阿尔伯塔大学Sambasivarao Damaraju小组提出了癌症恶病质中人类骨骼肌的分子亚型。2025年9月10日出版的《自然》发表了这项成果。

基于亚型之间的差异表达，课题组人员确定了可能导致癌症相关的细胞质量和功能损失的生物学过程，包括转录后调节的改变和神经元系统的扰动；细胞因子风暴与细胞免疫反应；与细胞外基质相关的通路；代谢异常包括异种代谢、止血、信号转导、胚胎和/或多能干细胞以及氨基酸代谢。亚型之间的差异表达表明涉及多个相互交织的高阶基因调控网络，提示（hub）长链非编码RNAs、microRNAs和mRNAs的网络相互作用可能是未来研究的目标。

据悉，癌症相关的细胞萎缩与不良的临床结果有关，但其潜在的生物学原理在人类中很大程度上是未知的。使用无监督聚类方法对RNAome（编码和非编码RNA）进行无偏分析，主题整合非负矩阵分解提供了一种识别不同分子亚型的方法，并在此应用于结直肠癌或胰腺癌患者的细胞。对84例患者的直腹活检进行了高通量新一代测序。综合非负矩阵分解与严格的质量指标，以确定两个高度一致的分子亚型癌症患者的细胞。1型患者（与2型患者相比）表现出恶病质的临床表现：体重严重减轻，肌纤维质量低，IIA型和IIX型肌纤维萎缩，生存率降低。

附：英文原文

Title: Molecular subtypes of human skeletal muscle in cancer cachexia

Author: Bhatt, Bhumi J., Ghosh, Sunita, Mazurak, Vera, Brun, Aurlien Q., Bathe, Oliver, Baracos, Vickie E., Damaraju, Sambasivarao

Issue&Volume: 2025-09-10

Abstract: Cancer-associated muscle wasting is associated with poor clinical outcomes1, but its underlying biology is largely uncharted in humans2. Unbiased analysis of the RNAome (coding and non-coding RNAs) with unsupervised clustering using integrative non-negative matrix factorization3 provides a means of identifying distinct molecular subtypes and was applied here to muscle of patients with colorectal or pancreatic cancer. Rectus abdominis biopsies from 84 patients were profiled using high-throughput next-generation sequencing. Integrative non-negative matrix factorization with stringent quality metrics for clustering identified two highly coherent molecular subtypes within muscle of patients with cancer. Patients with subtype 1 (versus subtype 2) showed clinical manifestations of cachexia: high-grade weight loss, low muscle mass, atrophy of type IIA and type IIX muscle fibres, and reduced survival. On the basis of differential expression between the subtypes, we identified biological processes that may contribute to cancer-associated loss of muscle mass and function, including altered posttranscriptional regulation and perturbation of neuronal systems; cytokine storm and cellular immune response; pathways related to extracellular matrix; and metabolic abnormalities spanning xenobiotic metabolism, haemostasis, signal transduction, embryonic and/or pluripotent stem cells, and amino acid metabolism. Differential expression between subtypes indicated the involvement of multiple intertwined higher-order gene regulatory networks, suggesting that network interactions of (hub) long non-coding RNAs, microRNAs and mRNAs could represent targets for future research.

DOI: 10.1038/s41586-025-09502-0

Source: https://www.nature.com/articles/s41586-025-09502-0