作者: David J. Clark , Hui Zhang
DOI: 10.1186/S12014-020-09291-W
关键词: Context (language use) 、 Disease 、 Renal cell carcinoma 、 Clinicopathological features 、 Proteomics 、 Patient stratification 、 Computational biology 、 Direct evaluation 、 Transcriptome 、 Medicine
摘要: Renal cell carcinoma is among the top 15 most commonly diagnosed cancers worldwide, comprising multiple sub-histologies with distinct genomic, proteomic, and clinicopathological features. Proteomic methodologies enable detection quantitation of protein profiles associated disease state have been explored to delineate dysregulated cellular processes renal carcinoma. In this review we highlight reports that employed proteomic technologies characterize tissue, blood, urine samples obtained from patients. We describe approaches utilized relate results studies in larger context biology. Moreover, discuss some unmet clinical needs how emerging can seek address them. There has significant progress molecular features carcinoma; however, despite large-scale characterized genomic transcriptomic profiles, curative treatments are still elusive. Proteomics facilitates a direct evaluation functional modules drive pathobiology, resulting would applications diagnostics, patient stratification, identification novel therapeutic interventions.