Research Papers:
Diagnostic and prognostic biomarker potential of kallikrein family genes in different cancer types
PDF | HTML | Supplementary Files | How to cite
Metrics: PDF 2504 views | HTML 4121 views | ?
Abstract
Prashant D. Tailor1,2, Sai Karthik Kodeboyina2, Shan Bai2, Nikhil Patel4, Shruti Sharma2, Akshay Ratnani1,2, John A. Copland5, Jin-Xiong She2 and Ashok Sharma2,3
1Medical College of Georgia, Augusta University, Augusta, GA, USA
2Center for Biotechnology and Genomic Medicine, Augusta University, Augusta, GA, USA
3Department of Population Health Sciences, Augusta University, Augusta, GA, USA
4Department of Pathology, Augusta University, Augusta, GA, USA
5Mayo Clinic, Jacksonville, FL, USA
Correspondence to:
Ashok Sharma, email: [email protected]
Keywords: cancer; TCGA; kallikreins; gene expression; prognosis
Received: September 21, 2017 Accepted: March 06, 2018 Published: April 03, 2018
ABSTRACT
Purpose: The aim of this study was to compare and contrast the expression of all members of the Kallikrein (KLK) family of genes across 15 cancer types and to evaluate their utility as diagnostic and prognostic biomarkers.
Results: Severe alterations were found in the expression of different Kallikrein genes across various cancers. Interestingly, renal clear cell and papillary carcinomas have similar kallikrein expression profiles, whereas, chromophobe renal cell carcinoma has a unique expression profile. Several KLK genes have excellent biomarker potential (AUC > 0.90) for chromophobe renal cell carcinoma (KLK2, KLK3, KLK4, KLK7, KLK15), renal papillary carcinoma (KLK1, KLK6, KLK7), clear cell renal cell carcinoma (KLK1, KLK6), thyroid carcinoma (KLK2, KLK4, KLK13, KLK15) and colon adenocarcinoma (KLK6, KLK7, KLK8, KLK10). Several KLK genes were significantly associated with mortality in clear cell renal cell carcinoma (KLK2: HR = 1.69; KLK4: HR = 1.63; KLK8: HR = 1.71; KLK10: HR = 2.12; KLK11: HR = 1.76; KLK14: HR = 1.86), papillary renal cell carcinoma (KLK6: HR = 3.38, KLK7: HR = 2.50), urothelial bladder carcinoma (KLK5: HR = 1.89, KLK6: HR = 1.71, KLK8: HR = 1.60), and hepatocellular carcinoma (KLK13: HR = 1.75).
Methods: The RNA-seq gene expression data were downloaded from The Cancer Genome Atlas (TCGA). Statistical analyses, including differential expression analysis, receiver operating characteristic curves and survival analysis (Cox proportional-hazards regression models) were performed.
Conclusions: A comprehensive analysis revealed the changes in the expression of different KLK genes associated with specific cancers and highlighted their potential as a diagnostic and prognostic tool.

PII: 24947