G. Aurilio, M. Santoni, A. Cimadamore, E. Verri, R. Montironi
{"title":"Prognostic Biomarkers in Patients with Renal Cell Carcinoma: Where are We Going from Here?","authors":"G. Aurilio, M. Santoni, A. Cimadamore, E. Verri, R. Montironi","doi":"10.37155/2717-5278-0301-1","DOIUrl":null,"url":null,"abstract":"Treatment algorithm in metastatic renal cell carcinoma (RCC) patients has rapidly evolved during the last decade, and determining the prognosis of these patients has become a priority step for correctly planning the treatment. In the present article, we firstly address the most currently used prognostic models and how they have changed the treatment algorithm in routine clinical care; then we assess whether patient selection may be improved in the firstline treatment and the usefulness of a prognostic model following first-line failure; ultimately we culminate in new clinical and molecular prognostic factors under investigation. For this last issue, biomarkers for immunotherapy and angiogenesis inhibitors, as well as biomarkers for liquid analysis and for clinical obesity are presented.","PeriodicalId":348972,"journal":{"name":"Trends in Oncology","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37155/2717-5278-0301-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Treatment algorithm in metastatic renal cell carcinoma (RCC) patients has rapidly evolved during the last decade, and determining the prognosis of these patients has become a priority step for correctly planning the treatment. In the present article, we firstly address the most currently used prognostic models and how they have changed the treatment algorithm in routine clinical care; then we assess whether patient selection may be improved in the firstline treatment and the usefulness of a prognostic model following first-line failure; ultimately we culminate in new clinical and molecular prognostic factors under investigation. For this last issue, biomarkers for immunotherapy and angiogenesis inhibitors, as well as biomarkers for liquid analysis and for clinical obesity are presented.