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

Shaolong Cao; Jennifer R. Wang; Shuangxi Ji; Peng Yang; Yaoyi Dai; Shuai Guo; Matthew D. Montierth; John Paul Shen; Xiao Zhao; Jingxiao Chen; Jaewon James Lee; Paola A. Guerrero; Nicholas Spetsieris; Nikolai Engedal; Sinja Taavitsainen; Kaixian Yu; Julie Livingstone; Vinayak Bhandari; Shawna M. Hubert; Najat C. Daw; P. Andrew Futreal; Eleni Efstathiou; Bora Lim; Andrea Viale; Jianjun Zhang; Matti Nykter; Bogdan A. Czerniak; Powel H. Brown; Charles Swanton; Pavlos Msaouel; Anirban Maitra; Scott Kopetz; Peter Campbell; Terence P. Speed; Paul C. Boutros; Hongtu Zhu; Alfonso Urbanucci; Jonas Demeulemeester; Peter Van Loo; Wenyi Wang

doi:10.1038/s41587-022-01342-x

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

Shaolong Cao, Jennifer R. Wang, Shuangxi Ji, Peng Yang, Yaoyi Dai, Shuai Guo, Matthew D. Montierth, John Paul Shen, Xiao Zhao, Jingxiao Chen, Jaewon James Lee, Paola A. Guerrero, Nicholas Spetsieris, Nikolai Engedal, Sinja Taavitsainen, Kaixian Yu, Julie Livingstone, Vinayak Bhandari, Shawna M. Hubert, Najat C. DawP. Andrew Futreal, Eleni Efstathiou, Bora Lim, Andrea Viale, Jianjun Zhang, Matti Nykter, Bogdan A. Czerniak, Powel H. Brown, Charles Swanton, Pavlos Msaouel, Anirban Maitra, Scott Kopetz, Peter Campbell, Terence P. Speed, Paul C. Boutros, Hongtu Zhu, Alfonso Urbanucci, Jonas Demeulemeester, Peter Van Loo, Wenyi Wang

Research output: Contribution to journal › Article › peer-review

25 Scopus citations

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.

Original language	English (US)
Pages (from-to)	1624-1633
Number of pages	10
Journal	Nature biotechnology
Volume	40
Issue number	11
DOIs	https://doi.org/10.1038/s41587-022-01342-x
State	Published - Nov 2022

ASJC Scopus subject areas

Biotechnology
Bioengineering
Biomedical Engineering
Applied Microbiology and Biotechnology
Molecular Medicine

MD Anderson CCSG core facilities

Biostatistics Resource Group
Tissue Biospecimen and Pathology Resource
Bioinformatics Shared Resource

Access to Document

10.1038/s41587-022-01342-x

Cite this

Cao, S., Wang, J. R., Ji, S., Yang, P., Dai, Y., Guo, S., Montierth, M. D., Shen, J. P., Zhao, X., Chen, J., Lee, J. J., Guerrero, P. A., Spetsieris, N., Engedal, N., Taavitsainen, S., Yu, K., Livingstone, J., Bhandari, V., Hubert, S. M., ... Wang, W. (2022). Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression. Nature biotechnology, 40(11), 1624-1633. https://doi.org/10.1038/s41587-022-01342-x

Cao, S, Wang, JR, Ji, S, Yang, P, Dai, Y, Guo, S, Montierth, MD, Shen, JP , Zhao, X, Chen, J, Lee, JJ, Guerrero, PA, Spetsieris, N, Engedal, N, Taavitsainen, S, Yu, K, Livingstone, J, Bhandari, V, Hubert, SM, Daw, NC , Futreal, PA, Efstathiou, E, Lim, B , Viale, A , Zhang, J, Nykter, M, Czerniak, BA, Brown, PH, Swanton, C, Msaouel, P , Maitra, A , Kopetz, S, Campbell, P, Speed, TP, Boutros, PC, Zhu, H, Urbanucci, A, Demeulemeester, J, Van Loo, P & Wang, W 2022, 'Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression', Nature biotechnology, vol. 40, no. 11, pp. 1624-1633. https://doi.org/10.1038/s41587-022-01342-x

@article{53837ef7eb944332a21177a941d305b7,

title = "Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression",

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.",

author = "Shaolong Cao and Wang, {Jennifer R.} and Shuangxi Ji and Peng Yang and Yaoyi Dai and Shuai Guo and Montierth, {Matthew D.} and Shen, {John Paul} and Xiao Zhao and Jingxiao Chen and Lee, {Jaewon James} and Guerrero, {Paola A.} and Nicholas Spetsieris and Nikolai Engedal and Sinja Taavitsainen and Kaixian Yu and Julie Livingstone and Vinayak Bhandari and Hubert, {Shawna M.} and Daw, {Najat C.} and Futreal, {P. Andrew} and Eleni Efstathiou and Bora Lim and Andrea Viale and Jianjun Zhang and Matti Nykter and Czerniak, {Bogdan A.} and Brown, {Powel H.} and Charles Swanton and Pavlos Msaouel and Anirban Maitra and Scott Kopetz and Peter Campbell and Speed, {Terence P.} and Boutros, {Paul C.} and Hongtu Zhu and Alfonso Urbanucci and Jonas Demeulemeester and {Van Loo}, Peter and Wenyi Wang",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = nov,

doi = "10.1038/s41587-022-01342-x",

language = "English (US)",

volume = "40",

pages = "1624--1633",

journal = "Nature biotechnology",

issn = "1087-0156",

publisher = "Nature Publishing Group",

number = "11",

}

TY - JOUR

T1 - Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression

AU - Cao, Shaolong

AU - Wang, Jennifer R.

AU - Ji, Shuangxi

AU - Yang, Peng

AU - Dai, Yaoyi

AU - Guo, Shuai

AU - Montierth, Matthew D.

AU - Shen, John Paul

AU - Zhao, Xiao

AU - Chen, Jingxiao

AU - Lee, Jaewon James

AU - Guerrero, Paola A.

AU - Spetsieris, Nicholas

AU - Engedal, Nikolai

AU - Taavitsainen, Sinja

AU - Yu, Kaixian

AU - Livingstone, Julie

AU - Bhandari, Vinayak

AU - Hubert, Shawna M.

AU - Daw, Najat C.

AU - Futreal, P. Andrew

AU - Efstathiou, Eleni

AU - Lim, Bora

AU - Viale, Andrea

AU - Zhang, Jianjun

AU - Nykter, Matti

AU - Czerniak, Bogdan A.

AU - Brown, Powel H.

AU - Swanton, Charles

AU - Msaouel, Pavlos

AU - Maitra, Anirban

AU - Kopetz, Scott

AU - Campbell, Peter

AU - Speed, Terence P.

AU - Boutros, Paul C.

AU - Zhu, Hongtu

AU - Urbanucci, Alfonso

AU - Demeulemeester, Jonas

AU - Van Loo, Peter

AU - Wang, Wenyi

PY - 2022/11

Y1 - 2022/11

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85131877909&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85131877909&partnerID=8YFLogxK

U2 - 10.1038/s41587-022-01342-x

DO - 10.1038/s41587-022-01342-x

M3 - Article

C2 - 35697807

AN - SCOPUS:85131877909

SN - 1087-0156

VL - 40

SP - 1624

EP - 1633

JO - Nature biotechnology

JF - Nature biotechnology

IS - 11

ER -

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

Abstract

ASJC Scopus subject areas

MD Anderson CCSG core facilities

Access to Document

Other files and links

Fingerprint

Cite this