Research Papers:
Validation of a hypoxia related gene signature in multiple soft tissue sarcoma cohorts
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Abstract
Lingjian Yang1, Laura Forker1, Joely J. Irlam1, Nischalan Pillay2,3, Ananya Choudhury1 and Catharine M. L. West1,4
1Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie Hospital, Manchester, UK
2Cancer Institute, University College London, London, UK
3Histopathology, Royal National Orthopaedic Hospital, Stanmore, UK
4NIHR Manchester Biomedical Research Centre, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
Correspondence to:
Catharine M. L. West, email: [email protected]
Keywords: soft tissue sarcoma; tumor hypoxia; gene expression signature; prognostic biomarker
Received: October 06, 2017 Accepted: November 13, 2017 Published: December 12, 2017
ABSTRACT
Purpose: There is a need for adjuvant/neo-adjuvant treatment strategies to prevent metastatic relapse in soft tissue sarcoma (STS). Tumor hypoxia is associated with a high-risk of metastasis and is potentially targetable. This study aimed to derive and validate a hypoxia mRNA signature for STS for future biomarker-driven trials of hypoxia targeted therapy.
Materials and Methods: RNA sequencing was used to identify seed genes induced by hypoxia in seven STS cell lines. Primary tumors in a training cohort (French training) were clustered into two phenotypes by seed gene expression and a de novo hypoxia signature derived. Prognostic significance of the de novo signature was evaluated in the training and two independent validation (French validation and The Cancer Genome Atlas) cohorts.
Results: 37 genes were up-regulated by hypoxia in all seven cell lines, and a 24-gene signature was derived. The high-hypoxia phenotype defined by the signature was enriched for well-established hypoxia genes reported in the literature. The signature was prognostic in univariable analysis, and in multivariable analysis in the training (n = 183, HR 2.16, P = 0.0054) and two independent validation (n = 127, HR 3.06, P = 0.0019; n = 258, HR 2.05, P = 0.0098) cohorts. Combining information from the de novo hypoxia signature and a genome instability signature significantly improved prognostication. Transcriptomic analyses showed high-hypoxia tumors had more genome instability and lower immune scores.
Conclusions: A 24-gene STS-specific hypoxia signature may be useful for prognostication and identifying patients for hypoxia-targeted therapy in clinical trials.
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