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Purpose: Immunotherapy (IO) in triple-negative breast cancer (TNBC) has improved survival outcomes, with promising improvements in pCR rates among early high-risk hormone receptor (HR)+/HER2- breast cancers. However, biomarkers are needed to select patients likely to benefit from IO. MHC-I and tumor-specific MHC-II (tsMHC-II) expression are candidate biomarkers for PD-(L)1 checkpoint inhibition but existing data from clinical trials included limited racial/ethnic diversity., Experimental Design: We performed multiplexed immunofluorescence assays in the Carolina Breast Cancer Study (CBCS; n = 1,628, 48% Black, 52% non-Black). Intrinsic subtype and P53 mutant-like status were identified using RNA-based multigene assays. We ranked participants based on tumoral MHC-I intensity (top 33% categorized as "MHC-Ihigh") and MHC-II+ (≥5% of tumor cells as tsMHC-II+). MHC-I/II were evaluated in association with clinicopathological features by race., Results: Black participants had higher frequency of TNBC (25% vs. 12.5%, P ≤ 0.001) and basal-like (30% vs. 14%, P ≤ 0.001) tumors overall, and higher frequency of basal-like (11% vs. 5.5%, P = 0.002) and TP53 mutant tumors (26% vs. 17%, P = 0.002) among HR+/HER2-. The frequency of tsMHC-II+ was higher in HR+/HER2- Black participants (7.9% vs. 4.9%, P = 0.04). Black participants also had higher frequency of MHC-Ihigh (38.7% vs. 28.2%, P < 0.001), which was significant among HR+/HER2- (28.2% vs. 22.1%, P = 0.02)., Conclusions: In this diverse study population, MHC-I and MHC-II tumor cell expression were more highly expressed in HR+/HER2- tumors from Black women, underscoring the importance of diverse and equitable enrollment in future IO trials., (©2024 American Association for Cancer Research.)

Background: Basal-like breast cancers (BLBCs) are a leading cause of cancer death due to their capacity to metastasize and lack of effective therapies. More than half of BLBCs have a dysfunctional BRCA1. Although most BRCA1-deficient cancers respond to DNA-damaging agents, resistance and tumor recurrence remain a challenge to survival outcomes for BLBC patients. Additional therapies targeting the pathways aberrantly activated by BRCA1 deficiency are urgently needed., Methods: Most BRCA1-deficient BLBCs carry a dysfunctional INK4-RB pathway. Thus, we created genetically engineered mice with Brca1 loss and deletion of p16 INK4A , or separately p18 INK4C , to model the deficient INK4-RB signaling in human BLBC. By using these mutant mice and human BRCA1-deficient and proficient breast cancer tissues and cells, we tested if there exists a druggable target in BRCA1-deficient breast cancers., Results: Heterozygous germline or epithelium-specific deletion of Brca1 in p18 INK4C - or p16 INK4A -deficient mice activated Pdgfrβ signaling, induced epithelial-to-mesenchymal transition, and led to BLBCs. Confirming this role, targeted deletion of Pdgfrβ in Brca1-deficient tumor cells promoted cell death, induced mesenchymal-to-epithelial transition, and suppressed tumorigenesis. Importantly, we also found that pharmaceutical inhibition of Pdgfrβ and its downstream target Pkcα suppressed Brca1-deficient tumor initiation and progression and effectively killed BRCA1-deficient cancer cells., Conclusions: Our work offers the first genetic and biochemical evidence that PDGFRβ-PKCα signaling is repressed by BRCA1, which establishes PDGFRβ-PKCα signaling as a therapeutic target for BRCA1-deficient breast cancers.

Background: HER2-positive (HER2+) breast cancer (BC) comprises all the four PAM50 molecular subtypes. Among these, the HER2-Enriched (HER2-E) appear to be associated with higher pathological complete response (pCR) rates following anti-HER2-based regimens. Here, we present a meta-analysis to validate the association of the HER2-E subtype with pCR following anti-HER2-based neoadjuvant treatments with or without chemotherapy (CT)., Methods: A systematic literature search was performed in February 2019. The primary objective was to compare the association between HER2-E subtype (versus others) and pCR. Selected secondary objectives were to compare the association between 1) HER2-E subtype and pCR in CT-free studies, 2) HER2-E subtype within hormone receptor (HR)-negative and HR+ disease and 3) HR-negative disease (versus HR+) and pCR in all patients and within HER2-E subtype. A random-effect model was applied. The Higgins' I 2 was used to quantify heterogeneity., Results: Sixteen studies were included, 5 of which tested CT-free regimens. HER2-E subtype was significantly associated with pCR in all patients (odds ratio [OR] = 3.50, p < 0.001, I 2  = 33%), in HR+ (OR = 3.61, p < 0.001, I 2  = 1%) and HR-negative tumors (OR = 2.28, p = 0.01, I 2  = 47%). In CT-free studies, HER2-E subtype was associated with pCR in all patients (OR = 5.52, p < 0.001, I 2  = 0%) and in HR + disease (OR = 4.08, p = 0.001, I 2  = 0%). HR-negative status was significantly associated with pCR compared to HR + status in all patients (OR = 2.41, p < 0.001, I 2  = 30%) and within the HER2-E subtype (OR = 1.76, p < 0.001, I 2  = 0%)., Conclusions: The HER2-E biomarker identifies patients with a higher likelihood of achieving a pCR following neoadjuvant anti-HER2-based therapy beyond HR status and CT use. Future trial designs to escalate or de-escalate systemic therapy in HER2+ disease should consider this genomic biomarker., Competing Interests: Declaration of Competing Interest FS has declared travel and accommodation expenses paid by Roche, Pfizer and Celgene. SDP has declared honoraria from Roche, Pfizer, Astra-Zeneca, Novartis, Celgene, Eli Lilly, Amgen and Eisai. AP has declared an immediate family member being employed by Novartis, personal honoraria from Pfizer, Novartis, Roche, MSD Oncology, Lilly and Daiichi Sankyo, travel, accommodations and expenses paid by Daiichi Sankyo, research funding from Roche and Novartis, consulting/advisory role for NanoString Technologies, Amgen, Roche, Novartis, Pfizer and Bristol-Myers Squibb and patent PCT/EP2016/080056: HER2 AS A PREDICTOR OF RESPONSE TO DUAL HER2 BLOCKADE IN THE ABSENCE OF CYTOTOXIC THERAPY. OTHER AUTHORS CoI. PFC had declared consultant role for Novartis, Eli Lilly, Astra Zeneca and Tesaro, honoraria from BMS, Roche, Eli Lilly, Novartis and AstraZeneca, research funding from Novartis, Roche, BMS, Merck-KGa, Italian Ministry of Health, Veneto Secretary of Health and University of Padova. CMP is an equity stock holder and consultant of BioClassifier LLC and is also listed an inventor on patent applications on the Breast PAM50. LAC has declared that Companies who have provided funds to her institution in the past 1–2 years either for her service on advisory/consultative programs or sponsored research were Genentech, Roche, Novartis, Seattle Genetics, G1 Therapeutics, Immunomedics and Innocrin.SP has received honoraria for talks and travel grants from Roche outside of the submitted work and serves as an advisor/consultant to Polyphor. RS has declared research funding from AstraZeneca, GlaxoSmithKline, Gilead Sciences, and PUMA Biotechnology, and consulting/advisory role with compensation for Macrogenics, and Eli Lilly. CKO has declared research funding from AstraZeneca and GlaxoSmithKline, advisory boards for Tolmar Pharmaceuticals, Genentech, and AstraZeneca, DMC for Eli Lilly and stockholder of GeneTex. MFR has declared research funding from GlaxoSmithKline and Genentech. JCB reports employment and stocks with Novartis. The other authors have nothing to declare., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Purpose: Female breast cancer demonstrates bimodal age frequency distribution patterns at diagnosis, interpretable as two main etiologic subtypes or groupings of tumors with shared risk factors. While RNA-based methods including PAM50 have identified well-established clinical subtypes, age distribution patterns at diagnosis as a proxy for etiologic subtype are not established for molecular and genomic tumor classifications., Methods: We evaluated smoothed age frequency distributions at diagnosis for Carolina Breast Cancer Study cases within immunohistochemistry-based and RNA-based expression categories. Akaike information criterion (AIC) values compared the fit of single density versus two-component mixture models. Two-component mixture models estimated the proportion of early-onset and late-onset categories by immunohistochemistry-based ER (n = 2860), and by RNA-based ESR1 and PAM50 subtype (n = 1965). PAM50 findings were validated using pooled publicly available data (n = 8103)., Results: Breast cancers were best characterized by bimodal age distribution at diagnosis with incidence peaks near 45 and 65 years, regardless of molecular characteristics. However, proportional composition of early-onset and late-onset age distributions varied by molecular and genomic characteristics. Higher ER-protein and ESR1-RNA categories showed a greater proportion of late age-at-onset. Similarly, PAM50 subtypes showed a shifting age-at-onset distribution, with most pronounced early-onset and late-onset peaks found in Basal-like and Luminal A, respectively., Conclusions: Bimodal age distribution at diagnosis was detected in the Carolina Breast Cancer Study, similar to national cancer registry data. Our data support two fundamental age-defined etiologic breast cancer subtypes that persist across molecular and genomic characteristics. Better criteria to distinguish etiologic subtypes could improve understanding of breast cancer etiology and contribute to prevention efforts.

Background: Full RNA-Seq is a fundamental research tool for whole transcriptome analysis. However, it is too costly and time consuming to be used in routine clinical practice. We evaluated the transcript quantification agreement between RNA-Seq and a digital multiplexed gene expression platform, and the subtype call after running the PAM50 assay in a series of breast cancer patients classified as triple negative by IHC/FISH. The goal of this study is to analyze the concordance between both expression platforms overall, and for calling PAM50 triple negative breast cancer intrinsic subtypes in particular., Results: The analyses were performed in paraffin-embedded tissues from 96 patients recruited in a multicenter, prospective, non-randomized neoadjuvant triple negative breast cancer trial (NCT01560663). Pre-treatment core biopsies were obtained following clinical practice guidelines and conserved as FFPE for further RNA extraction. PAM50 was performed on both digital multiplexed gene expression and RNA-Seq platforms. Subtype assignment was based on the nearest centroid classification following this procedure for both platforms and it was concordant on 96% of the cases (N = 96). In four cases, digital multiplexed gene expression analysis and RNA-Seq were discordant. The Spearman correlation to each of the centroids and the risk of recurrence were above 0.89 in both platforms while the agreement on Proliferation Score reached up to 0.97. In addition, 82% of the individual PAM50 genes showed a correlation coefficient > 0.80., Conclusions: In our analysis, the subtype calling in most of the samples was concordant in both platforms and the potential discordances had reduced clinical implications in terms of prognosis. If speed and cost are the main driving forces then the preferred technique is the digital multiplexed platform, while if whole genome patterns and subtype are the driving forces, then RNA-Seq is the preferred method.

Background: Use of cyclin D1 (CCND1) gene amplification as a breast cancer biomarker has been hampered by conflicting assessments of the relationship between cyclin D1 protein levels and patient survival. Here, we aimed to clarify its prognostic and treatment predictive potential through comprehensive long-term survival analyses., Methods: CCND1 amplification was assessed using SNP arrays from two cohorts of 1965 and 340 patients with matching gene expression array and clinical follow-up data of over 15 years. Kaplan-Meier and multivariable Cox regression analyses were used to determine survival differences between CCND1 amplified vs. non-amplified tumours in clinically relevant patient sets, within PAM50 subtypes and within treatment-specific subgroups. Boxplots and differential gene expression analyses were performed to assess differences between amplified vs. non-amplified tumours within PAM50 subtypes., Results: When combining both cohorts, worse survival was found for patients with CCND1-amplified tumours in luminal A (HR = 1.68; 95% CI, 1.15-2.46), luminal B (1.37; 1.01-1.86) and ER+/LN-/HER2- (1.66; 1.14-2.41) subgroups. In gene expression analysis, CCND1-amplified luminal A tumours showed increased proliferation (P < 0.001) and decreased progesterone (P = 0.002) levels along with a large overlap in differentially expressed genes when comparing luminal A and B-amplified vs. non-amplified tumours., Conclusions: Our results indicate that CCND1 amplification is associated with worse 15-year survival in ER+/LN-/HER2-, luminal A and luminal B patients. Moreover, luminal A CCND1-amplified tumours display gene expression changes consistent with a more aggressive phenotype. These novel findings highlight the potential of CCND1 to identify patients that could benefit from long-term treatment strategies.

The 2013 update of the American Society of Clinical Oncology-College of American Pathologists (ASCO-CAP) human epidermal growth factor receptor 2 (HER2) testing guidelines recommend using an alternative chromosome 17 probe assay to resolve HER2 results determined to be equivocal by immunohistochemistry (IHC) or fluorescence in-situ hybridization (FISH). However, it is unclear if cases considered HER2-positive (HER2 + ) by the alternative probe method are similar to those classified as HER2 + by traditional IHC and FISH criteria and benefit the same from HER2-targeted therapies. We studied the clinical and pathologic features of all 31 breast cancers classified as HER2 + by the alternative probe method at our institution since 2013 and determined their PAM50 intrinsic molecular subtypes. For comparison, we analyzed 19 consecutive cases that were classified as HER2 + by traditional FISH criteria during the same time period. Thirty (97%) cancers in the alternative probe cohort were estrogen receptor (ER)-positive (ER + ), while only 9/19 (47%) of traditional HER2 controls were ER + (p = 0.0002). Sufficient tissue for intrinsic subtype analysis was available for 20/31 cancers in the alternative probe cohort and 9/19 in the traditional HER2 + group. None (0%) of the 20 alternative probe-positive cases were of the HER2-enriched intrinsic subtype, while 8/9 (89%) of those HER2 + by traditional FISH criteria were HER2-enriched (p = 0.0001). These findings suggest that breast cancers classified as HER2 + only by the alternative probe method are biologically distinct from those classified as HER2 + by traditional criteria, and raises questions as to whether or not they derive the same benefit from HER2-targeted therapies.

Breast cancers detected after a negative breast screening examination and prior to the next screening are referred to as interval cancers. These cancers generally have poor clinical characteristics compared with screen-detected cancers, but associations between interval cancer and genomic cancer characteristics are not well understood. Mammographically screened women diagnosed with primary invasive breast cancer from 1993 to 2013 ( n = 370) were identified by linking the Carolina Breast Cancer Study and the Carolina Mammography Registry. Among women with a registry-identified screening mammogram 0 to 24 months before diagnosis, cancers were classified as screen-detected ( N = 165) or interval-detected ( N = 205). Using logistic regression, we examined the association of mode of detection with cancer characteristics (clinical, IHC, and genomic), overall, and in analyses stratified on mammographic density and race. Interval cancer was associated with large tumors [>2 cm; OR, 2.3; 95% confidence interval (CI), 1.5-3.7], positive nodal status (OR, 1.8; 95% CI, 1.1-2.8), and triple-negative subtype (OR, 2.5; 95% CI, 1.1-5.5). Interval cancers were more likely to have non-Luminal A subtype (OR, 2.9; 95% CI, 1.5-5.7), whereas screen-detected cancers tended to be more indolent (96% had low risk of recurrence genomic scores; 71% were PAM50 Luminal A). When stratifying by mammographic density and race, associations between interval detection and poor prognostic features were similar by race and density status. Strong associations between interval cancers and poor-prognosis genomic features (non-Luminal A subtype and high risk of recurrence score) suggest that aggressive tumor biology is an important contributor to interval cancer rates. Cancer Prev Res; 11(6); 327-36. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Introduction: Molecular subtyping of lung adenocarcinoma (AD) and lung squamous cell carcinoma (SCC) reveal biologically diverse tumors that vary in their genomic and clinical attributes., Methods: Published immune cell signatures and several lung AD and SCC gene expression data sets, including The Cancer Genome Atlas, were used to examine immune response in relation to AD and SCC expression subtypes. Expression of immune cell populations and other immune related genes, including CD274 molecule gene (CD274) (programmed death ligand 1), was investigated in the tumor microenvironment relative to the expression subtypes of the AD (terminal respiratory unit, proximal proliferative, and proximal inflammatory) and SCC (primitive, classical, secretory, and basal) subtypes., Results: Lung AD and SCC expression subtypes demonstrated significant differences in tumor immune landscape. The proximal proliferative subtype of AD demonstrated low immune cell expression among ADs whereas the secretory subtype showed elevated immune cell expression among SCCs. Tumor expression subtype was a better predictor of immune cell expression than CD274 (programmed death ligand 1) in SCC tumors but was a comparable predictor in AD tumors. Nonsilent mutation burden was not correlated with immune cell expression across subtypes; however, major histocompatibility complex class II gene expression was highly correlated with immune cell expression. Increased immune and major histocompatibility complex II gene expression was associated with improved survival in the terminal respiratory unit and proximal inflammatory subtypes of AD and in the primitive subtype of SCC., Conclusions: Molecular expression subtypes of lung AD and SCC demonstrate key and reproducible differences in immune host response. Evaluation of tumor expression subtypes as potential biomarkers for immunotherapy should be investigated., (Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Biological changes that occur during metastatic progression of breast cancer are still incompletely characterized. In this study, we compared intrinsic molecular subtypes and gene expression in 123 paired primary and metastatic tissues from breast cancer patients. Intrinsic subtype was identified using a PAM50 classifier and χ 2 tests determined the differences in variable distribution. The rate of subtype conversion was 0% in basal-like tumors, 23.1% in HER2-enriched (HER2-E) tumors, 30.0% in luminal B tumors, and 55.3% in luminal A tumors. In 40.2% of cases, luminal A tumors converted to luminal B tumors, whereas in 14.3% of cases luminal A and B tumors converted to HER2-E tumors. We identified 47 genes that were expressed differentially in metastatic versus primary disease. Metastatic tumors were enriched for proliferation-related and migration-related genes and diminished for luminal-related genes. Expression of proliferation-related genes were better at predicting overall survival in metastatic disease (OSmet) when analyzed in metastatic tissue rather than primary tissue. In contrast, a basal-like gene expression signature was better at predicting OSmet in primary disease compared with metastatic tissue. We observed correlations between time to tumor relapse and the magnitude of changes of proliferation, luminal B, or HER2-E signatures in metastatic versus primary disease. Although the intrinsic subtype was largely maintained during metastatic progression, luminal/HER2-negative tumors acquired a luminal B or HER2-E profile during metastatic progression, likely reflecting tumor evolution or acquisition of estrogen independence. Overall, our analysis revealed the value of stratifying gene expression by both cancer subtype and tissue type, providing clinicians more refined tools to evaluate prognosis and treatment. Cancer Res; 77(9); 2213-21. ©2017 AACR ., (©2017 American Association for Cancer Research.)

The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at www.dx.ai/tcga&#95;breast. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd., (Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.)

Purpose: The current study evaluated associative effects of breast cancer cells with the tumor microenvironment and its influence on tumor behavior., Experimental Design: Formalin-fixed, paraffin-embedded tissue and matched protein lysates were evaluated from two independent breast cancer patient datasets (TCGA and MD Anderson). Reverse-phase protein arrays (RPPA) were utilized to create a proteomics signature to define breast tumor subtypes. Expression patterns of cell lines and normal breast tissues were utilized to determine markers that were differentially expressed in stroma and cancer cells. Protein localization and stromal contents were evaluated for matched cases by imaging., Results: A subtype of breast cancers designated "Reactive," previously identified by RPPA that was not predicted by mRNA profiling, was extensively characterized. These tumors were primarily estrogen receptor (ER)-positive/human EGF receptor (HER)2-negative, low-risk cancers as determined by enrichment of low-grade nuclei, lobular or tubular histopathology, and the luminal A subtype by PAM50. Reactive breast cancers contained high numbers of stromal cells and the highest extracellular matrix content typically without infiltration of immune cells. For ER-positive/HER2-negative cancers, the Reactive classification predicted favorable clinical outcomes in the TCGA cohort (HR, 0.36; P < 0.05)., Conclusions: A protein stromal signature in breast cancers is associated with a highly differentiated phenotype. The stromal compartment content and proteins are an extended phenotype not predicted by mRNA expression that could be utilized to subclassify ER-positive/HER2-negative breast cancers. Clin Cancer Res; 22(20); 5068-78. ©2016 AACR., (©2016 American Association for Cancer Research.)

The role of biomarkers has increased in cancer clinical trials such that novel designs are needed to efficiently answer questions of both drug effects and biomarker performance. We advocate Bayesian hierarchical models for response-adaptive randomized phase II studies integrating single or multiple biomarkers. Prior selection allows one to control a gradual and seamless transition from randomized-blocks to marker-enrichment during the trial. Adaptive randomization is an efficient design for evaluating treatment efficacy within biomarker subgroups, with less variable final sample sizes when compared to nested staged designs. Inference based on the Bayesian hierarchical model also has improved performance in identifying the sub-population where therapeutics are effective over independent analyses done within each biomarker subgroup.

Background: Controversy exists regarding the impact of CYP2D6 genotype on tamoxifen responsiveness. We examined loss of heterozygosity (LOH) at the CYP2D6 locus and determined its impact on genotyping error when tumor tissue is used as a DNA source., Methods: Genomic tumor data from the adjuvant and metastatic settings (The Cancer Genome Atlas [TCGA] and Foundation Medicine [FM]) were analyzed to characterize the impact of CYP2D6 copy number alterations (CNAs) and LOH on Hardy Weinberg equilibrium (HWE). Additionally, we analyzed CYP2D6 *4 genotype from formalin-fixed paraffin-embedded (FFPE) tumor blocks containing nonmalignant tissue and buccal (germline) samples from patients on the North Central Cancer Treatment Group (NCCTG) 89-30-52 tamoxifen trial. All statistical tests were two-sided., Results: In TCGA samples (n =627), the CYP2D6 LOH rate was similar in estrogen receptor (ER)-positive (41.2%) and ER-negative (35.2%) but lower in HER2-positive tumors (15.1%) (P < .001). In FM ER+ samples (n = 290), similar LOH rates were observed (40.8%). In 190 NCCTG samples, the agreement between CYP2D6 genotypes derived from FFPE tumors and FFPE tumors containing nonmalignant tissue was moderate (weighted Kappa = 0.74; 95% CI = 0.63 to 0.84). Comparing CYP2D6 genotypes derived from buccal cells to FFPE tumor DNA, CYP2D6*4 genotype was discordant in six of 31(19.4%). In contrast, there was no disagreement between CYP2D6 genotypes derived from buccal cells with FFPE tumors containing nonmalignant tissue., Conclusions: LOH at the CYP2D6 locus is common in breast cancer, resulting in potential misclassification of germline CYP2D6 genotypes. Tumor DNA should not be used to determine germline CYP2D6 genotype without sensitive techniques to detect low frequency alleles and quality control procedures appropriate for somatic DNA., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: The clinical impact of the biological heterogeneity within HER2-positive (HER2+) breast cancer is not fully understood. Here, we evaluated the molecular features and survival outcomes of the intrinsic subtypes within HER2+ breast cancer., Methods: We interrogated The Cancer Genome Atlas (n = 495) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets (n = 1730) of primary breast cancers for molecular data derived from DNA, RNA and protein, and determined intrinsic subtype. Clinical HER2 status was defined according to American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines or DNA copy-number aberration by single nucleotide polymorphism arrays. Cox models tested the prognostic significance of each variable in patients not treated with trastuzumab (n = 1711)., Results: Compared with clinically HER2 (cHER2)-negative breast cancer, cHER2+ breast cancer had a higher frequency of the HER2-enriched (HER2E) subtype (47.0% vs 7.1%) and a lower frequency of Luminal A (10.7% vs 39.0%) and Basal-like (14.1% vs 23.4%) subtypes. The likelihood of cHER2-positivity in HER2E, Luminal B, Basal-like and Luminal A subtypes was 64.6%, 20.0%, 14.4% and 7.3%, respectively. Within each subtype, only 0.3% to 3.9% of genes were found differentially expressed between cHER2+ and cHER2-negative tumors. Within cHER2+ tumors, HER2 gene and protein expression was statistically significantly higher in the HER2E and Basal-like subtypes than either luminal subtype. Neither cHER2 status nor the new 10-subtype copy number-based classification system (IntClust) added independent prognostic value to intrinsic subtype., Conclusions: When the intrinsic subtypes are taken into account, cHER2-positivity does not translate into large changes in the expression of downstream signaling pathways, nor does it affect patient survival in the absence of HER2 targeting., (© The Author 2014. Published by Oxford University Press.)

Breast cancer is a heterogeneous disease, divisible into a variable number of clinical subtypes. A fundamental question is how many etiological classes underlie the clinical spectrum of breast cancer? An etiological subtype reflects a grouping with a common set of causes, whereas a clinical subtype represents a grouping with similar prognosis and/or prediction. Herein, we review the evidence for breast cancer etiological heterogeneity. We then evaluate the etiological evidence with mRNA profiling data. A bimodal age distribution at diagnosis with peak frequencies near ages 50 and 70 years is a fundamental characteristic of breast cancer for important tumor features, clinical characteristics, risk factor profiles, and molecular subtypes. The bimodal peak frequencies at diagnosis divide breast cancer overall into a "mixture" of two main components in varying proportions in different cancer populations. The first breast cancer tends to arise early in life with modal age-at-diagnosis near 50 years and generally behaves aggressively. The second breast cancer occurs later in life with modal age near 70 years and usually portends a more indolent clinical course. These epidemiological and molecular data are consistent with a two-component mixture model and compatible with a hierarchal view of breast cancers arising from two main cell types of origin. Notwithstanding the potential added value of more detailed categorizations for personalized breast cancer treatment, we suggest that the development of better criteria to identify the two proposed etiologic classes would advance breast cancer research and prevention., (Published by Oxford University Press 2014.)

BRCA1-mutated breast cancer is associated with basal-like disease; however, it is currently unclear if the presence of a BRCA1 mutation depicts a different entity within this subgroup. In this study, we compared the molecular features among basal-like tumors with and without BRCA1 mutations. Fourteen patients with BRCA1-mutated (nine germline and five somatic) tumors and basal-like disease, and 79 patients with BRCA1 non-mutated tumors and basal-like disease, were identified from the cancer genome atlas dataset. The following molecular data types were evaluated: global gene expression, selected protein and phospho-protein expression, global miRNA expression, global DNA methylation, total number of somatic mutations, TP53 and PIK3CA somatic mutations, and global DNA copy-number aberrations. For intrinsic subtype identification, we used the PAM50 subtype predictor. Within the basal-like disease, we observed minor molecular differences in terms of gene, protein, and miRNA expression, and DNA methylation variation, according to BRCA1 status (either germinal or somatic). However, there were significant differences according to average number of mutations and DNA copy-number aberrations, and four amplified regions (2q32.2, 3q29, 6p22.3, and 22q12.2), which are characteristic in high-grade serous ovarian carcinomas, were observed in both germline and somatic BRCA1-mutated breast tumors. These results suggest that minor, but potentially relevant, baseline molecular features exist among basal-like tumors according to BRCA1 status. Additional studies are needed to better clarify if BRCA1 genetic status is an independent prognostic feature, and more importantly, if BRCA1 mutation status is a predictive biomarker of benefit from DNA-damaging agents among basal-like disease.

Gene expression profiling of breast cancer delineates a particularly aggressive subtype referred to as 'basal-like', which comprises ∼15% of all breast cancers, afflicts younger women and is refractory to endocrine and anti-HER2 therapies. Immunohistochemical surrogate definitions for basal-like breast cancer, such as the clinical ER/PR/HER2 triple-negative phenotype and models incorporating positive expression for CK5 (CK5/6) and/or EGFR are heavily cited. However, many additional biomarkers for basal-like breast cancer have been described in the literature. A parallel comparison of 46 proposed immunohistochemical biomarkers of basal-like breast cancer was performed against a gene expression profile gold standard on a tissue microarray containing 42 basal-like and 80 non-basal-like breast cancer cases. Ki67 and PPH3 were the most sensitive biomarkers (both 92%) positively expressed in the basal-like subtype, whereas CK14, IMP3 and NGFR were the most specific (100%). Among biomarkers surveyed, loss of INPP4B (a negative regulator of phosphatidylinositol signaling) was 61% sensitive and 99% specific with the highest odds ratio (OR) at 108, indicating the strongest association with basal-like breast cancer. Expression of nestin, a common marker of neural progenitor cells that is also associated with the triple-negative/basal-like phenotype and poor breast cancer prognosis, possessed the second highest OR at 29 among the 46 biomarkers surveyed, as well as 54% sensitivity and 96% specificity. As a positively expressed biomarker, nestin possesses technical advantages over INPP4B that make it a more ideal biomarker for identification of basal-like breast cancer. The comprehensive immunohistochemical biomarker survey presented in this study is a necessary step for determining an optimized surrogate immunopanel that best defines basal-like breast cancer in a practical and clinically accessible way.

Triple-negative (TN) and basal-like (BL) breast cancer definitions have been used interchangeably to identify breast cancers that lack expression of the hormone receptors and overexpression and/or amplification of HER2. However, both classifications show substantial discordance rates when compared to each other. Here, we molecularly characterize TN tumors and BL tumors, comparing and contrasting the results in terms of common patterns and distinct patterns for each. In total, when testing 412 TN and 473 BL tumors, 21.4% and 31.5% were identified as non-BL and non-TN, respectively. TN tumors identified as luminal or HER2-enriched (HER2E) showed undistinguishable overall gene expression profiles when compared versus luminal or HER2E tumors that were not TN. Similar findings were observed within BL tumors regardless of their TN status, which suggests that molecular subtype is preserved regardless of individual marker results. Interestingly, most TN tumors identified as HER2E showed low HER2 expression and lacked HER2 amplification, despite the similar overall gene expression profiles to HER2E tumors that were clinically HER2-positive. Lastly, additional genomic classifications were examined within TN and BL cancers, most of which were highly concordant with tumor intrinsic subtype. These results suggest that future clinical trials focused on TN disease should consider stratifying patients based upon BL versus non-BL gene expression profiles, which appears to be the main biological difference seen in patients with TN breast cancer.

Background: ER-positive (ER+) breast cancer includes all of the intrinsic molecular subtypes, although the luminal A and B subtypes predominate. In this study, we evaluated the ability of six clinically relevant genomic signatures to predict relapse in patients with ER+ tumors treated with adjuvant tamoxifen only., Methods: Four microarray datasets were combined and research-based versions of PAM50 intrinsic subtyping and risk of relapse (PAM50-ROR) score, 21-gene recurrence score (OncotypeDX), Mammaprint, Rotterdam 76 gene, index of sensitivity to endocrine therapy (SET) and an estrogen-induced gene set were evaluated. Distant relapse-free survival (DRFS) was estimated by Kaplan-Meier and log-rank tests, and multivariable analyses were done using Cox regression analysis. Harrell's C-index was also used to estimate performance., Results: All signatures were prognostic in patients with ER+ node-negative tumors, whereas most were prognostic in ER+ node-positive disease. Among the signatures evaluated, PAM50-ROR, OncotypeDX, Mammaprint and SET were consistently found to be independent predictors of relapse. A combination of all signatures significantly increased the performance prediction. Importantly, low-risk tumors (>90% DRFS at 8.5 years) were identified by the majority of signatures only within node-negative disease, and these tumors were mostly luminal A (78%-100%)., Conclusions: Most established genomic signatures were successful in outcome predictions in ER+ breast cancer and provided statistically independent information. From a clinical perspective, multiple signatures combined together most accurately predicted outcome, but a common finding was that each signature identified a subset of luminal A patients with node-negative disease who might be considered suitable candidates for adjuvant endocrine therapy alone.

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: Epidermal growth factor receptor (EGFR) is a targetable receptor frequently overexpressed in basal-like breast cancer, which comprises most triple-negative breast cancers (TNBCs), the only subtype without established targeted therapy., Patients and Methods: In this randomized phase II trial, patients with metastatic TNBC received anti-EGFR antibody cetuximab (400 mg/m(2) load then 250 mg/m(2) per week intravenously [IV]) alone, with carboplatin (area under the curve of 2, once per week IV) added after progression or as concomitant therapy from the beginning. Response rate (RR) was the primary end point; others included time to progression (TTP), overall survival (OS), and toxicity. Embedded correlative studies included molecular subtyping on archival tissue. Fresh tumor tissue before and after 7 to 14 days of therapy was used for microarray analyses exploring EGFR pathway activity and inhibition., Results: In 102 patients with TNBC, RRs were 6% (two of 31) to cetuximab and 16% (four of 25) to cetuximab plus carboplatin after progression. RR to those treated from the beginning with cetuximab plus carboplatin was 17% (12 of 71); 31% of patients responded or had prolonged disease stabilization. The cetuximab plus carboplatin regimen was well tolerated, but both TTP and OS were short at 2.1 months (95% CI, 1.8 to 5.5 months) and 10.4 months (95% CI, 7.7 to 13.1 months), respectively. Of 73 patients with archival tissue for analysis, 74% had basal-like molecular subtype. Sixteen patients had tumor biopsies before and 1 week after therapy; genomic patterns of the EGFR pathway showed activation in 13 and inhibition by therapy in five., Conclusion: Despite strong preclinical data, combination cetuximab plus carboplatin in metastatic TNBC produced responses in fewer than 20% of patients. EGFR pathway analysis showed that most TNBCs involved activation. However, cetuximab blocked expression of the EGFR pathway in only a minority, suggesting that most had alternate mechanisms for pathway activation.

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥ 3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group.

Introduction: In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line., Methods: We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ~ 15 kb)., Results: Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5' regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival., Conclusion: Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.

Introduction: In breast cancer, gene expression analyses have defined five tumor subtypes (luminal A, luminal B, HER2-enriched, basal-like and claudin-low), each of which has unique biologic and prognostic features. Here, we comprehensively characterize the recently identified claudin-low tumor subtype., Methods: The clinical, pathological and biological features of claudin-low tumors were compared to the other tumor subtypes using an updated human tumor database and multiple independent data sets. These main features of claudin-low tumors were also evaluated in a panel of breast cancer cell lines and genetically engineered mouse models., Results: Claudin-low tumors are characterized by the low to absent expression of luminal differentiation markers, high enrichment for epithelial-to-mesenchymal transition markers, immune response genes and cancer stem cell-like features. Clinically, the majority of claudin-low tumors are poor prognosis estrogen receptor (ER)-negative, progesterone receptor (PR)-negative, and epidermal growth factor receptor 2 (HER2)-negative (triple negative) invasive ductal carcinomas with a high frequency of metaplastic and medullary differentiation. They also have a response rate to standard preoperative chemotherapy that is intermediate between that of basal-like and luminal tumors. Interestingly, we show that a group of highly utilized breast cancer cell lines, and several genetically engineered mouse models, express the claudin-low phenotype. Finally, we confirm that a prognostically relevant differentiation hierarchy exists across all breast cancers in which the claudin-low subtype most closely resembles the mammary epithelial stem cell., Conclusions: These results should help to improve our understanding of the biologic heterogeneity of breast cancer and provide tools for the further evaluation of the unique biology of claudin-low tumors and cell lines.

Purpose: Compared with white women, black women experience a disproportionate burden of aggressive breast cancer for reasons that remain unknown and understudied. In the first study of its kind, we determined the distribution of molecular subtypes of invasive breast tumors in indigenous black women in West Africa., Patients and Methods: The study comprised 507 patients diagnosed with breast cancer between 1996 and 2007 at six geographic regions in Nigeria and Senegal. Formalin-fixed and paraffin-embedded sections were constructed into tissue microarrays and immunostained with 15 antibodies. Five molecular subtypes were determined, and hierarchical cluster analysis was conducted to explore subgroups for unclassified cases., Results: The mean (+/- standard deviation) age of 378 patients in the first cohort was 44.8 +/- 11.8 years, with the majority of women presenting with large (4.4 +/- 2.0 cm) high-grade tumors (83%) in advanced stages (72% node positive). The proportions of estrogen receptor (ER) -positive, progesterone receptor-positive, and human epidermal growth factor receptor 2 (HER2) -positive tumors were 24%, 20%, and 17%, respectively. Triple negativity for these markers was predominant, including basal-like (27%) and unclassified subtype (28%). Other subtypes were luminal A (27%), luminal B (2%), and HER2 positive/ER negative (15%). The findings were replicated in the second cohort of 129 patients. The unclassified cases could be grouped into a bad prognosis branch, with expression of vascular endothelial growth factor, B-cell lymphoma extra-large protein, and Cyclin E, and a good prognosis branch, with expression of B-cell lymphoma protein 2 and Cyclin D1., Conclusion: These findings underscore the urgent need for research into the etiology and treatment of the aggressive molecular subtypes that disproportionately affect young women in the African diaspora.

Background: Tumor metastases pose the greatest threat to a patient's survival, and thus, understanding the biology of disseminated cancer cells is critical for developing effective therapies., Methods: Microarrays and immunohistochemistry were used to analyze primary breast tumors, regional (lymph node) metastases, and distant metastases in order to identify biological features associated with distant metastases., Results: When compared with each other, primary tumors and regional metastases showed statistically indistinguishable gene expression patterns. Supervised analyses comparing patients with distant metastases versus primary tumors or regional metastases showed that the distant metastases were distinct and distinguished by the lack of expression of fibroblast/mesenchymal genes, and by the high expression of a 13-gene profile (that is, the 'vascular endothelial growth factor (VEGF) profile') that included VEGF, ANGPTL4, ADM and the monocarboxylic acid transporter SLC16A3. At least 8 out of 13 of these genes contained HIF1alpha binding sites, many are known to be HIF1alpha-regulated, and expression of the VEGF profile correlated with HIF1alpha IHC positivity. The VEGF profile also showed prognostic significance on tests of sets of patients with breast and lung cancer and glioblastomas, and was an independent predictor of outcomes in primary breast cancers when tested in models that contained other prognostic gene expression profiles and clinical variables., Conclusion: These data identify a compact in vivo hypoxia signature that tends to be present in distant metastasis samples, and which portends a poor outcome in multiple tumor types.This signature suggests that the response to hypoxia includes the ability to promote new blood and lymphatic vessel formation, and that the dual targeting of multiple cell types and pathways will be needed to prevent metastatic spread.

Introduction: Perhaps the major challenge in developing more effective therapeutic strategies for the treatment of breast cancer patients is confronting the heterogeneity of the disease, recognizing that breast cancer is not one disease but multiple disorders with distinct underlying mechanisms. Gene-expression profiling studies have been used to dissect this complexity, and our previous studies identified a series of intrinsic subtypes of breast cancer that define distinct populations of patients with respect to survival. Additional work has also used signatures of oncogenic pathway deregulation to dissect breast cancer heterogeneity as well as to suggest therapeutic opportunities linked to pathway activation., Methods: We used genomic analyses to identify relations between breast cancer subtypes, pathway deregulation, and drug sensitivity. For these studies, we use three independent breast cancer gene-expression data sets to measure an individual tumor phenotype. Correlation between pathway status and subtype are examined and linked to predictions for response to conventional chemotherapies., Results: We reveal patterns of pathway activation characteristic of each molecular breast cancer subtype, including within the more aggressive subtypes in which novel therapeutic opportunities are critically needed. Whereas some oncogenic pathways have high correlations to breast cancer subtype (RAS, CTNNB1, p53, HER1), others have high variability of activity within a specific subtype (MYC, E2F3, SRC), reflecting biology independent of common clinical factors. Additionally, we combined these analyses with predictions of sensitivity to commonly used cytotoxic chemotherapies to provide additional opportunities for therapeutics specific to the intrinsic subtype that might be better aligned with the characteristics of the individual patient., Conclusions: Genomic analyses can be used to dissect the heterogeneity of breast cancer. We use an integrated analysis of breast cancer that combines independent methods of genomic analyses to highlight the complexity of signaling pathways underlying different breast cancer phenotypes and to identify optimal therapeutic opportunities.

Purpose: Human invasive breast cancers (IBC) show enormous histologic and biological diversity. This study comprehensively evaluated diversity in ductal carcinoma in situ (DCIS), the immediate precursors of IBCs., Experimental Design: The extent of diversity for conventional histologic grade and standard prognostic biomarkers assessed by immunohistochemistry was evaluated in a series of pure DCIS (n = 200) compared with a contemporaneous series of IBCs (n = 200). A subset of the DCIS (n = 25) was evaluated by DNA microarrays for the presence of luminal, basal, and erbB2 intrinsic subtypes. The extent of diversity within individual cases of DCIS (n = 120) was determined by assessing multiple regions independently for histologic (nuclear) grade and several biomarkers by immunohistochemistry, which approximate microarrays in determining intrinsic subtypes., Results: DCIS showed a broad distribution of conventional histologic grades and standard biomarkers ranging from well to poorly differentiated, nearly identical to IBCs. Microarrays showed the same intrinsic subtypes in DCIS as in IBCs. However, higher resolution analysis showed that multiple histologic grades, biomarker phenotypes, and intrinsic subtypes often coexist within the same DCIS, and these diverse regions probably compete for dominance. Diversity within cases of DCIS was highly correlated with mutated p53 (P = 0.0007)., Conclusions: These results support the hypothesis that poorly differentiated DCIS gradually evolve from well-differentiated DCIS by randomly acquiring genetic defects resulting in increasingly abnormal cellular features. This diversity is amplified by defects resulting in genetic instability (e.g., p53 mutation), and the alterations are propagated to IBC in a manner independent of progression to invasion.

Purpose: FOXA1, a forkhead family transcription factor, is essential for optimum expression of approximately 50% of estrogen receptor alpha (ERalpha):estrogen responsive genes. FOXA1 is expressed in breast cancer cells. It segregates with genes that characterize the luminal subtypes in DNA microarray analyses. The utility of FOXA1 as a possible independent prognostic factor has not been determined in breast cancers., Materials and Methods: A tissue microarray comprising tumors from 438 patients with 15.4 years median follow-up was analyzed for FOXA1 expression by immunohistochemistry. Interpretable FOXA1 expression obtained in 404 patients was analyzed along with other prognostic factors like tumor grade, size, nodal status, ER, progesterone receptor (PR), and HER2/neu., Results: FOXA1 expression (score >3) was seen in 300 of 404 breast cancers and it correlated with ER (P = 0.000001), PR (P = 0.00001), and luminal A subtype (P = 0.000001). Loss of expression was noted with worsening tumor grade (P = 0.001). Univariate analysis showed nodal status (P = 0.0000012), tumor size (P = 0.00001), FOXA1 (P = 0.0004), and ER (P = 0.012) to be predictors of breast cancer-specific survival. Multivariate analysis showed only nodal status (P = 0.001) and tumor size (P = 0.039) to be significant prognostic factors, whereas FOXA1 (P = 0.060) and ER (P = 0.131) were not significant. In luminal subtype A patient subgroup, FOXA1 expression was associated with better cancer-specific survival (P = 0.024) and in ER-positive subgroup, it was better predictor of cancer-specific survival (P = 0.009) than PR (P = 0.213)., Conclusion: FOXA1 expression correlates with luminal subtype A breast cancer and it is significant predictor of cancer-specific survival in patients with ER-positive tumors. Prognostic ability of FOXA1 in these low-risk breast cancers may prove to be useful in clinical treatment decisions.

Aims: The prognostic factors and expression of molecular markers in male breast carcinomas are similar to those in female breast cancers. The identification of distinct cytokeratin (CK) profiles (basal as opposed to luminal cells) helps to identify subsets of tumours with different clinical behaviour. The aim of this study was to investigate CK expression in male breast cancer., Methods and Results: Thirty-two cases of male breast cancer were studied. The panel of CKs studied by immunohistochemistry included: 5/6, 14, 17, 18 and 19. Pathological findings and CK expression were analysed in all cases. Histological patterns included ductal carcinoma in situ, invasive ductal carcinoma and mixed patterns. Four cases were positive for CK5/6 and CK14, identifying a basal-like phenotype. CK17 was negative in all but two cases. All cases expressing either CK5/6 or CK14 were invasive carcinomas of high nuclear and histological grade and were also larger compared with the tumours not expressing CK5/6 and CK14. All tumours except three (also negative for CK5/6) expressed CK18 and CK19. The four basal-like tumours were negative for Her-2 expression., Conclusions: Male breast carcinomas have a basal-like phenotype that is similar in frequency to that of female breast carcinomas. The expression of CK5/6 and CK14 identifies a subset of pathologically aggressive male breast cancers.

When normal tissue and tumour samples are compared by microarray analysis, the biggest differences most often occur in the expression levels of genes that control cell proliferation. However, this difference is detected whenever mRNA samples that are taken from two cell populations with different proliferation rates are compared. Although the exact genes that comprise this 'proliferation signature' often differ, they are almost always genes that are involved in the fundamental process of cell proliferation. Can the proliferation signature be used to improve our understanding of the cell cycle and cancer pathogenesis, as well as being used as a biomarker for cancer diagnosis and prognosis?

The prognostication of head and neck squamous cell carcinoma (HNSCC) is largely based upon the tumor size and location and the presence of lymph node metastases. Here we show that gene expression patterns from 60 HNSCC samples assayed on cDNA microarrays allowed categorization of these tumors into four distinct subtypes. These subtypes showed statistically significant differences in recurrence-free survival and included a subtype with a possible EGFR-pathway signature, a mesenchymal-enriched subtype, a normal epithelium-like subtype, and a subtype with high levels of antioxidant enzymes. Supervised analyses to predict lymph node metastasis status were approximately 80% accurate when tumor subsite and pathological node status were considered simultaneously. This work represents an important step toward the identification of clinically significant biomarkers for HNSCC.

While several prognostic factors have been identified in breast carcinoma, the clinical outcome remains hard to predict for individual patients. Better predictive markers are needed to help guide difficult treatment decisions. In a previous study of 78 breast carcinoma specimens, we noted an association between poor clinical outcome and the expression of cytokeratin 17 and/or cytokeratin 5 mRNAs. Here we describe the results of immunohistochemistry studies using monoclonal antibodies against these markers to analyze more than 600 paraffin-embedded breast tumors in tissue microarrays. We found that expression of cytokeratin 17 and/or cytokeratin 5/6 in tumor cells was associated with a poor clinical outcome. Moreover, multivariate analysis showed that in node-negative breast carcinoma, expression of these cytokeratins was a prognostic factor independent of tumor size and tumor grade.