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Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer

BACKGROUND: Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear. METHODS: Data fr...

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Autores principales: Patel, Neal, Hakansson, Alexander, Ohtake, Shinji, Muraki, Peter, Proudfout, James A., Liu, Yang, Webber, Lisa, Ibarra, Arkaitz, Liu, Vinnie Y. T., Davicioni, Elai, Chamie, Karim, Pantuck, Allan, Shuch, Brian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028022/
https://www.ncbi.nlm.nih.gov/pubmed/36397716
http://dx.doi.org/10.1002/cam4.5399
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author Patel, Neal
Hakansson, Alexander
Ohtake, Shinji
Muraki, Peter
Proudfout, James A.
Liu, Yang
Webber, Lisa
Ibarra, Arkaitz
Liu, Vinnie Y. T.
Davicioni, Elai
Chamie, Karim
Pantuck, Allan
Shuch, Brian
author_facet Patel, Neal
Hakansson, Alexander
Ohtake, Shinji
Muraki, Peter
Proudfout, James A.
Liu, Yang
Webber, Lisa
Ibarra, Arkaitz
Liu, Vinnie Y. T.
Davicioni, Elai
Chamie, Karim
Pantuck, Allan
Shuch, Brian
author_sort Patel, Neal
collection PubMed
description BACKGROUND: Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear. METHODS: Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA‐seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease‐free status was the primary endpoint assessed. RESULTS: SSIGN and RS were calculated for 428 patients with non‐metastatic ccRCC. SSIGN low‐, intermediate‐, and high‐risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3‐year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease‐free status (sub‐distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00–1.43)], p = 0.05). By risk groups, RS further risk stratified the SSIGN intermediate‐risk group (sHR 2.22 [95% CI 1.10–4.50], p = 0.03). SSIGN intermediate‐risk patients with low and high RS had a 3‐year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination. CONCLUSIONS: Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate‐risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted.
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spelling pubmed-100280222023-03-22 Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer Patel, Neal Hakansson, Alexander Ohtake, Shinji Muraki, Peter Proudfout, James A. Liu, Yang Webber, Lisa Ibarra, Arkaitz Liu, Vinnie Y. T. Davicioni, Elai Chamie, Karim Pantuck, Allan Shuch, Brian Cancer Med Research Articles BACKGROUND: Risk stratification of kidney cancer patients after nephrectomy may tailor surveillance intensity and selection for adjuvant therapy. Transcriptomic approaches are effective in predicting recurrence, but whether they add value to clinicopathologic models remains unclear. METHODS: Data from patients with clear cell renal cell carcinoma (ccRCC) was downloaded from The Cancer Genome Atlas. Clinicopathologic variables were used to calculate SSIGN (stage, size, grade, and necrosis) scores. The 16 gene recurrence score (RS) signature was generated using RNA‐seq data. Transcriptomic risk groups were calculated using the original thresholds. SSIGN groups were divided into low, intermediate, and high risk. Disease‐free status was the primary endpoint assessed. RESULTS: SSIGN and RS were calculated for 428 patients with non‐metastatic ccRCC. SSIGN low‐, intermediate‐, and high‐risk groups demonstrated 2.7%, 15.2%, and 27.5%, 3‐year recurrence risk, respectively. On multivariable analysis, the RS was associated with disease‐free status (sub‐distribution hazard ratio (sHR) 1.43 per 25 RS [95% CI (1.00–1.43)], p = 0.05). By risk groups, RS further risk stratified the SSIGN intermediate‐risk group (sHR 2.22 [95% CI 1.10–4.50], p = 0.03). SSIGN intermediate‐risk patients with low and high RS had a 3‐year recurrence rate of 8.0% and 25.2%, respectively. Within this risk group, the area under the curve (AUC) at 3 years was 0.69 for SSIGN, 0.74 for RS, and 0.78 for their combination. CONCLUSIONS: Transcriptomic recurrence scores improve risk prediction even when controlling for clinicopathologic factors. Utility may be best suited for intermediate‐risk patients who have heterogeneous outcomes and further refinement for clinical utility is warranted. John Wiley and Sons Inc. 2022-11-17 /pmc/articles/PMC10028022/ /pubmed/36397716 http://dx.doi.org/10.1002/cam4.5399 Text en © 2022 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Patel, Neal
Hakansson, Alexander
Ohtake, Shinji
Muraki, Peter
Proudfout, James A.
Liu, Yang
Webber, Lisa
Ibarra, Arkaitz
Liu, Vinnie Y. T.
Davicioni, Elai
Chamie, Karim
Pantuck, Allan
Shuch, Brian
Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
title Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
title_full Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
title_fullStr Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
title_full_unstemmed Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
title_short Transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
title_sort transcriptomic recurrence score improves recurrence prediction for surgically treated patients with intermediate‐risk clear cell kidney cancer
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10028022/
https://www.ncbi.nlm.nih.gov/pubmed/36397716
http://dx.doi.org/10.1002/cam4.5399
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