REFERENCES

1. Rini BI, Campbell SC, Escudier B. Renal cell carcinoma. Lancet 2009;373:1119-32.

2. Ljungberg B, Bensalah K, Canfield S, et al. EAU guidelines on renal cell carcinoma: 2014 update. Eur Urol 2015;67:913-24.

3. Wolff I, May M, Hoschke B, et al. Do we need new high-risk criteria for surgically treated renal cancer patients to improve the outcome of future clinical trials in the adjuvant setting? Results of a comprehensive analysis based on the multicenter CORONA database. Eur J Surg Oncol 2016;42:744-50.

4. Motzer RJ, Hutson TE, McCann L, Deen K, Choueiri TK. Overall survival in renal-cell carcinoma with pazopanib versus sunitinib. N Engl J Med 2014;370:1769-70.

5. Aweys H, Lewis D, Sheriff M, et al. Renal cell cancer - insights in drug resistance mechanisms. Anticancer Res 2023;43:4781-92.

6. Hsieh JJ, Purdue MP, Signoretti S, et al. Renal cell carcinoma. Nat Rev Dis Primers 2017;3:17009.

7. Choueiri TK, Motzer RJ. Systemic therapy for metastatic renal-cell carcinoma. N Engl J Med 2017;376:354-66.

8. Motzer RJ, Escudier B, McDermott DF, et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med 2015;373:1803-13.

9. Brown JE, Royle KL, Gregory W, et al. Temporary treatment cessation versus continuation of first-line tyrosine kinase inhibitor in patients with advanced clear cell renal cell carcinoma (STAR): an open-label, non-inferiority, randomised, controlled, phase 2/3 trial. Lancet Oncol 2023;24:213-27.

10. Yang Y, Hsu PJ, Chen YS, Yang YG. Dynamic transcriptomic m6A decoration: writers, erasers, readers and functions in RNA metabolism. Cell Res 2018;28:616-24.

11. Paramasivam A, Priyadharsini JV, Raghunandhakumar S. Implications of m6A modification in autoimmune disorders. Cell Mol Immunol 2020;17:550-1.

12. Paramasivam A, Vijayashree Priyadharsini J. Novel insights into m6A modification in circular RNA and implications for immunity. Cell Mol Immunol 2020;17:668-9.

13. Paramasivam A, Vijayashree Priyadharsini J, Raghunandhakumar S. N6-adenosine methylation (m6A): a promising new molecular target in hypertension and cardiovascular diseases. Hypertens Res 2020;43:153-4.

14. Fu Y, Dominissini D, Rechavi G, He C. Gene expression regulation mediated through reversible m6A RNA methylation. Nat Rev Genet 2014;15:293-306.

15. Tong J, Cao G, Zhang T, et al. m6A mRNA methylation sustains Treg suppressive functions. Cell Res 2018;28:253-6.

16. Pinello N, Sun S, Wong JJ. Aberrant expression of enzymes regulating m6A mRNA methylation: implication in cancer. Cancer Biol Med 2018;15:323-34.

17. Guo L, Yang H, Zhou C, Shi Y, Huang L, Zhang J. N6-methyladenosine RNA modification in the tumor immune microenvironment: novel implications for immunotherapy. Front Immunol 2021;12:773570.

18. Wang P, Wang X, Zheng L, Zhuang C. Gene signatures and prognostic values of m6A regulators in hepatocellular carcinoma. Front Genet 2020;11:540186.

19. Zhao R, Li B, Zhang S, et al. The N6-methyladenosine-modified pseudogene HSPA7 correlates with the tumor microenvironment and predicts the response to immune checkpoint therapy in glioblastoma. Front Immunol 2021;12:653711.

20. Xu W, Tian X, Liu W, et al. m6A regulator-mediated methylation modification model predicts prognosis, tumor microenvironment characterizations and response to immunotherapies of clear cell renal cell carcinoma. Front Oncol 2021;11:709579.

21. Tibshirani R. Regression shrinkage and selection via the lasso: a retrospective. J R Stat Soc Series B 2011;73:273-82.

22. Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res 2004;10:7252-9.

23. Jiang P, Gu S, Pan D, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med 2018;24:1550-8.

24. Chen B, Khodadoust MS, Liu CL, Newman AM, Alizadeh AA. Profiling tumor infiltrating immune cells with CIBERSORT. In: von Stechow L, editor. Cancer Systems Biology. New York: Springer; 2018. pp. 243-59.

25. Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol 2017;14:749-62.

26. Zheng J, Yu H, Batur J, et al. A multicenter study to develop a non-invasive radiomic model to identify urinary infection stone in vivo using machine-learning. Kidney Int 2021;100:870-80.

27. Cai J, Zheng J, Shen J, et al. A radiomics model for predicting the response to bevacizumab in brain necrosis after radiotherapy. Clin Cancer Res 2020;26:5438-47.

28. Zheng J, Kong J, Wu S, et al. Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach. Cancer 2019;125:4388-98.

29. van Griethuysen JJM, Fedorov A, Parmar C, et al. Computational radiomics system to decode the radiographic phenotype. Cancer Res 2017;77:e104-7.

30. Cao G, Li HB, Yin Z, Flavell RA. Recent advances in dynamic m6A RNA modification. Open Biol 2016;6:160003.

31. Wang X, Feng J, Xue Y, et al. Structural basis of N6-adenosine methylation by the METTL3-METTL14 complex. Nature 2016;534:575-8.

32. Liu J, Yue Y, Han D, et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation. Nat Chem Biol 2014;10:93-5.

33. Gundert L, Strick A, von Hagen F, et al. Systematic expression analysis of m6A RNA methyltransferases in clear cell renal cell carcinoma. BJUI Compass 2021;2:402-11.

34. Xu T, Gao S, Ruan H, et al. METTL14 acts as a potential regulator of tumor immune and progression in clear cell renal cell carcinoma. Front Genet 2021;12:609174.

35. Cui Q, Shi H, Ye P, et al. m6A RNA methylation regulates the self-renewal and tumorigenesis of glioblastoma stem cells. Cell Rep 2017;18:2622-34.

36. Weng H, Huang H, Wu H, et al. METTL14 inhibits hematopoietic stem/progenitor differentiation and promotes leukemogenesis via mRNA m6A modification. Cell Stem Cell 2018;22:191-205.e9.

37. Xie W, Wei L, Guo J, Guo H, Song X, Sheng X. Physiological functions of Wilms’ tumor 1-associating protein and its role in tumourigenesis. J Cell Biochem 2019;120:10884-92.

38. Qu N, Qin S, Zhang X, et al. Multiple m6A RNA methylation modulators promote the malignant progression of hepatocellular carcinoma and affect its clinical prognosis. BMC Cancer 2020;20:165.

39. Qian JY, Gao J, Sun X, et al. KIAA1429 acts as an oncogenic factor in breast cancer by regulating CDK1 in an N6-methyladenosine-independent manner. Oncogene 2019;38:6123-41.

40. Li J, Cao J, Liang C, Deng R, Li P, Tian J. The analysis of N6-methyladenosine regulators impacting the immune infiltration in clear cell renal cell carcinoma. Med Oncol 2022;39:41.

41. Xing Q, Luan J, Liu S, Ma L, Wang Y. Six RNA binding proteins (RBPs) related prognostic model predicts overall survival for clear cell renal cell carcinoma and is associated with immune infiltration. Bosn J Basic Med Sci 2022;22:435-52.

42. Xu X, Yu Y, Zong K, Lv P, Gu Y. Up-regulation of IGF2BP2 by multiple mechanisms in pancreatic cancer promotes cancer proliferation by activating the PI3K/Akt signaling pathway. J Exp Clin Cancer Res 2019;38:497.

43. Long JC, Caceres JF. The SR protein family of splicing factors: master regulators of gene expression. Biochem J 2009;417:15-27.

44. Merdzhanova G, Edmond V, De Seranno S, et al. E2F1 controls alternative splicing pattern of genes involved in apoptosis through upregulation of the splicing factor SC35. Cell Death Differ 2008;15:1815-23.

45. Haupt S, Berger M, Goldberg Z, Haupt Y. Apoptosis - the p53 network. J Cell Sci 2003;116:4077-85.

46. Kędzierska H, Popławski P, Hoser G, et al. Decreased expression of SRSF2 splicing factor inhibits apoptotic pathways in renal cancer. Int J Mol Sci 2016;17:1598.

47. Garner E, Martinon F, Tschopp J, Beard P, Raj K. Cells with defective p53-p21-pRb pathway are susceptible to apoptosis induced by p84N5 via caspase-6. Cancer Res 2007;67:7631-7.

48. Mercer J, Figg N, Stoneman V, Braganza D, Bennett MR. Endogenous p53 protects vascular smooth muscle cells from apoptosis and reduces atherosclerosis in ApoE knockout mice. Circ Res 2005;96:667-74.

49. Amin AR, Thakur VS, Gupta K, et al. Restoration of p53 functions protects cells from concanavalin A-induced apoptosis. Mol Cancer Ther 2010;9:471-9.

50. Haitel A, Wiener HG, Baethge U, Marberger M, Susani M. mdm2 expression as a prognostic indicator in clear cell renal cell carcinoma: comparison with p53 overexpression and clinicopathological parameters. Clin Cancer Res 2000;6:1840-4.

51. Lasorsa F, Rutigliano M, Milella M, et al. Cancer stem cells in renal cell carcinoma: origins and biomarkers. Int J Mol Sci 2023;24:13179.

52. Lucarelli G, Netti GS, Rutigliano M, et al. MUC1 expression affects the immunoflogosis in renal cell carcinoma microenvironment through complement system activation and immune infiltrate modulation. Int J Mol Sci 2023;24:4814.

53. Lucarelli G, Rutigliano M, Loizzo D, et al. MUC1 tissue expression and its soluble form CA15-3 identify a clear cell renal cell carcinoma with distinct metabolic profile and poor clinical outcome. Int J Mol Sci 2022;23:13968.

Journal of Cancer Metastasis and Treatment
ISSN 2454-2857 (Online) 2394-4722 (Print)

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/

Portico

All published articles are preserved here permanently:

https://www.portico.org/publishers/oae/