Background: Splice-disrupt genomic variants are one of the causes of cancer-causing errors in gene expression. Little is known about splice-disrupt genomic variants. Methods and results: Here, pattern of splice-disrupt variants was investigated using 21,842,764 genomic variants in different types of prostate cancer. A particular attention was paid to genomic locations of splice-disrupt variants on target genes. HLA-A in prostate cancer, MSR1 in familial prostate cancer, and EGFR in both castration-resistant prostate cancer and metastatic castration-resistant had the highest allele frequencies of splice-disrupt variations. Some splice-disrupt variants, located on coding sequences of NCOR2, PTPRC, and CRP, were solely present in the advanced metastatic castration-resistant prostate cancer. High-risk splice-disrupt variants were identified based on computationally calculated Polymorphism Phenotyping (PolyPhen), Sorting Intolerant From Tolerant (SIFT), and Genomic Evolutionary Rate Profiling (GERP) + + scores as well as the recorded clinical significance in dbSNP database of NCBI. Functional annotation of damaging splice-disrupt variants highlighted important cancer-associated functions, including endocrine resistance, lipid metabolic process, steroid metabolic process, regulation of mitotic cell cycle, and regulation of metabolic process. This is the first study that profiles the splice-disrupt genomic variants and their target genes in prostate cancer. Literature mining based variant analysis highlighted the importance of rs1800716 variant, located on the CYP2D6 gene, involved in a range of important functions, such as RNA spicing, drug interaction, death, and urotoxicity. Conclusions: This is the first study that profiles the splice-disrupt genomic variants and their target genes in different types of prostate cancer. Unravelling alternative splicing opens a new avenue towards the establishment of new diagnostic and prognostic markers for prostate cancer progression and metastasis.
Funding
This research was supported by use of the Nectar Research Cloud, a collaborative Australian research platform supported by the Australian Research Data Commons (ARDC) and National Collaborative Research Infrastructure Strategy (NCRIS). Additionally, this work was supported by resources provided by the Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia.
History
Publication Date
2022-06-01
Journal
Molecular Biology Reports
Volume
49
Issue
6
Pagination
(p. 4237-4246)
Publisher
Springer
ISSN
0301-4851
Rights Statement
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