Urological Cancer Management

Al-Mamari, Said Abdallah; Al-Busaidy, Salim Said

doi:10.1007/978-3-319-16301-7

Cited by 1 publication

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“…In general, the earlier the disease is detected, the better the outlook for treatment and arresting cancer progression in patients. Besides the advances, we have to be aware of the risks and adverse effects on the quality of life related to the over-diagnosis and immediate treatment of benign conditions such as prostatitis, inflammation of the prostate and benign prostatic hyperplasia (BPH), a noncancerous enlargement of the prostate gland 38,39 .…”

Section: Clinical Assessment Of Prostate Cancermentioning

confidence: 99%

Computational analysis of genomic variants affecting predicted microRNA:target interactions in prostate cancer.

Pérez¹,

Andrea²

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Prostate cancer (PCa) is the most common cancer of men in the United States and is third only to lung and colon as a cause of cancer death. Clinical behavior of the disease is variable and the combination of prostate-specific antigen (PSA) screening and Gleason score staging are currently the best available molecular and pathology tools to predict outcomes. Cancer biology research establishes microRNAs (miRNAs) as key molecular components in both normal and pathological states. Thus, elucidating miRNAs perturbed by genomic alterations will expand our understanding of the molecular taxonomy of PCa with the aim to complement current practices in the diagnosis, prognosis, and treatment of the disease. This study reports the computational analysis of genomic variants affecting the seed sequence of five miRNAs, changing the prediction of microRNA:target interactions in PC3, an androgen-independent cell line that closely resembles prostatic small cell neuroendocrine carcinoma (SCNC). Genomic variants were detected via deep-sequencing of PC3 and further computational work focused on mapping changes within the seed sequence of predicted mature miRNAs. Five microRNA candidates (from now on denominated microRNA*) with changes in the g2-g8 seed region were selected: miR-3161*-5p with rs35834266 G>insA; miR-3620*-5p with rs2070960 C>T; miR-1178*-5p with rs7311975 T>G; miR-4804*-5pwith rs266435 C>G; and miR-449c*-3p with rs35770269 A>T. Subsequently, the computational prediction of miRNA*:target interactions revealed 643 new relationships. After functional enrichment analysis of new targets, seven genes were associated with endocrine resistance (ABCB11, CDKN1B, NOTCH2, SHC4, CCND1, SP1, ADCY2) and five genes with endocrine and other factor regulated calcium reabsorption (ATP1A2, ESR1, PRRKCB, AP2B1, SLC8A1) categories. A gene-disease association literature search was performed for each of the aforementioned genes in order to understand if they have been implicated in cancer, where CDKN1B, NOTCH2, CCND1 have been reported to participate in prostate cancer progression. Microarray gene expression analyses showed that few predicted microRNA* targets were underexpressed in untreated PC3 samples versus prostate epithelial cells from the GEO database. However, after assessing the frequency of observed underexpressed genes per candidate microRNA* using a Fisher's exact test, miR-4804*-5p target genes (TNKS and GUCY1A3) were statistically significant. Next steps included the comparison between iii groups of genes subject to non-mutated microRNA and mutated microRNA* regulation using a Kruskal-Wallis non-parametric test. Results were consistent with the microRNA-gene expression regulation model despite the genomic variant in the seed region, nevertheless the effect of miR-3161*-5p, miR-3620*-5p, miR-1178*-5p, miR-4804*-5p, and miR-449c*-3p cannot be predicted solely with the indirect experimental approach that microarray gene expression platforms provide. For this reason, the assessment of recurrent pairwise microRNA-mRNA expression...

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Section: Clinical Assessment Of Prostate Cancermentioning

confidence: 99%

Computational analysis of genomic variants affecting predicted microRNA:target interactions in prostate cancer.

Pérez¹,

Andrea²

View full text Add to dashboard Cite

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Urological Cancer Management

Cited by 1 publication

References 0 publications

Computational analysis of genomic variants affecting predicted microRNA:target interactions in prostate cancer.

Computational analysis of genomic variants affecting predicted microRNA:target interactions in prostate cancer.

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