Table_1_Establishment and Validation of a Genetic Label Associated With M2 Macrophage Infiltration to Predict Survival in Patients With Colon Cancer and to Assist in Immunotherapy.DOCX

BackgroundColon cancer is a malignant tumor with high morbidity and mortality. Researchers have tried to interpret it from different perspectives and divided it into different subtypes to facilitate individualized treatment. With the rise in the use of immunotherapy, its value in the field of tumor has begun to emerge. From the perspective of immune infiltration, this study classified colon cancer according to the infiltration of M2 macrophages in patients with colon cancer and further explored the same.
MethodsCibersort algorithm was used to analyze the level of immune cell infiltration in patients with colon cancer in The Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis (WGCNA), Consensus Clustering analysis, Lasso analysis, and univariate Kaplan–Meier analysis were used to screen and verify the hub genes associated with M2 macrophages. Principal component analysis (PCA) was used to establish the M2 macrophage-related score (M2I Score). The correlation between M2I Score and somatic cell variation and microsatellite instability (MSI) were analyzed. Furthermore, the correlation between M2 macrophage score and differences in immunotherapy sensitivity was also explored.
ResultsM2 macrophage infiltration was associated with poor prognosis. Four hub genes (ANKS4B, CTSD, TIMP1, and ZNF703) were identified as the progression-related genes associated with M2 macrophages. A stable and accurate M2I Score for M2 macrophages used in colon adenocarcinoma was determined based on four hub genes. The M2I Score was positively correlated with the tumor mutation load (TMB). The M2I Score of the group with high instability of microsatellites was higher than that of the group with low instability of microsatellites and microsatellite-stable group. Combined with the Cancer Immunome Atlas database, we concluded that patients with high M2I Scores were more sensitive to programmed cell death protein 1 (PD-1) inhibitors and PD-1 inhibitors combined with cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) inhibitors. The low-rating group may have better efficacy without immune checkpoint inhibitors or with CTLA4 inhibitors alone.
ConclusionFour prognostic hub genes associated with M2 macrophages were screened to establish the M2I Score. Patients were divided into two subgroups: high M2I Score group and low M2I Score group. TMB, MSI, and sensitivity to immunotherapy were higher in the high-rated group. PD-1 inhibitors or PD-1 combined with CTLA-4 inhibitors are preferred for patients in the high-rated group who are more sensitive to immunotherapy.

背景
结直肠癌是一种发病率与死亡率均较高的恶性肿瘤。研究者们尝试从不同视角解析结直肠癌的发病机制，并将其划分为不同亚型以助力个体化治疗。随着免疫治疗应用的普及，其在肿瘤领域的应用价值日益凸显。本研究从免疫浸润视角出发，基于结直肠癌患者的M2巨噬细胞浸润水平对结直肠癌进行分型，并开展了进一步的探索研究。

方法
本研究采用Cibersort算法（Cibersort）分析癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据库中结直肠癌患者的免疫细胞浸润水平。通过加权基因共表达网络分析（Weighted gene co-expression network analysis, WGCNA）、一致性聚类分析、Lasso分析、单因素Kaplan-Meier分析筛选并验证与M2巨噬细胞相关的核心基因。采用主成分分析（Principal component analysis, PCA）构建M2巨噬细胞相关评分（M2I Score）。分析M2I Score与体细胞变异、微卫星不稳定性（microsatellite instability, MSI）的相关性，并进一步探索M2巨噬细胞评分与免疫治疗敏感性的关联。

结果
M2巨噬细胞浸润与不良预后显著相关。本研究筛选出4个与M2巨噬细胞相关的进展核心基因（ANKS4B、CTSD、TIMP1及ZNF703）。基于上述4个核心基因，构建了稳定且精准的结肠腺癌M2巨噬细胞相关评分（M2I Score）。M2I Score与肿瘤突变负荷（tumor mutation load, TMB）呈正相关。高微卫星不稳定性组的M2I Score显著高于低微卫星不稳定性组及微卫星稳定组。结合癌症免疫图谱数据库分析结果，本研究发现M2I Score较高的患者对程序性死亡蛋白1（PD-1）抑制剂以及PD-1抑制剂联合细胞毒性T淋巴细胞相关蛋白4（CTLA-4）抑制剂的治疗敏感性更高。而低评分组患者在不使用免疫检查点抑制剂或仅使用CTLA-4抑制剂时，可能获得更优的治疗效果。

结论
本研究筛选出4个与M2巨噬细胞相关的预后核心基因，并以此构建了M2I Score。将结直肠癌患者划分为高M2I Score组与低M2I Score两个亚组。高评分组患者的肿瘤突变负荷（TMB）、微卫星不稳定性（MSI）以及免疫治疗敏感性均更高。对于免疫治疗敏感性更高的高评分组患者，优先推荐使用PD-1抑制剂或PD-1抑制剂联合CTLA-4抑制剂进行治疗。