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      Regulation of ferroptosis‐related genes in CD8+ NKT cells and classical monocytes may affect the immunotherapy response after combined treatment in triple negative breast cancer

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          Abstract

          Background

          Drug resistance has led to the failure of immunotherapy in triple negative breast cancer patients. Here we aimed to explore the mechanisms of drug resistance in patients in order to enhance their response to immunotherapy.

          Methods

          We downloaded publicly available single‐cell RNA‐sequencing data of peripheral blood mononuclear cells from patients after treatment to investigate the possible mechanisms of drug resistance. The publicly available TCGA transcriptomic data and somatic mutation data were used for further validation. In this study, a series of bioinformatics and machine learning methods were employed.

          Results

          We identified the vital roles of CD8+ NKT cells and classical monocytes in the immunotherapy response of triple‐negative breast cancer patients. The proportion of these cell types was significantly increased in group partial response. We also found that downregulation of ferroptosis‐related genes regulates the immune pathway. The analysis of scRNA data and TCGA transcriptomic data presented that DUSP1 may play a crucial role in immunotherapy resistance.

          Conclusion

          Overall, the composition of the tumor microenvironment affects the immunotherapy response of patients, and DUSP1 may be a potential target for overcoming drug resistance.

          Abstract

          Combined therapy with atezolizumab and paclitaxel will downregulate the expression of DDIT4 in CD8+ NKT cells and DUSP1 in classical monocytes, which leading to reduced ferroptosis in both cells and consequently inhibited tumor progression.

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          Most cited references39

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              Comprehensive Integration of Single-Cell Data

              Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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                Author and article information

                Contributors
                xzhangrm@whu.edu.cn , gongyp@whu.edu.cn
                yaoyi2018@whu.edu.cn
                xzhangrm@whu.edu.cn
                Journal
                Thorac Cancer
                Thorac Cancer
                10.1111/(ISSN)1759-7714
                TCA
                Thoracic Cancer
                John Wiley & Sons Australia, Ltd (Melbourne )
                1759-7706
                1759-7714
                13 October 2023
                December 2023
                : 14
                : 34 ( doiID: 10.1111/tca.v14.34 )
                : 3369-3380
                Affiliations
                [ 1 ] Cancer Center Renmin Hospital of Wuhan University Wuhan China
                [ 2 ] Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology Peking University Cancer Hospital & Institute Beijing China
                [ 3 ] Department of Anesthesiology, East Hospital Renmin Hospital of Wuhan University Wuhan China
                [ 4 ] Department of Breast Renmin Hospital of Wuhan University Wuhan China
                Author notes
                [*] [* ] Correspondence

                Yiping Gong and Xue Zhang, Department of Breast, Renmin Hospital of Wuhan University, Wuhan, China.

                Email: gongyp@ 123456whu.edu.cn and xzhangrm@ 123456whu.edu.cn

                Yi Yao, Cancer Center, Renmin Hospital of Wuhan University, Wuhan, China.

                Email: yaoyi2018@ 123456whu.edu.cn

                Author information
                https://orcid.org/0000-0003-0050-8237
                Article
                TCA15128
                10.1111/1759-7714.15128
                10693945
                37830388
                3c6e9ded-f8fb-415c-9c39-f49acbee4baa
                © 2023 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 20 July 2023
                : 25 September 2023
                Page count
                Figures: 7, Tables: 0, Pages: 12, Words: 6333
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                December 2023
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.5 mode:remove_FC converted:03.12.2023

                drug resistance,ferroptosis,immunotherapy,triple‐negative breast cancer,tumor microenvironment

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