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Immune gene expression profiling reveals heterogeneity in luminal breast tumors.

ABSTRACT: BACKGROUND:Heterogeneity of immune gene expression patterns of luminal breast cancer (BC), which is clinically heterogeneous and overall considered as low immunogenic, has not been well studied especially in non-European populations. Here, we aimed at characterizing the immune gene expression profile of luminal BC in an Asian population and associating it with patient characteristics and tumor genomic features. METHODS:We performed immune gene expression profiling of tumor and adjacent normal tissue in 92 luminal BC patients from Hong Kong using RNA-sequencing data and used unsupervised consensus clustering to stratify tumors. We then used luminal patients from The Cancer Genome Atlas (TCGA, N?=?564) and a Korean breast cancer study (KBC, N?=?112) as replication datasets. RESULTS:Based on the expression of 130 immune-related genes, luminal tumors were stratified into three distinct immune subtypes. Tumors in one subtype showed higher level of tumor-infiltrating lymphocytes (TILs), characterized by T cell gene activation, higher expression of immune checkpoint genes, higher nonsynonymous mutation burden, and higher APOBEC-signature mutations, compared with other luminal tumors. The high-TIL subtype was also associated with lower ESR1/ESR2 expression ratio and increasing body mass index. The comparison of the immune profile in tumor and matched normal tissue suggested a tumor-derived activation of specific immune responses, which was only seen in high-TIL patients. Tumors in a second subtype were characterized by increased expression of interferon-stimulated genes and enrichment for TP53 somatic mutations. The presence of three immune subtypes within luminal BC was replicated in TCGA and KBC, although the pattern was more similar in Asian populations. The germline APOBEC3B deletion polymorphism, which is prevalent in East Asian populations and was previously linked to immune activation, was not associated with immune subtypes in our study. This result does not support the hypothesis that the germline APOBEC3B deletion polymorphism is the driving force for immune activation in breast tumors in Asian populations. CONCLUSION:Our findings suggest that immune gene expression and associated genomic features could be useful to further stratify luminal BC beyond the current luminal A/B classification and a subset of luminal BC patients may benefit from checkpoint immunotherapy, at least in Asian populations.

SUBMITTER: Zhu B

PROVIDER: S-EPMC6924001 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Immune gene expression profiling reveals heterogeneity in luminal breast tumors.

Zhu Bin B Tse Lap Ah LA Wang Difei D Koka Hela H Zhang Tongwu T Abubakar Mustapha M Lee Priscilla P Wang Feng F Wu Cherry C Tsang Koon Ho KH Chan Wing-Cheong WC Law Sze Hong SH Li Mengjie M Li Wentao W Wu Suyang S Liu Zhiguang Z Huang Bixia B Zhang Han H Tang Eric E Kan Zhengyan Z Lee Soohyeon S Park Yeon Hee YH Nam Seok Jin SJ Wang Mingyi M Sun Xuezheng X Jones Kristine K Zhu Bin B Hutchinson Amy A Hicks Belynda B Prokunina-Olsson Ludmila L Shi Jianxin J Garcia-Closas Montserrat M Chanock Stephen S Yang Xiaohong R XR

Breast cancer research : BCR 20191219 1

<h4>Background</h4>Heterogeneity of immune gene expression patterns of luminal breast cancer (BC), which is clinically heterogeneous and overall considered as low immunogenic, has not been well studied especially in non-European populations. Here, we aimed at characterizing the immune gene expression profile of luminal BC in an Asian population and associating it with patient characteristics and tumor genomic features.<h4>Methods</h4>We performed immune gene expression profiling of tumor and adj ...[more]

PMID: 31856876

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Project description:Background: Breast cancer is a complex disease, encompassed by different clinically and molecularly stratified entities. In 2000, Perou and colleagues demonstrated that tumor phenotypic diversity correlates with differences in global gene expression patterns, which in turn reflect aspects of the biological behavior of the tumors. Gene expression profiling has distinguished sporadic breast tumor sub-classes with genetic, histopathological and clinical differences, however, little is known about the molecular classification of hereditary breast tumors. It has been recently suggested that most tumors arising in BRCA1 mutation carriers display a basal-like phenotype, with the percentages reported in different studies ranging from 44 to almost 100%. In the present study we used expression profiling to produce a molecular classification of BRCA1-associated breast tumors and applied an integrative approach to examine biological dependencies or differences. Methods and Findings: We used frozen tumor tissue from fourteen patients all of which harbored germline pathological mutations in BRCA1. Total RNA extraction, amplification and labeling with Cy5 were performed using standard protocols. Universal Human Reference RNA (Stratagene) was used as a reference and labeled with Cy3. Each pair of Cy3/Cy5 samples was hybridized onto the CNIO human OncoChip V2, which consists of a spotted microarray with 11,675 cDNA clones from the I.M.A.G.E. Consortium. Two channel ratios (Cy5/Cy3) for each spot were generated and quantified using GenePix Pro 5.1 (Axon Instruments, Inc., Union City, CA, USA). Data were normalized and filtered and multiple statistical analyses were performed. The data are deposited in the GEO database under the accession number GSE12350. A tissue microarray (TMA) containing an independent series of 15 BRCA1 tumors was used to validate some of the results obtained. We have described molecular signatures that define BRCA1 subclasses depending on the expression of the gene encoding for Estrogen Receptor, ESR1. Signatures were found to be molecularly associated with different biological processes and transcriptional regulatory programs. The signature of ESR1-positive tumors was mainly linked to cell proliferation-related processes and, therefore, regulated by the estrogen receptor, while the signature of ESR1-negative tumors was mainly linked to the immune response and possibly regulated by transcription factors of the REL/NFκB family. These signatures were then verified in an independent series of hereditary and sporadic breast tumors, which revealed a possible prognostic value for each subclass. Over-expression of immune response genes appears to be a common feature of ER-negative sporadic and hereditary breast cancer and is associated with good prognosis. Interestingly, the ESR1-negative tumors were sub-stratified into two groups presenting light differences in the magnitude of the expression of immune response transcripts and REL/NFκB transcription factors, and this could be dependent on the type of germline alteration. In addition, analysis of the human protein-protein interaction network provides the wiring diagram of critical molecular associations in BRCA1 tumorigenesis and identifies close relationships between the different signatures. Conclusions: In summary, in the present study we have established the gene expression profiling of a series of BRCA1 tumors and found that there is a further degree of heterogeneity beyond the main classification by the expression of ESR1 and the presence or absence of a basal-like phenotype. We have identified specific signatures for ESR1-positive and ESR1-negative BRCA1 tumors, the latter characterized by the enrichment of immune response and cell cycle genes, and have found that slight differences in the level of expression of the immune response stratify the ESR1-negative BRCA1 tumors into two additional sub-groups (A and B) with possible prognostic differences. NFkB could be a major driver responsible for the levels of both immune response and apoptotic genes in this group of tumors, which could in turn be related to the type of germline mutation in BRCA1. This study reveals the molecular complexity of BRCA1 breast tumors, which are found to display similarities to sporadic tumors, and suggests possible prognostic implications. 14 samples (primary breast tumors containing a BRCA1 mutation) were hybridized to a cDNA microarray in order to investigate the possible heterogeneity within the BRCA1 group.

Project description:Gene co-expression networks have become a usual approach to integrate the vast amounts of information coming from gene expression studies in cancer cohorts. The reprogramming of the gene regulatory control and the molecular pathways depending on such control are central to the characterization of the disease, aiming to unveil the consequences for cancer prognosis and therapeutics. There is, however, a multitude of factors which have been associated with anomalous control of gene expression in cancer. In the particular case of co-expression patterns, we have previously documented a phenomenon of loss of long distance co-expression in several cancer types, including breast cancer. Of the many potential factors that may contribute to this phenomenology, copy number variants (CNVs) have been often discussed. However, no systematic assessment of the role that CNVs may play in shaping gene co-expression patterns in breast cancer has been performed to date. For this reason we have decided to develop such analysis. In this study, we focus on using probabilistic modeling techniques to evaluate to what extent CNVs affect the phenomenon of long/short range co-expression in Luminal B breast tumors. We analyzed the co-expression patterns in chromosome 8, since it is known to be affected by amplifications/deletions during cancer development. We found that the CNVs pattern in chromosome 8 of Luminal B network does not alter the co-expression patterns significantly, which means that the co-expression program in this cancer phenotype is not determined by CNV structure. Additionally, we found that region 8q24.3 is highly dense in interactions, as well as region p21.3. The most connected genes in this network belong to those cytobands and are associated with several manifestations of cancer in different tissues. Interestingly, among the most connected genes, we found MAF1 and POLR3D, which may constitute an axis of regulation of gene transcription, in particular for non-coding RNA species. We believe that by advancing on our knowledge of the molecular mechanisms behind gene regulation in cancer, we will be better equipped, not only to understand tumor biology, but also to broaden the scope of diagnostic, prognostic and therapeutic interventions to ultimately benefit oncologic patients.

Project description:BackgroundChemotherapeutic drug concentrations vary across different regions of tumors and this is thought to be involved in development of chemotherapy resistance. Insufficient drug delivery to some regions of the tumor may be due to spatial differences in expression of genes involved in the disposition, transport, and detoxification of drugs (pharmacogenes). Therefore, in this study, we analyzed the spatial expression of 286 pharmacogenes in six breast cancer tissues using the recently developed Visium spatial transcriptomics platform to (1) determine if these pharmacogenes are expressed heterogeneously across tumor tissue and (2) to determine which pharmacogenes have the most spatial expression heterogeneity.Methods and resultsThe spatial transcriptomics technology sequences the transcriptome of 55 um diameter barcoded sections (spots) across a tissue sample. We analyzed spatial gene expression profiles of four biobank-sourced breast tumor samples in addition to two breast tumor sample datasets from 10× Genomics. We define heterogeneity as the interquartile range of read counts. Collectively, we identified 8887 spots in tumor regions, 3814 in stroma, 44 in lymphocytes, and 116 in normal regions based on pathologist annotation of the tissues. We showed statistically significant differences in expression of pharmacogenes in tumor regions compared to surrounding non-tumor regions. We also observed that the most heterogeneously expressed genes within tumor regions were involved in reactive oxygen species (ROS) handling and detoxification mechanisms. GPX4, GSTP1, MGST3, SOD1, CYP4Z1, CYB5R3, GSTK1, and NAT1 showed the most heterogeneous expression within tumor regions.ConclusionsThe heterogeneous expression of these pharmacogenes may have important implications for cancer therapy due to their ability to impact drug distribution and efficacy throughout the tumor. Our results suggest that chemoresistance caused by expression of GPX4, GSTP1, MGST3, and SOD1 may be intrinsic, not acquired, since the heterogeneity is not specific to chemotherapy-treated samples or cell type. Additionally, we identified candidate chemoresistance pharmacogenes that can be further tested through focused follow-up studies.

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Immune gene expression profiling reveals heterogeneity in luminal breast tumors.

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Immune gene expression profiling reveals heterogeneity in luminal breast tumors.

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