PDF(Pubmed)
Abstract：
BACKGROUND: Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.
METHODS: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.
RESULTS: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).
CONCLUSIONS: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.
METHODS: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.
RESULTS: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).
CONCLUSIONS: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.
摘要：
背景：已提出共同癌症机制的表征以改善治疗策略和预后。这里,我们旨在鉴定多种实体癌的肿瘤微环境中共有的细胞-细胞相互作用(CCI),并评估其与癌症死亡率的相关性.
方法：通过NicheNet分析来自乳腺癌的单细胞RNA测序数据，结肠,肝脏,肺，和卵巢癌。这些CCI用于构建代表跨癌症的常见CCI的共享多细胞肿瘤模型(共享MCTM)。从shared-MCTM中鉴定出基因签名，并在两个大型独立队列中的mRNA和蛋白质水平上进行了测试：癌症基因组图谱（TCGA，22种癌症的9185个肿瘤样本和727个对照)和英国生物库(UKBB，10,384名癌症患者和5063名对照患者在17种癌症中具有蛋白质组学数据)。Cox比例风险模型用于评估签名与10年全因死亡率的关联。包括性别特异性分析。
结果：共有MCTM来源于5个个体癌症。从这种共享的MCTM和最突出的调节细胞类型中提取了共享的基因标签，基质癌相关成纤维细胞（mCAF）。在两个独立的群组中,与在mRNA和蛋白质水平上的对照相比,该标记在多种癌症中表现出显著的表达变化。重要的是,这与两个队列中癌症患者的死亡率显著相关.TCGA中的脑癌（HR[95CI]=6.90[4.64-10.25]）和UKBB中的卵巢癌（5.53[2.08-8.80]）的风险比最高。性别特异性分析揭示了不同的风险，与女性（1.84[1.44-2.37]）相比，男性（2.41[1.97-2.96]）与蛋白质签名评分相关的死亡风险更高。
结论：我们从代表不同癌症共同CCI的综合共享MCTM中鉴定了一个基因签名，并揭示了mCAF在肿瘤微环境中的调节作用。基因标签的致病性相关性得到了两个独立队列中mRNA和蛋白质水平的差异表达以及与死亡率的关联的支持。
方法：通过NicheNet分析来自乳腺癌的单细胞RNA测序数据，结肠,肝脏,肺，和卵巢癌。这些CCI用于构建代表跨癌症的常见CCI的共享多细胞肿瘤模型(共享MCTM)。从shared-MCTM中鉴定出基因签名，并在两个大型独立队列中的mRNA和蛋白质水平上进行了测试：癌症基因组图谱（TCGA，22种癌症的9185个肿瘤样本和727个对照)和英国生物库(UKBB，10,384名癌症患者和5063名对照患者在17种癌症中具有蛋白质组学数据)。Cox比例风险模型用于评估签名与10年全因死亡率的关联。包括性别特异性分析。
结果：共有MCTM来源于5个个体癌症。从这种共享的MCTM和最突出的调节细胞类型中提取了共享的基因标签，基质癌相关成纤维细胞（mCAF）。在两个独立的群组中,与在mRNA和蛋白质水平上的对照相比,该标记在多种癌症中表现出显著的表达变化。重要的是,这与两个队列中癌症患者的死亡率显著相关.TCGA中的脑癌（HR[95CI]=6.90[4.64-10.25]）和UKBB中的卵巢癌（5.53[2.08-8.80]）的风险比最高。性别特异性分析揭示了不同的风险，与女性（1.84[1.44-2.37]）相比，男性（2.41[1.97-2.96]）与蛋白质签名评分相关的死亡风险更高。
结论：我们从代表不同癌症共同CCI的综合共享MCTM中鉴定了一个基因签名，并揭示了mCAF在肿瘤微环境中的调节作用。基因标签的致病性相关性得到了两个独立队列中mRNA和蛋白质水平的差异表达以及与死亡率的关联的支持。
