构建新型预后标志物，揭示免疫景观，筛选肝癌中 M2 样肿瘤相关巨噬细胞相关生物标志物。
M2-like tumor-associated macrophage-related biomarkers to construct a novel prognostic signature, reveal the immune landscape, and screen drugs in hepatocellular carcinoma.
机构信息
State Key Laboratory of Cancer Biology, National Clinical Research Center for Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
出版信息
Front Immunol. 2022 Sep 13;13:994019. doi: 10.3389/fimmu.2022.994019. eCollection 2022.
BACKGROUND
M2-like tumor-associated macrophages (M2-like TAMs) have important roles in the progression and therapeutics of cancers. We aimed to detect novel M2-like TAM-related biomarkers in hepatocellular carcinoma (HCC) integrative analysis of single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data to construct a novel prognostic signature, reveal the "immune landscape", and screen drugs in HCC.
METHODS
M2-like TAM-related genes were obtained by overlapping the marker genes of TAM identified from scRNA-seq data and M2 macrophage modular genes identified by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were carried out to screen prognostic genes from M2-like TAM-related genes, followed by a construction of a prognostic signature, delineation of risk groups, and external validation of the prognostic signature. Analyses of immune cells, immune function, immune evasion scores, and immune-checkpoint genes between high- and low-risk groups were done to further reveal the immune landscape of HCC patients. To screen potential HCC therapeutic agents, analyses of gene-drug correlation and sensitivity to anti-cancer drugs were conducted.
RESULTS
A total of 127 M2-like TAM-related genes were identified by integrative analysis of scRNA-seq and bulk-seq data. PDLIM3, PAM, PDLIM7, FSCN1, DPYSL2, ARID5B, LGALS3, and KLF2 were screened as prognostic genes in HCC by univariate Cox regression and LASSO regression analyses. Then, a prognostic signature was constructed and validated based on those genes for predicting the survival of HCC patients. In terms of drug screening, expression of PAM and LGALS3 was correlated positively with sensitivity to simvastatin and ARRY-162, respectively. Based on risk grouping, we predicted 10 anticancer drugs with high sensitivity in the high-risk group, with epothilone B having the lowest half-maximal inhibitory concentration among all drugs tested.
CONCLUSIONS
Our findings enhance understanding of the M2-like TAM-related molecular mechanisms involved in HCC, reveal the immune landscape of HCC, and provide potential targets for HCC treatment.
背景
M2 样肿瘤相关巨噬细胞（M2 样 TAMs）在癌症的进展和治疗中具有重要作用。我们旨在检测肝细胞癌（HCC）中新型 M2 样 TAM 相关生物标志物，通过单细胞 RNA 测序（scRNA-seq）和批量 RNA-seq 数据的综合分析，构建一个新的预后标志物，揭示“免疫景观”，并筛选 HCC 中的药物。
方法
通过重叠 scRNA-seq 数据中鉴定的 TAM 标记基因和批量 RNA-seq 数据中加权基因共表达网络分析（WGCNA）鉴定的 M2 巨噬细胞模块基因，获得 M2 样 TAM 相关基因。使用单变量 Cox 回归和最小绝对值收缩和选择算子（LASSO）回归分析从 M2 样 TAM 相关基因中筛选预后基因，然后构建预后标志物，划定风险组，并对外验证预后标志物。分析高风险组和低风险组之间的免疫细胞、免疫功能、免疫逃逸评分和免疫检查点基因，进一步揭示 HCC 患者的免疫景观。为筛选潜在的 HCC 治疗药物，进行基因-药物相关性和抗癌药物敏感性分析。
结果
通过 scRNA-seq 和批量-seq 数据的综合分析，共鉴定出 127 个 M2 样 TAM 相关基因。通过单变量 Cox 回归和 LASSO 回归分析，从 HCC 中筛选出 PDLIM3、PAM、PDLIM7、FSCN1、DPYSL2、ARID5B、LGALS3 和 KLF2 作为预后基因。然后，基于这些基因构建并验证了一个预测 HCC 患者生存的预后标志物。在药物筛选方面，PAM 和 LGALS3 的表达与辛伐他汀和 ARRY-162 的敏感性呈正相关。基于风险分组，我们预测在高风险组中，10 种抗癌药物具有高敏感性，在所有测试的药物中，表阿霉素 B 的半数最大抑制浓度最低。
结论
我们的研究结果增强了对 HCC 中涉及的 M2 样 TAM 相关分子机制的理解，揭示了 HCC 的免疫景观，并为 HCC 治疗提供了潜在的靶点。
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