Medical Digital Twin Research Group, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, Stockholm, Sweden.
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
J Transl Med. 2024 May 11;22(1):444. doi: 10.1186/s12967-024-05268-7.
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.
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.
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]).
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.
已经提出了对癌症机制的特征进行描述,以改善治疗策略和预后。在这里,我们旨在鉴定多个实体瘤中肿瘤微环境内的共享细胞-细胞相互作用(CCI),并评估其与癌症死亡率的关联。
通过对乳腺癌、结肠癌、肝癌、肺癌和卵巢癌的单细胞 RNA 测序数据进行 NicheNet 分析,鉴定每个癌症的 CCI。这些 CCI 用于构建代表癌症间共同 CCI 的共享多细胞肿瘤模型(共享-MCTM)。从共享-MCTM 中鉴定出一个基因特征,并在两个独立的大队列中进行 mRNA 和蛋白质水平的测试:癌症基因组图谱(TCGA,22 种癌症中 9185 个肿瘤样本和 727 个对照)和英国生物库(UKBB,17 种癌症中有 10384 名癌症患者和 5063 名对照有蛋白质组学数据)。Cox 比例风险模型用于评估特征与 10 年全因死亡率的关联,包括按性别进行的分析。
从五个独立的癌症中得出了一个共享-MCTM。从这个共享-MCTM 和最突出的调节细胞类型基质癌相关成纤维细胞(mCAF)中提取出一个共享基因特征。在两个独立的队列中,与对照组相比,该特征在多个癌症中在 mRNA 和蛋白质水平上均表现出显著的表达变化。重要的是,它在两个队列中的癌症患者中均与死亡率显著相关。在 TCGA 中,脑癌的最高危险比最高(HR [95%CI] = 6.90 [4.64-10.25]),而 UKBB 中卵巢癌的最高(5.53 [2.08-8.80])。按性别进行的分析显示出不同的风险,与女性(1.84 [1.44-2.37])相比,男性的蛋白特征评分与更高的死亡率风险相关(2.41 [1.97-2.96])。
我们从代表不同癌症中共同 CCI 的综合共享-MCTM 中鉴定出一个基因特征,并揭示了 mCAF 在肿瘤微环境中的调节作用。该基因特征的发病相关性在两个独立队列的 mRNA 和蛋白质水平上的差异表达和与死亡率的关联得到了支持。