Volume 27, Issue 1 (1-2023)                   IBJ 2023, 27(1): 23-33 | Back to browse issues page

PMID: 36624663

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Background: Hypoxic tumor microenvironment is one of the important impediments for conventional cancer therapy. This study aimed to computationally identify hypoxia-related messenger RNA (mRNA) signatures in nine hypoxic-conditioned cancer cell lines and investigate their role during hypoxia.
Methods: Nine RNA sequencing (RNA-Seq) expression data sets were retrieved from the Gene Expression Omnibus database. Dierentially expressed genes (DEGs) were identified in each cancer cell line. Then 23 common DEGs were selected by comparing the gene lists across the nine cancer cell lines. Reverse transcription-quantitative PCR (qRT-PCR) was performed to validate the identified DEGs. 
Results: By comparing the data sets, GAPDH, LRP1, ALDOA, EFEMP2, PLOD2, CA9, EGLN3, HK, PDK1, KDM3A, UBC, and P4HA1 were identified as hub genes. In addition, miR-335-5p, miR-122-5p, miR-6807-5p, miR-1915-3p, miR-6764-5p, miR-92-3p, miR-23b-3p, miR-615-3p, miR-124-3p, miR-484, and miR-455-3p were determined as common micro RNAs. Four DEGs were selected for mRNA expression validation in cancer cells under normoxic and hypoxic conditions with qRT-PCR. The results also showed that the expression levels determined by qRT-PCR were consistent with RNA-Seq data.
Conclusion: The identified protein-protein interaction network of common DEGs could serve as potential hypoxia biomarkers and might be helpful for improving therapeutic strategies.
Keywords: Hypoxia, MicroRNA, RNAseq

1. Jing X, Yang F, Shao C, Wei K, Xie M, Shen H, Shu Y. Role of hypoxia in cancer therapy by regulating the tumor microenvironment. Molecular cancer 2019; 18(1): 157. [DOI:10.1186/s12943-019-1089-9]
2. Challapalli A, Carroll L, Aboagye EO. Molecular mechanisms of hypoxia in cancer. Clinical and translational imaging 2017; 5(3): 225-253. [DOI:10.1007/s40336-017-0231-1]
3. Makhijani RK, Raut SA, Purohit HJ. Identification of common key genes in breast, lung and prostate cancer and exploration of their heterogeneous expression. Oncology letters 2018; 15(2): 1680-1690. [DOI:10.3892/ol.2017.7508]
4. Kulshrestha A, Suman S, Ranjan R. Network analysis reveals potential markers for pediatric adrenocortical carcinoma. Oncotargets and therapy 2016; 9: 4569-4581. [DOI:10.2147/OTT.S108485]
5. Mao Y, Nie Q, Yang Y, Mao G. Identification of co‑expression modules and hub genes of retinoblastoma via co‑expression analysis and protein‑protein interaction networks. Molecular medicine reports 2020; 22(2): 1155-1168. [DOI:10.3892/mmr.2020.11189]
6. Mirabelli P, Coppola L, Salvatore M. Cancer cell lines are useful model systems for medical rsearch. Cancers (Basel). 2019; 11(8): 1098. [DOI:10.3390/cancers11081098]
7. Oliveto S, Mancino M, Manfrini N, Biffo S. Role of microRNAs in translation regulation and cancer. World journal of biological chemistry 2017; 8(1): 45-56. [DOI:10.4331/wjbc.v8.i1.45]
8. Kulshreshtha R, Ferracin M, Wojcik SE, Garzon R, Alder H, Agosto-Perez FJ, Davuluri R, Liu CG, Croce CM, Negrini M, Calin GA, Ivan M. A microRNA signature of hypoxia. Molecular and cellular biology 2007; 27(5): 1859-1867. [DOI:10.1128/MCB.01395-06]
9. Lan H, Lu H, Wang X, Jin H. MicroRNAs as Potential Biomarkers in Cancer: Opportunities and challenges. BioMed research international 2015; 2015: 125094. [DOI:10.1155/2015/125094]
10. Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000research 2015; 4: 1521. [DOI:10.12688/f1000research.7563.1]
11. Conway JR, Lex A, Gehlenborg N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics 2017; 33(18): 2938-2940. [DOI:10.1093/bioinformatics/btx364]
12. Li Z, Zhao K, Tian H. Integrated analysis of differential expression and alternative splicing of non-small cell lung cancer based on RNA sequencing. Oncology letters 2017; 14(2): 1519-1525. [DOI:10.3892/ol.2017.6300]
13. Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S, Hub W, Presence Working Group. AmiGO: online access to ontology and annotation data. Bioinformatics 2009; 25(2): 288-289. [DOI:10.1093/bioinformatics/btn615]
14. Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y. KEGG for linking genomes to life and the environment. Nucleic acids research 2008; 36(Database issue): D480-484. [DOI:10.1093/nar/gkm882]
15. Mi H, Muruganujan A, Thomas PD. PANTHER in 2013: modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic acids research 2013; 41(Database issue): D377-386. [DOI:10.1093/nar/gks1118]
16. Xia J, Gill EE, Hancock REW. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data. Nature protocols 2015;10(6):823-44. [DOI:10.1038/nprot.2015.052]
17. Chen SJ, Liao DL, Chen CH, Wang TY, Chen KC. Construction and analysis of protein-protein interaction network of heroin use disorder. Scientific reports 2019; 9(1): 4980. [DOI:10.1038/s41598-019-41552-z]
18. Soofi A, Taghizadeh M, Tabatabaei SM, Rezaei Tavirani M, Shakib H, Namaki S, Safari Alighiarloo N. Centrality analysis of protein-protein interaction networks and molecular docking prioritize potential drug-targets in type 1 diabetes. Iranian journal of pharmaceutical research 2020; 19(4): 121-134.
19. Li CY, Cai JH, Tsai JJP, Wang CCN. Identification of hub genes associated with development of head and neck squamous cell carcinoma by integrated bioinformatics analysis. Frontiers in oncology 2020; 10: 681. [DOI:10.3389/fonc.2020.00681]
20. Hsu SD, Lin FM, Wu WY, Liang C, Huang WC, Chan WL, Tsai WT, Chen GZ, Lee CJ, Chiu CM, Chien CH, Wu NH, Huang CY, Tsou AP, Huang HD. miRTarBase: a database curates experimentally validated microRNA-target interactions. Nucleic acids research 2011; 39(Database issue): D163-169. [DOI:10.1093/nar/gkq1107]
21. Sethupathy P, Corda B, Hatzigeorgiou AG. TarBase: A comprehensive database of experimentally supported animal microRNA targets. RNA 2006; 12(2): 192-197. [DOI:10.1261/rna.2239606]
22. Shayan S, Arashkia A, Bahramali G, Abdoli A, Nosrati MSS, Azadmanesh K. Cell type-specific response of colon cancer tumor cell lines to oncolytic HSV-1 virotherapy in hypoxia. Cancer cell international 2022; 22(1): 164. [DOI:10.1186/s12935-022-02564-4]
23. Bakhashab S, Lary S, Ahmed F, Schulten HJ, Bashir A, Ahmed FW, Al-Malki AL, Jamal HS, Gari MA, Weaver JU. Reference genes for expression studies in hypoxia and hyperglycemia models in human umbilical vein endothelial cells. G3 (Bethesda, Md) 2014; 4(11): 2159-2165. [DOI:10.1534/g3.114.013102]
24. Si W, Shen J, Zheng H, Fan W. The role and mechanisms of action of microRNAs in cancer drug resistance. Clinical epigenetics 2019; 11(1): 25. [DOI:10.1186/s13148-018-0587-8]
25. He X, Zhang J. Why Do Hubs Tend to Be Essential in Protein Networks? PLOS genetics 2006; 2(6): e88. [DOI:10.1371/journal.pgen.0020088]
26. Ardila DC, Aggarwal V, Singh M, Chattopadhyay A, Chaparala S, Sant S. Identifying molecular signatures of distinct modes of collective migration in response to the microenvironment using three-dimensional breast cancer models. Cancers (Basel) 2021; 13(6). 1429. [DOI:10.3390/cancers13061429]
27. Cal R, Castellano J, Revuelta-López E, Aledo R, Barriga M, Farré J, Vilahur G, Nasarre L, Hove-Madsen L, Badimon L, Llorente-Cortés V. Low-density lipoprotein receptor-related protein 1 mediates hypoxia-induced very low density lipoprotein-cholesteryl ester uptake and accumulation in cardiomyocytes. Cardiovascular research 2012; 94(3): 469-479. [DOI:10.1093/cvr/cvs136]
28. Koslowski M, Luxemburger U, Türeci Ö, Sahin U. Tumor-associated CpG demethylation augments hypoxia-induced effects by positive autoregulation of HIF-1α. Oncogene 2011; 30(7): 876-882. [DOI:10.1038/onc.2010.481]
29. Liberti MV, Locasale JW. The warburg effect: how does it benefit cancer cells? Trends in biochemical sciences 2016; 41(3): 211-218. [DOI:10.1016/j.tibs.2015.12.001]
30. Seki SM, Gaultier A. Exploring non-metabolic functions of glycolytic enzymes in immunity. Frontiers in immunology 2017; 8: 1549. [DOI:10.3389/fimmu.2017.01549]
31. Jacquin MA, Chiche J, Zunino B, Bénéteau M, Meynet O, Pradelli LA, Marchetti S, Cornille A, Carles M, Ricci JE. GAPDH binds to active Akt, leading to Bcl-xL increase and escape from caspase-independent cell death. Cell death and differentiation 2013; 20(8): 1043-1054. [DOI:10.1038/cdd.2013.32]
32. Chiche J, Pommier S, Beneteau M, Mondragón L, Meynet O, Zunino B, Mouchotte A, Verhoeyen E, Guyot M, Pagès G, Mounier N, Imbert V, Colosetti P, Goncalvès D, Marchetti S, Brière J, Carles M, Thieblemont C, Ricci JE. GAPDH enhances the aggressiveness and the vascularization of non-Hodgkin's B lymphomas via NF-κB-dependent induction of HIF-1α. Leukemia 2015; 29(5): 1163-1176. [DOI:10.1038/leu.2014.324]
33. Demarse NA, Ponnusamy S, Spicer EK, Apohan E, Baatz JE, Ogretmen B, Davies C. Direct binding of glyceraldehyde 3-phosphate dehydrogenase to telomeric DNA protects telomeres against chemotherapy-induced rapid degradation. Journal of molecular biology 2009; 394(4): 789-803. [DOI:10.1016/j.jmb.2009.09.062]
34. Chang YC, Chan YC, Chang WM, Lin YF, Yang CJ, Su CY, Huang MS, T H Wu A, Hsiao M. Feedback regulation of ALDOA activates the HIF-1α/MMP9 axis to promote lung cancer progression. Cancer letters 2017; 403: 28-36. [DOI:10.1016/j.canlet.2017.06.001]
35. Saito Y, Takasawa A, Takasawa K, Aoyama T, Akimoto T, Ota M, Magara K, Murata M, Hirohashi Y, Hasegawa T, Sawada N, Saito T, Osanai M. Aldolase A promotes epithelial-mesenchymal transition to increase malignant potentials of cervical adenocarcinoma. Cancer science 2020; 111(8): 3071-3081. [DOI:10.1111/cas.14524]
36. Du J, Yang M, Chen S, Li D, Chang Z, Dong Z. PDK1 promotes tumor growth and metastasis in a spontaneous breast cancer model. Oncogene 2016; 35(25): 3314-3323. [DOI:10.1038/onc.2015.393]
37. Siu MKY, Jiang Y-x, Wang J-j, Leung THY, Ngu SF, Cheung ANY, Ngan HYS, Chan KKL. PDK1 promotes ovarian cancer metastasis by modulating tumor-mesothelial adhesion, invasion, and angiogenesis via α5β1 integrin and JNK/IL-8 signaling. Oncogenesis 2020; 9(2): 24. [DOI:10.1038/s41389-020-0209-0]
38. Kim JW, Tchernyshyov I, Semenza GL, Dang CV. HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell metabolism 2006; 3(3): 177-185. [DOI:10.1016/j.cmet.2006.02.002]
39. Gibadulinova A, Bullova P, Strnad H, Pohlodek K, Jurkovicova D, Takacova M, Pastorekova S, Svastova E. CAIX-Mediated control of LIN28/let-7 axis contributes to metabolic adaptation of breast cancer cells to hypoxia. International journal of molecular sciences 2020; 21(12): 4299. [DOI:10.3390/ijms21124299]
40. Du W, Liu N, Zhang Y, Liu X, Yang Y, Chen W, He Y. PLOD2 promotes aerobic glycolysis and cell progression in colorectal cancer by upregulating HK2. Biochemistry and cell biology 2020; 98(3): 386-395. [DOI:10.1139/bcb-2019-0256]
41. Zhang P, Yang X, Wang L, Zhang D, Luo Q, Wang B. Overexpressing miR‑335 inhibits DU145 cell proliferation by targeting early growth response 3 in prostate cancer. International journal of oncology 2019; 54(6): 1981-1994. [DOI:10.3892/ijo.2019.4778]
42. Wang X, Wu G, Cao G, Chen X, Huang J, Jiang X, Hou J. MicroRNA‑335 inhibits bladder cancer cell growth and migration by targeting mitogen‑activated protein kinase 1. Molecular medicine reports 2016; 14(2): 1765-1770. [DOI:10.3892/mmr.2016.5448]
43. Wang K, Yang S, Gao Y, Zhang C, Sui Q. MicroRNA‑769‑3p inhibits tumor progression in glioma by suppressing ZEB2 and inhibiting the Wnt/β‑catenin signaling pathwayCorrigendum in /10.3892/ol.2021.12489. Oncology letters 2020; 19(1): 992-1000. [DOI:10.3892/ol.2019.11135]
44. Németh K, Darvasi O, Likó I, Szücs N, Czirják S, Reiniger L, Szabó B, Krokker L, Pállinger E, Igaz P, Patócs A, Butz H. Comprehensive analysis of circulating microRNAs in plasma of patients with pituitary adenomas. Journal of clinical endocrinology and metabolism 2019; 2018: 02479. [DOI:10.1210/jc.2018-02479]
45. Kiss I, Mlčochová J, Součková K, Fabian P, Poprach A, Halamkova J, Svoboda M, Vyzula V, Slaby O. MicroRNAs as outcome predictors in patients with metastatic colorectal cancer treated with bevacizumab in combination with FOLFOX. Oncollogy letters 2017; 14(1): 743-750. [DOI:10.3892/ol.2017.6255]
46. Zeng Y, Lv Y, Tao L, Ma J, Zhang H, Xu H, Xiao B , Shi Q, Ma K, Chen L. G6PC3, ALDOA and CS induction accompanies mir-122 down-regulation in the mechanical asphyxia and can serve as hypoxia biomarkers. Oncotarget 2016; 7(46): 74526-74536. [DOI:10.18632/oncotarget.12931]
47. Zhao Y, Yan M, Yun Y, Zhang J, Zhang R, Li Y, Wu X, Liu Q, Miao W, Jiang H. MicroRNA-455-3p functions as a tumor suppressor by targeting eIF4E in prostate cancer. Oncology reports 2017; 37(4): 2449-2458. [DOI:10.3892/or.2017.5502]
48. Li Z, Meng Q, Pan A, Wu X, Cui J, Wang Y, Li L. MicroRNA-455-3p promotes invasion and migration in triple negative breast cancer by targeting tumor suppressor EI24. Oncotarget 2017; 8(12): 19455-1966. [DOI:10.18632/oncotarget.14307]
49. Cui HW, Han WY, Hou LN, Yang L, Li X, Su XL. miR-1915-3p inhibits Bcl-2 expression in the development of gastric cancer. Bioscience reports 2019; 39(5): BSR20182321. [DOI:10.1042/BSR20182321]
50. Pu J, Long Y, Zhou J, Zhan Y, Qin X. MiR-124 regulates apoptosis in hypoxia-induced human brain microvessel endothelial cells through targeting Bim. Applied biological chemistry 2018; 61(6): 689-696. [DOI:10.1007/s13765-018-0407-z]
51. Ahn YH, Ko YH. Diagnostic and therapeutic implications of microRNAs in non-Small cell lung cancer. International journal of molecular sciences 2020; 21(22): 8782. [DOI:10.3390/ijms21228782]
52. Hannafon BN, Cai A, Calloway CL, Xu Y-F, Zhang R, Fung K-M, Ding WQ. miR-23b and miR-27b are oncogenic microRNAs in breast cancer: evidence from a CRISPR/Cas9 deletion study. BMC cance 2019; 19(1): 642. [DOI:10.1186/s12885-019-5839-2]
53. Godínez-Rubí M, Ortuño-Sahagún D. miR-615 fine-tunes growth and development and has a Role in cancer and in neural repair. Cells 2020; 9(7): 1566. [DOI:10.3390/cells9071566]

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