Table_1_Identification of a Novel Immune Landscape Signature for Predicting Prognosis and Response of Colon Cancer to Immunotherapy.docx

PurposeTo construct an immune-related gene prognostic index (IRGPI) for colon cancer and elucidate the molecular and immune characteristics as well as the benefit of immune checkpoint inhibitor (ICI) therapy in IRGPI-defined groups of colon cancer.
Experimental DesignTranscriptional and clinical data of colon cancer samples were obtained from The Cancer Genome Atlas (TCGA) (n = 521). Immune-related genes were obtained from ImmPort and InnateDB databases. 21 immune-related hub genes were identified byweighted gene co-expression network analysis (WGCNA). the Cox regression method was used to construct IRGPI and validated with Gene Expression Omnibus (GEO) dataset (n = 584). Finally, the molecular and immune profiles in the groups defined by IRGPI and the benefit of ICI treatment were analyzed.
Results8 genes were identified to construct IRGPI. IRGPI-low group had a better overall survival (OS) than IRGPI-high group. And this was well validated in the GEO cohort. Overall results showed that those with low IRGPI scores were enriched in antitumor metabolism, and collated with high infiltration of resting memory CD4 T cells and less aggressive phenotypes, benefiting more from ICI treatment. Conversely, high IRGPI scores were associated with cell adhesion molecules (CAMs) and chemokine signaling pathways, high infiltration of macrophage M1, suppressed immunity, more aggressive colon cancer phenotypes, as well as reduced therapeutic benefit from ICI treatment.
ConclusionsIRGPI is a promising biomarker to differentiate the prognostic and molecular profile of colon cancer, as well as the therapeutic benefits of ICI treatment.

研究目的：构建结直肠癌免疫相关基因预后指数（immune-related gene prognostic index, IRGPI），并阐明IRGPI分型的结直肠癌患者的分子与免疫特征，以及其对免疫检查点抑制剂（immune checkpoint inhibitor, ICI）治疗的获益情况。
实验设计：从癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库获取521例结直肠癌样本的转录组与临床数据。免疫相关基因从ImmPort及InnateDB数据库获取。通过加权基因共表达网络分析（weighted gene co-expression network analysis, WGCNA）筛选得到21个免疫相关核心基因。采用Cox回归法构建IRGPI，并在基因表达综合（Gene Expression Omnibus, GEO）数据集（n=584）中进行验证。最后分析IRGPI分型的结直肠癌患者的分子与免疫特征，以及ICI治疗获益情况。
研究结果：共筛选得到8个基因用于构建IRGPI。IRGPI低分组患者的总生存期（overall survival, OS）优于高分组，该结果在GEO队列中得到有效验证。整体分析显示，IRGPI低评分患者富集于抗肿瘤代谢通路，且表现为静息记忆CD4+ T细胞高浸润、肿瘤侵袭性较低的表型，从ICI治疗中获益更多。反之，IRGPI高评分患者与细胞黏附分子（cell adhesion molecules, CAMs）及趋化因子信号通路相关，表现为M1型巨噬细胞高浸润、免疫抑制、肿瘤侵袭性更强的表型，且从ICI治疗中获益较少。
研究结论：IRGPI是一项具有应用前景的生物标志物，可用于区分结直肠癌患者的预后与分子特征，同时可预测患者接受ICI治疗的获益情况。