Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression
Menée à partir de données de séquençage d'ARNs messagers d'échantillons tumoraux d'origine humaine puis validée à partir de données du projet "The Cancer Genome Atlas" portant sur 6 590 patients, cette étude met en évidence une association entre l'estimation du niveau d'expression de l'ARN messager total de la tumeur et la progression de la maladie
Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene alteration and intra-tumor genetic heterogeneity as well as by pan-cancer trends in metabolic dysregulation. Taken together, our results indicate that measuring cell-type-specific total mRNA expression in tumor cells predicts tumor phenotypes and clinical outcomes.
Nature Biotechnology , article en libre accès, 2022