Dataset Information

Screening of immunosuppressive factors for biomarkers of breast cancer malignancy phenotypes and subtype-specific targeted therapy.

ABSTRACT: We aimed to screen and validate immunosuppressive factors in luminal- and basal-like breast cancer cell lines and tissue samples associated with malignant phenotypes. The mRNA microarray datasets, GSE40057 and GSE1561, were downloaded and remodeled, and differentially expressed genes were identified. Weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) and KEGG pathway enrichment analysis were performed to explore the immune-related events related to the basal-like breast cancer. The online resources, GOBO, Kaplan-Meier Plotter and UALCAN, were employed to screen for immunosuppressive factors associated with breast cancer malignant phenotypes. Immunohistochemistry was used to evaluate VEGFA and MIF levels in breast tumors and normal breast tissues; qPCRs and western blots were used to validate the expression of clinical immuno-oncology (IO) therapeutic targets CD274 (PD-L1) and IL8 in cell lines. The results showed that various immune-related events contribute to basal-like breast cancer. First, TGF?1 and IL8 had higher average expression levels in more malignant cell lines; second, MIF and VEGFA had higher average expression levels in more malignant breast cancer tissues, and the high expression levels were associated with poor survival rate. Third, IO targets CD274 and IL8 which were confirmed to be more suitable for the treatment of basal-like breast cancer. In view of the above, during the formation and development of breast cancer, immune-related genes are always activated, and immunosuppressive factors, IL8, TGF?1, MIF, and VEGFA are up-regulated. Such molecules could be used as biomarkers for breast cancer prognosis. However, because individual immune-related factors can play several biological roles, the mechanistic relationship between immunosuppressive factors and breast cancer malignant phenotypes and the feasibility of their application as drug targets require further investigation.

SUBMITTER: Wang P

PROVIDER: S-EPMC6599676 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Screening of immunosuppressive factors for biomarkers of breast cancer malignancy phenotypes and subtype-specific targeted therapy.

Wang Ping P Liu Jiaxuan J Song Yunlei Y Liu Qiang Q Wang Chao C Qian Caiyun C Zhang Shuhua S Zhu Weifeng W Yang Xiaohong X Wan Fusheng F Liu Zhuoqi Z Luo Daya D

PeerJ 20190627

We aimed to screen and validate immunosuppressive factors in luminal- and basal-like breast cancer cell lines and tissue samples associated with malignant phenotypes. The mRNA microarray datasets, GSE40057 and GSE1561, were downloaded and remodeled, and differentially expressed genes were identified. Weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) and KEGG pathway enrichment analysis were performed to explore the immune-related events related to the basal-like breast ...[more]

PMID: 31293831

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Project description:Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

Project description:BackgroundFew somatic mutations have been linked to breast cancer metastasis, whereas transcriptomic differences among primary tumors correlate with incidence of metastasis, especially to the lungs and brain. However, the epigenomic alterations and transcription factors (TFs) which underlie these alterations remain unclear.MethodsTo identify these, we performed RNA-seq, Chromatin Immunoprecipitation and sequencing (ChIP-seq) and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) of the MDA-MB-231 cell line and its brain (BrM2) and lung (LM2) metastatic sub-populations. We incorporated ATAC-seq data from TCGA to assess metastatic open chromatin signatures, and gene expression data from human metastatic datasets to nominate transcription factor biomarkers.ResultsOur integrated epigenomic analyses found that lung and brain metastatic cells exhibit both shared and distinctive signatures of active chromatin. Notably, metastatic sub-populations exhibit increased activation of both promoters and enhancers. We also integrated these data with chromosome conformation capture coupled with ChIP-seq (HiChIP) derived enhancer-promoter interactions to predict enhancer-controlled pathway alterations. We found that enhancer changes are associated with endothelial cell migration in LM2, and negative regulation of epithelial cell proliferation in BrM2. Promoter changes are associated with vasculature development in LM2 and homophilic cell adhesion in BrM2. Using ATAC-seq, we identified a metastasis open-chromatin signature that is elevated in basal-like and HER2-enriched breast cancer subtypes and associates with worse prognosis in human samples. We further uncovered TFs associated with the open chromatin landscapes of metastatic cells and whose expression correlates with risk for metastasis. While some of these TFs are associated with primary breast tumor subtypes, others more specifically correlate with lung or brain metastasis.ConclusionsWe identify distinctive epigenomic properties of breast cancer cells that metastasize to the lung and brain. We also demonstrate that signatures of active chromatin sites are partially linked to human breast cancer subtypes with poor prognosis, and that specific TFs can independently distinguish lung and brain relapse.

Dataset Information

Screening of immunosuppressive factors for biomarkers of breast cancer malignancy phenotypes and subtype-specific targeted therapy.

Publications

Screening of immunosuppressive factors for biomarkers of breast cancer malignancy phenotypes and subtype-specific targeted therapy.

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