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Purpose: To improve on current standards for breast cancer prognosis and prediction of chemotherapy benefit by developing a risk model that incorporates the gene expression-based "intrinsic" subtypes luminal A, luminal B, HER2-enriched, and basal-like., Methods: A 50-gene subtype predictor was developed using microarray and quantitative reverse transcriptase polymerase chain reaction data from 189 prototype samples. Test sets from 761 patients (no systemic therapy) were evaluated for prognosis, and 133 patients were evaluated for prediction of pathologic complete response (pCR) to a taxane and anthracycline regimen., Results: The intrinsic subtypes as discrete entities showed prognostic significance ( P = 2.26E-12) and remained significant in multivariable analyses that incorporated standard parameters (estrogen receptor status, histologic grade, tumor size, and node status). A prognostic model for node-negative breast cancer was built using intrinsic subtype and clinical information. The C-index estimate for the combined model (subtype and tumor size) was a significant improvement on either the clinicopathologic model or subtype model alone. The intrinsic subtype model predicted neoadjuvant chemotherapy efficacy with a negative predictive value for pCR of 97%., Conclusion: Diagnosis by intrinsic subtype adds significant prognostic and predictive information to standard parameters for patients with breast cancer. The prognostic properties of the continuous risk score will be of value for the management of node-negative breast cancers. The subtypes and risk score can also be used to assess the likelihood of efficacy from neoadjuvant chemotherapy.

Exosomes are membrane nanovesicles implicated in cell-to-cell signaling in which they transfer their molecular cargo from the parent to the recipient cells. This role essentially depends on the exosomes' small size, which is the prerequisite for their rapid migration through the crowded extracellular matrix and into and out of circulation. Here we report much lower exosome mobility than expected from the size of their vesicles, implicate membrane proteins in a substantially impeded rate of migration, and suggest an approach to quantifying the impact. The broadly distributed excess hydrodynamic resistance provided by surface proteins produces a highly heterogeneous and microenvironment-dependent hindrance to exosome mobility. The implications of the findings on exosome-mediated signaling are discussed., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Breast tumor subtyping has failed to provide impact in susceptibility genetics. The PAM50 assay categorizes breast tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like. However, tumors are often more complex than simple categorization can describe. The identification of heritable tumor characteristics has potential to decrease heterogeneity and increase power for gene finding. Methods: We used 911 sporadic breast tumors with PAM50 expression data to derive tumor dimensions using principal components (PC). Dimensions in 238 tumors from high-risk pedigrees were compared with the sporadic tumors. Proof-of-concept gene mapping, informed by tumor dimension, was performed using Shared Genomic Segment (SGS) analysis. Results: Five dimensions (PC1-5) explained the majority of the PAM50 expression variance: three captured intrinsic subtype, two were novel (PC3, PC5). All five replicated in 745 TCGA tumors. Both novel dimensions were significantly enriched in the high-risk pedigrees (intrinsic subtypes were not). SGS gene-mapping in a pedigree identified a 0.5 Mb genome-wide significant region at 12q15 This region segregated through 32 meioses to 8 breast cancer cases with extreme PC3 tumors ( P = 2.6 × 10 -8 ). Conclusions: PC analysis of PAM50 gene expression revealed multiple independent, quantitative measures of tumor diversity. These tumor dimensions show evidence for heritability and potential as powerful traits for gene mapping. Impact: Our study suggests a new approach to describe tumor expression diversity, provides new avenues for germline studies, and proposes a new breast cancer locus. Similar reparameterization of expression patterns may inform other studies attempting to model the effects of tumor heterogeneity. Cancer Epidemiol Biomarkers Prev; 27(6); 644-52. ©2018 AACR ., (©2018 American Association for Cancer Research.)

To identify gene expression biomarkers and pathways targeted by sulindac and erlotinib given in a chemoprevention trial with a significant decrease in duodenal polyp burden at 6 months ( P < 0.001) in familial adenomatous polyposis (FAP) patients, we biopsied normal and polyp duodenal tissues from patients on drug versus placebo and analyzed the RNA expression. RNA sequencing was performed on biopsies from the duodenum of FAP patients obtained at baseline and 6-month endpoint endoscopy. Ten FAP patients on placebo and 10 on sulindac and erlotinib were selected for analysis. Purity of biopsied polyp tissue was calculated from RNA expression data. RNAs differentially expressed between endpoint polyp and paired baseline normal were determined for each group and mapped to biological pathways. Key genes in candidate pathways were further validated by quantitative RT-PCR. RNA expression analyses of endpoint polyp compared with paired baseline normal for patients on placebo and drug show that pathways activated in polyp growth and proliferation are blocked by this drug combination. Directly comparing polyp gene expression between patients on drug and placebo also identified innate immune response genes (IL12 and IFNγ) preferentially expressed in patients on drug. Gene expression analyses from tissue obtained at endpoint of the trial demonstrated inhibition of the cancer pathways COX2/PGE2, EGFR, and WNT. These findings provide molecular evidence that the drug combination of sulindac and erlotinib reached the intended tissue and was on target for the predicted pathways. Furthermore, activation of innate immune pathways from patients on drug may have contributed to polyp regression. Cancer Prev Res; 11(1); 4-15. ©2017 AACR See related editorial by Shureiqi, p. 1 ., (©2017 American Association for Cancer Research.)

Background: Breastfeeding is associated with decreased breast cancer risk, yet associations with prognosis and survival by tumor subtype are largely unknown., Methods: 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., Results: 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., Conclusions: History of breastfeeding might affect prognosis and survival by establishing a luminal tumor environment with lower proliferative activity., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: Invasive 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., Methods: Early-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/m(2)) 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., Results: Highly 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., Conclusions: ER 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.

Epidemiologic studies have shown that diabetics receiving the biguanide metformin, as compared with sulfonylureas or insulin, have a lower incidence of breast cancer. Metformin increases levels of activated AMPK (AMP-activated protein kinase) and decreases circulating IGF-1; encouraging its potential use in both cancer prevention and therapeutic settings. In anticipation of clinical trials in nondiabetic women, the efficacy of metformin in nondiabetic rat and mouse mammary cancer models was evaluated. Metformin was administered by gavage or in the diet, at a human equivalent dose, in standard mammary cancer models: (i) methylnitrosourea (MNU)-induced estrogen receptor-positive (ER(+)) mammary cancers in rats, and (ii) MMTV-Neu/p53KO ER(-) (estrogen receptor-negative) mammary cancers in mice. In the MNU rat model, metformin dosing (150 or 50 mg/kg BW/d, by gavage) was ineffective in decreasing mammary cancer multiplicity, latency, or weight. Pharmacokinetic studies of metformin (150 mg/kg BW/d, by gavage) yielded plasma levels (Cmax and AUC) higher than humans taking 1.5 g/d. In rats bearing small palpable mammary cancers, short-term metformin (150 mg/kg BW/d) treatment increased levels of phospho-AMPK and phospho-p53 (Ser20), but failed to reduce Ki67 labeling or expression of proliferation-related genes. In the mouse model, dietary metformin (1,500 mg/kg diet) did not alter final cancer incidence, multiplicity, or weight. Metformin did not prevent mammary carcinogenesis in two mammary cancer models, raising questions about metformin efficacy in breast cancer in nondiabetic populations., (©2015 American Association for Cancer Research.)

Background: Data are lacking to describe gene expression-based breast cancer intrinsic subtype patterns for population-based patient groups., Methods: 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., Results: 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)., Conclusions: 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., Impact: Subtyping in a population-based cohort revealed distinct profiles by age and race., (©2014 AACR.)

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.

Background: Many 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., Methods: We 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., Results: ESR1, 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., Conclusions: The 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.

Purpose: 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., Experimental Design: 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., Results: Intrinsic subtypes were associated with RFS (P = 0.0005) 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), 0.6-2.1 for RFS and HR, 1.3; 95% CI, 0.7-2.5 for OS]., Conclusion: 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., (©2012 AACR.)

Background: Multivariate assays (MVAs) for assisting clinical decisions are becoming commonly available, but due to complexity, are often considered a high-risk approach. A key concern is that uncertainty on the assay's final results is not well understood. This study focuses on developing a process to characterize error introduced in the MVA's results from the intrinsic error in the laboratory process: sample preparation and measurement of the contributing factors, such as gene expression., Methods: Using the PAM50 Breast Cancer Intrinsic Classifier, we show how to characterize error within an MVA, and how these errors may affect results reported to clinicians. First we estimated the error distribution for measured factors within the PAM50 assay by performing repeated measures on four archetypal samples representative of the major breast cancer tumor subtypes. Then, using the error distributions and the original archetypal sample data, we used Monte Carlo simulations to generate a sufficient number of simulated samples. The effect of these errors on the PAM50 tumor subtype classification was estimated by measuring subtype reproducibility after classifying all simulated samples. Subtype reproducibility was measured as the percentage of simulated samples classified identically to the parent sample. The simulation was thereafter repeated on a large, independent data set of samples from the GEICAM 9906 clinical trial. Simulated samples from the GEICAM sample set were used to explore a more realistic scenario where, unlike archetypal samples, many samples are not easily classified., Results: All simulated samples derived from the archetypal samples were classified identically to the parent sample. Subtypes for simulated samples from the GEICAM set were also highly reproducible, but there were a non-negligible number of samples that exhibit significant variability in their classification., Conclusions: We have developed a general methodology to estimate the effects of intrinsic errors within MVAs. We have applied the method to the PAM50 assay, showing that the PAM50 results are resilient to intrinsic errors within the assay, but also finding that in non-archetypal samples, experimental errors can lead to quite different classification of a tumor. Finally we propose a way to provide the uncertainty information in a usable way for clinicians.

Development and preclinical testing of new cancer therapies is limited by the scarcity of in vivo models that authentically reproduce tumor growth and metastatic progression. We report new models for breast tumor growth and metastasis in the form of transplantable tumors derived directly from individuals undergoing treatment for breast cancer. These tumor grafts illustrate the diversity of human breast cancer and maintain essential features of the original tumors, including metastasis to specific sites. Co-engraftment of primary human mesenchymal stem cells maintains phenotypic stability of the grafts and increases tumor growth by promoting angiogenesis. We also report that tumor engraftment is a prognostic indicator of disease outcome for women with newly diagnosed breast cancer; orthotopic breast tumor grafting is a step toward individualized models for tumor growth, metastasis and prognosis. This bank of tumor grafts also serves as a publicly available resource for new models in which to study the biology of breast cancer.

Background: Based on preclinical studies and a phase I trial of the combination of bortezomib and pegylated liposomal doxorubicin (PLD), which both showed activity in breast cancer, we conducted a phase II study of this regimen in patients with metastatic breast cancer., Patients and Methods: Patients received bortezomib 1.3 mg/m2 on days 1, 4, 8, and 11 of an every-21-day cycle, along with PLD 30 mg/m2 on day 4. The primary objective was to evaluate the response rate of this combination, while secondary objectives were to obtain further safety data about this combination, to evaluate the time to disease progression (TTP), and to evaluate response by the breast cancer subtype., Results: One of 12 evaluable patients had a partial response (8%), while 3 (25%) had stable disease. At 26 months follow-up, the median overall survival was 4.3 months (95% CI, 1.2-26.2) and the median TTP was 1.3 months (95% CI, 0.8-14.0 months). The combination was well tolerated, with the most common events including low-grade nausea and vomiting, neutropenia, and neuropathy, and no cardiac toxicity was seen. Of the 7 tumors subtyped, no association was seen between intrinsic subtype or receptor status and response., Conclusion: The combination of PLD and bortezomib was well tolerated but has minimal activity in heavily pretreated unselected metastatic breast cancer.

Purpose: To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)-positive breast cancers from patients uniformly treated with adjuvant tamoxifen., Experimental Design: Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and 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., Results: Despite clinical ER positivity, 10% of cases were assigned to nonluminal 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 follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 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-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior., Conclusion: 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 IHC using standard cut points., (©2010 AACR.)