Abstract

BackgroundHypoxia, which affects the development, metastasis and prognosis of cancer, represents a key feature of cancer. This study describe a hypoxia risk factor model, with predicting the prognosis of cervical cancer.MethodsBased on hypoxia pathway related genes, we divided cervical cancer samples into high and low expression groups. A cox analysis was then performed. Genes from these cervical cancer samples showing a significant impact on OS were selected for cluster analysis to obtain two subtypes. The TPM dataset of TCGA was divided into training and validation sets. For the training set, a lasso analysis was conducted as based on cox analysis of meaningful genes and a risk factor model was constructed. The constructed model was verified in internal and external data sets. Finally, RT-PCR, immunohistochemistry were used to detect the expression of relative genes or proteins and functional assays were used to evaluate the biological function of signature genes.ResultsTwo molecular subtypes were obtained, Cluster2 vs Cluster1.These subtypes were obtained by clustering with a total of 149 DEGs (Differential expressed genes) being in line with this standard, of which 27 were up-regulated and 122 were down-regulated. The five genes with lambda = 0.0571 were selected to construct the model, the RiskScore = AK4*0.042 + HK2*0.021 + P4HA1*0.22 + TGFBI*0.1 + VEGFA*0.077. Further, in order to verify the signature, we used TCGA-test and GSE44001 chip datasets to test, and finally got a good risk prediction effect in those datasets. Moreover, the result of RT-PCR and immunohistochemistry demonstrated that AK4, HK2, P4HA1, TGFBI and VEGFA were all highly expressed in these cervical cancer tissue samples. The functional study shown that expression of AK4, HK2, P4HA1, TGFBI and VEGFA can regulate the proliferation, migration, and invasion ability of cervical cancer cells in vitro.ConclusionsIn summary, we developed a 5-gene signature prognostic hierarchical system based on the hypoxic pathway of cervical cancer, which is independent of clinical characteristics. And also conducted experimental verifications on these signature gene. Therefore, we propose that use of this classifier as a molecular diagnostic test can provide an effective means for evaluating the prognostic risk of cervical cancer patients, and provide potential targets for the treatment of cervical cancer patients.

Highlights

  • Hypoxia, which affects the development, metastasis and prognosis of cancer, represents a key feature of cancer

  • The The Cancer Genome Atlas (TCGA)-TPM data of cervical cancer samples were divided into high and low expression groups according to the median of gene expression and a cox analysis as based on overall survival (OS) was conducted

  • We found that Adenylate kinase 4 (AK4), Hexokinase 2 (HK2), Proline 4-hydroxylase subunit α-1 (P4HA1), TGFBI and Vascular endothelial growth factor A (VEGFA) were associated with high gene expressions and a high risk related factor, results which were consistent with TCGA training set performance findings

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Summary

Introduction

Hypoxia, which affects the development, metastasis and prognosis of cancer, represents a key feature of cancer. This study describe a hypoxia risk factor model, with predicting the prognosis of cervical cancer. Yang et al Cancer Cell Int (2021) 21:345 cancer, with poor prognosis in developing countries [3, 4]. For women with metastatic or recurrent diseases, the overall prognosis remains poor [9]. As the prognosis of cervical cancer varies markedly as a function of patient’s genetic heterogeneity, it is clear that the identification of effective genetic biomarkers would significantly enhance the capacity to predict the prognosis of this condition [10,11,12]

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