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      Multi‐omics analysis of disulfidptosis regulators and therapeutic potential reveals glycogen synthase 1 as a disulfidptosis triggering target for triple‐negative breast cancer

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          Abstract

          Disruption of disulfide homeostasis during biological processes can have fatal consequences. Excess disulfides induce cell death in a novel manner, termed as “disulfidptosis.” However, the specific mechanism of disulfidptosis has not yet been elucidated. To determine the cancer types sensitive to disulfidptosis and outline the corresponding treatment strategies, we firstly investigated the crucial functions of disulfidptosis regulators pan‐cancer at multi‐omics levels. We found that different tumor types expressed dysregulated levels of disulfidptosis regulators, most of which had an impact on tumor prognosis. Moreover, we calculated the disulfidptosis activity score in tumors and validated it using multiple independent datasets. Additionally, we found that disulfidptosis activity was correlated with classic biological processes and pathways in various cancers. Disulfidptosis activity was also associated with tumor immune characteristics and could predict immunotherapy outcomes. Notably, the disulfidptosis regulator, glycogen synthase 1 ( GYS1), was identified as a promising target for triple‐negative breast cancer and validated via in vitro and in vivo experiments. In conclusion, our study elucidated the complex molecular phenotypes and clinicopathological correlations of disulfidptosis regulators in tumors, laying a solid foundation for the development of disulfidptosis‐targeting strategies for cancer treatment.

          Abstract

          Flowchart of our study. By utilizing multi‐omics pan‐cancer cohorts, our study firstly offers a pan‐cancer blueprint of the molecular and clinical characteristics of disulfidptosis regulators, as wells as disulfidptosis activity, which lay a solid foundation for the disulfidptosis‐targeting strategy in precision cancer treatment.

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          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            GSVA: gene set variation analysis for microarray and RNA-Seq data

            Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.
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              The blockade of immune checkpoints in cancer immunotherapy.

              Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.
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                Author and article information

                Contributors
                2018012078@usc.edu.cn
                xiexm@sysucc.org.cn
                zouyt@sysucc.org.cn
                Journal
                MedComm (2020)
                MedComm (2020)
                10.1002/(ISSN)2688-2663
                MCO2
                MedComm
                John Wiley and Sons Inc. (Hoboken )
                2688-2663
                28 February 2024
                March 2024
                : 5
                : 3 ( doiID: 10.1002/mco2.v5.3 )
                : e502
                Affiliations
                [ 1 ] State Key Laboratory of Oncology in South China Guangdong Provincial Clinical Research Center for Cancer Sun Yat‐Sen University Cancer Center Guangzhou Guangdong China
                [ 2 ] The First Affiliated Hospital Hengyang Medical School University of South China Hengyang Hunan China
                Author notes
                [*] [* ] Correspondence

                Yutian Zou and Xiaoming Xie, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat‐Sen University Cancer Center, 651 Dongfeng East Road, Guangzhou 510060, Guangdong, China.

                Email: zouyt@ 123456sysucc.org.cn and xiexm@ 123456sysucc.org.cn

                Manbo Cai, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang 421001, Hunan, China.

                Email: 2018012078@ 123456usc.edu.cn

                Author information
                https://orcid.org/0000-0002-3206-782X
                https://orcid.org/0000-0002-5205-9923
                Article
                MCO2502
                10.1002/mco2.502
                10901283
                38420162
                73441d99-e313-4404-85eb-25490d41aa72
                © 2024 The Authors. MedComm published by Sichuan International Medical Exchange & Promotion Association (SCIMEA) and John Wiley & Sons Australia, Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 January 2024
                : 21 September 2023
                : 01 February 2024
                Page count
                Figures: 8, Tables: 0, Pages: 19, Words: 8852
                Funding
                Funded by: Chih Kuang Scholarship for Outstanding Young Physician‐Scientists of Sun Yat‐sen University Cancer Center
                Award ID: No.2023zgjh06
                Funded by: China National Postdoctoral Program for Innovative Talents
                Award ID: No.BX20230447
                Funded by: the Key Guiding Project of Hunan Provincial Health Commission
                Award ID: 202104101985
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 82173366
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                March 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.8 mode:remove_FC converted:28.02.2024

                disulfidptosis,pan‐cancer,prognosis,single‐cell rna‐seq,tumor microenvironment

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