■TGF-β信号通路异常可导致结直肠癌(CRC)的侵袭表型,导致预后不良。在TGF-β相关基因的基础上建立有效的预后因子对准确识别CRC患者的风险至关重要。
■我们从数据库和以前的文献中对CRC患者的TGF-β相关基因进行了差异分析,以获得TGF-β相关的差异表达基因(TRDEGs)。利用LASSO-Cox回归建立基于TRDEGs的CRC预后特征模型。使用两个GEO验证集对模型进行了验证。采用Wilcoxon秩和检验模型与临床因素的相关性。使用ESTIMATE算法和ssGSEA和肿瘤突变负荷(TMB)分析来分析高风险(HR)和低风险(LR)组的免疫状况和突变负荷。利用CellMiner数据库来鉴定对特征基因具有高敏感性的治疗药物。
■我们建立了具有良好预测准确性的六基因风险预后模型,独立预测CRC患者的预后。由于较高的免疫浸润和TMB,HR组更有可能经历免疫疗法益处。特征基因TGFB2能够抑制XAV-939、星孢菌素、和达沙替尼,但促进药物如CUDC-305和CUDC-305的副产品的疗效。同样,RBL1可以抑制氟奋乃静和咪喹莫特的药物作用,但可以促进伊罗芬的药物作用。
■根据TGF-β相关基因开发了CRC风险预后特征,为CRC患者的风险和进一步的治疗选择提供参考。
UNASSIGNED: Aberrant TGF-β signaling pathway can lead to invasive phenotype of colorectal cancer (CRC), resulting in poor prognosis. It is pivotal to develop an effective prognostic factor on the basis of TGF-β-related genes to accurately identify risk of CRC patients.
UNASSIGNED: We performed differential analysis of TGF-β-related genes in CRC patients from databases and previous literature to obtain TGF-β-related differentially expressed genes (TRDEGs). LASSO-Cox regression was utilized to build a CRC prognostic feature model based on TRDEGs. The model was validated using two GEO validation sets. Wilcoxon rank-sum test was utilized to test correlation of model with clinical factors. ESTIMATE algorithm and ssGSEA and tumor mutation burden (TMB) analysis were used to analyze immune landscape and mutation burden of high-risk (HR) and low-risk (LR) groups. CellMiner database was utilized to identify therapeutic drugs with high sensitivity to the feature genes.
UNASSIGNED: We established a six-gene risk prognostic model with good predictive accuracy, which independently predicted CRC patients\' prognoses. The HR group was more likely to experience immunotherapy benefits due to higher immune infiltration and TMB. The feature gene TGFB2 could inhibit the efficacy of drugs such as XAV-939, Staurosporine, and Dasatinib, but promote the efficacy of drugs such as CUDC-305 and by-product of CUDC-305. Similarly, RBL1 could inhibit the drug action of Fluphenazine and Imiquimod but promote that of Irofulven.
UNASSIGNED: A CRC risk prognostic signature was developed on basis of TGF-β-related genes, which provides a reference for risk and further therapeutic selection of CRC patients.