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Nat Med. 2019 Oct 7. doi: 10.1038/s41591-019-0595-z. [Epub ahead of print]

A clonal expression biomarker associates with lung cancer mortality.

Author information

1
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, Paul O'Gorman Building, London, UK.
2
Bill Lyons Informatics Centre, University College London Cancer Institute, Paul O'Gorman Building, London, UK.
3
Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK.
4
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, Paul O'Gorman Building, London, UK. nbirkbak@clin.au.dk.
5
Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK. nbirkbak@clin.au.dk.
6
Department of Molecular Medicine, Aarhus University, Aarhus, Denmark. nbirkbak@clin.au.dk.
7
Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. nbirkbak@clin.au.dk.
8
Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Budapest, Hungary.
9
Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK.
10
Danish Cancer Society Research Center, Copenhagen, Denmark.
11
Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
12
Genomics Equipment Park, The Francis Crick Institute, London, UK.
13
Department of Tumor Biology, National Korányi Institute of Pulmonology, Semmelweis University, Budapest, Hungary.
14
Division of Thoracic Surgery, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.
15
Department of Thoracic Surgery, National Institute of Oncology, Semmelweis University, Budapest, Hungary.
16
Department of Pathology, National Korányi Institute of Pulmonology, Semmelweis University, Budapest, Hungary.
17
Department of Pathology, National Institute of Oncology, Budapest, Hungary.
18
Lund University, Laboratory Medicine Region Skåne, Department of Clinical Sciences Lund, Pathology, Lund, Sweden.
19
Department of Pathology, UCL Cancer Institute, London, UK.
20
Department of Oncology and Radiotherapy, Medical University of Gdansk, Gdansk, Poland.
21
SE-NAP Brain Metastasis Research Group, 2nd Department of Pathology, Semmelweis University, Budapest, Hungary.
22
Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, MI, USA.
23
Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
24
Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, USA.
25
Department of Urology, University of Michigan, Ann Arbor, MI, USA.
26
Howard Hughes Medical Institute, University of Michigan, Ann Arbor, MI, USA.
27
Cancer Research UK & University College London Cancer Trials Centre, University College London, London, UK.
28
Department of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden.
29
Computational Health Informatics Program, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
30
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, Paul O'Gorman Building, London, UK. nicholas.mcgranahan.10@ucl.ac.uk.
31
Cancer Genome Evolution Research Group, University College London Cancer Institute, University College London, London, UK. nicholas.mcgranahan.10@ucl.ac.uk.
32
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, Paul O'Gorman Building, London, UK. charles.swanton@crick.ac.uk.
33
Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute, London, UK. charles.swanton@crick.ac.uk.

Abstract

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage1. Transcriptomic intratumor heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types2-6. Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types.

PMID:
31591602
DOI:
10.1038/s41591-019-0595-z

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