Yu-Xin Wan, Xin-Yu Zhu, Yu Zhao, Na Sun, Tian-Tong-Fei Jiang, Juan Xu
{"title":"Computational dissection of the regulatory mechanisms of aberrant metabolism in remodeling the microenvironment of breast cancer.","authors":"Yu-Xin Wan, Xin-Yu Zhu, Yu Zhao, Na Sun, Tian-Tong-Fei Jiang, Juan Xu","doi":"10.16288/j.yczz.24-167","DOIUrl":null,"url":null,"abstract":"<p><p>The composition of T cell subsets and tumor-specific T cell interactions within the tumor microenvironment (TME) contribute to the heterogeneity observed in breast cancer. Moreover, aberrant tumor metabolism is often intimately linked to dysregulated anti-tumor immune function of T cells. Identifying key metabolic genes that affect immune cell interactions thus holds promise for uncovering potential therapeutic targets in the treatment of breast cancer. This study leverages single-cell transcriptomic data from breast cancer to investigate tumor-specific T-cell subsets and their interacting subnetworks in the TME during cancer progression. We further assess the metabolic pathway activities of tumor-specifically activated T-cell subsets. The results reveal that metabolic pathways involved in insulin synthesis, secretion, degradation, as well as fructose catabolism, significantly influence multiple T cell interactions. By integrating the metabolic pathways that significantly up-regulate T cells in tumors and influence their interactions, we identify key abnormal metabolic genes associated with T-cell collaboration and further develop a breast cancer risk assessment model. Additionally, using gene expression profiles of prognosis-related genes significantly associated with aberrant metabolism and drug IC50 values, we predict targeted drugs, yielding potential candidates like GSK-J4 and PX-12. This study integrate the analysis of abnormal T-cell interactions and metabolic pathway abnormalities in the breast cancer TME, elucidating their roles in cancer progression and providing leads for novel breast cancer therapeutic strategies.</p>","PeriodicalId":35536,"journal":{"name":"遗传","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"遗传","FirstCategoryId":"1091","ListUrlMain":"https://doi.org/10.16288/j.yczz.24-167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
The composition of T cell subsets and tumor-specific T cell interactions within the tumor microenvironment (TME) contribute to the heterogeneity observed in breast cancer. Moreover, aberrant tumor metabolism is often intimately linked to dysregulated anti-tumor immune function of T cells. Identifying key metabolic genes that affect immune cell interactions thus holds promise for uncovering potential therapeutic targets in the treatment of breast cancer. This study leverages single-cell transcriptomic data from breast cancer to investigate tumor-specific T-cell subsets and their interacting subnetworks in the TME during cancer progression. We further assess the metabolic pathway activities of tumor-specifically activated T-cell subsets. The results reveal that metabolic pathways involved in insulin synthesis, secretion, degradation, as well as fructose catabolism, significantly influence multiple T cell interactions. By integrating the metabolic pathways that significantly up-regulate T cells in tumors and influence their interactions, we identify key abnormal metabolic genes associated with T-cell collaboration and further develop a breast cancer risk assessment model. Additionally, using gene expression profiles of prognosis-related genes significantly associated with aberrant metabolism and drug IC50 values, we predict targeted drugs, yielding potential candidates like GSK-J4 and PX-12. This study integrate the analysis of abnormal T-cell interactions and metabolic pathway abnormalities in the breast cancer TME, elucidating their roles in cancer progression and providing leads for novel breast cancer therapeutic strategies.
肿瘤微环境(TME)中 T 细胞亚群的组成和肿瘤特异性 T 细胞的相互作用导致了乳腺癌的异质性。此外,肿瘤代谢异常往往与 T 细胞抗肿瘤免疫功能失调密切相关。因此,识别影响免疫细胞相互作用的关键代谢基因有望发现治疗乳腺癌的潜在靶点。本研究利用乳腺癌的单细胞转录组数据,研究癌症进展过程中肿瘤特异性 T 细胞亚群及其在 TME 中的相互作用子网络。我们进一步评估了肿瘤特异性活化 T 细胞亚群的代谢通路活动。结果发现,参与胰岛素合成、分泌、降解以及果糖分解的代谢通路对多种 T 细胞相互作用有显著影响。通过整合肿瘤中 T 细胞明显上调并影响其相互作用的代谢途径,我们确定了与 T 细胞协作相关的关键异常代谢基因,并进一步开发了乳腺癌风险评估模型。此外,利用与异常代谢和药物 IC50 值显著相关的预后相关基因的基因表达谱,我们预测了靶向药物,并得出了 GSK-J4 和 PX-12 等潜在候选药物。这项研究整合了对乳腺癌TME中异常T细胞相互作用和代谢途径异常的分析,阐明了它们在癌症进展中的作用,并为新型乳腺癌治疗策略提供了线索。