GABRQ expression is a potential prognostic marker for patients with clear cell renal cell carcinoma

Lee,Dongjun; Ha,Mihyang; Hong,Chae  Mi; Kim,Jayoung; Park,Su  Min; Park,Dongsu; Sohn,Dong  Hyun; Shin,Ho  Jin; Yu,Hak‑Sun; Kim,Chi  Dae; Kang,Chi‑Dug; Han,Myoung‑Eun; Oh,Sae‑Ock; Kim,Yun  Hak

doi:10.3892/ol.2019.10960

GABRQ expression is a potential prognostic marker for patients with clear cell renal cell carcinoma

Authors:
- Dongjun Lee
- Mihyang Ha
- Chae Mi Hong
- Jayoung Kim
- Su Min Park
- Dongsu Park
- Dong Hyun Sohn
- Ho Jin Shin
- Hak‑Sun Yu
- Chi Dae Kim
- Chi‑Dug Kang
- Myoung‑Eun Han
- Sae‑Ock Oh
- Yun Hak Kim
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Affiliations: Department of Convergence Medical Science, Pusan National University School of Medicine, Yangsan, Gyeongsangnam‑do 50612, Republic of Korea, Department of Anatomy, Pusan National University School of Medicine, Yangsan, Gyeongsangnam‑do 50612, Republic of Korea, Department of Molecular Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA, Department of Microbiology and Immunology, Pusan National University School of Medicine, Yangsan, Gyeongsangnam‑do 50612, Republic of Korea, Department of Hematology‑Oncology, Pusan National University School of Medicine, Yangsan, Gyeongsangnam‑do 50612, Republic of Korea, Department of Parasitology, Pusan National University School of Medicine, Yangsan, Gyeongsangnam‑do 50612, Republic of Korea, Department of Pharmacology, Pusan National University School of Medicine, Yangsan, Gyeongsangnam‑do 50612, Republic of Korea
Published online on: October 4, 2019 https://doi.org/10.3892/ol.2019.10960
Pages: 5731-5738
Copyright: © Lee et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Novel biomarkers of ccRCC may provide crucial information on tumor features and prognosis. The present study aimed to determine whether the expression of γ‑aminobutyric acid (GABA) A receptor subunit θ (GABRQ) could serve as a novel prognostic marker of ccRCC. GABA is the main inhibitory neurotransmitter in the brain that activates the receptor GABAA, which is comprised of three subunit isoforms: GABRA3, GABRB3 and GABRQ. A recent study reported that GABRQ is involved in the initiation and progression of hepatocellular carcinoma; however, the role of GABRQ in ccRCC remains unknown. In the present study, clinical and transcriptomic data were obtained from cohorts of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Differential GABRQ expression levels among early (TI and II), late (TIII and IV), nonmetastatic (M0) and metastatic (M1, primary tumor) stages of ccRCC samples were then identified. Furthermore, the use of GABRQ as a prognostic gene was analyzed using Uno's C‑index based on the time‑dependent area under the curve (AUC), the AUC of the receiver operating characteristic curve at 5 years, the Kaplan‑Meier survival curve and multivariate analysis. The survival curve analysis revealed that low GABRQ mRNA expression was significantly associated with a poor prognosis of ccRCC (P<0.001 and P=0.0012 for TCGA and ICGC data, respectively). In addition, analyses of the C‑index and AUC values further supported this discriminatory power. Furthermore, the prognostic value of GABRQ mRNA expression was confirmed by multivariate Cox regression analysis. Taken together, these results suggested that GABRQ mRNA expression may be considered as a novel prognostic biomarker of ccRCC.

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1	Siegel RL, Miller KD and Jemal A: Cancer statistics, 2018. CA Cancer J Clin. 68:7–30. 2018. View Article : Google Scholar : PubMed/NCBI
2	Choueiri TK and Motzer RJ: Systemic therapy for metastatic renal-cell carcinoma. N Engl J Med. 376:354–366. 2017. View Article : Google Scholar : PubMed/NCBI
3	Srigley JR, Delahunt B, Eble JN, Egevad L, Epstein JI, Grignon D, Hes O, Moch H, Montironi R, Tickoo SK, et al: The international society of urological pathology (ISUP) Vancouver classification of renal Neoplasia. Am J Surg Pathol. 37:1469–1489. 2013. View Article : Google Scholar : PubMed/NCBI
4	Nickerson ML, Jaeger E, Shi Y, Durocher JA, Mahurkar S, Zaridze D, Matveev V, Janout V, Kollarova H, Bencko V, et al: Improved identification of von Hippel-Lindau gene alterations in clear cell renal tumors. Clin Cancer Res. 14:4726–4734. 2008. View Article : Google Scholar : PubMed/NCBI
5	Powles T, Albiges L, Staehler M, Bensalah K, Dabestani S, Giles RH, Hofmann F, Hora M, Kuczyk MA, Lam TB, et al: Updated European association of urology guidelines recommendations for the treatment of first-line metastatic clear cell renal cancer. Eur Urol. Dec 7–2017.doi: 10.1016/j.eururo.2017.11.016 (Epub ahead of print).
6	Powles T, Staehler M, Ljungberg B, Bensalah K, Canfield SE, Dabestani S, Giles R, Hofmann F, Hora M, Kuczyk MA, et al: Updated EAU Guidelines for clear cell renal cancer patients who fail vegf targeted therapy. Eur Urol. 69:4–6. 2016. View Article : Google Scholar : PubMed/NCBI
7	Karakiewicz PI, Briganti A, Chun FK, Trinh QD, Perrotte P, Ficarra V, Cindolo L, De la Taille A, Tostain J, Mulders PF, et al: Multi-institutional validation of a new renal cancer-specific survival nomogram. J Clin Oncol. 25:1316–1322. 2007. View Article : Google Scholar : PubMed/NCBI
8	Garcia-Martin E, Martinez C, Alonso-Navarro H, Benito-León J, Lorenzo-Betancor O, Pastor P, Puertas I, Rubio L, López-Alburquerque T, Agúndez JA and Jiménez-Jiménez FJ: Gamma-aminobutyric acid GABRA4, GABRE, and GABRQ receptor polymorphisms and risk for essential tremor. Pharmacogenet Genomics. 21:436–439. 2011. View Article : Google Scholar : PubMed/NCBI
9	Neelands TR, Zhang J and Macdonald RL: GABA(A) receptors expressed in undifferentiated human teratocarcinoma NT2 cells differ from those expressed by differentiated NT2-N cells. J Neurosci. 19:7057–7065. 1999. View Article : Google Scholar : PubMed/NCBI
10	Haydar TF, Wang F, Schwartz ML and Rakic P: Differential modulation of proliferation in the neocortical ventricular and subventricular zones. J Neurosci. 20:5764–5774. 2000. View Article : Google Scholar : PubMed/NCBI
11	Li YH, Liu Y, Li YD, Liu YH, Li F, Ju Q, Xie PL and Li GC: GABA stimulates human hepatocellular carcinoma growth through overexpressed GABAA receptor theta subunit. World J Gastroenterol. 18:2704–2711. 2012. View Article : Google Scholar : PubMed/NCBI
12	International Cancer Genome Consortium, ; Hudson TJ, Anderson W, Artez A, Barker AD, Bell C, Bernabé RR, Bhan MK, Calvo F, Eerola I, et al: International network of cancer genome projects. Nature. 464:993–998. 2010. View Article : Google Scholar : PubMed/NCBI
13	Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, Jacobsen A, Byrne CJ, Heuer ML, Larsson E, et al: The cBio cancer genomics portal: An open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2:401–404. 2012. View Article : Google Scholar : PubMed/NCBI
14	Cancer Genome Atlas Research Network, ; Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C and Stuart JM: The cancer genome atlas pan-cancer analysis project. Nat Genet. 45:1113–1120. 2013. View Article : Google Scholar : PubMed/NCBI
15	Ha M, Han ME, Kim JY, Jeong DC, Oh SO and Kim YH: Prognostic role of TPD52 in acute myeloid leukemia: A retrospective multicohort analysis. J Cell Biochem. 120:3672–3678. 2019. View Article : Google Scholar : PubMed/NCBI
16	Han ME, Kim JY, Kim GH, Park SY, Kim YH and Oh SO: SAC3D1: A novel prognostic marker in hepatocellular carcinoma. Sci Rep. 8:156082018. View Article : Google Scholar : PubMed/NCBI
17	Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, Barrette T, Pandey A and Chinnaiyan AM: ONCOMINE: A cancer microarray database and integrated data-mining platform. Neoplasia. 6:1–6. 2004. View Article : Google Scholar : PubMed/NCBI
18	Cho SH, Pak K, Jeong DC, Han ME, Oh SO and Kim YH: The AP2M1 gene expression is a promising biomarker for predicting survival of patients with hepatocellular carcinoma. J Cell Biochem. 120:4140–4146. 2019. View Article : Google Scholar : PubMed/NCBI
19	Kim YH, Jeong DC, Pak K, Goh TS, Lee CS, Han ME, Kim JY, Liangwen L, Kim CD, Jang JY, et al: Gene network inherent in genomic big data improves the accuracy of prognostic prediction for cancer patients. Oncotarget. 8:77515–77526. 2017.PubMed/NCBI
20	Uno H, Cai T, Pencina MJ, D'Agostino RB and Wei LJ: On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data. Stat Med. 30:1105–1117. 2011.PubMed/NCBI
21	Hoshida Y, Nijman SM, Kobayashi M, Chan JA, Brunet JP, Chiang DY, Villanueva A, Newell P, Ikeda K, Hashimoto M, et al: Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma. Cancer Res. 69:7385–7392. 2009. View Article : Google Scholar : PubMed/NCBI
22	Shtraizent N, DeRossi C, Nayar S, Sachidanandam R, Katz LS, Prince A, Koh AP, Vincek A, Hadas Y, Hoshida Y, et al: MPI depletion enhances O-GlcNAcylation of p53 and suppresses the Warburg effect. Elife. 6(pii): e224772017. View Article : Google Scholar : PubMed/NCBI
23	Subramanian P and Haas NB: Recent advances in localized RCC: A focus on VEGF and immuno-oncology therapies. Urol Oncol. 36:23–30. 2018. View Article : Google Scholar : PubMed/NCBI
24	Wang Y, Chen L, Wang G, Cheng S, Qian K, Liu X, Wu CL, Xiao Y and Wang X: Fifteen hub genes associated with progression and prognosis of clear cell renal cell carcinoma identified by coexpression analysis. J Cell Physiol. 234:10225–10237. 2019. View Article : Google Scholar : PubMed/NCBI
25	Guan L, Tan J, Li H and Jin X: Biomarker identification in clear cell renal cell carcinoma based on miRNA-seq and digital gene expression-seq data. Gene. 647:205–212. 2018. View Article : Google Scholar : PubMed/NCBI
26	Gao C, Zhou C, Zhuang J, Liu L, Liu C, Li H, Liu G, Wei J and Sun C: MicroRNA expression in cervical cancer: Novel diagnostic and prognostic biomarkers. J Cell Biochem. 119:7080–7090. 2018. View Article : Google Scholar : PubMed/NCBI
27	Joseph J, Niggemann B, Zaenker KS and Entschladen F: The neurotransmitter gamma-aminobutyric acid is an inhibitory regulator for the migration of SW 480 colon carcinoma cells. Cancer Res. 62:6467–6469. 2002.PubMed/NCBI
28	Azuma H, Inamoto T, Sakamoto T, Kiyama S, Ubai T, Shinohara Y, Maemura K, Tsuji M, Segawa N, Masuda H, et al: Gamma-aminobutyric acid as a promoting factor of cancer metastasis; induction of matrix metalloproteinase production is potentially its underlying mechanism. Cancer Res. 63:8090–8096. 2003.PubMed/NCBI
29	Plummer PN, Colson NJ, Lewohl JM, MacKay RK, Fernandez F, Haupt LM and Griffiths LR: Significant differences in gene expression of GABA receptors in peripheral blood leukocytes of migraineurs. Gene. 490:32–36. 2011. View Article : Google Scholar : PubMed/NCBI
30	Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T, et al: A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 351:2817–2826. 2004. View Article : Google Scholar : PubMed/NCBI
31	Wittner BS, Sgroi DC, Ryan PD, Bruinsma TJ, Glas AM, Male A, Dahiya S, Habin K, Bernards R, Haber DA, et al: Analysis of the MammaPrint breast cancer assay in a predominantly postmenopausal cohort. Clin Cancer Res. 14:2988–2993. 2008. View Article : Google Scholar : PubMed/NCBI
32	Chen HY, Yu SL, Chen CH, Chang GC, Chen CY, Yuan A, Cheng CL, Wang CH, Terng HJ, Kao SF, et al: A five-gene signature and clinical outcome in non-small-cell lung cancer. N Engl J Med. 356:11–20. 2007. View Article : Google Scholar : PubMed/NCBI
33	Goh TS, Lee JS, II Kim J, Park YG, Pak K, Jeong DC, Oh SO and Kim YH: Prognostic scoring system for osteosarcoma using network-regularized high-dimensional Cox-regression analysis and potential therapeutic targets. J Cell Physiol. 234:13851–13857. 2019. View Article : Google Scholar : PubMed/NCBI
34	Pak K, Kim YH, Suh S, Goh TS, Jeong DC, Kim SJ, Kim IJ, Han ME and Oh SO: Development of a risk scoring system for patients with papillary thyroid cancer. J Cell Mol Med. 23:3010–3015. 2019. View Article : Google Scholar : PubMed/NCBI
35	Kim YH, Jeong DC, Pak K, Han ME, Kim JY, Liangwen L, Kim HJ, Kim TW, Kim TH, Hyun DW and Oh SO: SLC2A2 (GLUT2) as a novel prognostic factor for hepatocellular carcinoma. Oncotarget. 8:68381–68392. 2017.PubMed/NCBI
36	Nault JC, De Reynies A, Villanueva A, Calderaro J, Rebouissou S, Couchy G, Decaens T, Franco D, Imbeaud S, Rousseau F, et al: A hepatocellular carcinoma 5-gene score associated with survival of patients after liver resection. Gastroenterology. 145:176–187. 2013. View Article : Google Scholar : PubMed/NCBI
37	van't Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, et al: Gene expression profiling predicts clinical outcome of breast cancer. Nature. 415:530–536. 2002. View Article : Google Scholar : PubMed/NCBI