Gene-Expression Analysis and the Basal-Like Breast Cancer Subtype

Background: Studies have demonstrated that tumor-associated macrophages (TAMs) are recruited to tumors before malignant conversion and are essential for promoting angiogenesis. We have previously demonstrated that a high % of intratumoral M2/alternatively activated macrophages is associated with high tumor grade, increased microvessel density (MVD) and the basal-like subtype. Increased % of M1/classically activated macrophages is significantly associated with low tumor grade and the luminal A subtype. A recent in vitro study has suggested that T regulatory cells (Tregs) induce alternative activation of macrophages. No study to date has characterized the association between Tregs, macrophage phenotype and molecular subtype in sporadic breast cancers. Methods: 80 breast tumors and paired normal tissue were obtained from the University of Chicago breast SPORE tissue bank under IRB approved protocols. Molecular subtype was assigned based on immunohistochemical staining into the following groups: luminal A (ER+ and/or PR+, HER2-), luminal B (ER+ and/or PR+, HER2+), HER2-like (ER/PR-, HER2+) and basal-like (ER/PR/HER2-, EGFR+ and/or CK5/6+). Macrophage phenotype was determined using double staining with CD68/CD163 (M2) and CD68/CD80 (M1). The number of Tregs was determined by staining for Foxp3. Microvessel density (MVD) was measured by staining using anti-CD34. Staining quantification was performed independently by two pathologists. To evaluate the association of Tregs with %M1, %M2 and MVD, Spearman's rho correlation coefficients were calculated. Treg density between tumor and normal was compared using the Wilcoxon signed rank test. Breast subtype and tumor grade were associated with Treg density using the Kruskal-Wallis method. Results: Of the tumors studied, 44 were luminal A, 22 basal-like, 3 HER2-like and 3 luminal B. The mean number of Tregs per mm2 was higher in tumor as compared to paired normal breast tissue (14 vs 0, p<0.001). Treg density was significantly associated with %M2 and inversely correlated with %M1 macrophages (p=0.018 and p=0.033, respectively). The basal-like subtype was associated with a higher median value of Tregs per mm2 as compared to the luminal A subtype (31.5 vs 0, p<0.001). While the density of Tregs increased with grade, this difference was not statistically significant. There was no significant association between Treg density and MVD. Discussion: We have clearly demonstrated that Treg density increases with tumor progression and is significantly associated with a high proportion of M2 macrophages in human breast tumors. Given the recent in vitro data which suggests that Tregs are responsible for M2 polarization, strategies aimed at blocking the effects of Tregs on the subsequent alternative activation of TAMs may be highly effective in preventing the release of pro-angiogenic cytokines that enable tumor progression. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1019.

Background: Although DNA methylation profiles in breast cancer have been connected to breast cancer molecular subtype, there have been no studies of the association of DNA methylation with stem cell phenotype. This study was designed to evaluate promoter CpG islands methylation of 15 genes with regard to breast cancer subtype and to investigate whether the patterns of CpG island methylation in each subtype are associated with cancer stem cell phenotype represented by CD44+/CD24- or ALDH1 expression. Methods: We performed MethyLight analysis for the methylation status of 15 promoter CpG island loci involved in breast cancer progression (APC, DLEC1, GRIN2B, GSTP1, HOXA1, HOXA10, IGF2, MT1G, RARB, RASSF1A, RUNX3, SCGB3A1, SFRP1, SFRP4, and TMEFF2) and determined cancer stem cell phenotype by CD44/CD24 and ALDH1 immunohistochmeistry in 36 luminal A, 33 luminal B, 30 luminal-HER2, 40 HER2 enriched, and 40 basal-like subtypes of breast cancer. Results: The number of CpG island loci methylated was significantly different among subtypes and it was highest in luminal-HER2 subtype and lowest in basal-like subtype. Methylation frequencies and levels in 12 out of the 15 genes were significantly different among all subtypes and basal-like subtype showed significantly lower methylation frequencies and levels in nine genes, compared to luminal A, luminal B, HER2 enriched, and luminal-HER2 subtypes. CD44+/CD24- or ALDH1+ putative stem cell populations were most enriched in basal-like subtype. The methylation of promoter CpG islands was significantly lower in CD44+/CD24-cell (+) tumors, compared to CD44+/CD24-cell (−) tumors, even within the basal-like subtype. ALDH1 (+) tumors also had significantly lower methylation, compared to ALDH1 (−) tumors. Conclusions: Our findings showed that promoter CpG island methylation was significantly different according to breast cancer subtype and stem cell phenotype of tumor, suggesting that breast cancers have different methylation patterns according to molecular subtypes and it is associated with stem cell phenotypes of the tumor. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-05-04.

Purpose Basal-like breast cancer, as defined by gene expression profiling, is associated with aggressive phenotype and poor clinical outcome. Recent immunohistochemical validation suggested that basal-like subtype could be characterized by staining for cytokeratin (CK) 5/6 and epidermal growth factor receptor (EGFR) in triple negative breast cancers (TNBCs). Most of studies evaluated surrogate immunopannel of biomarkers to define basal-like breast cancer subtypes only in the TNBCs, although not all basal-like breast cancers are triple negative breast cancers (TNBCs). The significance of basal marker expression in other than triple negative breast cancer remains to be evaluated. To define prognostic impact of basal marker expression in HER2 positive breast cancer, we investigated cytokeratin (CK) 5/6 and epidermal growth factor receptor (EGFR) expression in patients with HER2 positive early breast cancer. Patients and Methods: Biomarker evaluation was performed using five immunohistochemical surrogate panel of estrogen receptor (ER), progesterone receptor (PR), HER2, CK 5/6 and EGFR in HER2 positive early breast cancers. Amplification of HER2 was confirmed by fluorescent in situ hybridization. HER2-positive breast cancer was classified by expression of basal markers (either EGFR or CK5/6) as “basal HER2- positive” (patients with HER2- positive disease who express basal markers) and “non-basal HER2” (patients with HER2-positive disease who did not express basal markers). We compared the prognostic significance of the basal marker expression between two groups. RESULTS: HER2 overexpression was found in 24.8% of early breast cancers with available tissue specimens from the primary tumor (236 of 952 cases). Basal marker co-expression was identified in 12.7% of HER2 positive early breast cancers. (30 of 236 patients) Basal HER2 positive breast cancer was significantly associated with age greater than 50 years (P=0.012), absence of ER (P < 0.001) and PR (P=0.004). The basal marker co-expression in patients with HER2 amplified early breast cancers demonstrated poorer overall survival (basal positive vs. basal negative, 85.6 months [95% confidence interval (CI), 70.8- 100.3 months] vs. 122.3 [C.I. 133.7-139.9], P=0.001) and disease free survival (DFS) (44.6 months [95% CI, 14.7-74.8] vs 110.7 months [95% CI, 96.4-123.9]; P=. 008) respectively. In lymph node positive group, basal marker expression retained its statistical significance at the multivariate level (P=0.047) HER2 positive breast cancer with lymph node involvement with basal marker expression showed substantially poorer overall survival with 2.1-fold (95% CI, 1.0-4.2) risk for death. CONCLUSION: Considerable number of HER2 positive breast cancer co-expressed basal markers. Our data demonstrated that simultaneous basal marker expression in HER2 positive early breast cancer is associated with poor clinical outcome. The molecular significance of basal marker expression in HER2 positive breast cancer needs to be further investigated. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P4-09-03.

Background: Accurate status determination of breast cancer (BC) biomarkers, including estrogen receptor (ER/ESR1), progesterone receptor (PR/PGR), human epidermal growth factor receptor 2 (HER2/ERBB2), and marker of proliferation Ki67 (MKI67), is crucial for guiding therapeutic decisions. However, current “gold standard” methods such as immunohistochemistry (IHC) for assessing these biomarkers in formalin-fixed paraffin-embedded (FFPE) tissues face challenges in standardization and exhibit substantial inter- and intra-laboratory variability, particularly for Ki67. To address these limitations, APIS Breast Cancer Subtyping Kit has been developed, utilizing reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) to evaluate the status of ER, PR, HER2, KI67, and a novel proliferative signature in breast cancer core needle biopsy (CNB) and resected specimens. The APIS Breast Cancer Subtyping Kit offers enhanced accuracy, improved reproducibility, and the ability to provide results in a timely manner. Herein we report the development and validation of the APIS Breast Cancer Subtyping Kit, assessing clinical performance using retrospective and prospective sample collection. Furthermore, reproducibility and reliability across three testing sites were evaluated. By comparing the results of the kit with those obtained through standard IHC, we demonstrate the reliability and utility of the APIS Breast Cancer Subtyping Kit for precise breast cancer subtyping and guiding personalized patient management decisions. Methods: FFPE tissue sections (n=652) taken by CNB or resection underwent histological analysis in accordance with laboratory’s standard of care methods. Samples with a HER2 score of 2+ were referred to fluorescence in situ hybridization (FISH) to determine ERBB2 amplification, with the FISH result replacing the IHC result in determining the HER2 status (positive/negative) of the sample. Tumors with greater than 1% positive stained nuclei for ER/PR were scored positive. A cut-off of 20% Ki67 staining was used for positive/negative status. The performance was assessed as the agreement with IHC/ISH status and reported as OPA (overall percent agreement) with corresponding 95% confidence intervals (95% CI). To assess the precision of the assay, a panel of RNA pools (samples) was repeatedly measured on different days across three independent laboratories. Reproducibility was evaluated using variance components analysis. Results: The APIS Breast Cancer Subtyping Kit showed high concordance (OPA) with IHC: 93.1% (95% CI: 90.9-94.8) for ER, 86.8% (95% CI: 84.0-89.2) for PR, 94.2% (95% CI: 92.2-95.8) for HER2 (IHC/FISH), 78.3% (95% CI: 75.0-81.3) for Ki67, and 80.1% (95% CI: 76.8-83.1) for proliferative signature (assessed against MKI67 IHC status). Inter-site reproducibility demonstrated excellent agreement in quantitative measurements, with a total SD ranging from 0.00 to 0.22. Binary single-marker status (positive/negative) calling achieved 100% reproducibility for ER, PR, and HER2 for all tested samples (negative/low positive/medium positive), as well as for most Ki67 samples (87% agreement for negative samples). Conclusions: APIS Breast Cancer Subtyping Kit demonstrated a high level of concordance with standard of care IHC/FISH in assessing breast cancer biomarker status. These findings suggest that the APIS Breast Cancer Subtyping Kit provides highly precise and reproducible quantitative assessment of BC biomarkers and molecular subtypes. Inclusion and exclusion criteria Citation Format: Anna Gasior, Joanna Gorniak, Sara Rollinson, Leanne Gough, Anne-Sophie Wegscheider, Axel Niendorf. Comprehensive Molecular Profiling of Breast Cancer: A real-time PCR assay for identifying ESR1, PGR, ERBB2, MKI67 and a novel proliferative signature in core needle biopsies and resected invasive breast cancer tissues [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-02-08.

ObjectiveTranscriptional profiling of epithelial ovarian cancer has revealed molecular subtypes correlating to biological and clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and investigate similarities with the well-established intrinsic molecular subtypes of breast cancer.MethodsGlobal gene expression profiling using Illumina's HT12 Bead Arrays was applied to 59 fresh-frozen serous ovarian malignant, benign and borderline tumors. Nearest centroid classification was performed applying previously published gene profiles for the ovarian and breast cancer subtypes. Correlations to gene expression modules representing key biological breast cancer features were also sought. Validation was performed using an independent, publicly available dataset.Results5,944 genes were significantly differentially expressed between benign and malignant serous ovarian tumors, with cell cycle processes enriched in the malignant subgroup. Borderline tumors were split between the two clusters. Significant correlations between the malignant serous tumors and the highly aggressive ovarian cancer signatures, and the basal-like breast cancer subtype were found. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer signature derived from borderline tumors. The borderline tumors in the study dataset, in addition, also correlated significantly to the luminal A breast cancer subtype. These findings remained when analyzed in an independent dataset, supporting links between the molecular subtypes of ovarian cancer and breast cancer beyond those recently acknowledged.ConclusionsThese data link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, and suggest that biomarkers and targeted therapies may overlap between these tumor subsets. The link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers.

Vascular endothelial growth factor-A (VEGFA) is a key inducer of angiogenesis, responsible for generating new blood vessels in the tumor microenvironment (TME) and facilitating metastasis. Notably, Avastin, which targets VEGFA, failed to demonstrate any significant benefit in clinical trials for breast cancer (BC). This study aimed to investigate the clinical relevance of VEGFA gene expression in BC. A total of 7,336 BC patients across eight independent cohorts: ISPY2 (GSE173839), Sweden Cancerome Analysis Network-Breast (SCAN-B) (GSE96058), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), GSE25066, GSE163882, GSE34138, GSE20194, and The Cancer Genome Atlas (TCGA), were analyzed. The calculated median VEGFA expression level was used to stratify these cohorts into high and low groups. High VEGFA was associated with worse disease-free, disease-specific, and overall survival in the METABRIC cohort, with findings supported by the SCAN-B cohort, which also showed worse overall survival (all P < 0.02). High VEGFA expression was seen in triple-negative breast cancer (TNBC) but not in BC with lymph node metastasis. Additionally, there was a significant correlation between high VEGFA expression and higher silent and non-silent mutations, single-nucleotide variant (SNV) neoantigens, homologous recombination defect, intratumoral heterogeneity, in the TCGA cohort. In the TCGA, METABRIC, and SCAN-B cohorts, high VEGFA BC was also associated with higher cell proliferation: higher Ki67 gene expression, higher Nottingham histological grade, and consistent enrichment of all the Hallmark cell proliferation-related gene sets. Unexpectedly, the angiogenesis gene set was not enriched in any of the cohorts and showed no association with infiltrations of lymphatic or blood vascular endothelial cells besides pericytes. High VEGFA BC had significantly less infiltration of anti-cancer immune cells but higher infiltration of pro-cancer immune cells in TCGA, METABRIC, and SCAN-B cohorts. Interestingly, BC, which had a pathological complete response (pCR) after anthracycline- and taxane-based neoadjuvant therapy, was associated with significantly heightened VEGFA expression in both estrogen receptor (ER)+/human epidermal growth factor receptor 2 (HER2)- and TNBC subtypes in the GSE25066 cohort and after immunotherapy in ER+/ HER2- subtype, but not TNBC in the ISPY2 cohort. Our research indicates that high VEGFA BC confers high cell proliferation, reduced immune cell infiltration, and poorer survival, but allows better response to anthracycline- and taxane-based chemotherapy, and immunotherapy.

Triple-negative breast cancer (TNBC) is a heterogenous disease. For personalized medicine, it is essential to identify and classify tumor subtypes to develop effective therapeutic strategies. Although gene expression profiling has identified several TNBC subtypes, classification of these tumors remains complex. Most TNBCs exhibit an aggressive phenotype, but some rare types have a favorable clinical course. In this review, we summarize the classification and characteristics related to the various TNBC subtypes, including the rare types. Therapeutic methods that are suitable for each subtype are also discussed. Of the intrinsic breast cancer subtypes identified by gene expression analysis, the basal-like subtype specifically displayed decreased expression of an estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) cluster. We also present results that characterize the TNBC and basal-like phenotypes. TNBC may be categorized into four major classes : basal-like, immune-enriched, mesenchymal, and luminal androgen receptor. Therapeutic strategies for each subtype have been proposed along with newly approved targeted therapies for TNBC, such as immune checkpoint inhibitors. Understanding the classification of TNBC based on gene expression profiling in association with clinicopathological factors will facilitate accurate pathological diagnosis and effective treatment selection. J. Med. Invest. 68 : 213-219, August, 2021.

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.

Unraveling Genes, Hormones, and Breast Cancer

Residual cancer burden (RCB) based on pathologic characteristics is the most powerful prognostic factor in breast cancer (BC) which received neoadjuvant chemotherapy (NAC) followed by surgery. According to RCB classification, class III predicted short survival duration regardless of BC subtypes according to hormone receptor (HR) and human epidermal growth factor receptor-2 (HER-2) state. However, up to 20-40% of BCs with RCB class III did not experience BC recurrence and had long term survival without disease recurrence. In our study, we evaluated genomic characteristics of BC which had high RCB class. We collected 96 fresh frozen BC specimens which had undergone surgery after NAC between 2010 and 2018 from Samsung Medical Center Biobank. We performed whole genome or exome sequencing, RNA sequencing and high-plex single-cell spatial transcriptomics. Of 96 BCs, 65 BCs had experienced BC recurrence and 31 BCs have not been BC recurrence. Of 65 BCs with dismal prognosis, 12 were HR+HER2-, four in HR+HER2+, 39 in triple negative breast cancer (TNBC) and 10 in HR-HER2+ BC. Of 31 BCs without recurrence, 11 were HR+HER2-, two in HR+HER2+, 14 in TNBC and four in HR-HER2+ BC. In HR+HER2- BC, ten of 12 BCs with dismal prognosis were categorized into basal like intrinsic subtype and two were into luminal B subtype compared that six of luminal A and five of luminal B subtype categorization in good prognosis BC group. Age associated mutation signature were enriched in HR+HER2- BC with good prognosis (p=0.027). Tumor microenvironment (TME) analysis using Kassandra suggested that high monocytes were associated with BC with dismal prognosis (p=0.00031). In single-cell spatial transcriptome analysis, T-cell abundance in the tumoral niche is associated with dismal prognosis in HR+HER2- BC (p=0.039). In TNBC, almost BCs (88.7%) were categorized into basal-like intrinsic subtype regardless of their prognosis. TME analysis presented that immune cells including macrophages and lymphocytes with CD4 and CD8 T cells were significantly enriched in TNBC with good prognosis (ps &amp;lt;0.05, respectively). In HER2+ BC, intrinsic subtypes were heterogeneous in both groups. Focal amplification in HER2+BC patient harbored DNA segments from different chromosomes more frequently than in those with good prognosis (p=0.00091), which was prominent in oncogenic extrachromosomal DNA amplifications compared to other oncogenic amplifications. In TME analysis, there were no specific cell enrichments according to BC prognosis but sing-cell spatial transcriptome analysis revealed that higher T-cell abundance in the tumoral niche was associated with HR+HER2+ BC with good prognosis (p=0.047). In conclusion, each BC subtype had their own genomic characteristics to determine their prognosis. Our study also suggested that TME characteristics was common prognostic factor for survival outcome of BC with residual tumor after NAC. Citation Format: Ji-Yeon Kim, Sabin Park, Sepil Ahn, Eun Seop Seo, Soyeon Kim, Mark Gregory, Emily Killingbeck, Eun Yoon Cho, Jeong Eon Lee, Jin Seok Ahn, Yeon Hee Park, Woong-Yang Park, Hoon Kim, Semin Lee, Young-Hyuck Im. Prognostication of genomic characteristics of residual breast cancer after neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7644.

Background: Mammographic density (MD), a measure of the amount of radiologically dense breast tissue, is one of the strongest breast cancer risk factors. Studies have found that high MD increases risk for both estrogen receptor (ER)-negative and positive breast cancers, but data relating MD to breast cancer subtypes are limited. Methods: We used data from the population-based Polish Breast Cancer Study to explore relationships between MD and breast cancer characteristics. This analysis includes 227 invasive breast cancers, which were available as frozen samples and used for mRNA and cytogenetic profiling, and fixed tissues, which were prepared as tissue microarrays for immunohistochemical analysis. Pre-treatment mammograms of the unaffected breast were retrieved for 184 (81%) cases ages 28-75 years. Craniocaudal views of digitized films were used to assess percent MD with Cumulus, a computer-assisted thresholding method. Analysis of variance (ANOVA) models were used to test the null hypothesis of no mean difference in MD between the breast cancer subtypes. Results: Tumor subtypes were classified by key immunohistochemical markers as luminal A (ER+ and/or progesterone receptor (PR)+, human epidermal growth factor receptor-2 (HER2)-; n=129), luminal B (ER+ and/or PR+, HER2+; n=6), HER2-expressing (ER-, PR-, HER2+; n=13), basal-like (ER-, PR-, HER2-, cytokeratin 5+, and/or HER1+; n=23), and unclassified (negative for all five markers; n=8). Five cases did not have interpretable staining for all five markers and were excluded. MD values were approximately normally distributed. Preliminary ANOVA models revealed no differences in mean percent MD by tumor subtypes (p=0.29) as follows: luminal A, 27.5% (95% confidence interval (CI): 24.9-30.2); luminal B, 27.0% (95% CI: 14.8-39.2); HER2-expressing, 27.2% (95% CI: 18.9-35.5); basal-like, 24.6% (95% CI: 18.4-30.8); and unclassified, 15.7% (95% CI: 5.2-26.3). In analysis of covariance models adjusted for age there was marginal evidence of elevated MD with the HER2-expressing subtype (p=0.04), but we cannot exclude the possibility that this is a chance finding. Conclusions: Our results do not provide strong support for an association between percent MD and breast cancer subtypes. To identify additional clues as to the biology underlying the MD-breast cancer relationship, ongoing analyses will relate MD to mRNA and cytogenetic profiles and data for protein expression via immunohistochemistry available for additional markers as previously reported. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2779.

Identification of molecular signatures that allow detection of the transition from normal breast epithelial cells to malignant invasive cells is a critical component in the development of diagnostic, therapeutic, and preventative strategies for human breast cancer. Substantial efforts have been devoted to deciphering breast cancer etiology at the genome level, but only a limited number of studies have appeared at the proteome level. In this work, we compared individual in situ proteome profiles of nonpatient matched nine noncancerous, normal breast epithelial (NBE) samples with nine estrogen receptor (ER)-positive (luminal subtype), invasive malignant breast epithelial (MBE) samples by combining laser capture microdissection (LCM) and quantitative shotgun proteomics. A total of 12,970 unique peptides were identified from the 18 samples, and 1623 proteins were selected for quantitative analysis using spectral index (SpI) as a measure of protein abundance. A total of 298 proteins were differentially expressed between NBE and MBE at 95% confidence level, and this differential expression correlated well with immunohistochemistry (IHC) results reported in the Human Protein Atlas (HPA) database. To assess pathway level patterns in the observed expression changes, we developed protein set enrichment analysis (PSEA), a modification of a well-known approach in gene expression analysis, Gene Set Enrichment Analysis (GSEA). Unlike single gene-based functional term enrichment analyses that only examines pathway overrepresentation of proteins above a given significance threshold, PSEA applies a weighted running sum statistic to the entire expression data to discover significantly enriched protein groups. Application of PSEA to the expression data in this study revealed not only well-known ER-dependent and cellular morphology-dependent protein abundance changes, but also significant alterations of downstream targets for multiple transcription factors (TFs), suggesting a role for specific gene regulatory pathways in breast tumorigenesis. A parallel GOMiner analysis revealed both confirmatory and complementary data to PSEA. The combination of the two annotation approaches yielded extensive biological feature mapping for in depth analysis of the quantitative proteomic data.

BackgroundBreast cancer heterogeneity is an essential element that plays a role in the therapy response variability and the patient’s outcome. This highlights the need for more precise subtyping methods that focus not only on tumor cells but also investigate the profile of stromal cells as well as immune cells.ObjectivesTo mine publicly available transcriptomic breast cancer datasets and reanalyze their transcriptomic profiling using unsupervised clustering in order to identify novel subsets in molecular subtypes of breast cancer, then explore the stromal and immune cells profile in each subset using bioinformatics and systems immunology approaches.Materials and MethodsTranscriptomic data from 1,084 breast cancer patients obtained from The Cancer Genome Atlas (TCGA) database were extracted and subjected to unsupervised clustering using a recently described, multi-step algorithm called Iterative Clustering and Guide-gene Selection (ICGS). For each cluster, the stromal and immune profile was investigated using ESTIMATE and CIBERSORT analytical tool. Clinical outcomes and differentially expressed genes of the characterized clusters were identified and validated in silico and in vitro in a cohort of 80 breast cancer samples by immunohistochemistry.ResultsSeven unique sub-clusters showed distinct molecular and clinical profiles between the well-known breast cancer subtypes. Those unsupervised clusters identified more homogenous subgroups in each of the classical subtypes with a different prognostic profile. Immune profiling of the identified clusters showed that while the classically activated macrophages (M1) are correlated with the more aggressive basal-like breast cancer subtype, the alternatively activated macrophages (M2) showed a higher level of infiltration in luminal A and luminal B subtypes. Indeed, patients with higher levels of M1 expression showed less advanced disease and better patient outcomes presented as prolonged overall survival. Moreover, the M1 high basal-like breast cancer group showed a higher expression of interferon-gamma induced chemokines and guanylate-binding proteins (GBPs) involved in immunity against microbes.ConclusionAdding immune profiling using transcriptomic data can add precision for diagnosis and prognosis and can cluster patients according to the available modalities of therapy in a more personalized approach.

Background: The principal objective of this study was to assess clinical outcomes by breast cancer subtype in patients with brain metastases. Methods: Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status was evaluated via immunohistochemical staining. Four survival time intervals were compared according to the subtype (ER+/HER2–, HER2+, triple negative (TN)). Results: 20 (30.3%) of the 66 patients in this study were ER+/HER2–, 20 (30.3%) were HER2+, and 26 (39.4%) were TN. The disease-free survival rates of ER+/HER2–, HER2+, and TN patients were 30.0, 17.0, and 17.9 months, respectively (p = 0.040). The median time intervals from distant metastasis to brain metastasis were 20.6, 19.5, and 9.0 months, respectively (p = 0.012). The times from initial diagnosis to brain metastasis were 52.9, 33.6, and 25.5 months, respectively (p = 0.026). However, the overall survival rates did not differ significantly (p = 0.276). Conclusions: Patients with TN breast cancer were more likely to develop distant metastasis earlier, and also evidenced poor overall survival. Triple receptor status may be employed as a prognostic marker for breast cancer patients with brain metastases.

Background: Breast cancer (BC) is a heterogeneous disease and can be classified according to the expression of four genes: estrogen receptor (ER), progesterone receptor (PGR), human epidermal growth factor receptor 2 (HER2) and marker of proliferation KI67. Four groups of BC have been described: Luminal A (ER+ or PGR+, KI67- HER2-), Luminal B (ER+ or PGR+, KI67+ or HER2+), HER2 (ER- HER2+) and triple negative (ER- PGR- HER2-). Autophagy is a lysosomal degradation pathway which plays a crucial dual role in tumorigenesis, producing pro-survival or pro-death activity. Altered autophagy has been observed in BC but no study has described transcript level variations of "autophagy genes" according to sub-groups. In order to further explore those alterations, we analyzed gene expression of 40 "autophagy genes" in normal and tumor cells using public transcriptomic data. Samples and Methods: 5497 transcriptomes were obtained from raw data downloaded from public databases. Two distinct Affymetrix series were built after GC-RMA normalization: one from HG-U133A arrays (n=2806) and one from HG-U133 plus2 arrays (n=2691). Each series was standardized with the Aroma R package that was designed to normalize multicenter extremely large Affymetrix data sets. The same computations were performed in the two data set in order to cross-validate the results. Samples were classified with a reduced number of genes (such as for St Gallen classification) and with classifiers using 50 or more than 300 genes (PAM50, CIT and IntClust centroids). Results: In each of the two series, there were about 500 Basal, 300 HER2, 1800 Luminal tumors and 100 normal epithelial breast cells. Positivity or negativity of four genes (ER, PGR, KI67, HER2) produced robust classifications concordant with PAM50 classification based upon centroids. Within the 40 "autophagy genes" studied, at least 10 genes were significantly correlated with one or two sub-groups: ATG3 and ATG9A were associated with ER- tumors including basal group; ATG2B , BECN1 and ULK2 were positively correlated with ER expression and luminal subtypes; ULK1 and RAB24 were associated with ER+HER2+ tumors and MAP1LC3B and ATG5 with ER-HER2+ subgroup; GABARAPL1 was more expressed in normal breast tissue than in cancer cells. Discussion: Exploring autophagy in large-scale transcriptome data, we confirmed a previous result showing that GABARAPL1 expression is reduced in breast cancer cells compared with the normal epithelial cells. Interestingly, transcript levels of "autophagy genes"were not evenly distributed among the different tumor subtypes. For instance, some genes were preferentially expressed in ER+ subtypes and others in ER- tumors, suggesting that autophagy might play different roles in the different subgroups, providing different potential targets for therapy. Citation Format: Feugeas J-P, Belmiloudi S, Boyer-Guittaut M, Peixoto P, Hervouet E. Relationships between breast cancer subtypes and expression of autophagy related genes [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-06-09.