A miRNA signature predicts benefit from addition of hypoxia-modifying therapy to radiation treatment in invasive bladder cancer

From Springer Nature via Jisc Publications RouterHistory: received 2020-09-03, rev-recd 2021-02-11, accepted 2021-02-19, registration 2021-02-19, pub-electronic 2021-04-12, online 2021-04-12, pub-print 2021-07-06Publication status: PublishedFunder: U.S. Department of Defense (United States Department of Defense); doi: https://doi.org/10.13039/100000005; Grant(s): W81XWH-17-1-0543Abstract: Background: miRNAs are promising biomarkers in oncology as their small size makes them less susceptible to degradation than mRNA in FFPE tissue. We aimed to derive a hypoxia-associated miRNA signature for bladder cancer. Methods: Taqman miRNA array cards identified miRNA seed genes induced under hypoxia in bladder cancer cell lines. A signature was derived using feature selection methods in a TCGA BLCA training data set. miRNA expression data were generated for 190 tumours from the BCON Phase 3 trial and used for independent validation. Results: A 14-miRNA hypoxia signature was derived, which was prognostic for poorer overall survival in the TCGA BLCA cohort (n = 403, p = 0.001). Univariable analysis showed that the miRNA signature predicted an overall survival benefit from having carbogen–nicotinamide with radiotherapy (HR = 0.30, 95% CI 0.094–0.95, p = 0.030) and performed similarly to a 24-gene mRNA signature (HR = 0.47, 95% CI 0.24–0.92, p = 0.025). Combining the signatures improved performance (HR = 0.26, 95% CI 0.08–0.82, p = 0.014) with borderline significance for an interaction test (p = 0.065). The interaction test was significant for local relapse-free survival LRFS (p = 0.033). Conclusion: A 14-miRNA hypoxia signature can be used with an mRNA hypoxia signature to identify bladder cancer patients benefitting most from having carbogen and nicotinamide with radiotherapy

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

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(2)) 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