Defining the role of TRIP13 in pancreatic cancer progression: An integrative biology approach.
Introduction
With the highest mortality rate, pancreatic cancer is one of the most aggressive forms of cancer. It is expected that by 2030, pancreatic cancer will become the second leading cause of cancer related deaths in the United States alone. As of today, there are very limited biomarkers available on diagnostic panels for specific early screenings of pancreatic cancer. In the current study we utilized datamining methods to analyze bioinformatic data related to TRIP13 such as: differential expression levels of TRIP13 in various cancers, correlation of TRIP13 expression in different pancreatic cancer stages, examined the correlation between TRIP13 and common cancer genes, and analyzed the overall survival rate in relation to TRIP13 expression. Additionally, an integrated approach was opted, and molecular biology methods were utilized to quantify the expression of TRIP13 in various progressive pancreatic cancer cell lines and human pancreatic tissue cores. This study has uncovered the role of TRIP13 on a transcriptional and translational level, which may lead to the discovery of TRIP13 as a specific biomarker for early pancreatic cancer detection, enhancing patient prognosis, and boosting targeted therapies in clinical settings.
Methods
The current study was conducted using an integrated biology approach. Here we have utilized various bioinformatics tools like ConSurf server for the TRIP13 protein structure elucidation. GTEx server was applied for the protein expression coverage, tissue specific gene expression analysis, and GEPIA2 was used for the pathological staging, disease-free survival plot, TRIP13 isoforms and phosphorylation sites. LinkedOmics employed for functional enrichment. Molecular biology techniques like qPCR, western blotting and IHC techniques were used to integrate and validate bioinformatics data.
Results
ConSurf server predicted 86 out of 432 amino acids as the highest conserved, and among 86 amino acids around 36 amino acids were exposed, and functional residues. Most of the highly conserved, exposed, and functional residues are in AAA+ ATPase domain (171-324 aa). The higher expression of TRIP13 has also shown a lower disease-free survival in PanCa and has strong positive association with CEACAM5 and S1004A. According to isoform analysis TRIP13 has total of 7 transcripts, among them, 2 transcripts (ENST00000166345.7 and ENST00000513435.1) of TRIP13 are coding transcripts. TRIP13 also holds various phosphorylation sites (S18, S41, Y56, S74, T183, Y206, S216, T302, S367, S370, S37 & S384). GTEx server was applied to evaluate the mRNA expression level of TRIP13 in disease free conditions. In this analysis TRIP13 showed negligible expression in pancreas, and the rest of the organs had higher expression of TRIP13 in normal condition. To validate differential expression of TRIP13 in important GI cancers, box plot analysis was performed, where we have noticed that pancreatic cancer was showing remarkably higher TRIP13 expression than normal pancreatic tissues. The apparent site of TRIP13 in the pancreatic cell clusters exhibiting the maximum expression was noticed in the fibroblast cells cluster. Molecular biology techniques like qPCR, western blotting, and IHC analysis demonstrated higher expression level of TRIP13 in moderately differentiated cell lines and tumor grades. Finally, the functional enrichment analysis was performed, and it was elucidated that the higher expression of TRIP13 leads to modulation of several important pathways like upregulation of DNA repair machinery, cellular senescence, and viral carcinogenesis.
Conclusion
This study demonstrates that TRIP13 can be a new early diagnostic biomarker for PanCa, and it also has prospective to upgrade the effectiveness of the current biomarker panel. Additionally, the integrated biology approach is announcing a significant prospect for the findings of specific and significant biomarkers not only for PanCa but can also be useful for other malignancies.