many environments at the present time. Broad treatment recommendations are presented. Such recommendations do not imply that each Panel member agrees: indeed, among more than 100 questions, only one (trastuzumab duration) commanded 100% agreement. The various recommendations in fact carried differing degrees of support, as reflected in the nuanced wording of the text below and in the votes recorded in supplementary Appendix S1, available at Annals of Oncology online. Detailed decisions on treatment will as always involve clinical consideration of disease extent, host factors, patient preferences and social and economic constraints.
surgery; radiation therapy; systemic adjuvant therapies; early breast cancer; St Gallen Consensus; subtypes
Gene expression signatures indicative of tumor proliferative capacity and tumor-immune cell interactions have emerged as principal biology-driven predictors of breast cancer outcomes. How these signatures relate to one another in biological and prognostic contexts remains to be clarified.
To investigate the relationship between proliferation and immune gene signatures, we analyzed an integrated dataset of 1,954 clinically annotated breast tumor expression profiles randomized into training and test sets to allow two-way discovery and validation of gene-survival associations. Hierarchical clustering revealed a large cluster of distant metastasis-free survival-associated genes with known immunological functions that further partitioned into three distinct immune metagenes likely reflecting B cells and/or plasma cells; T cells and natural killer cells; and monocytes and/or dendritic cells. A proliferation metagene allowed stratification of cases into proliferation tertiles. The prognostic strength of these metagenes was largely restricted to tumors within the highest proliferation tertile, though intrinsic subtype-specific differences were observed in the intermediate and low proliferation tertiles. In highly proliferative tumors, high tertile immune metagene expression equated with markedly reduced risk of metastasis whereas tumors with low tertile expression of any one of the three immune metagenes were associated with poor outcome despite higher expression of the other two metagenes.
These findings suggest that a productive interplay among multiple immune cell types at the tumor site promotes long-term anti-metastatic immunity in a proliferation-dependent manner. The emergence of a subset of effective immune responders among highly proliferative tumors has novel prognostic ramifications.
Breast cancer; gene signatures; hierarchical clustering; immune metagene; intrinsic subtypes; metagene tertiles; multivariable analysis; prognosis; proliferation metagene; survival analysis
Changes in iron regulation characterize the malignant state. However, the pathways that effect these changes and their specific impact on prognosis remain poorly understood. We capitalized on publicly available microarray datasets comprising 674 breast cancer cases to systematically investigate how expression of genes related to iron metabolism is linked to breast cancer prognosis. Of 61 genes involved in iron regulation, 49% were statistically significantly associated with distant metastasis-free survival (DMFS). Cases were divided into test and training cohorts and the supervised principal component method was used to stratify cases into risk groups. Optimal risk stratification was achieved with a model comprising 16 genes, which we term the iron regulatory gene signature (IRGS). Multivariable analysis revealed that the IRGS contributes information not captured by conventional prognostic indicators (hazard ratio 1.61; 95% CI 1.16–2.24; p=0.004). The IRGS successfully stratified homogeneously treated patients, including ER+ patients treated with tamoxifen monotherapy, both with (p=0.006) and without (p=0.03) lymph node metastases. To test whether multiple pathways were embedded within the IRGS, we evaluated the performance of two gene dyads with known roles in iron biology in ER+ patients treated with tamoxifen monotherapy (n=371). For both dyads, gene combinations that minimized intracellular iron content (anti-import: TFRCLow/HFEHigh; or pro-export: FPHigh/HAMPLow) were associated with favorable prognosis (p<0.005). Although the clinical utility of the IRGS will require further evaluation, its ability to both identify high risk patients within traditionally low risk groups and low risk patients within high risk groups has the potential to affect therapeutic decision-making.
We retrospectively reviewed the results of stereotactic body radiotherapy (SBRT) in 46 patients with a total of 136 metastases from primary sarcoma. The purpose of this study was to evaluate the overall response rate and side effects of SBRT in metastatic sarcoma. The patients were treated at Karolinska University Hospital between 1994 and 2005, using 3D conformal multifield technique and a stereotactic body-frame. Prescribed doses ranged from 4 to 20 Gy per fraction in 1–5 fractions, with total doses of 10–48 Gy. All 46 patients were diagnosed with a primary sarcoma. The treated metastases were localized mainly in the lungs. A total number of 136 metastases were treated (1–14 per patient). Overall response rate (local control = CR, PR and SD) for each tumour was 88 % (119/135). Median follow-up was 21.8 months (range 2.7–112.8 months). Thirteen patients (31 %) were long-term survivors (>36 months), and 5 patients are still alive after last follow-up. Two cases of serious non-lethal side effects were seen, one patient had a colon perforation and another patient had contracture of the hip region. SBRT is a safe, convenient and effective non-invasive treatment with high local control for patients with metastatic sarcoma.
Electronic supplementary material
The online version of this article (doi:10.1007/s12032-012-0256-2) contains supplementary material, which is available to authorized users.
Stereotactic body radiotherapy; Sarcoma; Metastases; High-dose fraction; Body-frame
The oncogenic capabilities of the cell cycle protein cyclin D1 have long been established in a breast cancer setting. The CCND1 gene is amplified in up to 15 % of breast tumors, with overexpression of its corresponding protein found in up to 50 % of cases. While gene amplification is consistently associated with reduced patient survival times and treatment resistance, repeated attempts to clarify the prognostic and predictive impact of the cyclin D1 protein in breast cancer have yielded contrasting results. Here, we recommend that any examination of cyclin D1 in a patient cohort should begin by determining CCND1 copy number, with subsequent removal and separate analysis of amplified cases. Next, the remaining tumors should be examined for cyclin D1 protein expression in the context of well-defined breast cancer subgroups. Only in this manner can the true clinical value of cyclin D1 be fully elucidated.
Cyclin D1; Breast cancer; Amplification; Protein expression; Independent analysis; Molecular subgroups; Ki67
The dyslexia candidate gene, DYX1C1, shown to regulate and interact with estrogen receptors and involved in the regulation of neuronal migration, has recently been proposed as a putative cancer biomarker. This study was undertaken to assess the prognostic value and therapy-predictive potential of DYX1C1 mRNA and protein expression in breast cancer.
DYX1C1 mRNA expression was assessed at the mRNA level in three independent population-derived patient cohorts. An association to estrogen/progesterone receptor status, Elston grade, gene expression subtype and lymph node status was analyzed within these cohorts. DYX1C1 protein expression was examined using immunohistochemistry in cancer and normal breast tissue. The statistical analyses were performed using the non-parametric Wilcoxon rank-sum test, ANOVA, Fisher's exact test and a multivariate proportional hazard (Cox) model.
DYX1C1 mRNA is significantly more highly expressed in tumors that have been classified as estrogen receptor α and progesterone receptor-positive. The expression of DYX1C1 among the molecular subtypes shows the lowest median expression within the basal type tumors, which are considered to have the worst prognosis. The expression of DYX1C1 is significantly lower in tumors graded as Elston grade 3 compared with grades 1 and 2. DYX1C1 protein is expressed in 88% of tumors and in all 10 normal breast tissues examined. Positive protein expression was significantly correlated to overall survival (Hazard ratio 3.44 [CI 1.84-6.42]) of the patients but not to any of the variables linked with mRNA expression.
We show that the expression of DYX1C1 in breast cancer is associated with several clinicopathological parameters and that loss of DYX1C1 correlates with a more aggressive disease, in turn indicating that DYX1C1 is a potential prognostic biomarker in breast cancer.
DYX1C1; Breast cancer; Estrogen receptor; Dyslexia
The p53 tumor suppressor is a key mediator of cellular responses to various stresses. Here we show that under conditions of basal physiologic and cell-culture stress, p53 inhibits expression of the CD44 cell-surface molecule via binding to a non-canonical p53-binding sequence in the CD44 promoter. This interaction enables an untransformed cell to respond to stress-induced, p53-dependent cytostatic and apoptotic signals that would otherwise be blocked by the actions of CD44. In the absence of p53 function, the resulting de-repressed CD44 expression is essential for the growth and tumor-initiating ability of highly tumorigenic mammary epithelial cells. In both tumorigenic and non-tumorigenic cells, CD44’s expression is positively regulated by p63, a paralogue of p53. Our data indicate that CD44 is a key tumor-promoting agent in transformed tumor cells lacking p53 function. They also suggest that the de-repression of CD44 resulting from inactivation of p53 can potentially aid the survival of immortalized, premalignant, cells.
The prognostic value of grading in breast cancer can be increased with microarray technology, but proposed strategies are disadvantaged by the use of specific training data or parallel microscopic grading. Here, we investigate the performance of a method that uses no information outside the breast profile of interest.
In 251 profiled tumours we optimised a method that achieves grading by comparing rank means for genes predictive of high and low grade biology; a simpler method that allows for truly independent estimation of accuracy. Validation was carried out in 594 patients derived from several independent data sets. We found that accuracy was good: for low grade (G1) tumors 83- 94%, for high grade (G3) tumors 74- 100%. In keeping with aim of improved grading, two groups of intermediate grade (G2) cancers with significantly different outcome could be discriminated.
This validates the concept of microarray-based grading in breast cancer, and provides a more practical method to achieve it. A simple R script for grading is available in an additional file. Clinical implementation could achieve better estimation of recurrence risk for 40 to 50% of breast cancer patients.
Breast Neoplasms; Microarray Analysis; Histology; Prognosis; Female
Male breast cancer is a rare disease, accounting for less than 1% of all breast cancer diagnoses worldwide. Most data on male breast cancer comes from small single-institution studies, and because of the paucity of data, the optimal treatment for male breast cancer is not known. This article summarizes a multidisciplinary international meeting on male breast cancer, sponsored by the National Institutes of Health Office of Rare Diseases and the National Cancer Institute Divisions of Cancer Epidemiology and Genetics and Cancer Treatment and Diagnosis. The meeting included representatives from the fields of epidemiology, genetics, pathology and molecular biology, health services research, and clinical oncology and the advocacy community, with a comprehensive review of the data. Presentations focused on highlighting differences and similarities between breast cancer in males and females. To enhance our understanding of male breast cancer, international consortia are necessary. Therefore, the Breast International Group and North American Breast Cancer Group have joined efforts to develop an International Male Breast Cancer Program and to pool epidemiologic data, clinical information, and tumor specimens. This international collaboration will also facilitate the future planning of clinical trials that can address essential questions in the treatment of male breast cancer.
Primary hyperparathyroidism (pHPT) is associated with an increased risk of developing breast cancer, but little is known about the underlying factors. The aim of this study was to compare women with a history of pHPT and a reference population in terms of standard factors predictive of prognosis and response to therapy for breast cancer.
We analyzed data collected from the National Swedish Cancer Register and from two regional oncologic center registries. Seventy-one women with breast cancer and a history of parathyroid adenomectomy were compared with 338 matched controls with breast cancer only. Tumor size, stage, hormone receptor status, lymph node status, cause of death, and cumulative survival were analyzed.
The mean age was 69 ± 11 years (95% confidence interval [CI]: 68–70) in both groups and the mean time interval between the parathyroid surgery and breast cancer diagnosis was 91 ± 68 months (95% CI: 72–111). There were no differences between the two groups regarding size, stage, lymph node metastases, or survival, but none of the cases with a history of pHPT were found in Stage III or IV.
In conclusion, factors predictive of prognosis and response to therapy in women with a history of pHPT and breast cancer are similar to those in breast cancer patients without pHPT.
breast cancer; primary hyperparathyroidism; prognostic factors
Mutational inactivation of the FBXW7/hCDC4 tumor suppressor gene (TSG) is common in many cancer types, but infrequent in breast cancers. This study investigates the presence and impact of FBXW7/hCDC4 promoter methylation in breast cancer.
FBXW7/hCDC4-β expression and promoter methylation was assessed in 161 tumors from two independent breast cancer cohorts. Associations between methylation status and clinicopathologic characteristics were assessed by Fisher's exact test. Survival was analyzed using the Kaplan-Meier method in addition to modeling the risk by use of a multivariate proportional hazard (Cox) model adjusting for possible confounders of survival.
Methylation of the promoter and loss of mRNA expression was found both in cell lines and primary tumors (43% and 51%, respectively). Using Cox modeling, a trend was found towards decreased hazard ratio (HR) for death in women with methylation of FBXW7/hCDC4-β in both cohorts (HR 0.53 (95% CI 0.23 to 1.23) and HR 0.50 (95% CI 0.23 to 1.08), respectively), despite an association between methylation and high-grade tumors (P = 0.017). Interestingly, in subgroups of patients whose tumors are p53 mutated or lymph-node positive, promoter methylation identified patients with significantly improved survival (P = 0.048 and P = 0.017, respectively).
We demonstrate an alternative mechanism for inactivation of the TSG FBXW7/hCDC4, namely promoter specific methylation. Importantly, in breast cancer, methylation of FBXW7/hCDC4-β is related to favorable prognosis despite its association with poorly differentiated tumors. Future work may define whether FBXW7/hCDC4 methylation is a biomarker of the response to chemotherapy and a target for epigenetic modulation therapy.
Adjuvant trastuzumab (Herceptin) treatment of breast cancer patients significantly improves their clinical outcome. Vaccination is an attractive alternative approach to provide HER-2/neu (Her2)-specific antibodies and may in addition concomitantly stimulate Her2-reactive T-cells. Here we report the first administration of a Her2-plasmid DNA (pDNA) vaccine in humans.
Patients and Methods
The vaccine, encoding a full-length signaling-deficient version of the oncogene Her2, was administered together with low doses of GM-CSF and IL-2 to patients with metastatic Her2-expressing breast carcinoma who were also treated with trastuzumab. Six of eight enrolled patients completed all three vaccine cycles. In the remaining two patients treatment was discontinued after one vaccine cycle due to rapid tumor progression or disease-related complications. The primary objective was the evaluation of safety and tolerability of the vaccine regimen. As a secondary objective, treatment-induced Her2-specific immunity was monitored by measuring antibody production as well as T-cell proliferation and cytokine production in response to Her2-derived antigens.
No clinical manifestations of acute toxicity, autoimmunity or cardiotoxicity were observed after administration of Her2-pDNA in combination with GM-CSF, IL-2 and trastuzumab. No specific T-cell proliferation following in vitro stimulation of freshly isolated PBMC with recombinant human Her2 protein was induced by the vaccination. Immediately after all three cycles of vaccination no or even decreased CD4+ T-cell responses towards Her2-derived peptide epitopes were observed, but a significant increase of MHC class II restricted T-cell responses to Her2 was detected at long term follow-up. Since concurrent trastuzumab therapy was permitted, λ-subclass specific ELISAs were performed to specifically measure endogenous antibody production without interference by trastuzumab. Her2-pDNA vaccination induced and boosted Her2-specific antibodies that could be detected for several years after the last vaccine administration in a subgroup of patients.
This pilot clinical trial demonstrates that Her2-pDNA vaccination in conjunction with GM-CSF and IL-2 administration is safe, well tolerated and can induce long-lasting cellular and humoral immune responses against Her2 in patients with advanced breast cancer.
The trial registration number at the Swedish Medical Products Agency for this trial is Dnr151:785/2001.
The growth of many soft tissue sarcomas is dependent on aberrant growth factor signaling, which promotes their proliferation and motility. With this in mind, we evaluated the effect of sorafenib, a receptor tyrosine kinase inhibitor, on cell growth and apoptosis in sarcoma cell lines of various histological subtypes. We found that sorafenib effectively inhibited cell proliferation in rhabdomyosarcoma, synovial sarcoma and Ewing’s sarcoma with IC50 values <5 μM. Sorafenib effectively induced growth arrest in rhabdomyosarcoma cells, which was concurrent with inhibition of Akt and Erk signaling. Studies of ligand-induced phosphorylation of Erk and Akt in rhabdomyosarcoma cells showed that insulin-like growth factor-1 is a potent activator, which can be blocked by treatment with sorafenib. In vivo sorafenib treatment of rhabdomyosarcoma xenografts had a significant inhibitory effect on tumor growth, which was associated with inhibited vascularization and enhanced necrosis in the adjacent tumor stroma. Our results demonstrate that in vitro and in vivo growth of rhabdomyosarcoma can be suppressed by treatment with sorafenib, and suggests the possibilities of using sorafenib as a potential adjuvant therapy for the treatment of rhabdomyosarcoma.
soft tissue sarcoma; kinase inhibitors; targeted therapy; vascularization
The impact of interactions between the two estrogen receptor (ER) subtypes, ERα and ERβ, on gene expression in breast cancer biology is not clear. The goal of this study was to examine transcriptomic alterations in cancer cells co-expressing both receptors and the association of gene expression signatures with disease outcome.
Transcriptional effects of ERβ overexpression were determined in a stably transfected cell line derived from ERα-positive T-47D cells. Microarray analysis was carried out to identify differential gene expression in the cell line, and expression of key genes was validated by quantitative polymerase chain reaction. Microarray and clinical data from patient samples were then assessed to determine the in vivo relevance of the expression profiles observed in the cell line.
A subset of 14 DNA replication and cell cycle-related genes was found to be specifically downregulated by ERβ. Expression profiles of four genes, CDC2, CDC6, CKS2, and DNA2L, were significantly inversely correlated with ERβ transcript levels in patient samples, consistent with in vitro observations. Kaplan-Meier analysis revealed better disease outcome for the patient group with an expression signature linked to higher ERβ expression as compared to the lower ERβ-expressing group for both disease-free survival (p = 0.00165) and disease-specific survival (p = 0.0268). These findings were further validated in an independent cohort.
Our findings revealed a transcriptionally regulated mechanism for the previously described growth inhibitory effects of ERβ in ERα-positive breast tumor cells and provide evidence for a functional and beneficial impact of ERβ in primary breast tumors.
Molecular markers and the rich biological information they contain have great potential for cancer diagnosis, prognostication and therapy prediction. So far, however, they have not superseded routine histopathology and staging criteria, partly because the few studies performed on molecular subtyping have had little validation and limited clinical characterization.
We obtained gene expression and clinical data for 412 breast cancers obtained from population-based cohorts of patients from Stockholm and Uppsala, Sweden. Using the intrinsic set of approximately 500 genes derived in the Norway/Stanford breast cancer data, we validated the existence of five molecular subtypes – basal-like, ERBB2, luminal A/B and normal-like – and characterized these subtypes extensively with the use of conventional clinical variables.
We found an overall 77.5% concordance between the centroid prediction of the Swedish cohort by using the Norway/Stanford signature and the k-means clustering performed internally within the Swedish cohort. The highest rate of discordant assignments occurred between the luminal A and luminal B subtypes and between the luminal B and ERBB2 subtypes. The subtypes varied significantly in terms of grade (p < 0.001), p53 mutation (p < 0.001) and genomic instability (p = 0.01), but surprisingly there was little difference in lymph-node metastasis (p = 0.31). Furthermore, current users of hormone-replacement therapy were strikingly over-represented in the normal-like subgroup (p < 0.001). Separate analyses of the patients who received endocrine therapy and those who did not receive any adjuvant therapy supported the previous hypothesis that the basal-like subtype responded to adjuvant treatment, whereas the ERBB2 and luminal B subtypes were poor responders.
We found that the intrinsic molecular subtypes of breast cancer are broadly present in a diverse collection of patients from a population-based cohort in Sweden. The intrinsic gene set, originally selected to reveal stable tumor characteristics, was shown to have a strong correlation with progression-related properties such as grade, p53 mutation and genomic instability.
Postmenopausal hormone-replacement therapy (HRT) increases breast-cancer risk. The influence of HRT on the biology of the primary tumor, however, is not well understood.
We obtained breast-cancer gene expression profiles using Affymetrix human genome U133A arrays. We examined the relationship between HRT-regulated gene profiles, tumor characteristics, and recurrence-free survival in 72 postmenopausal women.
HRT use in patients with estrogen receptor (ER) protein positive tumors (n = 72) was associated with an altered regulation of 276 genes. Expression profiles based on these genes clustered ER-positive tumors into two molecular subclasses, one of which was associated with HRT use and had significantly better recurrence free survival despite lower ER levels. A comparison with external data suggested that gene regulation in tumors associated with HRT was negatively correlated with gene regulation induced by short-term estrogen exposure, but positively correlated with the effect of tamoxifen.
Our findings suggest that post-menopausal HRT use is associated with a distinct gene expression profile related to better recurrence-free survival and lower ER protein levels. Tentatively, HRT-associated gene expression in tumors resembles the effect of tamoxifen exposure on MCF-7 cells.
Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction.
We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined.
Among the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston–Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively.
We have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.
There are currently a number of competing techniques for low-level processing of oligonucleotide array data. The choice of technique has a profound effect on subsequent statistical analyses, but there is no method to assess whether a particular technique is appropriate for a specific data set, without reference to external data.
We analyzed coregulation between genes in order to detect insufficient normalization between arrays, where coregulation is measured in terms of statistical correlation. In a large collection of genes, a random pair of genes should have on average zero correlation, hence allowing a correlation test. For all data sets that we evaluated, and the three most commonly used low-level processing procedures including MAS5, RMA and MBEI, the housekeeping-gene normalization failed the test. For a real clinical data set, RMA and MBEI showed significant correlation for absent genes. We also found that a second round of normalization on the probe set level improved normalization significantly throughout.
Previous evaluation of low-level processing in the literature has been limited to artificial spike-in and mixture data sets. In the absence of a known gold-standard, the correlation criterion allows us to assess the appropriateness of low-level processing of a specific data set and the success of normalization for subsets of genes.