利用机器学习整合单细胞和批量 RNA 测序数据，构建和验证胃癌中新型细胞黏附分子相关预后模型。

Utilizing machine learning to integrate single-cell and bulk RNA sequencing data for constructing and validating a novel cell adhesion molecules related prognostic model in gastric cancer.

机构信息

Department of General Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China; Wenzhou Collaborative Innovation Center of Gastrointestinal Cancer in Basic Research and Precision Medicine, Wenzhou Key Laboratory of Cancer-related Pathogens and Immunity, Department of Microbiology and Immunology, Institute of Molecular Virology and Immunology, School of Basic Medical Sciences, Wenzhou Medical University, Wenzhou, China; Department of General Surgery, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang Province, China.

出版信息

Comput Biol Med. 2024 Sep;180:108998. doi: 10.1016/j.compbiomed.2024.108998. Epub 2024 Aug 12.

DOI:10.1016/j.compbiomed.2024.108998

PMID:39137671

Abstract

BACKGROUND

Cell adhesion molecules (CAMs) play a vital role in cell-cell interactions, immune response modulation, and tumor cell migration. However, the unique role of CAMs in gastric cancer (GC) remains largely unexplored.

METHODS

This study characterized the genetic alterations and mRNA expression of CAMs. The role of CD34, a representative molecule, was validated in 375 GC tissues. The activity of the CAM pathway was further tested using single-cell and bulk characterization. Next, data from 839 patients with GC from three cohorts was analyzed using univariate Cox and random survival forest methods to develop and validate a CAM-related prognostic model.

RESULTS

Most CAM-related genes exhibited multi-omics alterations and were associated with clinical outcomes. There was a strong correlation between increased CD34 expression and advanced clinical staging (P = 0.026), extensive vascular infiltration (P = 0.003), and unfavorable prognosis (Log-rank P = 0.022). CD34 expression was also found to be associated with postoperative chemotherapy and tumor immunotherapy response. Furthermore, the CAM pathway was significantly activated and mediated poor prognosis. Additionally, eight prognostic signature genes (PSGs) were identified in the training cohort. There was a substantial upregulation of the expression of immune checkpoints and a pronounced infiltration of immune cells in GC tissues with high PSG score, which is consistent with the prediction of increased sensitivity to immunotherapy. Moreover, 9 compounds from the CTRPv2 database and 13 from the Profiling Relative Inhibition Simultaneously in Mixture (PRISM) database were identified as potential therapeutic drugs for patients with GC with high PSG score.

CONCLUSION

Thorough understanding of CAM pathways regulation and the innovative PSG score model hold significant implications for medical diagnosis, potentially enhancing personalized treatment strategies and improving patient outcomes in GC management.

摘要

背景

细胞黏附分子（CAMs）在细胞-细胞相互作用、免疫反应调节和肿瘤细胞迁移中发挥着至关重要的作用。然而，CAM 在胃癌（GC）中的独特作用在很大程度上仍未得到探索。

方法

本研究对 CAM 的遗传改变和 mRNA 表达进行了特征描述。在 375 份 GC 组织中验证了代表性分子 CD34 的作用。使用单细胞和批量特征分析进一步测试了 CAM 途径的活性。接下来，使用单变量 Cox 和随机生存森林方法分析了来自三个队列的 839 名 GC 患者的数据，以开发和验证与 CAM 相关的预后模型。

结果

大多数与 CAM 相关的基因表现出多组学改变，并与临床结局相关。CD34 表达增加与临床分期较晚（P=0.026）、广泛的血管浸润（P=0.003）和预后不良（Log-rank P=0.022）呈强相关性。CD34 表达也与术后化疗和肿瘤免疫治疗反应相关。此外，CAM 途径显著激活并介导不良预后。此外，在训练队列中鉴定出 8 个预后特征基因（PSGs）。在 PSG 评分较高的 GC 组织中，免疫检查点的表达显著上调，免疫细胞浸润明显，这与增加对免疫治疗敏感性的预测一致。此外，从 CTRPv2 数据库中鉴定出 9 种化合物，从 Profiling Relative Inhibition Simultaneously in Mixture (PRISM) 数据库中鉴定出 13 种化合物，这些化合物可能成为 PSG 评分较高的 GC 患者的潜在治疗药物。