转移性肿瘤中转录异质性的泛癌全景

Metastasis, the spread of cancer from its original site to distant organs, is the leading cause of cancer-related mortality. A deeper understanding of the molecular mechanisms underlying metastatic progression is therefore of critical clinical importance. The availability of large-scale pan-cancer bulk RNA-seq datasets from both primary and metastatic tumors provides a unique opportunity to investigate the shared and distinct transcriptional features of metastasis. Furthermore, this creates an unprecedented opportunity to perform systematic analyses across metastatic tumors from diverse cancer types.However, our initial pan-cancer analysis demonstrated that several major confounding factors,most notably strong tissue background signals in metastatic samples, pose significant challenges for accurately comparing primary and metastatic tumors. We have previously established effective strategies to adjust for immune and stromal components in bulk transcriptomic data. Building on this foundation, we have recently extended our approach to address a key obstacle in studying metastasis: the overwhelming influence of tissue-of-origin signals at metastatic sites.To evaluate our method, we first performed in silico simulations of normal-tissue background correction using TCGA pan-cancer RNA-seq data. We further generated pseudo-bulk profiles from single-cell RNA-seq datasets spanning multiple cancer types, each exhibiting varying degrees of background tissue contamination. Across these datasets, our analyses demonstrate that this approach effectively removes confounding signals, thereby enabling more accurate transcriptomic comparisons between primary and metastatic tumors. Application of this method to large pan-cancer bulk RNA-seq cohorts revealed promising and novel biological insights, including both shared and cancer-type-specific transcriptional programs associated with metastatic progression.Our preliminary analysis indicates that multiple hallmark pathways, including oxidative phosphorylation and epithelial-mesenchymal transition (EMT), are broadly upregulated across metastatic tumors in pan-cancer datasets. In addition, we observe pronounced immunosuppressive signaling within the tumor microenvironment of metastatic lesions, suggesting that metabolic rewiring and immune evasion are coordinated features of metastatic disease.