Dataset Information

Identification of CTLA-4 associated with tumor microenvironment and competing interactions in triple negative breast cancer by co-expression network analysis.

ABSTRACT: Background: The study of CTLA-4 inhibitors has been one of the hot spots in the field of tumor immunotherapy. As the most immunogenic subtype of breast cancer, Triple negative breast cancer (TNBC) has a great potential in the treatment strategy. The aim of this study was to explore the relevant genes and pathways of CTLA-4 in TNBC and to explore the prognostic value, so as to provide a theoretical basis for clinical studies. Materials and methods: We used the data from The Cancer Genome Atlas (TCGA) to analyze the expression of CTLA-4 in different types of breast cancer, and analyzed the TNBC data of CTLA-4 related co-expression genes by WGCNA and enrichment analysis. LncRNA-miRNA-CTLA-4 network was constructed to explore the immune infiltration and immune checkpoint associated with CTLA-4. The effect of CTLA-4 on clinical outcomes in TNBC patients was also evaluated. Finally, we used data from GEO database to verify the differences of CTLA-4 in different molecular types of breast cancer and related prognostic results. Results: CTLA-4 was significantly higher in TNBC than in Luminal subtype and Her-2 + subtype (P=0.019 and P<0.001, separately), and was significantly higher in ER and PR negative samples than in ER and PR positive samples (P<0.001). CTLA-4 related genes mainly enriched in biological process of leukocyte differentiation, regulation of leukocyte activation and T cell activation. Hsa-mir-92a was found to be a survival significance marker associated with CTLA-4 and lncRNA-miRNA-CTLA-4 network was constructed. The results of immune infiltration analysis showed that CTLA-4 was mainly related with T cell (r=0.74). For immune checkpoints analysis, CTLA-4 was mainly related to PDCD1(r=0.72) and CD28(r=0.64). In TNBC, high expression of CTLA-4 is related to good survival (P=0.0061). Results consistent with previous analysis were obtained in the GEO database, the expression of CTLA-4 in TNBC was significantly higher than that in non-TNBC (p<0.001), CTLA-4 was associated with favorable survival of TNBC (p<0.001). Conclusion: Among all types of breast cancer, the expression of CTLA-4 was the highest in TNBC.CTLA-4 in TNBC can be regulated by hsa-mir-92a to form ceRNA networks and influence the prognosis of TNBC patients through the leukocyte differentiation, regulation of leukocyte activation and T cell activation pathway.

SUBMITTER: Peng Z

PROVIDER: S-EPMC7532512 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of CTLA-4 associated with tumor microenvironment and competing interactions in triple negative breast cancer by co-expression network analysis.

Peng Ziqi Z Su Peng P Yang Yuhong Y Yao Xue X Zhang Yiqi Y Jin Feng F Yang Bowen B

Journal of Cancer 20200909 21

<b>Background:</b> The study of CTLA-4 inhibitors has been one of the hot spots in the field of tumor immunotherapy. As the most immunogenic subtype of breast cancer, Triple negative breast cancer (TNBC) has a great potential in the treatment strategy. The aim of this study was to explore the relevant genes and pathways of CTLA-4 in TNBC and to explore the prognostic value, so as to provide a theoretical basis for clinical studies. <b>Materials and methods:</b> We used the data from The Cancer G ...[more]

PMID: 33033520

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Project description:Heterogeneity of triple-negative breast cancer is well known at clinical, histopathological, and molecular levels. Genomic instability and greater mutation rates, which may result in the creation of neoantigens and enhanced immunogenicity, are additional characteristics of this breast cancer type. Clinical outcome is poor due to early age of onset, high metastatic potential, and increased likelihood of distant recurrence. Consequently, efforts to elucidate molecular mechanisms of breast cancer development, progression, and metastatic spread have been initiated to improve treatment options and improve outcomes for these patients. The extremely complex and heterogeneous tumor immune microenvironment is made up of several cell types and commonly possesses disorganized gene expression. Altered signaling pathways are mainly associated with mutated genes including p53, PIK3CA, and MAPK, and which are positively correlated with genes regulating immune response. Of note, particular immunity-associated genes could be used in prognostic indexes to assess the most effective management. Recent findings highlight the fact that long non-coding RNAs also play an important role in shaping tumor microenvironment formation, and can mediate tumor immune evasion. Identification of molecular signatures, through the use of multi-omics approaches, and effector pathways that drive early stages of the carcinogenic process are important steps in developing new strategies for targeted cancer treatment and prevention. Advances in immunotherapy by remodeling the host immune system to eradicate tumor cells have great promise to lead to novel therapeutic strategies. Current research is focused on combining immune checkpoint inhibition with chemotherapy, PARP inhibitors, cancer vaccines, or natural killer cell therapy. Targeted therapies may improve therapeutic response, eliminate therapeutic resistance, and improve overall patient survival. In the future, these evolving advancements should be implemented for personalized medicine and state-of-art management of cancer patients.

Project description:Patients with triple-negative breast cancer (TNBC) have a poor prognosis, partly because of the absence of targeted therapies. Recognition of the key role of immune responses against cancer has allowed the advent of immunotherapy, focused on the inhibition of negative immune checkpoints, such as CTLA-4. CTLA-4 is also expressed in some cancer cells, but its activity in tumor cells is not completely understood. Thus, the aim of the present work was to determine the biological landscape and functions of CTLA-4 expressed in TNBC cells through preclinical and in silico analysis. Exploration of CTLA-4 by immunohistochemistry in 50 TNBC tumors revealed membrane and cytoplasmic expression at different intensities. Preclinical experiments, using TNBC cell lines, showed that stimulation of CTLA-4 with CD80 enhances activation of the ERK1/2 signaling pathway, while CTLA-4 blockade by Ipilimumab induces the activation of AKT and reduces cell proliferation in vitro. We then developed an analytic pipeline to define the effects of CTLA-4 in available public data that allowed us to identify four distinct tumor clusters associated with CTLA-4 activation, which are characterized by enrichment of distinctive pathways associated with cell adhesion, MAPK signaling, TGF-ß, VEGF, TNF-?, drug metabolism, ion and amino acid transport, and KRAS signaling, among others. In addition, blockade of CTLA-4 induced increased secretion of IL-2 by tumor cells, suggesting that the receptor regulates cellular functions that may impact the immune microenvironment. This is relevant because a deep characterization of immune infiltrate, conducted using public data to estimate the abundancies of immune-cell types, showed that CTLA-4-activated-like tumors present a conditional immune state similar to an escape phenotype exploited by cancer cells. Finally, by interrogating transcriptional predictors of immunotherapy response, we defined that CTLA-4 activation correlates with high immune scores related to good clinical predicted responses to anti-CTLA-4 therapy. This work sheds new light on the roles of activated CLTA-4 in the tumor compartment and suggests an important interplay between tumor CLTA-4-activated portraits and immune-infiltrating cell populations.

Dataset Information

Identification of CTLA-4 associated with tumor microenvironment and competing interactions in triple negative breast cancer by co-expression network analysis.

Publications

Identification of CTLA-4 associated with tumor microenvironment and competing interactions in triple negative breast cancer by co-expression network analysis.

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