Jennifer Rui Wang

Tumor cell total mRNA expression shapes the molecular and clinical phenotype of cancer

Publisher: Cold Spring Harbor Laboratory

Date: 02-10-2020

DOI: 10.1101/2020.09.30.306795

Abstract: Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content have not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data, which performs transcriptomic deconvolution while adjusting for mixed genomes. We used single-cell RNA sequencing data to demonstrate total mRNA expression as a feature of tumor phenotype. We estimated and validated TmS in 5,015 patients across 15 cancer types identifying significant inter-in idual variability. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Cancer type-specific patterns of genetic alterations, intra-tumor genetic heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring cell-type specific total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important biological and clinical implications.

Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression

Publisher: Springer Science and Business Media LLC

Date: 13-06-2022

DOI: 10.1038/S41587-022-01342-X

Abstract: 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.

The University Of Texas MD Anderson Cancer Center

Location: United States of America

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Johns Hopkins University

Location: United States of America

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University Of Toronto

Location: No location found

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University Of Texas MD Anderson Cancer Center

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Johns Hopkins Bloomberg School Of Public Health

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Johns Hopkins Bloomberg School Of Public Health

Location: United States of America

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University Of Toronto

Location: Canada

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