Table1_Construction and Verification of a Fibroblast-Related Prognostic Signature Model for Colon Cancer.XLSX

Traditionally, cancer-associated fibroblasts (CAFs), an essential component of tumor microenvironment, were exert a crucial part in colon cancer progression. In this study, single-cell RNA-sequencing (scRNA-seq) data from 23 and bulk RNA-seq data from 452 colon cancer patients were extracted from the GEO database and TCGA-COAD and GEO databases, respectively. From single-cell analysis, 825 differentially expressed genes (DEGs) in CAFs were identified between each pair of six newly defined CAFs, named enCAF, adCAF, vaCAF, meCAF, erCAF, and cyCAF. Cell communication analysis with the iTALK package showed communication relationship between CAFs, including cell autocrine, cytokine, and growth factor subtypes, such as receptor-ligand pairs of TNFSF14-LTBR, IL6-F3, and IL6-IL6ST. Herein, we demonstrated the presence and prognostic value of adCAF and erCAF in colon cancer based on CIBERSORTx, combining single-cell marker genes and transcriptomics data. The prognostic significance of the enCAF and erCAF has been indirectly proved by both the correlation analysis with macrophages and CAFs, and the quantitative reverse transcription-polymerase chain reaction (qRT-PCR) experiment based on 20 paired tumor samples. A prognostic model was constructed with 10 DEGs using the LASSO Cox regression method. The model was validated using two testing datasets, indicate a significant survival accuracy (p < 0.0025). Correlation analyses between clinical information, such as age, gender, tumor stage and tumor features (tumor purity and immune score), and risk scores revealed our CAF-related model’s robustness and excellent performance. Cell infiltration analysis by xCell revealed that the interaction between CAFs and multiple non-specific immune cells such as macrophages and the dendritic cell was a vital factor affecting immune score and prognosis. Finally, we analyzed how common anti-cancer drugs, including camptothecin, docetaxel and bortezomib, and immunotherapy, such as anti-PD-1 treatment, could be different in low-risk and high-risk patients inferred from our CAF-related model. In conclusion, the study utilized refined colon cancer fibroblast subsets and established the prognostic effects from the interaction with nonspecific immune cell.

传统上，作为肿瘤微环境核心组成部分的肿瘤相关成纤维细胞（cancer-associated fibroblasts, CAFs）在结肠癌进展中发挥关键作用。本研究分别从GEO数据库以及TCGA-COAD和GEO数据库中，提取了23例样本的单细胞RNA测序（single-cell RNA-sequencing, scRNA-seq）数据与452例结肠癌患者的批量RNA测序数据。通过单细胞分析，在新定义的6类CAFs（分别命名为enCAF、adCAF、vaCAF、meCAF、erCAF及cyCAF）的两两比较中，共鉴定出825个CAFs差异表达基因（differentially expressed genes, DEGs）。使用iTALK工具包进行细胞通讯分析后，揭示了CAFs之间的通讯关系，涵盖细胞自分泌、细胞因子及生长因子亚型等多种类型，例如TNFSF14-LTBR、IL6-F3及IL6-IL6ST等受体-配体对。本研究基于CIBERSORTx平台，结合单细胞标记基因与转录组学数据，证实了adCAF与erCAF在结肠癌中的存在性及其预后价值。通过与巨噬细胞及CAFs的相关性分析，以及基于20对肿瘤样本的定量反转录聚合酶链反应（quantitative reverse transcription-polymerase chain reaction, qRT-PCR）实验，间接验证了enCAF与erCAF的预后意义。本研究采用LASSO Cox回归方法，以10个DEGs构建了预后模型，并通过两个测试数据集对该模型进行验证，结果显示其生存预测准确率具有显著统计学意义（p < 0.0025）。对年龄、性别、肿瘤分期等临床信息，以及肿瘤纯度、免疫评分等肿瘤特征与风险评分进行相关性分析，结果证实本研究构建的CAFs相关模型具有良好的稳定性与优异的预测性能。通过xCell进行细胞浸润分析发现，CAFs与巨噬细胞、树突状细胞等多种非特异性免疫细胞的相互作用，是影响免疫评分与预后的关键因素。最后，本研究基于构建的CAFs相关模型，分析了喜树碱（camptothecin）、多西他赛（docetaxel）、硼替佐米（bortezomib）等常见抗癌药物，以及抗PD-1治疗等免疫治疗手段在高低风险患者中的疗效差异。综上，本研究通过精细化分型的结肠癌成纤维细胞亚群，阐明了其与非特异性免疫细胞相互作用所产生的预后效应。