Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, China.
The Second Clinical Medicine School, Nanchang University, Nanchang 330006, China.
Biomolecules. 2022 Dec 14;12(12):1877. doi: 10.3390/biom12121877.
Colorectal cancers (CRCs) continue to be the leading cause of cancer-related deaths worldwide. The exact landscape of the molecular features of TGF-β pathway-inducing CRCs remains uncharacterized.
Unsupervised hierarchical clustering was performed to stratify samples into two clusters based on the differences in TGF-β pathways. Weighted gene co-expression network analysis was applied to identify the key gene modules mediating the different characteristics between two subtypes. An algorithm integrating the least absolute shrinkage and selection operator (LASSO), XGBoost, and random forest regression was performed to narrow down the candidate genes. Further bioinformatic analyses were performed focusing on COMP-related immune infiltration and functions.
The integrated machine learning algorithm identified COMP as the hub gene, which exhibited a significant predictive value for two subtypes with an area under the curve (AUC) value equaling 0.91. Further bioinformatic analysis revealed that COMP was significantly upregulated in various cancers, especially in advanced CRCs, and regulated the immune infiltration, especially M2 macrophages and cancer-associated fibroblasts in CRCs.
Comprehensive immune analysis and experimental validation demonstrate that COMP is a reliable signature for subtype prediction. Our results could provide a new point for TGFβ-targeted anticancer drugs and contribute to guiding clinical decision making for CRC patients.
结直肠癌(CRC)仍然是全球癌症相关死亡的主要原因。TGF-β 通路诱导 CRC 的分子特征的全貌尚未确定。
基于 TGF-β 通路的差异,对样本进行无监督层次聚类,将样本分为两群。应用加权基因共表达网络分析鉴定介导两种亚型不同特征的关键基因模块。整合最小绝对收缩和选择算子(LASSO)、XGBoost 和随机森林回归的算法用于缩小候选基因的范围。进一步进行了集中于 COMP 相关免疫浸润和功能的生物信息学分析。
集成机器学习算法确定 COMP 为枢纽基因,其对两种亚型具有显著的预测价值,曲线下面积(AUC)值等于 0.91。进一步的生物信息学分析表明,COMP 在各种癌症中显著上调,特别是在晚期 CRC 中,并调节免疫浸润,特别是 CRC 中的 M2 巨噬细胞和癌相关成纤维细胞。
全面的免疫分析和实验验证表明,COMP 是亚型预测的可靠标志物。我们的结果可为 TGFβ 靶向抗癌药物提供新的切入点,并有助于指导 CRC 患者的临床决策。