Novel VHL substrate targets SFMBT1 and ZHX2 may be important prognostic predictors in patients with ccRCC

Chen,Yufeng; Zhu,Liangsong; Xue,Song; Shi,Jian; He,Chunfeng; Zhang,Qingchuan

doi:10.3892/ol.2021.12640

Novel VHL substrate targets SFMBT1 and ZHX2 may be important prognostic predictors in patients with ccRCC

Authors:
- Yufeng Chen
- Liangsong Zhu
- Song Xue
- Jian Shi
- Chunfeng He
- Qingchuan Zhang
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Affiliations: Department of Urology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200333, P.R. China, Department of Urology, Zhongshan Hospital, Fudan University, Shanghai 200030, P.R. China
Published online on: March 16, 2021 https://doi.org/10.3892/ol.2021.12640
Article Number: 379
Copyright: © Chen et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Renal cell carcinoma is one of the most malignant cancers, with limited prognostic prediction system. The present study aimed to determine the prognostic value of novel von Hippel‑Lindau (VHL) substrate targets in predicting the outcome of clear cell renal cell carcinoma (ccRCC). A total of 97 patients with ccRCC were enrolled in the present study, and the tissue microarray that was constructed using 97 ccRCC samples was used for immunohistochemical analysis. Univariate and multivariate Cox regression analyses were performed to determine the independent prognostic factors. Reverse transcription‑quantitative PCR analysis demonstrated that the mRNA expression levels of scm‑like with four malignant brain tumor domains (SFMBT1) and zinc fingers and homeoboxes 2 (ZHX2) were upregulated in cancer tissues compared with adjacent normal tissues. Among the 97 patients with ccRCC, SFMBT1 expression was upregulated in 61.9% (60/97), while ZHX2 expression was upregulated in 52.6% (51/97). Overall survival (OS) and disease‑free survival (DFS) analyses indicated that SFMBT1 or ZHX2 alone were of limited predictive value; however, the combined expression of these two targets (high SFMBT1 and high ZHX2 expression, SHZH group) was significantly associated with OS (P=0.0350) and DFS (P=0.0434). In addition, multivariate analysis identified SHZH as an independent prognostic factor in patients with ccRCC. Taken together, these results suggest that SFMBT1 and ZHX2 act as novel substrate targets of VHL and, to the best of our knowledge, the present study was the first to provide insight on the co‑expression of these two targets in representing a promising biomarker to predict the outcome of patients with ccRCC.

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1	Siegel RL, Miller KD and Jemal A: Cancer statistics, 2020. CA Cancer J Clin. 70:7–30. 2020. View Article : Google Scholar : PubMed/NCBI
2	Escudier B, Porta C, Schmidinger M, Rioux-Leclercq N, Bex A, Khoo V, Grünwald V, Gillessen S and Horwich A; ESMO Guidelines Committee. Electronic address, : clinicalguidelines@esmo.org: Renal cell carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 30:706–720. 2019. View Article : Google Scholar : PubMed/NCBI
3	Cancer Genome Atlas Research Network, . Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature. 499:43–49. 2013. View Article : Google Scholar : PubMed/NCBI
4	Kaelin WG Jr: Molecular basis of the VHL hereditary cancer syndrome. Nat Rev Cancer. 2:673–682. 2002. View Article : Google Scholar : PubMed/NCBI
5	Escudier B, Szczylik C, Porta C and Gore M: Treatment selection in metastatic renal cell carcinoma: Expert consensus. Nat Rev Clin Oncol. 9:327–337. 2012. View Article : Google Scholar : PubMed/NCBI
6	Harshman LC, Xie W, Bjarnason GA, Knox JJ, MacKenzie M, Wood L, Srinivas S, Vaishampayan UN, Tan MH, Rha SY, et al: Conditional survival of patients with metastatic renal-cell carcinoma treated with VEGF-targeted therapy: A population-based study. Lancet Oncol. 13:927–935. 2012. View Article : Google Scholar : PubMed/NCBI
7	Ficarra V, Novara G, Galfano A, Brunelli M, Cavalleri S, Martignoni G and Artibani W: The ‘stage, size, grade and necrosis’ score is more accurate than the University of California los angeles integrated staging system for predicting cancer-specific survival in patients with clear cell renal cell carcinoma. BJU Int. 103:165–170. 2009. View Article : Google Scholar : PubMed/NCBI
8	Ko JJ, Xie W, Kroeger N, Lee JL, Rini BI, Knox JJ, Bjarnason GA, Srinivas S, Pal SK, Yuasa T, et al: The international metastatic renal cell Carcinoma database consortium model as a prognostic tool in patients with metastatic renal cell carcinoma previously treated with first-line targeted therapy: A population-based study. Lancet Oncol. 16:293–300. 2015. View Article : Google Scholar : PubMed/NCBI
9	Zhu L, Wang J, Kong W, Huang J, Dong B, Huang Y, Xue W and Zhang J: LSD1 inhibition suppresses the growth of clear cell renal cell carcinoma via upregulating P21 signaling. Acta Pharm Sin B. 9:324–334. 2019. View Article : Google Scholar : PubMed/NCBI
10	Liao Y, Xiao H, Cheng M and Fan X: Bioinformatics analysis reveals biomarkers with cancer stem cell characteristics in lung squamous cell carcinoma. Front Genet. 11:4272020. View Article : Google Scholar : PubMed/NCBI
11	Liao Y, Wang Y, Cheng M, Huang C and Fan X: Weighted gene coexpression network analysis of features that control cancer stem cells reveals prognostic biomarkers in lung adenocarcinoma. Front Genet. 11:3112020. View Article : Google Scholar : PubMed/NCBI
12	Zhu L, Ding R, Zhang J, Zhang J and Lin Z: Cyclin-dependent kinase 5 acts as a promising biomarker in clear cell renal cell carcinoma. BMC Cancer. 19:6982019. View Article : Google Scholar : PubMed/NCBI
13	Ivan M, Kondo K, Yang H, Kim W, Valiando J, Ohh M, Salic A, Asara JM, Lane WS and Kaelin WG Jr: HIFalpha targeted for VHL-mediated destruction by proline hydroxylation: Implications for O2 sensing. Science. 292:464–468. 2001. View Article : Google Scholar : PubMed/NCBI
14	Hon WC, Wilson MI, Harlos K, Claridge TD, Schofield CJ, Pugh CW, Maxwell PH, Ratcliffe PJ, Stuart DI and Jones EY: Structural basis for the recognition of hydroxyproline in HIF-1 alpha by pVHL. Nature. 417:975–978. 2002. View Article : Google Scholar : PubMed/NCBI
15	Cho H, Du X, Rizzi JP, Liberzon E, Chakraborty AA, Gao W, Carvo I, Signoretti S, Bruick RK, Josey JA, et al: On-target efficacy of a HIF-2α antagonist in preclinical kidney cancer models. Nature. 539:107–111. 2016. View Article : Google Scholar : PubMed/NCBI
16	Zhang J, Wu T, Simon J, Takada M, Saito R, Fan C, Liu XD, Jonasch E, Xie L, Chen X, et al: VHL substrate transcription factor ZHX2 as an oncogenic driver in clear cell renal cell carcinoma. Science. 361:290–295. 2018. View Article : Google Scholar : PubMed/NCBI
17	Zhu L, Ding R, Yan H, Zhang J and Lin Z: ZHX2 drives cell growth and migration via activating MEK/ERK signal and induces sunitinib resistance by regulating the autophagy in clear cell renal cell carcinoma. Cell Death Dis. 11:3372020. View Article : Google Scholar : PubMed/NCBI
18	Liu X, Simon JM, Xie H, Hu L, Wang J, Zurlo G, Fan C, Ptacek TS, Herring L, Tan X, et al: Genome-wide screening identifies SFMBT1 as an oncogenic driver in cancer with VHL loss. Mol Cell. 77:1294–1306.e5. 2020. View Article : Google Scholar : PubMed/NCBI
19	Matos LL, Trufelli DC, de Matos MG and da Silva Pinhal MA: Immunohistochemistry as an important tool in biomarkers detection and clinical practice. Biomark Insights. 5:9–20. 2010. View Article : Google Scholar : PubMed/NCBI
20	Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI
21	Edge SB and Compton CC: The American joint committee on cancer: The 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 17:1471–1474. 2010. View Article : Google Scholar : PubMed/NCBI
22	Fuhrman SA, Lasky LC and Limas C: Prognostic significance of morphologic parameters in renal cell carcinoma. Am J Surg Pathol. 6:655–663. 1982. View Article : Google Scholar : PubMed/NCBI
23	Bonasio R, Lecona E and Reinberg D: MBT domain proteins in development and disease. Semin Cell Dev Biol. 21:221–230. 2010. View Article : Google Scholar : PubMed/NCBI
24	Tang M, Shen H, Jin Y, Lin T, Cai Q, Pinard MA, Biswas S, Tran Q, Li G, Shenoy AK, et al: The malignant brain tumor (MBT) domain protein SFMBT1 is an integral histone reader subunit of the LSD1 demethylase complex for chromatin association and epithelial-to-mesenchymal transition. J Biol Chem. 288:27680–27691. 2013. View Article : Google Scholar : PubMed/NCBI
25	Kawata H, Yamada K, Shou Z, Mizutani T, Yazawa T, Yoshino M, Sekiguchi T, Kajitani T and Miyamoto K: Zinc-fingers and homeoboxes (ZHX) 2, a novel member of the ZHX family, functions as a transcriptional repressor. Biochem J. 373:747–757. 2003. View Article : Google Scholar : PubMed/NCBI
26	Lv Z, Zhang M, Bi J, Xu F, Hu S and Wen J: Promoter hypermethylation of a novel gene, ZHX2, in hepatocellular carcinoma. Am J Clin Pathol. 125:740–746. 2006. View Article : Google Scholar : PubMed/NCBI
27	Nagel S, Schneider B, Meyer C, Kaufmann M, Drexler HG and Macleod RA: Transcriptional deregulation of homeobox gene ZHX2 in Hodgkin lymphoma. Leuk Res. 36:646–655. 2012. View Article : Google Scholar : PubMed/NCBI