Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Nat Biotechnol. 2022 Nov;40(11):1624-1633. doi: 10.1038/s41587-022-01342-x. Epub 2022 Jun 13.
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.
单细胞 RNA 测序研究表明,总 mRNA 含量与肿瘤表型相关。然而,技术和分析上的挑战迄今为止阻碍了对总 mRNA 含量的大规模泛癌研究。在这里,我们提出了一种从批量测序数据中定量肿瘤特异性总 mRNA 表达(TmS)的方法,该方法考虑了通过转录组/基因组反卷积估计的肿瘤转录物比例、纯度和倍性。我们在 15 种癌症类型的 6590 名患者肿瘤中估计和验证了 TmS,发现了显著的肿瘤间变异性。在癌症中,高 TmS 与疾病进展和死亡风险增加相关。TmS 受到癌症特异性基因改变模式和肿瘤内遗传异质性以及代谢失调的泛癌趋势的影响。总之,我们的结果表明,测量肿瘤细胞中细胞类型特异性总 mRNA 表达可预测肿瘤表型和临床结果。