PAM50 Gene Research Articles

Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response.

IntroductionThe molecular biology involving neoadjuvant chemotherapy (NAC) response is poorly understood. To elucidate the impact of NAC on the breast cancer transcriptome and its association with clinical outcome, we analyzed gene expression data derived from serial tumor samples of patients with breast cancer who received NAC in the I-SPY 1 TRIAL.MethodsExpression data were collected before treatment (T1), 24–96 hours after initiation of chemotherapy (T2) and at surgery (TS). Expression levels between T1 and T2 (T1 vs. T2; n = 36) and between T1 and TS (T1 vs. TS; n = 39) were compared. Subtype was assigned using the PAM50 gene signature. Differences in early gene expression changes (T2 − T1) between responders and nonresponders, as defined by residual cancer burden, were evaluated. Cox proportional hazards modeling was used to identify genes in residual tumors associated with recurrence-free survival (RFS). Pathway analysis was performed with Ingenuity software.ResultsWhen we compared expression profiles at T1 vs. T2 and at T1 vs. TS, we detected significantly altered expression of 150 and 59 transcripts, respectively. We observed notable downregulation of proliferation and immune-related genes at T2. Lower concordance in subtype assignment was observed between T1 and TS (62 %) than between T1 and T2 (75 %). Analysis of early gene expression changes (T2 − T1) revealed that decreased expression of cell cycle inhibitors was associated with poor response. Increased interferon signaling (TS − T1) and high expression of cell proliferation genes in residual tumors (TS) were associated with reduced RFS.ConclusionsSerial gene expression analysis revealed candidate immune and proliferation pathways associated with response and recurrence. Larger studies incorporating the approach described here are warranted to identify predictive and prognostic biomarkers in the NAC setting for specific targeted therapies.Clinical trial registrationClinicalTrials.gov identifier: NCT00033397. Registered 9 Apr 2002.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-015-0582-3) contains supplementary material, which is available to authorized users.

Abstract S4-05: Impact of intrinsic subtype by PAM50 and other gene signatures on pathologic complete response (pCR) rates in triple-negative breast cancer (TNBC) after neoadjuvant chemotherapy (NACT) +/- carboplatin (Cb) or bevacizumab (Bev): CALGB 40603/150709 (Allianc

Abstract Background: Adding either Cb or Bev to standard NACT significantly increases pCR rates in TNBC (Sikov et al, SABCS 2013). Genomic analysis may help us to identify determinants of response within this clinical phenotype. Methods: Patients (pts) with clinical stage II-III TNBC received weekly paclitaxel x 12 followed by ddAC x 4 +/- Cb and/or Bev. Pre-treatment biopsies were collected in formalin, RNAlater and OCT; residual disease at surgery was biopsied when possible. Illumina mRNA sequencing (RNAseq) was performed. Gene expression values were normalized to a TCGA subset of clinically TNBC samples prior to downstream analysis. pCR was defined as the absence of residual invasive cancer in the breast (ypT0/is). For each molecular signature, prognostic (effect on pCR in the overall study population) and predictive (effect of the addition of Cb or Bev, separately, on pCR) relationships were explored with logistic regression models. Results: PAM50 subtype analysis was performed on 367 pre-treatment samples (of 443 pts who started NACT); pCR results were available for 360, comprising the analysis subset. 87% of these displayed a basal-like gene expression pattern, 2% claudin-low, 4% HER2-enriched, <1% luminal A and 7% normal-like. In pts with basal-like tumors, pCRs rose from 47% to 61% with the addition of Cb (p=0.014), an increment which did not differ significantly from the overall study population (adding in the small number of non-basal-like tumors) (interaction p=0.93). In contrast, the addition of Bev increased pCRs in basal-like tumors from 45% to 64% (p=0.0009), while reducing pCRs in non-basal-likes from 60% to 43% (interaction p=0.024); thus, a basal-like gene expression pattern was predictive of benefit from Bev. Expression of a variety of immune signatures (B cell, T cell, IgG) was positively associated with pCR, but not predictive of increased benefit from either Cb or Bev. High expression of the HER2 amplicon signature was uncommon and not prognostic for pCR overall but was associated with reduced benefit from Cb (interaction p = 0.025). High proliferation, high p53 mutation and low IE (estrogen signaling) signatures were prognostic for higher pCR rates and predictive of benefit from Bev (interaction p=0.031, 0.0017, 0.0002, respectively). In basal-like pts with residual disease, surgical samples often (52%) displayed a normal-like PAM50 pattern, though this might be due to ‘contamination’ in low volume residual disease. Conclusions: Selection criteria led to accrual of a high % of pts with basal-like tumors, limiting our ability to assess prognostic or predictive impact of intrinsic subtype on pCR. Given that limitation, the magnitude of pCR benefit with Cb was consistent across subtypes, while a basal-like pattern was predictive of greater pCR increment with Bev. Ongoing studies will test a large number of other gene signatures and biomarkers, including the Lehmann et al subtypes. Recognition of clinically relevant subpopulations within TNBC may distinguish pts likely to achieve a pCR from those for whom an investigational approach might be considered. Citation Format: William M Sikov, William T Barry, Katherine A Hoadley, Brandelyn N Pitcher, Baljit Singh, Sara M Tolaney, Charles S Kuzma, Timothy J Pluard, George Somlo, Elisa R Port, Mehra Golshan, Donald A Berry, Olwen M Hahn, Lisa A Carey, Charles M Perou, Clifford A Hudis, Eric P Winer. Impact of intrinsic subtype by PAM50 and other gene signatures on pathologic complete response (pCR) rates in triple-negative breast cancer (TNBC) after neoadjuvant chemotherapy (NACT) +/- carboplatin (Cb) or bevacizumab (Bev): CALGB 40603/150709 (Allianc [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S4-05.

Abstract P6-16-03: Intrinsic subtypes and MRI patterns in brain metastasis associated with breast cancer

Abstract Background: Breast cancer is the 2nd most common cancer to metastasize to the brain. The development of brain metastasis (BM) is associated with a lower median survival compared with other locations of metastasis and carries with it high morbidity and reduced quality of life. There are limited treatment options and virtually no approved targeted therapies for this disease. We have previously reported specific pathways enriched in BM compared to primary tumors and now further this study to examine pathways by intrinsic subtype and location of and number of BM. Methods: Archival FFPE material was obtained from BM using pathology records; clinical data, including MRI images, was retrieved from medical records and institutional tumor registry under an IRB protocol. Tumor DNA/RNA was extracted from 2 mm cores macrodissected from the FFPE tissue blocks using the Qiagen AllPrep DNA/RNA FFPE kit. Gene expression profiling was performed using Affymetrix Human Transcriptome Array 2.0 microarray on BM samples for which sufficient RNA was available. Gene-level expression quantification was derived after RMA normalization using the Affymetrix Transcriptome Analysis Console. PAM50 subtypes were assigned by clustering samples using median-subtracted PAM50 gene expression levels. Differential gene expression was estimated using the non-parametric Mann-Whitney test, followed by assessment of false discovery rate using the Banjamini-Hochberg FDR methodology. Pathway enrichment analysis was performed using the NCI Pathway Interaction Database. Results: Gene expression profiling showed the following intrinsic subtype distribution among all BM: luminal A 32% (19/59), luminal B 31% (18/59), HER2 enriched 7% (4/59), and basal subtype 31% (18/59). At time of development of BM 64% (38/59) of patients presented with a single lesion compared to 36% (21/59) of patients who presented with multiple lesions (p=0.12). Thirty-nine percent (7/18) of patients with basal subtypes were observed to present with multiple BM compared to 61% (11/18) non-basal subtypes (p=0.25). In addition, 12% (13/59) of BM were found to be exclusively dural-based lesions. They appeared more frequently in the luminal subtypes [11/13 vs 2/13; p=0.06]. A total of 314 genes were differentially expressed (Wilcox pval < 0.05; FDR < 0.01) between the basal and luminal subtypes. As expected, we found that the FOXA transcription factor network was up-regulated in luminal when compared to the basal subtype, whereas the FOXM1 transcription factor network was up-regulated in the basals. We also found a total of 28 genes to be significantly differentially expressed (Wilcox pval < 0.05; FDR < 0.01) between the dural and non-dural BM. The beta1 integrin and syndecan-1 pathways were significantly enriched, along with angiogenesis and lymphatic endothelium pathways. Key genes in these pathways (COL1A1, COL1A2, COL3A1, CDH11, were found to be at least 2-fold up-regulated in the dural BM compared to non-dural BM. Conclusion: Identifying pathways that are differentially expressed between intrinsic subtypes may help us develop new targeted therapies to provide more treatment options for breast cancer patients with brain metastasis. Citation Format: Nicole Williams, Vinay Varadan, Aditi Vadodkar, Kristy Miskimen, Stephanie Kim, Shaveta Vinayak, Paula Silverman, Jill Barnholtz-Sloan, Andrew Sloan, Cheryl Thompson, Lisa Rogers, Hannah Gilmore, Lyndsay Harris. Intrinsic subtypes and MRI patterns in brain metastasis associated with breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-16-03.

Association of high obesity with PAM50 breast cancer intrinsic subtypes and gene expression.

BackgroundInvasive breast cancers are now commonly classified using gene expression into biologically and clinically distinct tumor subtypes. However, the role of obesity in breast tumor gene expression and intrinsic subtype is unknown.MethodsEarly-stage breast cancer (BC) patients (n = 1,676) were sampled from two prospective cohorts. The PAM50 qRT-PCR assay was used to: a) assess tumor gene expression levels for ESR1, PGR, ERBB2, and 10 proliferation genes and b) classify tumors into intrinsic subtype (Luminal A, Luminal B, Basal-like, HER2-enriched, Normal-like). Body mass index (BMI) around BC diagnosis (kg/m2) was categorized as: underweight (<18.5), normal (18.5-24), overweight (25–29), mildly obese (30–34), and highly obese (≥35). In a cross-sectional analysis, we evaluated associations of BMI with gene expression using linear regression models, and associations of BMI with non-Luminal A intrinsic subtypes, compared with Luminal A subtype, using multinomial logistic regression. Statistical significance tests were two-sided.ResultsHighly obese women had tumors with higher expression of proliferation genes compared with normal weight women (adjusted mean difference = 0.44; 95% CI: 0.18, 0.71), yet mildly obese (adjusted mean difference = 0.16; 95% CI: −0.06, 0.38) and overweight (adjusted mean difference = 0.18; 95% CI: −0.01, 0.36) women did not. This association was stronger in postmenopausal women (p for interaction = 0.06). Being highly obese, however, was inversely associated with ESR1 expression (adjusted mean difference = −0.95; 95% CI: −1.47, −0.42) compared with being normal weight, whereas being mildly obese and overweight were not. In addition, women with Basal-like and Luminal B subtypes, relative to those with Luminal A subtype, were more likely to be highly obese, compared with normal-weight.ConclusionsER expression may not increase correspondingly with increasing degree of obesity. Highly obese patients are more likely to have tumor subtypes associated with high proliferation and poorer prognosis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1263-4) contains supplementary material, which is available to authorized users.

Breastfeeding, PAM50 tumor subtype, and breast cancer prognosis and survival.

Breastfeeding is associated with decreased breast cancer risk, yet associations with prognosis and survival by tumor subtype are largely unknown. We conducted a cohort study of 1636 women from two prospective breast cancer cohorts. Intrinsic tumor subtype (luminal A, luminal B, human epidermal growth factor receptor 2 [HER2]-enriched, basal-like) was determined by the PAM50 gene expression assay. Breastfeeding history was obtained from participant questionnaires. Questionnaires and medical record reviews documented 383 recurrences and 290 breast cancer deaths during a median follow-up of nine years. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) between breastfeeding and tumor subtype. Cox regression was used to estimate hazard ratios (HRs) for breast cancer recurrence or death. Statistical significance tests were two-sided. Breast cancer patients with basal-like tumors were less likely to have previously breastfed than those with luminal A tumors (OR = 0.56, 95% CI = 0.39 to 0.80). Among all patients, ever breastfeeding was associated with decreased risk of recurrence (HR = 0.70, 95% CI = 0.53 to 0.93), especially breastfeeding for six months or more (HR = 0.63, 95% CI = 0.46 to 0.87, P trend = .01). Similar associations were observed for breast cancer death. Among women with luminal A subtype, ever breastfeeding was associated with decreased risks of recurrence (HR = 0.52, 95% CI = 0.31 to 0.89) and breast cancer death (HR = 0.52, 95% CI = 0.29 to 0.93), yet no statistically significant associations were observed among the other subtypes. Effects appeared to be limited to tumors with lower expression of proliferation genes. History of breastfeeding might affect prognosis and survival by establishing a luminal tumor environment with lower proliferative activity.

Abstract 3263: Association of high obesity with PAM50 breast cancer intrinsic subtypes and gene expression

Abstract Background: Obesity is associated with breast cancer (BC) in postmenopausal women, but its relationship with intrinsic subtype is unclear. We examined associations of body mass index (BMI) with intrinsic subtype and expression of selected genes among women with invasive BC. Methods: A case-cohort of 1,676 BC patients was sampled from two prospective Kaiser Permanente Northern California cohorts: LACE (AJCC stage I (≥1 cm), II, IIIA diagnosed 1997-2000) and Pathways (invasive stage ≥0.5 cm diagnosed 2006-2008). The PAM50 quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) assay was used to: a) classify tumors into intrinsic subtype (Luminal A, Luminal B, Basal-like, HER2-E, Normal-like) and b) assess gene expression levels for ESR1, PGR, ERBB2, and a composite of 10 proliferation genes. BMI was from self-reported weight and height within one year prior to BC diagnosis and categorized as: normal (&amp;lt;25 kg/m2), overweight (25-29 kg/m2), obese (30-34 kg/m2), and highly obese (≥35 kg/m2). Using multinomial logistic regression, we evaluated associations of BMI with non-Luminal A intrinsic subtypes. Linear regression models were used to evaluate associations with gene expression. Models were stratified by menopausal status and adjusted for age at diagnosis, race/ethnicity, and stage. Results: The cohort was comprised of 52% Luminal A, 21% Luminal B, 10% Basal-like, 14% HER2-E, and 3% Normal-like subtypes. Basal-like was more prevalent in the highly obese (19%), compared with the other BMI groups (8%-10%), whereas Luminal A was less common in the highly obese (36%), compared with the other groups (49%-57%). Greater expression of proliferation genes was seen with increasing BMI (p&amp;lt;0.01). In the postmenopausal group, compared to normal weight women, those who were highly obese had an increased odds of Basal-like vs. Luminal A tumors (OR=4.14; 95% CI: 2.08, 8.23) and Luminal B vs. Luminal A tumors (OR=3.17; 95% CI: 1.54, 6.54). However, these elevated odds were largely non-significant and attenuated among obese and overweight women. In the postmenopausal group, highly obese women had tumors with higher expression of proliferation genes compared with normal weight women (β=0.48; 95% CI: 0.16, 0.79), yet obese (β=0.14; 95% CI: -0.09, 0.37) and overweight (β=0.11; 95% CI: -0.10, 0.33) women did not. In contrast, being highly obese was associated with lower ESR1 expression (β=-0.51; 95% CI: -1.09, 0.06) compared with normal weight, whereas obese (β=0.28; 95% CI: -0.16, 0.71) and overweight (β=0.04; 95% CI: -0.32, 0.39) were not. These reported associations, except for ESR1 expression, were not evident in premenopausal women. Discussion: Among postmenopausal women with breast cancer, those who were highly obese, but not mildly obese, had increased odds of Basal-like and Luminal B subtypes and had tumors with greater expression of proliferation genes. Tumor subtypes may vary by level of obesity. Citation Format: Marilyn L. Kwan, Candyce H. Kroenke, Carol Sweeney, Philip S. Bernard, Erin Weltzien, Adrienne Castillo, Rachel E. Factor, Kaylynn Shakespear, Inga J. Stijleman, Charles P. Quesenberry, Laurel A. Habel, Lawrence H. Kushi, Bette J. Caan. Association of high obesity with PAM50 breast cancer intrinsic subtypes and gene expression. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3263. doi:10.1158/1538-7445.AM2014-3263

Abstract 363: Planar filtered gene regulatory networks in breast cancer

Abstract Gene co-expression network analysis has been shown to be effective in identifying functional co-expressed gene modules associated with complex human diseases such as cancer, Alzheimers’ disease, obesity and diabetes. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of modules to be detected and numerical thresholds for defining coexpression/interaction, or do not naturally reproduce the hallmarks of complex systems such as scale-free degree distribution of small-worldness). In order to mitigate these problems as whole or in part, we have developed a novel co-expression network analysis approach, Planar Filtered Network Analysis (PFNA). PFNA utilizes a graph filtering technique to identify “true” interactions by means of embedding candidate interactions on a topological sphere(2, 3). Planar Filtered Networks (PFN) are naturally scale-free, small-world, and are comprised of a number of highly co-expressed gene modules). Furthermore, PFNA allows differential topology analysis of networks from different disease states based on centrality and peripherality metrics). We performed PFNA on the breast cancer data from The Cancer Genome Atlas (TCGA), and identified a number of novel gene modules associated with overall survival of the whole cohort or patient subgroups defined by receptor status (ER, PR, HER2) and PAM50 biomarkers(6). PFNA uncovers not only gene modules enriched for genes in well-known cancer pathways such as cell-cycle and immune response, but also novel modules that prognostically stratify patients with triple negative or basal breast cancers. Notably, several modules involved in G-protein coupled receptor signaling, protocadherin α and β pathways are highly predictive of survival for patients with triple negative disease. Furthermore, the differential topology analysis reveals that breast cancer biomarkers such as PAM50 and poor prognosis gene sets developed by van’t Veer et al(7) are more central in the tumor network than the one based on the matched adjacent normal breast tissues. In summary, PFNA reveals a number of novel high-level molecular features of the highly heterogeneous breast cancer. This novel network analysis method provides a set of unsupervised tools to objectively identify subnetworks that are associated with complex diseases such as breast cancer. 1. R. Albert, A. L. Barabasi. Rev Mod Phys 74, 47. 2. M.Tumminello, T. Aste, T. Di Matteo, R. N. Mantegna. Proc Natl Acad Sci U S A 102,10421. 3. T.Aste, T. Di Matteo, S. T. Hyde. Physica A 346, 20. 4. W.M. Song, T. Di Matteo, T. Aste. Phys RevE Stat Nonlin Soft Matter Phys 85,046115. 5. F.Pozzi, T. Di Matteo, T. Aste. Adv Complex Syst 11, 927. 6. J. S. Parker et al.. Journal of clinical oncology: 27, 1160. 7. L.J. van 't Veer et al.. Nature 415, 530. Citation Format: Won-min Song, Tao Huang, Seungyeul Yoo, EunJee Lee, Yongzhong Zhao, Li Wang, Zhidong Tu, Xudong Dai, Hanna Irie, Jun Zhu, Bin Zhang. Planar filtered gene regulatory networks in breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 363. doi:10.1158/1538-7445.AM2014-363

Clinical validation of the Prosigna breast cancer prognostic gene signature assay on formalin-fixed paraffin embedded breast cancer tumors with comparison to standard molecular markers.

e11518 Background: The Prosigna Breast Cancer Prognostic Gene Signature Assay is a FDA-cleared test for assessing the risk of cancer recurrence in women with hormone receptor positive breast cancer. The assay is based on the PAM50 gene signature, which generates a numeric risk score (0-100) and a risk category. The studies described here were used to validate the FDA-cleared test for routine use in the clinical laboratory. Methods: Thirty-two FFPE breast tumors with known node status, tumor size and ER/PR/HER2 status by IHC were categorized for risk of recurrence by a molecular pathologist. Outcome data was available for an additional 10 of the breast tumor samples. RNA was extracted from all 42 tumor samples and analyzed on the Prosigna assay. Results of the Prosigna assay - which produces both a risk score and categorization – were compared to the previously determined risk categorizations. To measure reproducibility of the Prosigna scores, two tumor samples were extracted three times each and analyzed ...

Intrinsic Subtypes from the PAM50 Gene Expression Assay in a Population-Based Breast Cancer Survivor Cohort: Prognostication of Short- and Long-term Outcomes

The PAM50, a gene expression assay to categorize breast tumors into intrinsic subtypes, has not been previously used to examine short- and long-term prognostication in a population-based cohort where treatment patterns and time of initial follow-up vary. In a stratified case-cohort design of 1,691 women from the LACE and Pathways breast cancer survivor cohorts, we used PAM50 to categorize tumors into Luminal A (LumA), Luminal B (LumB), HER2-enriched (HER2-E), Basal-like and Normal-like, and to examine risk of early and late recurrence and mortality by Cox proportional hazards regression. Compared with LumA, cumulative risk of recurrence and breast cancer death was higher for LumB, HER2-E, and Basal-like tumors at 2, 5, and 10 years. However, HR of breast cancer death varied over time [<5 years (early) vs. > 5 years (late)] for both Basal-like (HR, 6.23 early vs. HR, 0.63 late) and HER2-E tumors (HR, 2.97 early vs. HR, 0.73 late) but not for LumB tumors where risk was elevated consistently (HR, 2.67 early vs. HR, 1.47 late). The contrast between LumB, HER2-E, and Basal-like compared with LumA on early recurrence was stronger when subtype was defined by PAM50 than by immunohistochemistry (IHC) markers. The PAM50 categorized intrinsic subtypes in a manner that more accurately predicts recurrence and survival, especially for luminal tumors, compared with commonly used methods that rely on traditional IHC clinical markers. The PAM50 is robust for use in epidemiologic studies and should be considered when archived tumor tissues are available.

Intrinsic Subtypes from PAM50 Gene Expression Assay in a Population-Based Breast Cancer Cohort: Differences by Age, Race, and Tumor Characteristics

Data are lacking to describe gene expression-based breast cancer intrinsic subtype patterns for population-based patient groups. We studied a diverse cohort of women with breast cancer from the Life After Cancer Epidemiology and Pathways studies. RNA was extracted from 1 mm punches from fixed tumor tissue. Quantitative reverse-transcriptase PCR was conducted for the 50 genes that comprise the PAM50 intrinsic subtype classifier. In a subcohort of 1,319 women, the overall subtype distribution based on PAM50 was 53.1% luminal A, 20.5% luminal B, 13.0% HER2-enriched, 9.8% basal-like, and 3.6% normal-like. Among low-risk endocrine-positive tumors (i.e., estrogen and progesterone receptor positive by immunohistochemistry, HER2 negative, and low histologic grade), only 76.5% were categorized as luminal A by PAM50. Continuous-scale luminal A, luminal B, HER2-enriched, and normal-like scores from PAM50 were mutually positively correlated. Basal-like score was inversely correlated with other subtypes. The proportion with non-luminal A subtype decreased with older age at diagnosis, P Trend < 0.0001. Compared with non-Hispanic Whites, African American women were more likely to have basal-like tumors, age-adjusted OR = 4.4 [95% confidence intervals (CI), 2.3-8.4], whereas Asian and Pacific Islander women had reduced odds of basal-like subtype, OR = 0.5 (95% CI, 0.3-0.9). Our data indicate that over 50% of breast cancers treated in the community have luminal A subtype. Gene expression-based classification shifted some tumors categorized as low risk by surrogate clinicopathologic criteria to higher-risk subtypes. Subtyping in a population-based cohort revealed distinct profiles by age and race.

Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens

BackgroundNanoString’s Prosigna™ Breast Cancer Prognostic Gene Signature Assay is based on the PAM50 gene expression signature. The test outputs a risk of recurrence (ROR) score, risk category, and intrinsic subtype (Luminal A/B, HER2-enriched, Basal-like). The studies described here were designed to validate the analytical performance of the test on the nCounter Analysis System across multiple laboratories.MethodsAnalytical precision was measured by testing five breast tumor RNA samples across 3 sites. Reproducibility was measured by testing replicate tissue sections from 43 FFPE breast tumor blocks across 3 sites following independent pathology review at each site. The RNA input range was validated by comparing assay results at the extremes of the specified range to the nominal RNA input level. Interference was evaluated by including non-tumor tissue into the test.ResultsThe measured standard deviation (SD) was less than 1 ROR unit within the analytical precision study and the measured total SD was 2.9 ROR units within the reproducibility study. The ROR scores for RNA inputs at the extremes of the range were the same as those at the nominal input level. Assay results were stable in the presence of moderate amounts of surrounding non-tumor tissue (<70% by area).ConclusionsThe analytical performance of NanoString’s Prosigna assay has been validated using FFPE breast tumor specimens across multiple clinical testing laboratories.

Race and breast cancer survival by intrinsic subtype based on PAM50 gene expression.

To evaluate whether differences in PAM50 breast cancer (BC) intrinsic (Luminal A, Luminal B, Basal-like, and HER2-enriched) subtypes help explain the Black-White BC survival disparity. Utilizing a stratified case-cohort design, this study included 1,635 women from the Pathways and Life After Cancer Epidemiology cohorts, selecting women with tumors based upon IHC classification, recurrences, and deaths.One millimeter punches were obtained from tumor tissue, and expression of the PAM50 genes for molecular subtype was determined by RT-qPCR of extracted RNA. Cox proportional hazards models were used to analyze associations between race and BC outcomes, adjusted for PAM50 BC subtype. All tests of statistical significance were two-sided. Black women had a higher prevalence of the Basal-like BC subtype. Adjusted for potential confounding variables and disease characteristics at diagnosis, Black women had higher risks of recurrence (HR 1.65, 95 % CI 1.06-2.57) and breast cancer-specific mortality (HR 1.71, 95 % CI 1.02-2.86) than White women, but adjusting further for subtype did not attenuate survival disparities. By contrast, Hispanic women had a lower risk of recurrence (HR 0.54, 95 % CI 0.30-0.96) than Whites. Among those with the Basal-like subtype, Black women had a similar recurrence risk as women in other race groups but a higher recurrence risk for all other subtypes. Hispanic women had a lower recurrence risk within each subtype, though associations were not significant, given limited power. Although Black women had a higher risk of the Basal-like subtype, which has poor prognosis, this did not explain the Black-White BC survival disparity.

Abstract B20: Prediction of lung cancer survival by genes in the PAM50 breast cancer panel.

Abstract Accumulating evidence shows that lung tumors are responsive to the steroid hormones β-estradiol and progesterone, and variables related to hormone receptor status have been reported to affect lung cancer survival. These findings suggest that there may be similarities in how hormonal pathways control tumor progression between lung cancer and breast cancer. We examined the relationship between disease-free survival (DFS) and expression of genes included in three published breast cancer survival signatures in a cohort of 104 early-stage (IA and IB) non-small cell lung cancers. Cases were selected from the University of Pittsburgh Lung Cancer SPORE Tissue Bank based on the following criteria: tumor tissue originated from a completely resected primary T1N0 or T2N0 adenocarinoma or squamous cell lung cancer; fresh-frozen lung cancer tissue was available; no neo-adjuvant therapy given; clinical variables (smoking history, age at diagnosis, sex, size of tumor, pleural invasion, site of recurrence) and outcome were known. RNA isolated from banked frozen tumor tissue was used to assess mRNA expression with the Illumina Human HT-12 v4 BeadChip; all mRNA analyzed had passed quality checks. Data were also subjected to background subtraction and quantile normalization. The Illumina BeadChip contains 16 out of 16 published Oncotype DX genes, 61 out of 66 MammaPrint genes, and 49 of 50 PAM50 genes. Supervised Principal Component Analysis was conducted to evaluate the ability to predict disease-free survival (DFS) for each gene panel as a group and also by using the top genes from the gene panels that showed differential expression in the lung cancer cohort. All results were subjected to 10-fold cross-validation. Genes from the Oncotype DX panel showed no differential expression in the cohort and had no ability to separate cases based on DFS. For the MammaPrint genes, three probes (ALDH4A1, FLT1, RECQL5) showed significant differences in expression in the cohort (p &amp;lt; 0.05), and the gene panel showed a relationship to DFS (HR 1.72, p = 0.07). Examination of the top differentially expressed genes did not improve prediction for the MammaPrint genes. For the PAM50 gene panel, three probes (CXXC5, FGFR4, FOXC1) showed significant differential expression (p &amp;lt; 0.05) and 23 probes showed differential expression at p &amp;lt; 0.1. The PAM50 gene panel as a group was able to separate lung cancer cases based on DFS (HR 1.9, p = 0.03). The PAM50 genes with differential expression at p &amp;lt; 0.1 also separated the cohort into four prognosis groups (p = 0.008 for trend). The worst prognosis group had a HR of 4.76 (p = 0.002). These genes were then analyzed in a subset of 44 cases in the Stage I cohort for whom ERβ protein expression status was known from immunohistochemistry (IHC) analysis. Comparing ERβ high (Allred score of &amp;gt;4, N= 20) and ERβ low (Allred score of 4 or less, N = 24) cases, the top PAM50 genes were more informative in ERβ high cases (HR 11.7, p = 0.0007) compared to ERβ low cases (HR 3.38, p = 0.045). For ERβ high cases, Kaplan-Meier survival curves showed that 50% of the high-risk group relapsed by 22 months, while 50% relapse was not reached in the low-risk group at 60 months. Similar analyses in the MammaPrint and Oncotype DX gene panels did not improve DFS prediction. We next validated the top PAM50 genes in a different cohort of 64 NSCLC cases, which included all stages and histologies, and had available ERβ IHC data, expression data from the Illumina Human HT-12 v4 BeadChip, and survival information. The top PAM50 genes were also able to predict DFS in this cohort: HR 2.19, p = 0.034 in all cases and HR 3.24, p = 0.042 in ERβ high cases. Pathway analysis indicated that the informative PAM50 genes describe a network that contains the estrogen and progesterone receptors, HER2, and cyclin E. The top canonical pathways identified were HER2/HER3 signaling and estrogen signaling. These results suggest that genes involved in interactions between hormonal and HER signaling may be predictive of lung cancer survival, especially in early-stage lung cancer, and provide further evidence for the importance of hormonal pathways in the biology of lung cancer. Supported by NCI SPORE in Lung Cancer P50 040990 and by the University of Pittsburgh Medical Center Genomics Initiative. Citation Format: Jill M. Siegfried, Yan Lin, Sanja Dacic, Brenda Diergaarde, Laura P. Stabile, Hui-Min Lin, Marjorie Romkes. Prediction of lung cancer survival by genes in the PAM50 breast cancer panel. [abstract]. In: Proceedings of the AACR-IASLC Joint Conference on Molecular Origins of Lung Cancer; 2014 Jan 6-9; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2014;20(2Suppl):Abstract nr B20.

Gene Expression Analysis Reveals Distinct Pathways of Resistance to Bevacizumab in Xenograft Models of Human ER-Positive Breast Cancer.

Bevacizumab, the recombinant antibody targeting vascular endothelial growth factor (VEGF), improves progression-free but not overall survival in metastatic breast cancer. To seek further insights in resistance mechanisms to bevacizumab at the molecular level, we developed VEGF and non-VEGF-driven ER-positive MCF7-derived xenograft models allowing comparison of tumor response at different timepoints. VEGF gene (MV165) overexpressing xenografts were initially sensitive to bevacizumab, but eventually acquired resistance. In contrast, parental MCF7 cells derived tumors were de novo insensitive to bevacizumab. Microarray analysis with qRT-PCR validation revealed that Follistatin (FST) and NOTCH were the top signaling pathways associated with resistance in VEGF-driven tumors (P<0.05). Based on the presence of VEGF, treatment with bevacizumab resulted in altered patterns of metagenes and PAM50 gene expression. In VEGF-driven model after short and long-term bevacizumab treatments, a change in the intrinsic subtype (luminal to myoepithelial/basal-like) was observed in association with increased expression of genes implicated with cancer stem cell phenotype (P<0.05). Our results show that the presence or absence of VEGF expression affects the response to bevacizumab therapy and gene pathways. In particular, long-term bevacizumab treatment shifts the cancer cells to a more aggressive myoepithelial/basal subtype in VEGF-expressing model, but not in non-VEGF model. These findings could shed light on variable results to anti-VEGF therapy in patients and emphasize the importance of patient stratification based on the VEGF expression. Our data strongly suggest consideration of patient subgroups for treatment and designing novel combinatory therapies in the clinical setting.

Genetic Background May Contribute to PAM50 Gene Expression Breast Cancer Subtype Assignments

Recent advances in genome wide transcriptional analysis have provided greater insights into the etiology and heterogeneity of breast cancer. Molecular signatures have been developed that stratify the conventional estrogen receptor positive or negative categories into subtypes that are associated with differing clinical outcomes. It is thought that the expression patterns of the molecular subtypes primarily reflect cell-of-origin or tumor driver mutations. In this study however, using a genetically engineered mouse mammary tumor model we demonstrate that the PAM50 subtype signature of tumors driven by a common oncogenic event can be significantly influenced by the genetic background on which the tumor arises. These results have important implications for interpretation of “snapshot” expression profiles, as well as suggesting that incorporation of genetic background effects may allow investigation into phenotypes not initially anticipated in individual mouse models of cancer.

Abstract 3650: PAM50 breast cancer subtyping and risk of recurrence in a population-based cohort.

Abstract BACKGROUND The PAM50 gene expression signature for identifying intrinsic subtypes of breast cancer has been shown to add significant clinical information beyond standard molecular biomarkers (ER, PR, Her2). Previous studies with the PAM50 have focused primarily on retrospective clinical trials in which the drug regimens and enrollment criteria are relatively homogenous. We assess the prognostic significance of subtyping within the community setting using therapies appropriate at the time of diagnosis. METHODS Two prospective studies of breast cancer survivors, Life After Cancer Epidemiology (LACE) and Pathways, were subtyped by the PAM50 using quantitative RT-PCR. LACE participants were diagnosed from 1997-2000 with tumors ≥1 cm; while Pathways enrolled subjects at time of diagnosis (2006-2008) with tumors ≥0.5 cm. Both studies included AJCC stages I-III. LACE participants were enrolled on average 2 years post-diagnosis, such that early recurrences were excluded. In addition, women in Pathways were diagnosed after 2006 when Herceptin treatment was available. Formalin-fixed, paraffin-embedded tumor blocks were centrally reviewed by a pathologist and 1mm directed punches of invasive cancer were taken for RNA extraction and expression profiling. A published algorithm was used for subtyping and provided a continuous gene expression score for proliferation, ESR1/ER, PGR/PR, and ERBB2/Her2 (Bastien et al, BMC Med Genomics. 2012 Oct 4;5:44). Subtype classification was correlated with disease-free survival, estimated using Kaplan-Meier plots and log-rank testing. Multivariable delayed entry Cox regression analyses determined the prognostic significance of subtypes in the context of standard clinical indicators of survival. RESULTS The PAM50 subtype distribution for the cohort was Luminal A (52%), Luminal B (20%), HER2-E (14%), Basal-like (10%), and Normal-like (4%). Approximately 7% of Luminal tumors (A and B) were called ER negative by immunohistochemistry (IHC). Luminal A tumors were more likely to be PR positive (82%) compared to those classified as Luminal B (61%). Only 2% of Luminal B tumors were low proliferation. The HER2-E subtype contained 66% clinically Her2+ tumors and the Basal-like tumors were 90% triple negative. In univariate analyses, women with non-Luminal A subtypes were all at higher risk of recurrence. Controlling for tumor size and positive nodes, those with Basal-like subtype still had a significantly higher risk of recurrence (HR=2.34, 95% CI 1.37, 3.98). CONCLUSIONS There are proportionally more Luminal A patients within the population-based studies compared to clinical trials that have focused on higher risk patients. The PAM50 subtype remains a significant prognostic indicator of recurrence in the context of standard therapies used in community practice today. Citation Format: Philip Bernard, Erin Weltzien, Inge Stijleman, Candyce H. Kroenke, Carole Davis, Marilyn L. Kwan, Charles Quesenberry, Adrienne Castillo, Laurel Habel, Rachel Factor, Larry Kushi, Carol Sweeney, Bette Caan. PAM50 breast cancer subtyping and risk of recurrence in a population-based cohort. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3650. doi:10.1158/1538-7445.AM2013-3650

Abstract P2-10-01: PAM50 gene signature is prognostic for breast cancer patients treated with adjuvant anthracycline and taxane based chemotherapy

Abstract Background: Intrinsic breast cancer subtypes determined by the PAM50 assay are reported to be prognostic independent of standard clinicopathological variables. The CALGB (Alliance) 9741 adjuvant trial randomized treatment in a 2×2 factorial design to (i) 2-wk (dose dense; DD) vs 3-wk therapy and (ii) sequential vs concurrent doxorubicin, cyclophosphamide, paclitaxel (A&amp;gt;T&amp;gt;C vs AC&amp;gt;T). DD therapy improved disease-free survival and overall survival (OS) (Citron et al. JCO 2003.). A significant interaction between intrinsic breast cancer subtypes and the use of DD therapy was hypothesized. Methods: C9741 was conducted in collaboration with ECOG, NCCTG, and SWOG. Biospecimens were collected from 1652 of 2005 subjects. Multiplexed gene expression profiling (NanoString Technologies, Inc) generated PAM50 subtype calls (luminal A, luminal B, HER2-enriched, basal-like), risk of relapse (ROR) score, and proliferation score for 1321 cases (80%). Excluded samples were due to insufficient tumor (n = 181) or RNA (n = 150). The primary endpoint was relapse-free survival (RFS). The primary analysis to determine if the clinical benefit of DD therapy is dependent on intrinsic subtype was conducted as a test of interaction in a Cox proportional hazards model (3 degrees of freedom, df; alpha=0.05). Similar analyses were performed for ROR score and proliferation score as continuous measures of risk (1 df). PAM50 subtype, ROR score, and proliferation score were evaluated in separate multivariate models adjusting for number of positive nodes, menopausal status, dose density, and sequence of therapy. Results: Improved outcomes for DD therapy in the evaluable subset mirrored results from the complete dataset (HR = 1.20; 95%CI 0.99–1.44) with a median follow-up of 12.3 yrs. Subtype analysis identified 32% luminal A (n = 417), 26% luminal B (n = 341), 20% HER2-enriched (n = 267), and 22% basal-like (n = 296). Intrinsic subtypes were prognostic of RFS (p &amp;lt; 0.0001) irrespective of treatment assignment with HRs relative to the luminal A subgroup of 1.50 (luminal B), 1.70 (HER2-enriched) and 1.66 (basal-like). No subtype specific treatment effect on RFS was identified (p = 0.44). ROR scores (range 0–100, median 60) were also prognostic of RFS (HR = 1.12 for a 10-unit change; 95% CI 1.07–1.18; p &amp;lt; 0.0001), but no association with DD therapy benefit was seen (p = 0.58). Similar results were obtained for the proliferation score, for OS as a secondary endpoint, and from multivariate models with clinical covariates. Conclusion: The prognostic value of PAM50 subtype, ROR score, and proliferation score remains highly significant in patients treated with contemporary adjuvant anthracycline and taxane based chemotherapy. Intrinsic subtype did not predict for improved survival with the 2-wk DD vs 3-wk treatment schedule; we hypothesize that this is because the prognostic differences by subtype outweighed the modest but significant clinical benefit of DD chemotherapy administration for the overall population. Planned clinical validation studies will assess the ability of PAM50 and other gene signatures to stratify patients and individualize systemic therapy regimens based on the expected risk of distant recurrence. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P2-10-01.

PAM50 Breast Cancer Subtyping by RT-qPCR and Concordance with Standard Clinical Molecular Markers

BackgroundMany methodologies have been used in research to identify the “intrinsic” subtypes of breast cancer commonly known as Luminal A, Luminal B, HER2-Enriched (HER2-E) and Basal-like. The PAM50 gene set is often used for gene expression-based subtyping; however, surrogate subtyping using panels of immunohistochemical (IHC) markers are still widely used clinically. Discrepancies between these methods may lead to different treatment decisions.MethodsWe used the PAM50 RT-qPCR assay to expression profile 814 tumors from the GEICAM/9906 phase III clinical trial that enrolled women with locally advanced primary invasive breast cancer. All samples were scored at a single site by IHC for estrogen receptor (ER), progesterone receptor (PR), and Her2/neu (HER2) protein expression. Equivocal HER2 cases were confirmed by chromogenic in situ hybridization (CISH). Single gene scores by IHC/CISH were compared with RT-qPCR continuous gene expression values and “intrinsic” subtype assignment by the PAM50. High, medium, and low expression for ESR1, PGR, ERBB2, and proliferation were selected using quartile cut-points from the continuous RT-qPCR data across the PAM50 subtype assignments.ResultsESR1, PGR, and ERBB2 gene expression had high agreement with established binary IHC cut-points (area under the curve (AUC) ≥ 0.9). Estrogen receptor positivity by IHC was strongly associated with Luminal (A and B) subtypes (92%), but only 75% of ER negative tumors were classified into the HER2-E and Basal-like subtypes. Luminal A tumors more frequently expressed PR than Luminal B (94% vs 74%) and Luminal A tumors were less likely to have high proliferation (11% vs 77%). Seventy-seven percent (30/39) of ER-/HER2+ tumors by IHC were classified as the HER2-E subtype. Triple negative tumors were mainly comprised of Basal-like (57%) and HER2-E (30%) subtypes. Single gene scoring for ESR1, PGR, and ERBB2 was more prognostic than the corresponding IHC markers as shown in a multivariate analysis.ConclusionsThe standard immunohistochemical panel for breast cancer (ER, PR, and HER2) does not adequately identify the PAM50 gene expression subtypes. Although there is high agreement between biomarker scoring by protein immunohistochemistry and gene expression, the gene expression determinations for ESR1 and ERBB2 status was more prognostic.

Xenografts faithfully recapitulate breast cancer-specific gene expression patterns of parent primary breast tumors

Though xenografts are used extensively for drug development in breast cancer, how well xenografts reflect the breadth of primary breast tumor subtypes has not been well characterized. Moreover, few studies have compared the gene expression of xenograft tumors to the primary tumors from which they were derived. Here we investigate whether the ability of human breast tumors (n = 20) to create xenografts in immune-deficient mice is associated with breast cancer immunohistochemical (IHC) and intrinsic subtype. We also characterize how precisely the gene expression of xenografts reprises that of parent breast tumors, using hierarchical clustering and other correlation-based techniques applied to Agilent 44K gene expression data from 16 samples including four matched primary tumor-xenograft pairs. Of the breast tumors studied, 25 % (5/20) generated xenografts. Receptor and intrinsic subtype were significant predictors of xenograft success, with all (4/4) triple-negative (TN) tumors and no (0/12) HR+Her2- tumors forming xenografts (P = 0.0005). Tumor cell expression of ALDH1, a stem cell marker, trended toward successful engraftment (P = 0.14), though CDK5/6, a basal marker, did not. Though hierarchical clustering across the 500 most variable genes segregated human breast tumors from xenograft tumors, when clustering was performed over the PAM50 gene set the primary tumor-xenograft pairs clustered together, with all IHC subtypes clustered in distinct groups. Greater similarity between primary tumor-xenograft pairs relative to random pairings was confirmed by calculation of the within-pair between-pair scatter ratio (WPBPSR) distribution (P = 0.0269), though there was a shift in the xenografts toward more aggressive features including higher proliferation scores relative to the primary. Triple-negative breast tumors demonstrate superior ability to create xenografts compared to HR+ tumors, which may reflect higher proliferation or relatively stroma-independent growth of this subtype. Xenograft tumors' gene expression faithfully resembles that of their parent tumors, yet also demonstrates a shift toward more aggressive molecular features.

A 50-Gene Intrinsic Subtype Classifier for Prognosis and Prediction of Benefit from Adjuvant Tamoxifen

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.