Quantification of hypoxia-related gene expression as a potential approach for clinical outcome prediction in breast cancer
Abstract : Breast cancers are solid tumors frequently characterized by regions with low oxygen concentrations. Cellular adaptations to hypoxia are mainly determined by " hypoxia inducible factors " that mediate transcriptional modifications involved in drug resistance and tumor progression leading to metastasis and relapse occurrence. In this study, we investigated the prognostic value of hypoxia-related gene expression in breast cancer. A systematic review was conducted to select a set of 45 genes involved in hypoxia signaling pathways and breast tumor progression. Gene expression was quantified by RT-qPCR in a retrospective series of 32 patients with invasive ductal carcinoma. Data were analyzed in relation to classical clinicopathological criteria and relapse occurrence. Coordinated overexpression of selected genes was observed in high-grade and HER2+ tumors. Hierarchical cluster analysis of gene expression significantly segregated relapsed patients (p = 0.008, Chi 2 test). All genes (except one) were up-regulated and six markers were significantly expressed in tumors from recurrent patients. The expression of this 6-gene set was used to develop a basic algorithm for identifying recurrent patients according to a risk score of relapse. Analysis of Kaplan-Meier relapse-free survival curves allowed the definition of a threshold score of 2 (p = 0.021, Mantel-Haenszel test). The risk of recurrence was increased by 40% in patients with a high score. In addition to classical prognostic factors, we showed that hyp-oxic markers have potential prognostic value for outcome and late recurrence prediction, leading to improved treatment decision-making for patients with early-stage invasive breast cancer. It will be necessary to validate the clinical relevance of this prognostic approach through independent studies including larger prospective patient cohorts.
Cited literature [33 references]
https://hal.uca.fr/hal-01652849
Contributor : Maud Privat <>
Submitted on : Thursday, November 30, 2017 - 5:39:08 PM
Last modification on : Wednesday, March 4, 2020 - 11:26:01 AM
Contributor : Maud Privat <>
Submitted on : Thursday, November 30, 2017 - 5:39:08 PM
Last modification on : Wednesday, March 4, 2020 - 11:26:01 AM
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ElGuerrab, Plos One, 2017.pdf
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