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Research ArticleArticles
Open Access

CYBA as a Potential Biomarker for Renal Cell Carcinoma: Evidence from an Integrated Genetic Analysis

CHI-FEN CHANG, SHU-PIN HUANG, YU-MEI HSUEH, PEI-LING CHEN, CHENG-HSUEH LEE, JIUN-HUNG GENG, CHAO-YUAN HUANG and BO-YING BAO
Cancer Genomics & Proteomics September 2023, 20 (5) 469-475; DOI: https://doi.org/10.21873/cgp.20398
CHI-FEN CHANG
1Department of Anatomy, School of Medicine, China Medical University, Taichung, Taiwan, R.O.C.;
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SHU-PIN HUANG
2Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, R.O.C.;
3Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.;
4Ph.D. Program in Environmental and Occupational Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.;
5Institute of Medical Science and Technology, College of Medicine, National Sun Yat-Sen University, Kaohsiung, Taiwan, R.O.C.;
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YU-MEI HSUEH
6Department of Family Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan, R.O.C.;
7Department of Public Health, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan, R.O.C.;
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PEI-LING CHEN
8Department of Urology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan, R.O.C.;
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CHENG-HSUEH LEE
2Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, R.O.C.;
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JIUN-HUNG GENG
2Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, R.O.C.;
9Department of Urology, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung, Taiwan, R.O.C.;
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CHAO-YUAN HUANG
8Department of Urology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan, R.O.C.;
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  • For correspondence: cyhuang0909@ntu.edu.tw
BO-YING BAO
10Department of Pharmacy, China Medical University, Taichung, Taiwan, R.O.C.;
11Department of Nursing, Asia University, Taichung, Taiwan, R.O.C.
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  • For correspondence: bao@mail.cmu.edu.tw
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Abstract

Background/Aim: Oxidative stress plays an important role in various pathogenic processes, and disruption in the coordinated production of NADPH oxidase (NOX)-derived reactive oxygen species has been associated with carcinogenesis. However, little is known about whether genetic variants in NOX can contribute to the development of renal cell carcinoma (RCC). Patients and Methods: This study aimed to bridge this knowledge gap by analysing the association of 10 single-nucleotide polymorphisms in the phagocyte NOX genes, CYBA and CYBB, with RCC risk and tumour characteristics in 630 RCC patients and controls. Differential gene expression and patient prognosis analyses were performed using gene expression data obtained from public databases. Results: Multivariate analysis and multiple testing corrections revealed the A allele of rs7195830 in CYBA to be a significant risk allele for RCC, compared to the G allele [odds ratio (OR)=1.70, 95% confidence interval (CI)=1.27-2.26, p<0.001]. A pooled analysis of 17 renal cancer gene expression datasets revealed a higher CYBA expression in RCC than in normal tissues. Moreover, high CYBA expression was associated with advanced tumour characteristics and worse patient prognosis. Conclusion: CYBA might play an oncogenic role in RCC and serve as a predictive indicator of patient prognosis.

Key Words:
  • Renal cell carcinoma
  • NADPH oxidase
  • single-nucleotide polymorphism
  • differentially expressed gene
  • prognosis

Renal cell carcinoma (RCC) is the most common type of renal cancer in adults and accounts for approximately 90% of all cases (1). In 2020, a total of 431,288 new cases of renal cancer, with 179,368 renal cancer-associated deaths were recorded worldwide (2). The global incidence of RCC has increased by 2-3% annually over the past two decades (3), making it a growing public health concern. The incidence of RCC is higher in developed countries and is more common in men than in women. Risk factors for the disease include smoking, obesity, hypertension, and a history of renal disease (4). Early detection is crucial for improving the outcomes and increasing the likelihood of successful treatment. Therefore, further research is required to understand the underlying causes of RCC and to develop new and effective treatments.

The phagocyte NADPH oxidases (NOX) are multi-protein complexes that generate reactive oxygen species (ROS) in phagocytes, such as neutrophils and macrophages. NOX are activated by various stimuli, including cytokines and growth factors, leading to the transfer of electrons from NADPH to oxygen and resulting in the generation of ROS (5). These ROS, in turn, act as stimuli and serve as signals in various cellular processes, including immune responses, inflammation, and tissue injury (6). The catalytic subunits of the phagocyte NOX are composed of the p22phox (encoded by CYBA) and gp91phox (encoded by CYBB) proteins, and mutations in these genes are associated with chronic granulomatous disease, which is an inherited disorder characterized by recurrent infections and abnormal inflammation (7). Besides the phagocyte NOX, CYBA is shared by several other NOX in a variety of nonphagocytic cells with different cellular functions (8). Dysregulation of the NOX activation, which leads to elevated ROS levels, has been linked to various pathophysiologies, such as cardiovascular diseases, diabetes, neurodegenerative diseases, and cancer (9). The ROS produced by NOX has been recently linked with the proliferation of human colon cancer cells and silencing NOX1 using short hairpin RNA hindered the cell cycle progression in the G1/S phase due to reduced cyclin D1 expression (10).

Single-nucleotide polymorphisms (SNPs) can serve as suitable markers to predict the predisposition to various diseases (11), including cancer, and represent a pathway towards personalized medicine. To date, limited studies have elucidated the role of genetic variations in NOX genes and their link with RCC. Consequently, this present case-control study, involving 630 participants, aimed to investigate the relationship between phagocyte NOX gene polymorphisms and the risk of RCC, as well as tumour characteristics. Furthermore, we examined the correlation between NOX gene expression levels and the clinical and pathological features in RCC patients.

Patients and Methods

Study population. A total of 312 patients with RCC, along with 318 sex- and age-matched, unrelated, healthy participants without any history of cancer, were recruited from three hospitals across Taiwan: Taipei Medical University Hospital, Taipei Municipal Wan Fang Hospital, and National Taiwan University Hospital. The details of the recruitment criteria, participation, and data collection have been described previously (12, 13). The distributions of body mass index and smoking behaviour did not differ between the controls and patients (14). The alcohol intake was lower, and the prevalence of diabetes and hypertension was higher among the patients than among the controls (p<0.001). A total of 68 (24.8%) and 55 (18.6%) patients were diagnosed with the stage III-IV and grade III-IV (a more aggressive form of RCC), respectively. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Research Ethics Committee of National Taiwan University Hospital (9100201527). Written informed consent was received from all the participants.

SNP selection and genotyping. Genomic DNA was extracted from whole blood using a QIAamp DNA Blood Kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s recommendations and stored at −80°C until further analysis. The SNPs in phagocyte NOX genes, CYBA and CYBB, were selected using the Han Chinese data in the 1000 Genomes Project and the Haploview software with a pairwise linkage disequilibrium r2>0.8 and minor allele frequency >0.05 (15, 16). Finally, 10 haplotype-tagging SNPs were determined and genotyped using the Affymetrix Axiom Genotyping arrays at the National Centre for Genome Medicine, Taiwan (17). The overall genotyping rate was between 98.0 and 99.8%.

Bioinformatic analyses. The functional prediction for the risk-associated SNP rs7195830 was performed with HaploReg (18), and the correlation between the rs7195830 and CYBA expression was assessed using the Genotype-Tissue Expression (GTEx) database (19).

Statistical analyses. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS; IBM, Armonk, NY, USA). The clinical characteristics were presented as the proportion (%) of participants, and the differences between the healthy controls and patients with RCC were analysed using Chi-squared (χ2) tests. The association between the SNPs and risk, grade, and stage of RCC was estimated by examining odds ratios (ORs) and 95% confidence intervals (CIs) which were determined using logistic regression analysis. The expression levels of CYBA were compared between the renal cancer and adjacent normal tissues using the standardized mean difference (SMD) and 95% CI using a random effects model with Review Manager (Cochrane, Oxford, UK). The correlations between the CYBA mRNA expression and tumour grade, stage, and survival of RCC were assessed using Spearman’s rank correlation tests and Kaplan-Meier survival curves from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Correction for multiple testing was performed using the false discovery rate (q-value) (20). p- and q-values <0.05 were considered statistically significant.

Results

Logistic regression was used to investigate the association of genetic variants in phagocyte NOX genes with the risk, grade, and stage of RCC (Table I). After adjusting for multiple testing (q<0.05), only CYBA rs7195830 showed a significant association with RCC risk, but none were found to be associated with tumour grade and stage. Specifically, individuals with the A allele at CYBA rs7195830 were at a significantly higher risk of developing RCC than those with the G allele (OR=1.57, 95% CI=1.21-2.02, p=0.001, q=0.024, Table II). Moreover, this association remained statistically significant when examined using the multivariate logistic regression analysis that was adjusted for sex, age, body mass index, smoking status, alcohol intake, and histories of diabetes and hypertension (adjusted OR=1.70, 95% CI=1.27-2.26, p<0.001, Table II).

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Table I.

Association of phagocyte NADPH oxidase gene polymorphisms with risk, grade, and stage of renal cell carcinoma.

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Table II.

Association between CYBA rs7195830 and the risk of renal cell carcinoma.

The results of the HaploReg analysis indicated that rs7195830 and its linked SNPs reside in an open chromatin region with enhancer histone marks, DNase I hypersensitivity, RNA polymerase II binding, and expression quantitative trait loci signals, and are likely to affect transcription factor binding and CYBA expression (Table III). The three-dimensional organization of human genomes, such as topologically associating domains (TADs), play a crucial role in gene regulation by constraining interactions between promoters and cis-regulatory elements. Chromatin conformation capture Hi-C data from the 3D genome browser (21) revealed that both rs7195830 and CYBA are situated within the same TAD across various tissues and cell lines. The GTEx database was further used to evaluate the correlation of rs7195830 with CYBA expression. The results demonstrated that individuals harbouring the risk allele of rs7195830 A exhibited a higher CYBA expression in the small intestine-terminal ileum tissues compared to those harbouring the G allele [normalized effect size (NES)=−0.069, p=0.027, Figure 1]. Moreover, a similar Genotype-gene expression relationship was observed in the renal cortex tissues, although this relationship was not statistically significant (NES=−0.085, p=0.31, Figure 1).

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Table III.

Regulatory annotation of CYBA rs7195830.

Figure 1.
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Figure 1.

Correlation of rs7195830 genotypes with CYBA expression in the renal cortex and small intestine–terminal ileum tissues based on the Genotype-Tissue Expression dataset. The values in brackets indicate the number of patients in each subgroup. NES, Normalized effect size.

To investigate the potential role of CYBA in renal cancer, the TCGA, Gene Expression Omnibus, and ArrayExpress databases were used to evaluate the effects of CYBA expression on tumour characteristics and patient prognosis. A total of 1418 renal cancer and 400 adjacent normal tissues from 17 independent datasets were included in the pooled analysis. The results revealed that CYBA expression was higher in the renal cancer tissues than in the noncancerous tissues (SMD=0.61, 95% CI=0.16-1.05, p=0.008, Figure 2). Analysis using the TCGA-KIRC dataset showed that high CYBA expression was positively correlated with an advanced tumour stage and grade (p<0.001, Figure 3). Moreover, the Kaplan-Meier survival analysis demonstrated that patients showing a high CYBA expression (separated by the median) exhibited shorter progression-free, overall, and RCC-specific survivals (p<0.001, Figure 3). However, CYBA expression was not associated with cancer progression and patient survival in the TCGA kidney renal papillary cell carcinoma and kidney chromophobe datasets, possibly as a result of smaller sample sizes (data not shown).

Figure 2.
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Figure 2.

Forest plot illustrating the differential CYBA expression between renal cancer and normal tissues. SD, Standard deviation; IV, inverse variance; CI, confidence interval; Std, standardized; TCGA, The Cancer Genome Atlas; KICH, kidney chromophobe; KIRC, kidney renal clear cell carcinoma; KIRP, kidney renal papillary cell carcinoma; df, degrees of freedom.

Figure 3.
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Figure 3.

CYBA expression is correlated with the aggressiveness of renal cancer and predicts worse clinical outcomes. CYBA expression is elevated during stage and grade progression, and a high CYBA expression is associated with worse progression-free, overall, and disease-specific survivals in The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma dataset. rho, Spearman’s rank correlation coefficient. The values in brackets indicate the number of patients in each subgroup.

Discussion

Despite numerous studies demonstrating the involvement of NOX-derived oxidative stress in cancer, our understanding of the relationship between NOX gene expression levels and polymorphisms with RCC remains limited. In this study, we found that CYBA rs7195830 was independently associated with the risk of RCC after adjustment for the known factors and correction for multiple testing. Furthermore, the expression of CYBA was up-regulated in the renal cancer tissues compared to the normal tissues, and high CYBA expression levels were found to be significantly associated with poorer survival in clear cell RCC.

The CYBA gene, located on chromosome 16, encodes a critical p22phox subunit of NOX. The NOX family comprises seven members, NOX1–5 and dual oxidases (DUOX1–2), and many NOX enzymes require association with CYBA to promote transmembrane electron transfer and to generate superoxide and hydrogen peroxide (22). NOX-derived ROS have been implicated in carcinogenesis. NOX1 is implicated in colon cancer, wherein its ability to produce ROS may promote tumour cell proliferation and metastasis (10, 23). The knockdown of NOX1 using short hairpin RNA in HT-29 human colon cancer cells inhibits mitogen-activated protein kinase (MAPK) signalling, impairs cyclin D1 expression, and blocks cell cycle progression in the G1/S phase (10). In myeloid leukemic cells, high levels of NOX2 hinder the destruction of malignant cells by triggering ROS-induced apoptosis of adjacent antileukemic lymphocytes (24). Moreover, the expression of NOX2 in cancer stem cells has been linked to leukemogenesis by promoting the maintenance of leukemic stem cell self-renewal and proliferation (25). In Epstein-Barr virus-infected gastric cancer cells, NOX2 expression increases by down-regulating miRNA34a to promote cell survival (26). Furthermore, NOX3 mediates the insulin-induced angiogenic response through p42/44 MAPK signalling in hepatocellular carcinoma cells (27). NOX4 is overexpressed in several forms of cancer, including RCC (28), glioma (29), and melanoma (30). In RCC, NOX4 can increase hypoxia-induced interleukin (IL)-6 and IL-8 secretion, resulting in cell invasion (28). CYBA protein levels and NOX-derived ROS production are elevated in von Hippel-Lindau (VHL)-deficient RCC cells, and the reintroduction of VHL into these cells leads to reduced CYBA expression and ROS production (31). Furthermore, gene silencing of CYBA results in the inhibition of AKT phosphorylation, and the use of specific NOX inhibitors decreases RCC cell growth and reduces tumour formation in vivo (31). Several studies have also reported significant associations between genetic variants in CYBA and the risks of cervical cancer (32), colorectal cancer (33), and end-stage renal disease (34), further supporting the significance of CYBA in cancer. Consistent with this, our data revealed that CYBA mRNA expression in the RCC tissue specimens is significantly higher than in the noncancerous tissue specimens. Furthermore, a high CYBA expression was correlated with a poorer survival rate, indicating that CYBA may have an oncogenic role in RCC. However, the risk allele rs7195830 A exhibited only a marginal increase in CYBA expression in the GTEx renal cortex tissues. Therefore, further investigations are required to identify additional molecular mechanisms that may alter CYBA expression in RCC.

Conclusion

Although the exact role of CYBA in RCC is not well understood, more in-depth research may uncover therapeutic targets within NOX pathways. The current study establishes a link between CYBA and RCC; however, this study has certain limitations, which include being limited to samples from Taiwanese individuals, which may impact its generalizability to other populations. Other crucial NOX-related genes that may have contributed to the development of RCC were not evaluated in the current study. Additionally, despite correcting for multiple testing with q-values, false positives remain a possibility. Furthermore, our sample size is relatively small compared to other genetic association studies. Lastly, our understanding of the biological mechanisms by which rs7195830 affects CYBA function and RCC progression remains incomplete. Although additional functional experiments are necessary, this study indicates that CYBA rs7195830 confers an increased risk of RCC, and targeting CYBA could be a promising therapeutic approach for treating RCC.

Acknowledgements

The Authors thank Chao-Shih Chen for data analysis, and the National Center for Genome Medicine, Ministry of Science and Technology of Taiwan, for technical support. The results published here are based in part on data generated by the HaploReg, 1000 Genomes, GTEx, and TCGA projects. This work was supported by the National Science and Technology Council of Taiwan (grant nos: 108-2320-B-039-050-MY3, 110-2314-B-002-113, 111-2314-B-002-240-MY3 and 111-2320-B-039-021-MY3), the Kaohsiung Medical University Hospital (grant nos: KMUH110-0R54 and KMUH110-0R55), and the China Medical University (grant nos: CMU109-MF-65, CMU110-MF-59, and CMU111-MF-09). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Footnotes

  • ↵* These Authors contributed equally to this study.

  • Conflicts of Interest

    The Authors declare that they have no potential conflicts of interest in regard to this study.

  • Authors’ Contributions

    CFC performed data collection and analysis. SPH and CYH contributed to project development and funding acquisition. YMH and PLC performed data collection. CHL and JHG performed data analysis. BYB contributed to project development, data analysis, and funding acquisition. All Authors prepared and agreed to the published version of the manuscript.

  • Received May 22, 2023.
  • Revision received June 17, 2023.
  • Accepted June 26, 2023.
  • Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).

References

  1. ↵
    1. Ljungberg B,
    2. Albiges L,
    3. Abu-Ghanem Y,
    4. Bedke J,
    5. Capitanio U,
    6. Dabestani S,
    7. Fernández-Pello S,
    8. Giles RH,
    9. Hofmann F,
    10. Hora M,
    11. Klatte T,
    12. Kuusk T,
    13. Lam TB,
    14. Marconi L,
    15. Powles T,
    16. Tahbaz R,
    17. Volpe A,
    18. Bex A
    : European Association of Urology Guidelines on renal cell carcinoma: the 2022 update. Eur Urol 82(4): 399-410, 2022. DOI: 10.1016/j.eururo.2022.03.006
    OpenUrlCrossRefPubMed
  2. ↵
    1. Sung H,
    2. Ferlay J,
    3. Siegel RL,
    4. Laversanne M,
    5. Soerjomataram I,
    6. Jemal A,
    7. Bray F
    : Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3): 209-249, 2021. DOI: 10.3322/caac.21660
    OpenUrlCrossRefPubMed
  3. ↵
    1. Capitanio U,
    2. Bensalah K,
    3. Bex A,
    4. Boorjian SA,
    5. Bray F,
    6. Coleman J,
    7. Gore JL,
    8. Sun M,
    9. Wood C,
    10. Russo P
    : Epidemiology of renal cell carcinoma. Eur Urol 75(1): 74-84, 2019. DOI: 10.1016/j.eururo.2018.08.036
    OpenUrlCrossRefPubMed
  4. ↵
    1. Chow W,
    2. Gridley G,
    3. Fraumeni JF Jr.,
    4. Järvholm B
    : Obesity, hypertension, and the risk of kidney cancer in men. N Engl J Med 343(18): 1305-1311, 2000. DOI: 10.1056/NEJM200011023431804
    OpenUrlCrossRefPubMed
  5. ↵
    1. Pecchillo Cimmino T,
    2. Ammendola R,
    3. Cattaneo F,
    4. Esposito G
    : NOX dependent ROS generation and cell metabolism. Int J Mol Sci 24(3): 2086, 2023. DOI: 10.3390/ijms24032086
    OpenUrlCrossRef
  6. ↵
    1. Singel KL,
    2. Segal BH
    : NOX2-dependent regulation of inflammation. Clin Sci (Lond) 130(7): 479-490, 2016. DOI: 10.1042/CS20150660
    OpenUrlCrossRef
  7. ↵
    1. Roos D,
    2. de Boer M,
    3. Kuribayashi F,
    4. Meischl C,
    5. Weening RS,
    6. Segal AW,
    7. Ahlin A,
    8. Nemet K,
    9. Hossle JP,
    10. Bernatowska-Matuszkiewicz E,
    11. Middleton-Price H
    : Mutations in the x-linked and autosomal recessive forms of chronic granulomatous disease. Blood 87(5): 1663-1681, 1996.
    OpenUrlFREE Full Text
  8. ↵
    1. Sumimoto H,
    2. Miyano K,
    3. Takeya R
    : Molecular composition and regulation of the Nox family NAD(P)H oxidases. Biochem Biophys Res Commun 338(1): 677-686, 2005. DOI: 10.1016/j.bbrc.2005.08.210
    OpenUrlCrossRefPubMed
  9. ↵
    1. Waghela BN,
    2. Vaidya FU,
    3. Agrawal Y,
    4. Santra MK,
    5. Mishra V,
    6. Pathak C
    : Molecular insights of NADPH oxidases and its pathological consequences. Cell Biochem Funct 39(2): 218-234, 2021. DOI: 10.1002/cbf.3589
    OpenUrlCrossRef
  10. ↵
    1. Juhasz A,
    2. Markel S,
    3. Gaur S,
    4. Liu H,
    5. Lu J,
    6. Jiang G,
    7. Wu X,
    8. Antony S,
    9. Wu Y,
    10. Melillo G,
    11. Meitzler JL,
    12. Haines DC,
    13. Butcher D,
    14. Roy K,
    15. Doroshow JH
    : NADPH oxidase 1 supports proliferation of colon cancer cells by modulating reactive oxygen species-dependent signal transduction. J Biol Chem 292(19): 7866-7887, 2017. DOI: 10.1074/jbc.M116.768283
    OpenUrlAbstract/FREE Full Text
  11. ↵
    1. Mias GI,
    2. Snyder M
    : Personal genomes, quantitative dynamic omics and personalized medicine. Quant Biol 1(1): 71-90, 2013. DOI: 10.1007/s40484-013-0005-3
    OpenUrlCrossRefPubMed
  12. ↵
    1. Huang CY,
    2. Hsueh YM,
    3. Chen LC,
    4. Cheng WC,
    5. Yu CC,
    6. Chen WJ,
    7. Lu TL,
    8. Lan KJ,
    9. Lee CH,
    10. Huang SP,
    11. Bao BY
    : Clinical significance of glutamate metabotropic receptors in renal cell carcinoma risk and survival. Cancer Med 7(12): 6104-6111, 2018. DOI: 10.1002/cam4.1901
    OpenUrlCrossRef
  13. ↵
    1. Huang C,
    2. Su C,
    3. Chu J,
    4. Huang S,
    5. Pu Y,
    6. Yang H,
    7. Chung C,
    8. Wu C,
    9. Hsueh Y
    : The polymorphisms of P53 codon 72 and MDM2 SNP309 and renal cell carcinoma risk in a low arsenic exposure area. Toxicol Appl Pharmacol 257(3): 349-355, 2011. DOI: 10.1016/j.taap.2011.09.018
    OpenUrlCrossRefPubMed
  14. ↵
    1. Huang CY,
    2. Huang SP,
    3. Hsueh YM,
    4. Chen LC,
    5. Lu TL,
    6. Bao BY
    : Genetic analysis identifies the role of HLF in renal cell carcinoma. Cancer Genomics Proteomics 17(6): 827-833, 2020. DOI: 10.21873/cgp.20236
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. 1000 Genomes Project Consortium,
    2. Abecasis GR,
    3. Auton A,
    4. Brooks LD,
    5. DePristo MA,
    6. Durbin RM,
    7. Handsaker RE,
    8. Kang HM,
    9. Marth GT,
    10. McVean GA
    : An integrated map of genetic variation from 1,092 human genomes. Nature 491(7422): 56-65, 2012. DOI: 10.1038/nature11632
    OpenUrlCrossRefPubMed
  16. ↵
    1. Li CY,
    2. Huang SP,
    3. Chen YT,
    4. Wu HE,
    5. Cheng WC,
    6. Huang CY,
    7. Yu CC,
    8. Lin VC,
    9. Geng JH,
    10. Lu TL,
    11. Bao BY
    : TNFRSF13B is a potential contributor to prostate cancer. Cancer Cell Int 22(1): 180, 2022. DOI: 10.1186/s12935-022-02590-2
    OpenUrlCrossRef
  17. ↵
    1. Chang HH,
    2. Lee CH,
    3. Chen YT,
    4. Huang CY,
    5. Yu CC,
    6. Lin VC,
    7. Geng JH,
    8. Lu TL,
    9. Huang SP,
    10. Bao BY
    : Genetic analysis reveals the prognostic significance of the DNA mismatch repair gene MSH2 in advanced prostate cancer. Cancers (Basel) 14(1): 223, 2022. DOI: 10.3390/cancers14010223
    OpenUrlCrossRefPubMed
  18. ↵
    1. Ward LD,
    2. Kellis M
    : HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res 44(D1): D877-D881, 2016. DOI: 10.1093/nar/gkv1340
    OpenUrlCrossRefPubMed
  19. ↵
    1. GTEx Consortium
    : The Genotype-Tissue Expression (GTEx) project. Nat Genet 45(6): 580-585, 2013. DOI: 10.1038/ng.2653
    OpenUrlCrossRefPubMed
  20. ↵
    1. Storey JD,
    2. Tibshirani R
    : Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 100(16): 9440-9445, 2003. DOI: 10.1073/pnas.1530509100
    OpenUrlAbstract/FREE Full Text
  21. ↵
    1. Wang Y,
    2. Song F,
    3. Zhang B,
    4. Zhang L,
    5. Xu J,
    6. Kuang D,
    7. Li D,
    8. Choudhary MNK,
    9. Li Y,
    10. Hu M,
    11. Hardison R,
    12. Wang T,
    13. Yue F
    : The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biol 19(1): 151, 2018. DOI: 10.1186/s13059-018-1519-9
    OpenUrlCrossRefPubMed
  22. ↵
    1. Bedard K,
    2. Krause K
    : The NOX family of ROS-generating NADPH oxidases: physiology and pathophysiology. Physiol Rev 87(1): 245-313, 2007. DOI: 10.1152/physrev.00044.2005
    OpenUrlCrossRefPubMed
  23. ↵
    1. Wang HP,
    2. Wang X,
    3. Gong LF,
    4. Chen WJ,
    5. Hao Z,
    6. Feng SW,
    7. Wu YB,
    8. Ye T,
    9. Cai YK
    : Nox1 promotes colon cancer cell metastasis via activation of the adam17 pathway. Eur Rev Med Pharmacol Sci 20(21): 4474-4481, 2016.
    OpenUrlPubMed
  24. ↵
    1. Aurelius J,
    2. Thorén FB,
    3. Akhiani AA,
    4. Brune M,
    5. Palmqvist L,
    6. Hansson M,
    7. Hellstrand K,
    8. Martner A
    : Monocytic AML cells inactivate antileukemic lymphocytes: role of NADPH oxidase/gp91(phox) expression and the PARP-1/PAR pathway of apoptosis. Blood 119(24): 5832-5837, 2012. DOI: 10.1182/blood-2011-11-391722
    OpenUrlAbstract/FREE Full Text
  25. ↵
    1. Adane B,
    2. Ye H,
    3. Khan N,
    4. Pei S,
    5. Minhajuddin M,
    6. Stevens BM,
    7. Jones CL,
    8. D’Alessandro A,
    9. Reisz JA,
    10. Zaberezhnyy V,
    11. Gasparetto M,
    12. Ho TC,
    13. Kelly KK,
    14. Myers JR,
    15. Ashton JM,
    16. Siegenthaler J,
    17. Kume T,
    18. Campbell EL,
    19. Pollyea DA,
    20. Becker MW,
    21. Jordan CT
    : The hematopoietic oxidase NOX2 regulates self-renewal of leukemic stem cells. Cell Rep 27(1): 238-254.e6, 2019. DOI: 10.1016/j.celrep.2019.03.009
    OpenUrlCrossRef
  26. ↵
    1. Kim S,
    2. Hur DY,
    3. Hong S,
    4. Kim JH
    : EBV-encoded EBNA1 regulates cell viability by modulating miR34a-NOX2-ROS signaling in gastric cancer cells. Biochem Biophys Res Commun 494(3-4): 550-555, 2017. DOI: 10.1016/j.bbrc.2017.10.095
    OpenUrlCrossRefPubMed
  27. ↵
    1. Carnesecchi S,
    2. Carpentier JL,
    3. Foti M,
    4. Szanto I
    : Insulin-induced vascular endothelial growth factor expression is mediated by the nadph oxidase nox3. Exp Cell Res 312(17): 3413-3424, 2006. DOI: 10.1016/j.yexcr.2006.07.003
    OpenUrlCrossRefPubMed
  28. ↵
    1. Fitzgerald JP,
    2. Nayak B,
    3. Shanmugasundaram K,
    4. Friedrichs W,
    5. Sudarshan S,
    6. Eid AA,
    7. DeNapoli T,
    8. Parekh DJ,
    9. Gorin Y,
    10. Block K
    : Nox4 mediates renal cell carcinoma cell invasion through hypoxia-induced interleukin 6- and 8- production. PLoS One 7(1): e30712, 2012. DOI: 10.1371/journal.pone.0030712
    OpenUrlCrossRefPubMed
  29. ↵
    1. Shono T,
    2. Yokoyama N,
    3. Uesaka T,
    4. Kuroda J,
    5. Takeya R,
    6. Yamasaki T,
    7. Amano T,
    8. Mizoguchi M,
    9. Suzuki SO,
    10. Niiro H,
    11. Miyamoto K,
    12. Akashi K,
    13. Iwaki T,
    14. Sumimoto H,
    15. Sasaki T
    : Enhanced expression of nadph oxidase nox4 in human gliomas and its roles in cell proliferation and survival. Int J Cancer 123(4): 787-792, 2008. DOI: 10.1002/ijc.23569
    OpenUrlCrossRefPubMed
  30. ↵
    1. Yamaura M,
    2. Mitsushita J,
    3. Furuta S,
    4. Kiniwa Y,
    5. Ashida A,
    6. Goto Y,
    7. Shang WH,
    8. Kubodera M,
    9. Kato M,
    10. Takata M,
    11. Saida T,
    12. Kamata T
    : Nadph oxidase 4 contributes to transformation phenotype of melanoma cells by regulating g2-m cell cycle progression. Cancer Res 69(6): 2647-2654, 2009. DOI: 10.1158/0008-5472.CAN-08-3745
    OpenUrlAbstract/FREE Full Text
  31. ↵
    1. Block K,
    2. Gorin Y,
    3. Hoover P,
    4. Williams P,
    5. Chelmicki T,
    6. Clark RA,
    7. Yoneda T,
    8. Abboud HE
    : Nad(p)h oxidases regulate hif-2alpha protein expression. J Biol Chem 282(11): 8019-8026, 2007. DOI: 10.1074/jbc.M611569200
    OpenUrlAbstract/FREE Full Text
  32. ↵
    1. Castaldo SA,
    2. da Silva AP,
    3. Matos A,
    4. Inacio A,
    5. Bicho M,
    6. Medeiros R,
    7. Alho I,
    8. Bicho MC
    : The role of cyba (p22phox) and catalase genetic polymorphisms and their possible epistatic interaction in cervical cancer. Tumour Biol 36(2): 909-914, 2015. DOI: 10.1007/s13277-014-2714-2
    OpenUrlCrossRef
  33. ↵
    1. Zhu L,
    2. Miao B,
    3. Dymerska D,
    4. Kuswik M,
    5. Bueno-Martinez E,
    6. Sanoguera-Miralles L,
    7. Velasco EA,
    8. Paramasivam N,
    9. Schlesner M,
    10. Kumar A,
    11. Yuan Y,
    12. Lubinski J,
    13. Bandapalli OR,
    14. Hemminki K,
    15. Forsti A
    : Germline variants of cyba and trpm4 predispose to familial colorectal cancer. Cancers (Basel) 14(3): 670, 2022. DOI: 10.3390/cancers14030670
    OpenUrlCrossRef
  34. ↵
    1. Zhou H,
    2. Chen M,
    3. Zhu Y,
    4. Wang B,
    5. Liu XN,
    6. Zuo Z,
    7. Tang FY
    : Polymorphisms in nadph oxidase cyba gene modify the risk of esrd in patients with chronic glomerulonephritis. Ren Fail 38(2): 262-267, 2016. DOI: 10.3109/0886022X.2015.1117905
    OpenUrlCrossRef
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Cancer Genomics - Proteomics: 20 (5)
Cancer Genomics & Proteomics
Vol. 20, Issue 5
September-October 2023
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CYBA as a Potential Biomarker for Renal Cell Carcinoma: Evidence from an Integrated Genetic Analysis
CHI-FEN CHANG, SHU-PIN HUANG, YU-MEI HSUEH, PEI-LING CHEN, CHENG-HSUEH LEE, JIUN-HUNG GENG, CHAO-YUAN HUANG, BO-YING BAO
Cancer Genomics & Proteomics Sep 2023, 20 (5) 469-475; DOI: 10.21873/cgp.20398

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CYBA as a Potential Biomarker for Renal Cell Carcinoma: Evidence from an Integrated Genetic Analysis
CHI-FEN CHANG, SHU-PIN HUANG, YU-MEI HSUEH, PEI-LING CHEN, CHENG-HSUEH LEE, JIUN-HUNG GENG, CHAO-YUAN HUANG, BO-YING BAO
Cancer Genomics & Proteomics Sep 2023, 20 (5) 469-475; DOI: 10.21873/cgp.20398
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Keywords

  • Renal cell carcinoma
  • NADPH oxidase
  • single-nucleotide polymorphism
  • differentially expressed gene
  • prognosis
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