Development and validation of a hypoxia-associated signature for lung adenocarcinoma.

Sci Rep

Translational Radiobiology Group, Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Christie NHS Foundation Trust Hospital, Manchester, M20 4BX, UK.

Published: January 2022

Hypoxia is common in non-small cell lung cancer (NSCLC) and an attractive therapeutic target. As hypoxia-targeting treatments are effective in patients with the most hypoxic tumours, we aimed to develop a lung adenocarcinoma (LUAD) hypoxia-related gene expression signature. RNAseq was used to identify genes significantly differentially expressed under hypoxia (1% O) in four LUAD cell lines. Identified genes were used for unsupervised clustering of a TCGA-LUAD training dataset (n = 252) and in a machine learning approach to build a hypoxia-related signature. Thirty-five genes were upregulated in common in three of the four lines and reduced in the training cohort to a 28-gene signature. The signature was prognostic in the TCGA training (HR 2.12, 95% CI 1.34-3.37, p = 0.0011) and test (n = 250; HR 2.13, 95% CI 1.32-3.45, p = 0.0016) datasets. The signature was prognostic for overall survival in a meta-analysis of nine other datasets (n = 1257; HR 2.08, 95% CI 1.60-2.70, p < 0.0001). The 28-gene LUAD hypoxia related signature can be taken forward for further validation using a suitable gene expression platform.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789914PMC
http://dx.doi.org/10.1038/s41598-022-05385-7DOI Listing

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