Tumor Cell Total MRNA Expression Shapes the Molecular and Clinical Phenotype of Cancer

• Activity Number: 308 - Statistical Methods for Studying Spatial Transcriptomics, Tissue Heterogeneity, and Pleiotropy
• Type: Topic-Contributed
• Date/Time: Wednesday, August 11, 2021 : 3:30 PM to 5:20 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Shaolong Cao* and Jennifer Rui Wang and Shuangxi Ji and Peng Yang and Jonas Demeulemeester and Peter Van Loo and Wenyi Wang
• Companies: University of Texas MD Anderson Cancer Center and University of Texas MD Anderson Cancer Center and University of Texas MD Anderson Cancer Center and University of Texas MD Anderson Cancer Center and KU Leuven and The Francis Crick Institute and University of Texas MD Anderson Cancer Center
• Keywords: Tumor heterogeneity; Mathematical deconvolution; TCGA; Multi-region sampling; Single-cell RNA-sequencing; Prognostic marker

Abstract

Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content has not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we evaluated total mRNA expression using single cell sequencing, and developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data. We estimated and validated TmS in 5,205 patients across 15 cancer types identifying significant inter-individual 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 heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important clinical and biological implications.