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整合单细胞和批量RNA测序分析可识别出与结直肠癌炎症相关的预后特征。

Integrated singlecell and bulk RNA-seq analysis identifies a prognostic signature related to inflammation in colorectal cancer.

作者信息

Yin Wen, Ao Yanting, Jia Qian, Zhang Chao, Yuan Liping, Liu Sha, Xiao Wanmeng, Luo Gang, Shi Xiaomin, Xin Chen, Chen Maolin, Lü Muhan, Yu Zehui

机构信息

Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou City, China.

Department of Pharmacy, The Affiliated Hospital of Southwest Medical University, Luzhou, China.

出版信息

Sci Rep. 2025 Jan 6;15(1):874. doi: 10.1038/s41598-024-84998-6.

Abstract

Inflammation can influence the development of CRC as well as immunotherapy and plays a key role in CRC. Therefore, this study aimed to investigate the potential of inflammation-related genes in CRC risk prediction. Inflammation gene models were constructed and validated by combining transcriptomic and single-cell data from TCGA and GEO databases, and the expression of inflammation-related genes was verified by RT-qPCR. We identified two molecular subtypes and three genetic subtypes, two risk subgroups according to median risk values, constructed a prognostic model including thirteen genes (TIMP1, GDF15, UCN, KRT4, POU4F1, NXPH1, SIX2, NPC1L1, KLK12, IGFL1, FOXD1, ASPG, and CYP4F8), and validated the performance of each aspect of the model in an external database. Patients in the high-risk group had worse survival with reduced immune cell infiltration and a greater tumor mutational load. The risk score correlated strongly with the immune checkpoints PD1, PDL1, PDL2, and CTLA4, and it is possible that high-risk patients are more sensitive to treatment involving immune checkpoints. In the single-cell data, GDF15 was most significantly expressed in cancer cell populations. Therefore, we further validated their expression in cells and tissues using qPCR. In summary, we developed a prognostic marker associated with inflammatory genes to provide new directions for subsequent studies and to help clinicians assess the prognosis of CRC patients as well as to develop personalized treatment strategies.

摘要

炎症可影响结直肠癌的发展以及免疫治疗,并在结直肠癌中起关键作用。因此,本研究旨在探讨炎症相关基因在结直肠癌风险预测中的潜力。通过整合来自TCGA和GEO数据库的转录组和单细胞数据构建并验证炎症基因模型,并通过RT-qPCR验证炎症相关基因的表达。我们鉴定出两种分子亚型和三种基因亚型,根据中位风险值划分出两个风险亚组,构建了一个包含13个基因(TIMP1、GDF15、UCN、KRT4、POU4F1、NXPH1、SIX2、NPC1L1、KLK12、IGFL1、FOXD1、ASPG和CYP4F8)的预后模型,并在外部数据库中验证了该模型各方面的性能。高风险组患者的生存率较差,免疫细胞浸润减少,肿瘤突变负荷更大。风险评分与免疫检查点PD1、PDL1、PDL2和CTLA4密切相关,高风险患者可能对涉及免疫检查点的治疗更敏感。在单细胞数据中,GDF15在癌细胞群体中表达最为显著。因此,我们进一步使用qPCR验证了它们在细胞和组织中的表达。总之,我们开发了一种与炎症基因相关的预后标志物,为后续研究提供新方向,并帮助临床医生评估结直肠癌患者的预后以及制定个性化治疗策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/029f/11701073/d52e2d7fd215/41598_2024_84998_Fig1_HTML.jpg

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