Grupo de Investigación en Biología del Cáncer, Instituto Nacional de Cancerología (INC), Bogotá, Colombia; Grupo de Apoyo y Seguimiento para la Investigación GASPI, Instituto Nacional de Cancerología (INC), Bogotá, Colombia.
Department of Human Genetics, McGill University, Montreal, QC, Canada, McGill University, Genome Centre, Montreal, QC, Canada.
Adv Genet. 2024;112:207-254. doi: 10.1016/bs.adgen.2024.08.005. Epub 2024 Aug 31.
Despite recent advancements in colorectal cancer (CRC) treatment, particularly with the introduction of immunotherapy and checkpoint inhibitors, the efficacy of these therapies remains limited to a subset of patients. To address this challenge, our study aimed to develop a prognostic biomarker based on immune-related genes to predict better outcomes in CRC patients and aid in treatment decision-making. We comprehensively analysed immune gene expression signatures associated with CRC prognosis to construct an immune meta-signature with prognostic potential. Utilising data from The Cancer Genome Atlas (TCGA), we employed Cox regression to identify immune-related genes with prognostic significance from multiple studies. Subsequently, we compared the expression levels of immune genes, levels of immune cell infiltration, and various immune-related molecules between high-risk and low-risk patient groups. Functional analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses provided insights into the biological pathways associated with the identified prognostic genes. Finally, we validated our findings using a separate CRC cohort from the Gene Expression Omnibus (GEO). Integration of the prognostic genes revealed significant disparities in survival outcomes. Differential expression analysis identified a set of immune-associated genes, which were further refined using LASSO penalisation and Cox regression. Univariate Cox regression analyses confirmed the autonomy of the gene signature as a prognostic indicator for CRC patient survival. Our risk prediction model effectively stratified CRC patients based on their prognosis, with the high-risk group showing enrichment in pro-oncogenic terms and pathways. Immune infiltration analysis revealed an augmented presence of certain immunosuppressive subsets in the high-risk group. Finally, we validated the performance of our prognostic model by applying the risk score equation to a different CRC patient dataset, confirming its prognostic potential in this new cohort. Overall, our study presents a novel immune-related gene signature with promising implications for predicting cancer progression and prognosis, thereby enabling more personalised management strategies for CRC patients.
尽管近年来在结直肠癌（CRC）治疗方面取得了进展，特别是免疫疗法和检查点抑制剂的引入，但这些疗法的疗效仍然局限于一部分患者。为了应对这一挑战，我们的研究旨在开发一种基于免疫相关基因的预后生物标志物，以预测 CRC 患者的更好结局并辅助治疗决策。我们全面分析了与 CRC 预后相关的免疫基因表达特征，构建了具有预后潜力的免疫元特征。我们利用来自癌症基因组图谱（TCGA）的数据，采用 Cox 回归从多项研究中鉴定出具有预后意义的免疫相关基因。随后，我们比较了高风险和低风险患者组之间免疫基因的表达水平、免疫细胞浸润水平和各种免疫相关分子。使用基因本体论和京都基因与基因组百科全书通路分析进行的功能分析提供了与鉴定的预后基因相关的生物学途径的见解。最后，我们使用来自基因表达综合数据库（GEO）的另一个 CRC 队列验证了我们的发现。预后基因的整合揭示了生存结果的显著差异。差异表达分析确定了一组免疫相关基因，进一步使用 LASSO 惩罚和 Cox 回归进行了精炼。单变量 Cox 回归分析证实了基因特征作为 CRC 患者生存的预后指标的自主性。我们的风险预测模型能够有效地根据患者的预后对 CRC 患者进行分层，高风险组在促癌基因和途径中表现出富集。免疫浸润分析显示高风险组中某些免疫抑制亚群的存在增加。最后，我们通过将风险评分方程应用于不同的 CRC 患者数据集来验证我们的预后模型的性能，证实了其在新队列中的预后潜力。总的来说，我们的研究提出了一种新的免疫相关基因特征，具有预测癌症进展和预后的潜力，从而为 CRC 患者提供了更个性化的管理策略。
