To compare clinical, immunohistochemical and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor positive breast cancers, from patients uniformly treated with adjuvant tamoxifen.
qRT-PCR assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median followup 11.7 years) and immunohistochemical (ER, PR, HER2, Ki67) data. Performance of predefined intrinsic subtype and Risk-Of-Relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell’s C index was used to compare fixed models trained in independent data sets, including proliferation signatures.
Despite clinical ER positivity, 10% of cases were assigned to non-Luminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease specific survival over the first 5 years of followup, relative to the most common Luminal A subtype, are 1.99 (95% CI: 1.09–3.64) for Luminal B, 3.65 (1.64–8.16) for HER2-enriched and 17.71 (1.71–183.33) for the basal like subtype. For node-negative disease, PAM50 qRT-PCR based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10 yr survival without chemotherapy. In node positive disease, PAM50-based prognostic models were also superior.
The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and immunohistochemistry using standard cutpoints.
It is now accepted that breast cancer is not a single disease, but instead it is composed of a spectrum of tumor subtypes with distinct cellular origins, somatic changes, and etiologies. Gene expression profiling using DNA microarrays has contributed significantly to our understanding of the molecular heterogeneity of breast tumor formation, progression, and recurrence. For example, at least two clinical diagnostic assays exist (i.e., OncotypeDX RS and Mammaprint®) that are able to predict outcome in patients using patterns of gene expression and predetermined mathematical algorithms. In addition, a new molecular taxonomy based upon the inherent, or “intrinsic,” biology of breast tumors has been developed; this taxonomy is called the “intrinsic subtypes of breast cancer,” which now identifies five distinct tumor types and a normal breast-like group. Importantly, the intrinsic subtypes of breast cancer predict patient relapse, overall survival, and response to endocrine and chemotherapy regimens. Thus, most of the clinical behavior of a breast tumor is already written in its subtype profile. Here, we describe the discovery and basic biology of the intrinsic subtypes of breast cancer, and detail how this interacts with underlying genetic alternations, response to therapy, and the metastatic process.
Mammary tumors have a variety of cellular origins and display significant heterogeneity. A new molecular taxonomy defines five tumor subtypes and can predict patient relapse, survival, and responses to therapy.
Recent studies suggest that intrinsic breast cancer subtypes may differ in their responsiveness to specific chemotherapy regimens. We examined this hypothesis on NCIC.CTG MA.5, a clinical trial randomizing premenopausal women with node-positive breast cancer to adjuvant CMF (cyclophosphamide-methotrexate-fluorouracil) versus CEF (cyclophosphamide-epirubicin-fluorouracil) chemotherapy.
Intrinsic subtype was determined for 476 tumors using the quantitative reverse transcriptase PCR PAM50 gene expression test. Luminal A, luminal B, HER2-enriched (HER2-E), and basal-like subtypes were correlated with relapse-free survival (RFS) and overall survival (OS), estimated using Kaplan-Meier plots and log-rank testing. Multivariable Cox regression analyses determined significance of interaction between treatment and intrinsic subtypes.
Intrinsic subtypes were associated with RFS (P = 0005) and OS (P < 0.0001) on the combined cohort. The HER2-E showed the greatest benefit from CEF versus CMF, with absolute 5-year RFS and OS differences exceeding 20%, whereas there was a less than 2% difference for non-HER2-E tumors (interaction test P = 0.03 for RFS and 0.03 for OS). Within clinically defined Her2+ tumors, 79% (72 of 91) were classified as the HER2-E subtype by gene expression and this subset was strongly associated with better response to CEF versus CMF (62% vs. 22%, P = 0.0006). There was no significant difference in benefit between CEF and CMF in basal-like tumors [n = 94; HR, 1.1; 95% confidence interval (CI), 0.6−.1 for RFS and HR, 1.3; 95% CI, 0.7−2.5 for OS].
HER2-E strongly predicted anthracycline sensitivity. The chemotherapy-sensitive basal- like tumors showed no added benefit for CEF over CMF, suggesting that nonanthracycline regimens may be adequate in this subtype although further investigation is required.
The 21-gene OncotypeDX recurrence score (RS) assay quantifies the risk of distant recurrence in tamoxifen-treated patients with node-negative, estrogen receptor (ER)–positive breast cancer. We investigated the association between RS and risk for locoregional recurrence (LRR) in patients with node-negative, ER-positive breast cancer from two National Surgical Adjuvant Breast and Bowel Project (NSABP) trials (NSABP B-14 and B-20).
Patients and Methods
RS was available for 895 tamoxifen-treated patients (from both trials), 355 placebo-treated patients (from B-14), and 424 chemotherapy plus tamoxifen-treated patients (from B-20). The primary end point was time to first LRR. Distant metastases, second primary cancers, and deaths before LRR were censored.
In tamoxifen-treated patients, LRR was significantly associated with RS risk groups (P < .001). The 10-year Kaplan-Meier estimate of LRR was 4.% (95% CI, 2.3% to 6.3%) for patients with a low RS (< 18), 7.2% (95% CI, 3.4% to 11.0%) for those with intermediate RS (18-30), and 15.8% (95% CI, 10.4% to 21.2%) for those with a high RS (> 30). There were also significant associations between RS and LRR in placebo-treated patients from B-14 (P = .022) and in chemotherapy plus tamoxifen–treated patients from B-20 (P = .028). In multivariate analysis, RS was an independent significant predictor of LRR along with age and type of initial treatment.
Similar to the association between RS and risk for distant recurrence, a significant association exists between RS and risk for LRR. This information has biologic consequences and potential clinical implications relative to locoregional therapy decisions for patients with node-negative and ER-positive breast cancer.
Risk assignment in breast cancer patients using the PAM50 Breast Cancer Intrinsic Classifier™ and the Oncotype DX® Recurrence Score in the same population was compared. There is good agreement between the two assays for high and low prognostic risk assignment but PAM50 assigns more patients to the low risk category. About half of the intermediate risk RS group was reclassified as low risk luminal A by PAM50, which suggests a potential complementary use for the assays.
To compare risk assignment by PAM50 Breast Cancer Intrinsic Classifier™ and Oncotype DX_Recurrence Score (RS) in the same population.
RNA was extracted from 151 estrogen receptor (ER)+ stage I–II breast cancers and gene expression profiled using PAM50 “intrinsic” subtyping test.
One hundred eight cases had complete molecular information; 103 (95%) were classified as luminal A (n = 76) or luminal B (n = 27). Ninety-two percent (n = 98) had a low (n = 59) or intermediate (n = 39) RS. Among luminal A cancers, 70% had low (n = 53) and the remainder (n = 23) had an intermediate RS. Among luminal B cancers, nine were high (33%) and 13 were intermediate (48%) by the RS. Almost all cancers with a high RS were classified as luminal B (90%, n = 9). One high RS cancer was identified as basal-like and had low ER/ESR1 and low human epidermal growth factor receptor 2 (HER2) expression by quantitative polymerase chain reaction in both assays. The majority of low RS cases were luminal A (83%, n = 53). Importantly, half of the intermediate RS cancers were re-categorized as low risk luminal A subtype by PAM50.
There is good agreement between the two assays for high (i.e., luminal B or RS > 31) and low (i.e., luminal B or RS < 18) prognostic risk assignment but PAM50 assigns more patients to the low risk category. About half of the intermediate RS group was reclassified as luminal A by PAM50.
Oncotype DX®; PAM50 assay; Gene expression profiles; Breast cancer; Prognosis
We examined if a combination of proliferation markers and estrogen receptor (ER) activity could predict early versus late relapses in ER-positive breast cancer and inform the choice and length of adjuvant endocrine therapy.
Baseline affymetrix gene-expression profiles from ER-positive patients who received no systemic therapy (n = 559), adjuvant tamoxifen for 5 years (cohort-1: n = 683, cohort-2: n = 282) and from 58 patients treated with neoadjuvant letrozole for 3 months (gene-expression available at baseline, 14 and 90 days) were analyzed. A proliferation score based on the expression of mitotic kinases (MKS) and an ER-related score (ERS) adopted from Oncotype DX® were calculated. The same analysis was performed using the Genomic Grade Index as proliferation marker and the luminal gene score from the PAM50 classifier as measure of estrogen-related genes. Median values were used to define low and high marker groups and four combinations were created. Relapses were grouped into time cohorts of 0–2.5, 0–5, 5-10 years.
In the overall 10 years period, the proportional hazards assumption was violated for several biomarker groups indicating time-dependent effects. In tamoxifen-treated patients Low-MKS/Low-ERS cancers had continuously increasing risk of relapse that was higher after 5 years than Low-MKS/High-ERS cancers [0 to 10 year, HR 3.36; p = 0.013]. High-MKS/High-ERS cancers had low risk of early relapse [0–2.5 years HR 0.13; p = 0.0006], but high risk of late relapse which was higher than in the High-MKS/Low-ERS group [after 5 years HR 3.86; p = 0.007]. The High-MKS/Low-ERS subset had most of the early relapses [0 to 2.5 years, HR 6.53; p < 0.0001] especially in node negative tumors and showed minimal response to neoadjuvant letrozole. These findings were qualitatively confirmed in a smaller independent cohort of tamoxifen-treated patients. Using different biomarkers provided similar results.
Early relapses are highest in highly proliferative/low-ERS cancers, in particular in node negative tumors. Relapses occurring after 5 years of adjuvant tamoxifen are highest among the highly-proliferative/high-ERS tumors although their risk of recurrence is modest in the first 5 years on tamoxifen. These tumors could be the best candidates for extended endocrine therapy.
Optimizing treatment through microarray-based molecular subtyping is a promising method to address the problem of heterogeneity in breast cancer; however, current application is restricted to prediction of distant recurrence risk. This study investigated whether breast cancer molecular subtyping according to its global intrinsic biology could be used for treatment customization.
Gene expression profiling was conducted on fresh frozen breast cancer tissue collected from 327 patients in conjunction with thoroughly documented clinical data. A method of molecular subtyping based on 783 probe-sets was established and validated. Statistical analysis was performed to correlate molecular subtypes with survival outcome and adjuvant chemotherapy regimens. Heterogeneity of molecular subtypes within groups sharing the same distant recurrence risk predicted by genes of the Oncotype and MammaPrint predictors was studied.
We identified six molecular subtypes of breast cancer demonstrating distinctive molecular and clinical characteristics. These six subtypes showed similarities and significant differences from the Perou-Sørlie intrinsic types. Subtype I breast cancer was in concordance with chemosensitive basal-like intrinsic type. Adjuvant chemotherapy of lower intensity with CMF yielded survival outcome similar to those of CAF in this subtype. Subtype IV breast cancer was positive for ER with a full-range expression of HER2, responding poorly to CMF; however, this subtype showed excellent survival when treated with CAF. Reduced expression of a gene associated with methotrexate sensitivity in subtype IV was the likely reason for poor response to methotrexate. All subtype V breast cancer was positive for ER and had excellent long-term survival with hormonal therapy alone following surgery and/or radiation therapy. Adjuvant chemotherapy did not provide any survival benefit in early stages of subtype V patients. Subtype V was consistent with a unique subset of luminal A intrinsic type. When molecular subtypes were correlated with recurrence risk predicted by genes of Oncotype and MammaPrint predictors, a significant degree of heterogeneity within the same risk group was noted. This heterogeneity was distributed over several subtypes, suggesting that patients in the same risk groups require different treatment approaches.
Our results indicate that the molecular subtypes established in this study can be utilized for customization of breast cancer treatment.
We hypothesize that measurement of gene expression related to estrogen receptor α (ER; gene name ESR1) within a breast cancer sample represents intrinsic tumoral sensitivity to adjuvant endocrine therapy.
A genomic index for sensitivity to endocrine therapy (SET) index was defined from genes coexpressed with ESR1 in 437 microarray profiles from newly diagnosed breast cancer, unrelated to treatment or outcome. The association of SET index and ESR1 levels with distant relapse risk was evaluated from microarrays of ER-positive breast cancer in two cohorts who received 5 years of tamoxifen alone as adjuvant endocrine therapy (n = 225 and 298, respectively), a cohort who received neoadjuvant chemotherapy followed by tamoxifen and/or aromatase inhibition (n = 122), and two cohorts who received no adjuvant systemic therapy (n = 208 and 133, respectively).
The SET index (165 genes) was significantly associated with distant relapse or death risk in both tamoxifen-treated cohorts (hazard ratio [HR] = 0.70, 95% CI, 0.56 to 0.88, P = .002; and HR = 0.76, 95% CI, 0.63 to 0.93, P = .007) and in the chemo-endocrine–treated cohort (HR = 0.19; 95% CI, 0.05 to 0.69, P = .011) independently from pathologic response to chemotherapy, but was not prognostic in two untreated cohorts. No distant relapse or death was observed after tamoxifen alone if node-negative and high SET or after chemo-endocrine therapy if intermediate or high SET.
The SET index of ER-related transcription predicted survival benefit from adjuvant endocrine therapy, not inherent prognosis. Prior chemotherapy seemed to enhance the efficacy of adjuvant endocrine therapy related to SET index.
The key to optimising our approach in early breast cancer is to individualise care. Each patient has a tumour with innate features that dictate their chance of relapse and their responsiveness to treatment. Often patients with similar clinical and pathological tumours will have markedly different outcomes and responses to adjuvant intervention. These differences are encoded in the tumour genetic profile. Effective biomarkers may replace or complement traditional clinical and histopathological markers in assessing tumour behaviour and risk. Development of high-throughput genomic technologies is enabling the study of gene expression profiles of tumours. Genomic fingerprints may refine prediction of the course of disease and response to adjuvant interventions. This review will focus on the role of multiparameter gene expression analyses in early breast cancer, with regards to prognosis and prediction. The prognostic role of genomic signatures, particularly the Mammaprint and Rotterdam signatures, is evolving. With regard to prediction of outcome, the Oncotype Dx multigene assay is in clinical use in tamoxifen treated patients. Extensive research continues on predictive gene identification for specific chemotherapeutic agents, particularly the anthracyclines, taxanes and alkylating agents.
To identify a group of patients who might benefit from the addition of weekly paclitaxel to conventional anthracycline-containing chemotherapy as adjuvant therapy of node-positive operable breast cancer. The predictive value of PAM50 subtypes and the 11-gene proliferation score contained within the PAM50 assay were evaluated in 820 patients from the GEICAM/9906 randomized phase III trial comparing adjuvant FEC to FEC followed by weekly paclitaxel (FEC-P). Multivariable Cox regression analyses of the secondary endpoint of overall survival (OS) were performed to determine the significance of the interaction between treatment and the (1) PAM50 subtypes, (2) PAM50 proliferation score, and (3) clinical and pathological variables. Similar OS analyses were performed in 222 patients treated with weekly paclitaxel versus paclitaxel every 3 weeks in the CALGB/9342 and 9840 metastatic clinical trials. In GEICAM/9906, with a median follow up of 8.7 years, OS of the FEC-P arm was significantly superior compared to the FEC arm (unadjusted HR = 0.693, p = 0.013). A benefit from paclitaxel was only observed in the group of patients with a low PAM50 proliferation score (unadjusted HR = 0.23, p < 0.001; and interaction test, p = 0.006). No significant interactions between treatment and the PAM50 subtypes or the various clinical–pathological variables, including Ki-67 and histologic grade, were identified. Finally, similar OS results were obtained in the CALGB data set, although the interaction test did not reach statistical significance (p = 0.109). The PAM50 proliferation score identifies a subset of patients with a low proliferation status that may derive a larger benefit from weekly paclitaxel.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-013-2416-2) contains supplementary material, which is available to authorized users.
Breast cancer; Paclitaxel; PAM50 subtypes; PAM50 proliferation score; Prediction of paclitaxel efficacy
Gene expression profiling classifies breast cancer into intrinsic subtypes based on the biology of the underlying disease pathways. We have used material from a prospective randomized trial of tamoxifen versus placebo in premenopausal women with primary breast cancer (NCIC CTG MA.12) to evaluate the prognostic and predictive significance of intrinsic subtypes identified by both the PAM50 gene set and by immunohistochemistry.
Total RNA from 398 of 672 (59%) patients was available for intrinsic subtyping with a quantitative reverse transcriptase PCR (qRT-PCR) 50-gene predictor (PAM50) for luminal A, luminal B, HER-2–enriched, and basal-like subtypes. A tissue microarray was also constructed from 492 of 672 (73%) of the study population to assess a panel of six immunohistochemical IHC antibodies to define the same intrinsic subtypes.
Classification into intrinsic subtypes by the PAM50 assay was prognostic for both disease-free survival (DFS; P = 0.0003) and overall survival (OS; P = 0.0002), whereas classification by the IHC panel was not. Luminal subtype by PAM50 was predictive of tamoxifen benefit [DFS: HR, 0.52; 95% confidence interval (CI), 0.32–0.86 vs. HR, 0.80; 95% CI, 0.50–1.29 for nonluminal subtypes], although the interaction test was not significant (P = 0.24), whereas neither subtyping by central immunohistochemistry nor by local estrogen receptor (ER) or progesterone receptor (PR) status were predictive. Risk of relapse (ROR) modeling with the PAM50 assay produced a continuous risk score in both node-negative and node-positive disease.
In the MA.12 study, intrinsic subtype classification by qRT-PCR with the PAM50 assay was superior to IHC profiling for both prognosis and prediction of benefit from adjuvant tamoxifen.
Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30–40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings.
We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29–3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response.
We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
Introduction. This study aimed to evaluate whether OncotypeDx test results predict receipt of adjuvant chemotherapy in breast cancer patients who received an OncotypeDx recurrence score (RS). Materials and Methods. Pathology records were used to identify breast cancer patients who had OncotypeDx testing between December 2004 and January 2009 (n = 118). Patient sociodemographic information, tumor characteristics, RS, and treatment-specific data were collected via chart review. RS was classified as follows: low (RS ≤ 17), intermediate (RS = 18–30), or high (RS ≥ 31). Bivariate analyses were conducted to investigate the relationship between adjuvant chemotherapy receipt and each sociodemographic and clinical characteristic; significant sociodemographic and clinical variables were included in a multivariable logistic regression model. Results. In multivariable analysis controlling for tumor size, histologic grade, and nuclear grade, only RS remained significantly associated with chemotherapy uptake. Relative to low RS, an intermediate (adjusted odds ratio [AOR], 21.24; 95% confidence interval [CI], 3.62–237.52) or high (AOR, 15.07; 95% CI, 1.28–288.21) RS was associated with a greater odds of chemotherapy uptake. Discussion. Results indicate that RS was significantly associated with adjuvant chemotherapy uptake, suggesting that OncotypeDx results were used to inform treatment decision making, although it is unclear if and how the information was conveyed to patients.
The Oncotype DX assay was recently reported to predict risk for distant recurrence among a clinical trial population of tamoxifen-treated patients with lymph node-negative, estrogen receptor (ER)-positive breast cancer. To confirm and extend these findings, we evaluated the performance of this 21-gene assay among node-negative patients from a community hospital setting.
A case-control study was conducted among 4,964 Kaiser Permanente patients diagnosed with node-negative invasive breast cancer from 1985 to 1994 and not treated with adjuvant chemotherapy. Cases (n = 220) were patients who died from breast cancer. Controls (n = 570) were breast cancer patients who were individually matched to cases with respect to age, race, adjuvant tamoxifen, medical facility and diagnosis year, and were alive at the date of death of their matched case. Using an RT-PCR assay, archived tumor tissues were analyzed for expression levels of 16 cancer-related and five reference genes, and a summary risk score (the Recurrence Score) was calculated for each patient. Conditional logistic regression methods were used to estimate the association between risk of breast cancer death and Recurrence Score.
After adjusting for tumor size and grade, the Recurrence Score was associated with risk of breast cancer death in ER-positive, tamoxifen-treated and -untreated patients (P = 0.003 and P = 0.03, respectively). At 10 years, the risks for breast cancer death in ER-positive, tamoxifen-treated patients were 2.8% (95% confidence interval [CI] 1.7–3.9%), 10.7% (95% CI 6.3–14.9%), and 15.5% (95% CI 7.6–22.8%) for those in the low, intermediate and high risk Recurrence Score groups, respectively. They were 6.2% (95% CI 4.5–7.9%), 17.8% (95% CI 11.8–23.3%), and 19.9% (95% CI 14.2–25.2%) for ER-positive patients not treated with tamoxifen. In both the tamoxifen-treated and -untreated groups, approximately 50% of patients had low risk Recurrence Score values.
In this large, population-based study of lymph node-negative patients not treated with chemotherapy, the Recurrence Score was strongly associated with risk of breast cancer death among ER-positive, tamoxifen-treated and -untreated patients.
Shorter duration of sleep has been associated with risk of a number of medical conditions, including breast cancer. However, no prior study has investigated the relationship of average sleep duration prior to diagnosis and cancer aggressiveness. OncotypeDX is a widely utilized test to guide treatment in early stage hormone receptor positive breast cancer by predicting likelihood of recurrence.
We reviewed medical records from ER+ early stage breast cancer patients participating in a case-control study for availability of OncotypeDX scores. All patients in the parent study were recruited at diagnosis and asked about average sleep duration in the two years prior to diagnosis. We analyzed data from 101 breast cancer patients with available OncotypeDX recurrence scores to test the hypothesis that shorter sleep is associated with greater likelihood of recurrence.
We found that OncotypeDX recurrence scores were strongly correlated with average hours of sleep per night prior to breast cancer diagnosis, with fewer hours of sleep associated with a higher (worse) recurrence score (R=−0.30, p=0.0031). This correlation was limited to post-menopausal breast cancer patients only (R=−0.41, p=0.0011, for postmenopausal patients; R=−0.05, p=0.80 for pre-menopausal patients). This association remains statistically significant after adjustment for age, physical activity, smoking status and body mass index in the entire study sample (p=0.0058) as well as in postmenopausal patients (p=0.0021).
This is the first study to suggest that women who routinely sleep shorter amounts of time may develop more aggressive breast cancers compared to women who sleep longer.
Breast cancer; OncotypeDX; sleep; recurrence
Identification of a molecular signature predicting the relapse of tamoxifen-treated primary breast cancers should help the therapeutical management of ER-positive cancers.
A series of 132 primary tumors from patients who received adjuvant tamoxifen were analysed for expression profiles at the whole genome level by 70-mer oligonucleotide microarrays. A supervised analysis was performed to identify an expression signature.
We defined a 36-gene signature that classified correctly 78% of patients with relapse and 80% of relapse-free patients (79% accuracy). Using 23 independent tumors, we confirmed the accuracy of the signature (78%), whose relevance was further demonstrated by using published microarray data from 60 tamoxifen-treated patients (63% accuracy).
Univariate analysis using the validation set of 83 tumors demonstrated that the 36-gene classifier was more efficient to predict disease-free survival than the traditional histo-pathological prognostic factors and as effective as the Nottingham Prognostic Index or the “Adjuvant!“ software. Multivariate analysis demonstrated that the molecular signature was the only independent prognostic factor. Comparison with several already published signatures demonstated that the 36-gene signature was among the best to classify tumors from both training and validation sets. Kaplan-Meier analyses emphasized its prognostic power both on the whole cohort of patients and on a subgroup with an intermediate risk of recurrence as defined by the St Gallen criteria.
This study identifies a molecular signature specifying a subgroup of patients who do not gain benefits from tamoxifen treatment. These patients may therefore be eligible for alternative endocrine therapies and/or chemotherapy.
Adult; Aged; Aged, 80 and over; Antineoplastic Agents, Hormonal; therapeutic use; Breast Neoplasms; diagnosis; drug therapy; genetics; Carcinoma; diagnosis; drug therapy; genetics; Chemotherapy, Adjuvant; Cluster Analysis; Disease-Free Survival; Drug Resistance, Neoplasm; genetics; Female; Follow-Up Studies; Gene Expression Profiling; Humans; Middle Aged; Neoplasm Recurrence, Local; diagnosis; genetics; Oligonucleotide Array Sequence Analysis; Prognosis; Receptors, Estrogen; genetics; Receptors, Progesterone; genetics; Sensitivity and Specificity; Tamoxifen; therapeutic use; Treatment Outcome; gene expression profiling; classifier; tamoxifen; breast cancer
Few markers are available that can predict response to tamoxifen treatment in estrogen receptor (ER)-positive breast cancers. Identification of such markers would be clinically useful. We attempted to identify molecular markers associated with tamoxifen failure in breast cancer.
Eighteen initially ER-positive patients treated with tamoxifen requiring salvage surgery (tamoxifen failure [TF] patients) were compared with 17 patients who were disease free 5 years after surgery plus tamoxifen adjuvant therapy (control patients). cDNA microarray, real-time quantitative PCR, and immunohistochemistry on tissue microarrays were used to generate and confirm a gene signature associated with tamoxifen failure. An independent series of 33 breast tumor samples from patients who relapsed (n = 14) or did not relapse (n = 19) under tamoxifen treatment from a different geographic location was subsequently used to explore the gene expression signature identified.
Using a screening set of 18 tumor samples (from eight control patients and 10 TF patients), a 47-gene signature discriminating between TF and control samples was identified using cDNA arrays. In addition to ESR1/ERα, the top-ranked genes selected by statistical cross-analyses were MET, FOS, SNCG, IGFBP4, and BCL2, which were subsequently validated in a larger set of tumor samples (from 17 control patients and 18 TF patients). Confirmation at the protein level by tissue microarray immunohistochemistry was observed for ER-α, γ-synuclein, and insulin-like growth factor binding protein 4 proteins in the 35 original samples. In an independent series of breast tumor samples (19 nonrelapsing and 14 relapsing), reduced expression of ESR1/ERα, IGFBP4, SNCG, BCL2, and FOS was observed in the relapsing group and was associated with a shorter overall survival. Low mRNA expression levels of ESR1/ERα, BCL2, and FOS were also associated with a shorter relapse-free survival (RFS). Using a Cox multivariate regression analysis, we identified BCL2 and FOS as independent prognostic markers associated with RFS. Finally, the BCL2/FOS signature was demonstrated to have more accurate prognostic value for RFS than ESR1/ERα alone (likelihood ratio test).
We identified molecular markers including a BCL2/FOS signature associated with tamoxifen failure; these markers may have clinical potential in the management of ER-positive breast cancer.
Within estrogen receptor-positive breast cancer (ER+ BC), the expression levels of proliferation-related genes can define two clinically distinct molecular subtypes. When treated with adjuvant tamoxifen, those ER+ BCs that are lowly proliferative have a good prognosis (luminal-A subtype), however the clinical outcome of those that are highly proliferative is poor (luminal-B subtype).
To investigate the biological basis for these observations, gene set enrichment analysis (GSEA) was performed using microarray data from 246 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. To create an in vitro model of growth factor (GF) signaling activation, MCF-7 cells were treated with heregulin (HRG), an HER3 ligand.
We found that a gene set linked to GF signaling was significantly enriched in the luminal-B tumors, despite only 10% of samples over-expressing HER2 by immunohistochemistry. To determine the biological significance of this observation, MCF-7 cells were treated with HRG. These cells displayed phosphorylation of HER2/3 and downstream ERK and S6. Treatment with HRG overcame tamoxifen-induced cell cycle arrest with higher S-phase fraction and increased anchorage independent colony formation. Gene expression profiles of MCF-7 cells treated with HRG confirmed enrichment of the GF signaling gene set and a similar proliferative signature observed in human ER+ BCs resistant to tamoxifen.
These data demonstrate that activation of GF signaling pathways, independent of HER2 over-expression, could be contributing to the poor prognosis of the luminal-B ER+ BC subtype.
Women with breast cancer involving the lymph nodes are typically treated with cytotoxic chemotherapy. Retrospective evaluations of prior studies suggest that the 21-gene test (OncotypeDX®), may allow identification of those who can safely avoid chemotherapy. To better understand the performance of the 21-gene test, the RxPONDER (Rx for Positive Node, Endocrine Responsive breast cancer) study was designed, a multicenter Phase III trial randomizing women with hormone receptor-positive and HER2-negative breast cancer involving 1–3 lymph nodes and a 21-gene assay recurrence score (RS) of 25 or less to endocrine therapy alone versus chemotherapy followed by endocrine therapy. As one of the first large-scale comparative-effectiveness studies in oncology, RxPONDER utilized an external stakeholder group to help inform the design of the trial. Stakeholders met with representatives of SWOG over several months through a structured discussion process. The stakeholder engagement process resulted in several changes being made to the trial design. In addition, stakeholder representatives from the health insurance industry provided guidance regarding a mechanism whereby the costs of OncotypeDX® would be paid by the majority of health insurers as part of the trial. The process may serve as a template for future studies evaluating the comparative effectiveness of genomic tests in oncology, particularly those that are conducted within cooperative clinical trials groups.
breast cancer; comparative effectiveness research; OncotypeDx; everolimus; stakeholder
Adjuvant treatment for early breast cancer is an evolving field. Since the advent of the initial cyclophosphamide, methotrexate and 5-fluorouracil (CMF) regimens, which reduced risk for recurrence and death, anthracyclines and subsequently taxanes were added to the cytotoxic armamentarium for use sequentially or in combination in the adjuvant setting. The efficacy and toxicity of each chemotherapy regimen must be viewed within the context of host co-morbidities and the specific biologic phenotype of the tumor. In the era of mammographic screening, small, node-negative breast cancer is the most frequent presentation of the disease. Patient selection for adjuvant chemotherapy has become a key issue. Traditional prognostic factors continue to be of value in determining the risk for relapse, but new and sophisticated genomic tools (such as Oncotype Dx® and Mammaprint®) are now available and may improve our ability to select patients. For those patients who do require adjuvant chemotherapy, the 'one size fits all' paradigm should never again feature in the treatment of early breast cancer, following the important insights yielded by biomarker research to identify those who will benefit the most from a particular drug. In this review we focus on some of the current controversies and potential future steps in adjuvant chemotherapy for treatment of early breast cancer.
Current immunohistochemical (IHC)-based definitions of luminal A and B breast cancers are imperfect when compared with multigene expression-based assays. In this study, we sought to improve the IHC subtyping by examining the pathologic and gene expression characteristics of genomically defined luminal A and B subtypes.
Patients and Methods
Gene expression and pathologic features were collected from primary tumors across five independent cohorts: British Columbia Cancer Agency (BCCA) tamoxifen-treated only, Grupo Español de Investigación en Cáncer de Mama 9906 trial, BCCA no systemic treatment cohort, PAM50 microarray training data set, and a combined publicly available microarray data set. Optimal cutoffs of percentage of progesterone receptor (PR) –positive tumor cells to predict survival were derived and independently tested. Multivariable Cox models were used to test the prognostic significance.
Clinicopathologic comparisons among luminal A and B subtypes consistently identified higher rates of PR positivity, human epidermal growth factor receptor 2 (HER2) negativity, and histologic grade 1 in luminal A tumors. Quantitative PR gene and protein expression were also found to be significantly higher in luminal A tumors. An empiric cutoff of more than 20% of PR-positive tumor cells was statistically chosen and proved significant for predicting survival differences within IHC-defined luminal A tumors independently of endocrine therapy administration. Finally, no additional prognostic value within hormonal receptor (HR) –positive/HER2-negative disease was observed with the use of the IHC4 score when intrinsic IHC-based subtypes were used that included the more than 20% PR-positive tumor cells and vice versa.
Semiquantitative IHC expression of PR adds prognostic value within the current IHC-based luminal A definition by improving the identification of good outcome breast cancers. The new proposed IHC-based definition of luminal A tumors is HR positive/HER2 negative/Ki-67 less than 14%, and PR more than 20%.
The overall survival rate is good for lymph-node-negative breast cancer patients, but they still suffer from serious over- and some undertreatments. Prognostic and predictive gene signatures for node-negative breast cancer have a high number of genes related to proliferation. The prognostic value of gene sets from commercial gene-expression assays were compared with proliferation markers.
Illumina WG6 mRNA microarray analysis was used to examine 94 fresh-frozen tumour samples from node-negative breast cancer patients. The patients were divided into low- and high-risk groups for distant metastasis based on the MammaPrint-related genes, and into low-, intermediate- and high-risk groups based on the recurrence score algorithm with genes included in Oncotype DX. These data were then compared to proliferation status, as measured by the mitotic activity index, the expressions of phosphohistone H3 (PPH3), and Ki67.
Kaplan-Meier survival analysis for distant-metastasis-free survival revealed that patients with weak and strong PPH3 expressions had 14-year survival rates of 87% (n = 45), and 65% (n = 49, p = 0.014), respectively. Analysis of the MammaPrint classification resulted in 14-year survival rates of 80% (n = 45) and 71% (n = 49, p = 0.287) for patients with low and high risks of recurrence, respectively. The Oncotype DX categorization yielded 14-year survival rates of 83% (n = 18), 79% (n = 42) and 68% (n = 34) for those in the low-, intermediate- and high-risk groups, respectively (p = 0.52). Supervised hierarchical cluster analysis for distant-metastasis-free survival in the subgroup of patients with strong PPH3 expression revealed that the genes involved in Notch signalling and cell adhesion were expressed at higher levels in those patients with distant metastasis.
This pilot study indicates that proliferation has greater prognostic value than the expressions of either MammaPrint- or Oncotype-DX-related genes. Furthermore, in the subgroup of patients with high proliferation, Notch signalling pathway genes appear to be expressed at higher levels in patients who develop distant metastasis.
Breast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) as well as clinical presentations of each molecualr subtype in Han Chinese population.
In all, 169 breast cancer samples (44 from Taiwan and 125 from China) of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) were retrieved for molecular subtype prediction.
For Sørlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD) remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed.
We suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective study with longer survival data is needed.
Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets, such as luminal A and B, basal, normal-like, and ERBB2+, and prognostic signatures including MammaPrint® and Oncotype DX, predicted genomic instability in our samples. This remarkable congruence suggests a biological interdependence of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome.
Abnormal cell division leading to the gain or loss of entire chromosomes and consequent genetic instability is a hallmark of cancer. Centromere protein –A (CENPA) is a centromere-specific histone-H3-like variant gene involved in regulating chromosome segregation during cell division. CENPA is one of the genes included in some of the commercially available RNA based prognostic assays for breast cancer (BCa)—the 70 gene signature MammaPrint® and the five gene Molecular Grade Index (MGISM). Our aim was to assess the immunohistochemical (IHC) expression of CENPA in normal and malignant breast tissue. Clinically annotated triplicate core tissue microarrays of 63 invasive BCa and 20 normal breast samples were stained with a monoclonal antibody against CENPA and scored for percentage of visibly stained nuclei. Survival analyses with Kaplan–Meier (KM) estimate and Cox proportional hazards regression models were applied to assess the associations between CENPA expression and disease free survival (DFS). Average percentage of nuclei visibly stained with CENPA antibody was significantly higher (p = 0.02) in BCa than normal tissue. The 3-year DFS in tumors over-expressing CENPA (>50% stained nuclei) was 79% compared to 85% in low expression tumors (<50% stained nuclei). On multivariate analysis, IHC expression of CENPA showed weak association with DFS (HR > 60.07; p = 0.06) within our small cohort. To the best of our knowledge, this is the first published report evaluating the implications of increased IHC expression of CENPA in paraffin embedded breast tissue samples. Our finding that increased CENPA expression may be associated with shorter DFS in BCa supports its exploration as a potential prognostic biomarker.
CENPA; breast cancer; immunohistochemistry