TT_I_P: Theoretical and Translational Medicine I. Posters
Áron Bartha 1,5, Gyöngyi Munkácsy 1, Péter Nyirády 4, Zsuzsanna Darula 2,3, Éva Klement 2,3, Balázs Győrffy 1,5
1 Department of Bioinformatics Semmelweis University, Budapest, Hungary
2 Single Cell Omics Advanced Core Facility, HCEMM, Szeged Hungary
3 Laboratory of Proteomics Research, BRC, Szeged Hungary
4 Dept. of Urology, Semmelweis University, Budapest, Hungary
5 2nd Department of Pediatrics, Semmelweis University, Budapest, Hungary
Introduction: Clear Cell Renal Cell Carcinoma (ccRCC) is the most common kidney cancer, making up roughly 80% of all renal carcinoma cases. Although patients with localized malignancy have relatively favorable survival rates (93% of patients surpass five-year survival), patients with distant carcinoma have considerably inferior prognosis. Thus, identification of key genes and proteins involved in the initiation and progression of ccRCC could provide valuable information to extend patient survival.
Aims: Here, our aim was to identify novel possible gene expression based biomarkers in patients with ccRCC.
Methods: First, by using in silico discovery datasets form gene chip and RNA-Seq data repositories, we estimated the top over-expressed genes in ccRCC, from patients with paired normal tissue samples as well. We employed RNA sequencing by using pathologically validated ccRCC patients tissue sample pairs to validate the strongest genes. The differential expression was also evaluated using targeted mass spectrometry to get proteome-level expression data as well.
Results: We assembled a sizeable database of 558 renal tissue samples, 414 from NCBI GEO and 144 from TCGA. We used these to uncover the top 30 multi-omic biomarker genes correlated to the pathogenesis of renal clear cell cancer. IGFBP3 (p = 2,17E-12), PLIN2 (p = 1,10E-11), and PFKP (p = 3,24E-12) were the most consistently upregulated genes involved in ccRCC. We collected a set of 162 renal tumor and normal tissue samples, and performed a validation using RNA-Seq and mass spectrometry in these. The independent dataset validated the differential mRNA expression of IGFBP3 (p = 2,75E-11), PLIN2 (p = 4,79E-11), and PFKP (p = 4,76E-05). The proteomic analysis further validated the differential expression of IGFBP3 (p = 2,64E-19), PLIN2 (p = 1,11E-33), and PFKP (p = 8,66E-35).
Conclusions: As today the molecularly targeted therapy of ccRCC is highly limited with only a few agents, our results help to uncover new therapy targets. Furthermore, our results provide comprehensive candidates which might be utilized as protein-based biomarkers in the clinical setting.
Funding: „SUPPORTED BY THE ÚNKP-20-3-II NEW NATIONAL EXCELLENCE PROGRAM OF THE MINISTRY FOR INNOVATION AND TECHNOLOGY FROM THE SOURCE OF THE NATIONAL RESEARCH, DEVELOPMENT AND INNOVATION FUND.” AND EFOP-3.6.3-VEKOP-16-2017-00009
Semmelweis University, Doctoral School of Pathological Sciences