The prognostic value of hypoxia-inducible factor-1α in advanced cancer survivors: a meta-analysis with trial sequential analysis

Ther Adv Med Oncol. 2019 Sep 24:11:1758835919875851. doi: 10.1177/1758835919875851. eCollection 2019.

Abstract

Background: Expression of hypoxia-inducible factors (HIFs) has been observed, but their prognostic role in advanced cancers remains uncertain. We conducted a meta-analysis to establish the prognostic effect of HIFs and to better guide treatment planning for advanced cancers.

Methods: Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Trial sequential analysis (TSA) was also performed. The clinical outcomes included overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), relapse/recurrence-free survival (RFS), and metastasis-free survival (MFS) in patients with advanced tumors according to multivariate analysis.

Results: A total of 31 studies including 3453 cases who received chemotherapy, radiotherapy, or chemoradiotherapy were identified. Pooled analyses revealed that HIF-1α expression was correlated with worse OS (HR = 1.61, p < 0.001), DFS (HR = 1.61, p < 0.001), PFS (HR = 1.49, p = 0.01), CSS (HR = 1.65, p = 0.056), RFS (HR = 2.10, p = 0.015), or MFS (HR = 2.36, p = 0.002) in advanced cancers. HIF-1α expression was linked to shorter OS in the digestive tract, epithelial ovarian, breast, non-small cell lung, and clear cell renal cell carcinomas. Subgroup analysis by study region showed that HIF-1α expression was correlated with poor OS in Europeans and Asians, while an analysis by histologic subtypes found that HIF-1α expression was not associated with OS in squamous cell carcinoma. No relationship was found between HIF-2α expression and OS, DFS, PFS, or CSS.

Conclusions: Targeting HIF-1α may be a useful therapeutic approach to improve survival for advanced cancer patients. Based on TSA, more randomized controlled trials are strongly suggested.

Keywords: HIF-1α; HIF-2α; advanced cancer; multivariate analysis; prognosis; therapies.