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Original Research

Open Access

Comprehensive analysis of hypoxia-related gene signature in cervical cancer

  • Tingting He1,2,†
  • Xiaoyu Tang1,†
  • Siru Chen3
  • Xin Chen1
  • Fuye Lin4
  • Minmin Yu5,*,
  • Changsong Lin4,*,

1Nanjing University of Chinese Medicine, 210023 Nanjing, Jiangsu, China

2Department of Gynecology, Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, 210022 Nanjing, Jiangsu, China

3Department of Traditional Chinese Medicine, The Affiliated Huai’an Hospital of Xuzhou Medical University and The Second People’s Hospital of Huai’an, 223002 Huai’an, Jiangsu, China

4Department of Bioinformatics, Nanjing Medical University, 211166 Nanjing, Jiangsu, China

5Department of Gynecology, Nanjing Hospital Affiliated to Nanjing University of Chinese Medicine, 210003 Nanjing, Jiangsu, China

DOI: 10.22514/ejgo.2023.105 Vol.44,Issue 6,December 2023 pp.105-121

Submitted: 14 July 2023 Accepted: 14 August 2023

Published: 15 December 2023

*Corresponding Author(s): Minmin Yu E-mail: njyy022@njucm.edu.cn
*Corresponding Author(s): Changsong Lin E-mail: lcs04bio@njmu.edu.cn

† These authors contributed equally.

Abstract

Hypoxia significantly influences the growth, metastasis and treatment resistance of cervical cancer (CC), thereby affecting patient prognosis. However, accurately predicting CC survival remains challenging, and the potential of hypoxia-related genes as prognostic markers remains uncertain. In this study, using CC single-cell transcriptional data from the Gene Expression Omnibus database, we employed the InferCNV package to identify tumor cells and used CellChat to confirm stronger intercellular interactions in tumor cells with high-hypoxia status. Next, we identified differentially expressed hypoxia-related genes (DEHLGs) by analyzing data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression, and Molecular Signature Database, which were further screened using univariate Cox regression and lasso regression analyses, based on which we constructed a hypoxia prognosis model comprising nine prognosis-related genes. Risk scores were generated using multivariate Cox regression analysis. The prognosis model revealed that the overall survival rate was higher in the low-risk than in the high-risk group. The model’s performance was assessed using the area under the time-dependent receiver operator characteristic curve, which yielded values of 0.836 and 0.804 for the training and test groups, respectively, indicating a robust prognostic capability of the model. A nomogram based on the nine hypoxia-related genes and training groups exhibited a favorable discriminatory ability for CC. Additionally, using CIBERSORT, we estimated the proportion of immune cells in patients with high- and low-hypoxia risk, revealing a higher proportion of macrophages (M0) and activated mast cells in the high-risk group. We successfully established a prognostic model for CC based on nine hypoxia-related genes to accurately predict the prognosis of affected patients.


Keywords

Hypoxia; Cervical cancer; Prognosis; Prediction; Gene signature


Cite and Share

Tingting He,Xiaoyu Tang,Siru Chen,Xin Chen,Fuye Lin,Minmin Yu,Changsong Lin. Comprehensive analysis of hypoxia-related gene signature in cervical cancer. European Journal of Gynaecological Oncology. 2023. 44(6);105-121.

References

[1] Small W, Bacon MA, Bajaj A, Chuang LT, Fisher BJ, Harkenrider MM, et al. Cervical cancer: a global health crisis. Cancer. 2017; 123: 2404–2412.

[2] Zhang XR, Li ZQ, Sun LX, Liu P, Li ZH, Li PF, et al. Cohort profile: Chinese cervical cancer clinical study. Frontiers in Oncology. 2021; 11: 690275.

[3] Belli C, Trapani D, Viale G, D’Amico P, Duso BA, Della Vigna P, et al. Targeting the microenvironment in solid tumors. Cancer Treatment Reviews. 2018; 65: 22–32.

[4] Cao G, Yue J, Ruan Y, Han Y, Zhi Y, Lu J, et al. Single-cell dissection of cervical cancer reveals key subsets of the tumor immune microenvironment. The EMBO Journal. 2023; 42: e110757.

[5] Mennerich D, Kubaichuk K, Kietzmann T. DUBs, hypoxia, and cancer. Trends in Cancer. 2019; 5: 632–653.

[6] Linge A, Löck S, Krenn C, Appold S, Lohaus F, Nowak A, et al. Independent validation of the prognostic value of cancer stem cell marker expression and hypoxia-induced gene expression for patients with locally advanced HNSCC after postoperative radiotherapy. Clinical and Translational Radiation Oncology. 2016; 1: 19–26.

[7] Xu H, Yuan Y, Wu W, Zhou M, Jiang Q, Niu L, et al. Hypoxia stimulates invasion and migration of human cervical cancer cell lines HeLa/SiHa through the Rab11 trafficking of integrin αvβ3/FAK/PI3K pathway-mediated Rac1 activation. Journal of Biosciences. 2017; 42: 491–499.

[8] Mustachio LM, Roszik J. Single-cell sequencing: current applications in precision onco-genomics and cancer therapeutics. Cancers. 2022; 14: 657.

[9] Hao Y, Hao S, Andersen-Nissen E, Mauck WM, Zheng S, Butler A, et al. Integrated analysis of multimodal single-cell data. Cell. 2021; 184: 3573–3587.e29.

[10] Aran D, Looney AP, Liu L, Wu E, Fong V, Hsu A, et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nature Immunology. 2019; 20: 163–172.

[11] Huang Q, Liu Y, Du Y, Garmire LX. Evaluation of cell type annotation R packages on single-cell RNA-seq data. Genomics, Proteomics & Bioinformatics. 2021; 19: 267–281.

[12] Aibar S, González-Blas CB, Moerman T, Huynh-Thu VA, Imrichova H, Hulselmans G, et al. SCENIC: single-cell regulatory network inference and clustering. Nature Methods. 2017; 14: 1083–1086.

[13] Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-Seq data. BMC Bioinformatics. 2013; 14: 7.

[14] Van de Sande B, Flerin C, Davie K, De Waegeneer M, Hulselmans G, Aibar S, et al. A scalable SCENIC workflow for single-cell gene regulatory network analysis. Nature Protocols. 2020; 15: 2247–2276.

[15] Yu G, Wang L, Han Y, He Q. ClusterProfiler: an R package for comparing biological themes among gene clusters. OMICS: A Journal of Integrative Biology. 2012; 16: 284–287.

[16] Jin S, Guerrero-Juarez CF, Zhang L, Chang I, Ramos R, Kuan CH, et al. Inference and analysis of cell-cell communication using CellChat. Nat Commun. 2021; 12: 1088.

[17] Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research. 2015; 43: e47.

[18] Ni J, Wang X, Stojanovic A, Zhang Q, Wincher M, Bühler L, et al. Single-Cell RNA sequencing of tumor-infiltrating NK cells reveals that inhibition of transcription factor HIF-1a unleashes NK cell activity. Immunity. 2020; 52: 1075–1087.e8.

[19] Wang Q, Guo X, Li L, Gao Z, Su X, Ji M, et al. N6-methyladenosine METTL3 promotes cervical cancer tumorigenesis and Warburg effect through YTHDF1/HK2 modification. Cell Death & Disease. 2020; 11: 911.

[20] Castelli S, Ciccarone F, Tavian D, Ciriolo MR. ROS-dependent HIF1a activation under forced lipid catabolism entails glycolysis and mitophagy as mediators of higher proliferation rate in cervical cancer cells. Journal of Experimental & Clinical Cancer Research. 2021; 40: 94.

[21] Zhu Y, Qiu Y, Zhang X. TKTL1 participated in malignant progression of cervical cancer cells via regulating AKT signal mediated PFKFB3 and thus regulating glycolysis. Cancer Cell International. 2021; 21: 678.

[22] Wen LJ, Hu XL, Li CY, Liu J, Li ZY, Li YZ, et al. Myosin 1b promotes migration, invasion and glycolysis in cervical cancer via ERK/HIF-1a pathway. American Journal of Translational Research. 2021; 13: 12536–12548.

[23] Xiong G, Stewart RL, Chen J, Gao T, Scott TL, Samayoa LM, et al. Collagen prolyl 4-hydroxylase 1 is essential for HIF-1a stabilization and TNBC chemoresistance. Nature Communications. 2018; 9: 4456.

[24] Zhou H, He Y, Li L, Wu C, Hu G. Overexpression of P4HA1 is correlated with poor survival and immune infiltrates in lung adenocarcinoma. BioMed Research International. 2020; 2020: 8024138.

[25] Shang X, Yuan B, Li J, Xi F, Mao J, Zhang C, et al. TGFBI is involved in the formation of polyploid cancer cells and the response to paclitaxel. Annals of Translational Medicine. 2021; 9: 693–693.

[26] Corona A, Blobe GC. The role of the extracellular matrix protein TGFBI in cancer. Cellular Signalling. 2021; 84: 110028.

[27] Fico F, Santamaria-Martínez A. TGFBI modulates tumour hypoxia and promotes breast cancer metastasis. Molecular Oncology. 2020; 14: 3198–3210.

[28] Yin R, Zhai X, Han H, Tong X, Li Y, Deng K. Characterizing the landscape of cervical squamous cell carcinoma immune microenvironment by integrating the single-cell transcriptomics and RNA-Seq. Immunity, Inflammation and Disease. 2022; 10: e608.

[29] Peng M, Yang D, Hou Y, Liu S, Zhao M, Qin Y, et al. Intracellular citrate accumulation by oxidized ATM-mediated metabolism reprogramming via PFKP and CS enhances hypoxic breast cancer cell invasion and metastasis. Cell Death & Disease. 2019; 10: 228.

[30] Shen J, Jin Z, Lv H, Jin K, Jonas K, Zhu C, et al. PFKP is highly expressed in lung cancer and regulates glucose metabolism. Cellular Oncology. 2020; 43: 617–629.

[31] Sha X, Wang K, Wang F, Zhang C, Yang L, Zhu X. Silencing PFKP restrains the stemness of hepatocellular carcinoma cells. Experimental Cell Research. 2021; 407: 112789.

[32] Sun G, Ni K. The role of cavin3 in the progression of lung cancer and its mechanism. BioMed Research International. 2020; 2020: 6364801.

[33] Chen L, Wu Q, Xu X, Yang C, You J, Chen F, et al. Cancer/testis antigen LDHC promotes proliferation and metastasis by activating the PI3K/Akt/GSK-3b-signaling pathway and the in lung adenocarcinoma. Experimental Cell Research. 2021; 398: 112414.

[34] Kuo YH, Chan TC, Lai HY, Chen TJ, Wu LC, Hsing CH, et al. Overexpression of pyruvate dehydrogenase kinase-3 predicts poor prognosis in urothelial carcinoma. Frontiers in Oncology. 2021; 11: 749142.

[35] Kurt B, Buendgens L, Wirtz TH, Loosen SH, Schulze-Hagen M, Truhn D, et al. Serum perilipin 2 (PLIN2) predicts multiple organ dysfunction in critically ill patients. Biomedicines. 2021; 9: 1210.

[36] Li K, Li J, Ye M, Jin X. The role of Siah2 in tumorigenesis and cancer therapy. Gene. 2022; 809: 146028.

[37] Nie C, Qin H, Zhang L. Identification and validation of a prognostic signature related to hypoxic tumor microenvironment in cervical cancer. PLOS ONE. 2022; 17: e0269462.

[38] Yang Y, Li Y, Qi R, Zhang L. Constructe a novel 5 hypoxia genes signature for cervical cancer. Cancer Cell International. 2021; 21: 345.

[39] Xie F, Dong D, Du N, Guo L, Ni W, Yuan H, et al. An 8‑gene signature predicts the prognosis of cervical cancer following radiotherapy. Molecular Medicine Reports. 2019; 20: 2990–3002.

[40] Mei J, Xing Y, Lv J, Gu D, Pan J, Zhang Y, et al. Construction of an immune-related gene signature for prediction of prognosis in patients with cervical cancer. International Immunopharmacology. 2020; 88: 106882.

[41] Nguyen NNY, Choi TG, Kim J, Jung MH, Ko SH, Shin Y, et al. A 70-gene signature for predicting treatment outcome in advanced-stage cervical cancer. Molecular Therapy—Oncolytics. 2020; 19: 47–56.


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