A clonal expression biomarker associates with lung cancer mortality
Authors listDhruva Biswas Nicolai Birkbak Rachel Rosenthal Crispin T Hiley Emilia Lim Krisztian Papp Stefan Boeing Marcin Krzystanek Dijana Djureinovic Linnea La Fleur Maria Greco Balázs Döme János Fillinger Hans Brunnström Yin Wu David A Moore Marcin Skrzypski Christopher Abbosh Kevin Litchfield Maise Al Bakir Tom Watkins Selvaraju Veeriah Gareth Wilson Mariam Jamal-Hanjani Judit Moldvay Johan Botling Arul M Chinnaiyan Patrick Micke Allan Hackshaw Jiri Bartek Istvan Csabai Zoltan Szallasi Javier Herrero Nicholas McGranahan Charles Swanton TRACERx Consortium
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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.
Journal Nature Medicine
Issue number 10