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      Integrative analyses identified gap junction beta‐2 as a prognostic biomarker and therapeutic target for breast cancer

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          Abstract

          Background

          Increasing evidence has shown that connexins are involved in the regulation of tumor development, immune escape, and drug resistance. This study investigated the gene expression patterns, prognostic values, and potential mechanisms of connexins in breast cancer.

          Methods

          We conducted a comprehensive analysis of connexins using public gene and protein expression databases and clinical samples from our institution. Connexin mRNA expressions in breast cancer and matched normal tissues were compared, and multiomics studies were performed.

          Results

          Gap junction beta‐2 mRNA was overexpressed in breast cancers of different pathological types and molecular subtypes, and its high expression was associated with poor prognosis. The tumor membrane of the gap junction beta‐2 mutated group was positive, and the corresponding protein was expressed. Somatic mutation and copy number variation of gap junction beta‐2 are rare in breast cancer. The gap junction beta‐2 transcription level in the p110α subunit of the phosphoinositide 3‐kinase mutant subgroup was higher than that in the wild‐type subgroup. Gap junction beta‐2 was associated with the phosphoinositide 3‐kinase‐Akt signaling pathway, extracellular matrix–receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, gap junction beta‐2 overexpression may be associated with phosphoinositide 3‐kinase and histone deacetylase inhibitor resistance, and its expression level correlated with infiltrating CD8+ T cells, macrophages, neutrophils, and dendritic cells.

          Conclusions

          Gap junction beta‐2 may be a promising therapeutic target for targeted therapy and immunotherapy and may be used to predict breast cancer prognosis.

          Abstract

          Gap junction beta‐2, a connexin protein, is overexpressed in various breast cancer subtypes and associated with poor prognosis. Notably, mutated Gap junction beta‐2 is localized on the tumor cell membrane, while somatic mutations and copy number variations are rare. Gap junction beta‐2 transcription levels were elevated in the p110α subunit of the phosphoinositide 3‐kinase (PI3K) mutant subgroup, linking it to the PI3K‐Akt signaling pathway, extracellular matrix–receptor interactions, focal adhesion, and proteoglycan regulation in cancer. Furthermore, Gap junction beta‐2 overexpression predicted resistance to PI3K and histone deacetylase inhibitors and correlated with immune cell infiltration, including CD8+ T cells, macrophages, neutrophils, and dendritic cells. Gap junction beta‐2 may serve as a dual therapeutic target for both targeted therapy and immunotherapy and could be a valuable predictor of breast cancer prognosis.

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          Most cited references48

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

            The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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              Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

              DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
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                Author and article information

                Contributors
                drmafei@126.com
                Journal
                Cancer Innov
                Cancer Innov
                10.1002/(ISSN)2770-9183
                CAI2
                Cancer Innovation
                John Wiley and Sons Inc. (Hoboken )
                2770-9191
                2770-9183
                19 May 2024
                August 2024
                : 3
                : 4 ( doiID: 10.1002/cai2.v3.4 )
                : e128
                Affiliations
                [ 1 ] Department of Medical Oncology Qilu Hospital of Shandong University Jinan China
                [ 2 ] Department of Medical Oncology Qilu Hospital, Cheeloo College of Medicine Shandong University Jinan China
                [ 3 ] Department of Medical Oncology National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
                Author notes
                [*] [* ] Correspondence Fei Ma, Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China. 

                Email: drmafei@ 123456126.com

                Author information
                http://orcid.org/0000-0001-5790-5052
                http://orcid.org/0000-0001-9432-1902
                Article
                CAI2128
                10.1002/cai2.128
                11212300
                de5cd0ed-7f8c-47cb-85c5-7831ab7759c9
                © 2024 The Authors. Cancer Innovation published by John Wiley & Sons Ltd on behalf of Tsinghua University Press.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 17 December 2023
                : 08 October 2023
                : 01 February 2024
                Page count
                Figures: 8, Tables: 2, Pages: 14, Words: 6591
                Funding
                Funded by: None
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                August 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.5 mode:remove_FC converted:28.06.2024

                breast cancer,connexin,gap junction beta‐2,phosphoinositide 3‐kinase‐akt‐mtor pathway,prognosis

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