ArticleWorld journal of surgical oncology2020
A risk stratification model based on four novel biomarkers predicts prognosis for patients with renal cell carcinoma.
Article in World journal of surgical oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Implications of ADP-Ribosylation Factor-Like Protein 4C (ARL4C) in Human Neoplasia With Special Emphasis on Ameloblastoma: A Scoping Review.Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology · 2026Article
- Review
- EFFECTS OF TREATMENT WITH TEMSIROLIMUS VERSUS INTERFERON ALPHA ON SURVIVAL OF PATIENTS WITH METASTATIC RENAL CELL CARCINOMA - SINGLE-CENTER REAL-WORLD EXPERIENCE.Acta clinica Croatica · 2024Article
- Identification of prognostic and therapeutic biomarkers in type 2 papillary renal cell carcinoma.World journal of surgical oncology · 2023Article
- The Effects of circ_000558/miR-1225-5p/ARL4C on Regulating the Proliferation of Renal Cell Carcinoma Cells.Journal of oncology · 2023Article
- ARL4C Regulates the Progression of Clear Cell Renal Cell Carcinoma by Affecting the Wnt/Journal of oncology · 2022Article
- STEAP3 Affects Ferroptosis and Progression of Renal Cell Carcinoma Through the p53/xCT Pathway.Technology in cancer research & treatmentArticle
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate prediction of the prognosis of RCC using a single biomarker is challenging due to the genetic heterogeneity of the disease. However, it is essential to develop an accurate system to allow better patient selection for optimal treatment strategies. ARL4C, ECT2, SOD2, and STEAP3 are novel molecular biomarkers identified in earlier studies as survival-related genes by comprehensive analyses of 43 primary RCC tissues and RCC cell lines.
methodsTo develop a prognostic model based on these multiple biomarkers, the expression of four biomarkers ARL4C, ECT2, SOD2, and STEAP3 in primary RCC tissue were semi-quantitatively investigated by immunohistochemical analysis in an independent cohort of 97 patients who underwent nephrectomy, and the clinical significance of these biomarkers were analyzed by survival analysis using Kaplan-Meier curves. The prognostic model was constructed by calculation of the contribution score to prognosis of each biomarker on Cox regression analysis, and its prognostic performance was validated.
resultsPatients whose tumors had high expression of the individual biomarkers had shorter cancer-specific survival (CSS) from the time of primary nephrectomy. The prognostic model based on four biomarkers segregated the patients into a high- and low-risk scored group according to defined cut-off value. This approach was more robust in predicting CSS compared to each single biomarker alone in the total of 97 patients with RCC. Especially in the 36 metastatic RCC patients, our prognostic model could more accurately predict early events within 2 years of diagnosis of metastasis. In addition, high risk-scored patients with particular strong SOD2 expression had a much worse prognosis in 25 patients with metastatic RCC who were treated with molecular targeting agents.
conclusionsOur findings indicate that a prognostic model based on four novel biomarkers provides valuable data for prediction of clinical prognosis and useful information for considering the follow-up conditions and therapeutic strategies for patients with primary and metastatic RCC.
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