Exploring the genetic differences between primary and metastatic prostate cancer using bioinformatic approaches: a preliminary study / Faris Aizat Ahmad Fajri ... [et al.]

Ahmad Fajri, Faris Aizat and Nazri, Muhammad Amru and Zulkifli, Muhamad Harith and Mohd Fauzi, Fazlin (2022) Exploring the genetic differences between primary and metastatic prostate cancer using bioinformatic approaches: a preliminary study / Faris Aizat Ahmad Fajri ... [et al.]. International Journal of Pharmaceuticals, Nutraceuticals and Cosmetic Science (IJPNaCS), 5 (1). pp. 48-66. ISSN 2682-8146

Abstract

Screening of prostate cancer (PCa) by measuring prostate cancer antigen has proven beneficial in reducing the mortality and progression of prostate cancer. However, its level can be affected if patients are taking certain drugs and/or suffering from certain medical conditions, causing a false negative. This can lead to PCa being undetected, where when untreated can lead to metastatic prostate cancer (MPC). Hence, in this study, genetic differences between PCa and MPC were explored using bioinformatics approaches to predict potential biomarkers for MPC. The study was divided into two parts, where the first involves feature selection and principal component analysis to differentiate PCa and MPC based on mRNA gene expression. Additionally, top 20 mutated genes for MPC were determined using odds ratio (OR). In the second phase, a predictive model was built using outcome of the mRNA gene expression analysis. The results showed that the mRNA expression of 26 identified genes could differentiate between PCa and MPC. This was further corroborated by the predictive model, where a sensitivity and specificity of 0.616 and 0.017 respectively was achieved. While importance is placed on sensitivity over specificity, further improvements involving more data need to be made to increase the specificity rate. Additionally, genes such as PAG24, BOP1 and GRWD1 should be investigated further as both potential biomarkers as well as potential pathways in MPC progression, based on further protein-protein interaction analysis. OR and protein-protein interaction suggests that androgen signalling pathway may crosstalk with NFκB signalling and breast cancer pathway. This preliminary study shows that bioinformatics approaches could aid in understanding MPC, which could lead to the discovery of novel targeted therapy and potential biomarkers.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ahmad Fajri, Faris Aizat
UNSPECIFIED
Nazri, Muhammad Amru
UNSPECIFIED
Zulkifli, Muhamad Harith
UNSPECIFIED
Mohd Fauzi, Fazlin
fazlin5465@uitm.edu.my
Subjects: Q Science > QH Natural history - Biology > Data processing. Bioinformatics
Q Science > QH Natural history - Biology > Genetics
R Medicine > RC Internal Medicine > Neoplasms. Tumors. Oncology
Divisions: Universiti Teknologi MARA, Selangor > Puncak Alam Campus > Faculty of Pharmacy
Journal or Publication Title: International Journal of Pharmaceuticals, Nutraceuticals and Cosmetic Science (IJPNaCS)
UiTM Journal Collections: UiTM Journal > International Journal of Pharmaceuticals, Nutraceuticals and Cosmetic Science (IJPNaCS)
ISSN: 2682-8146
Volume: 5
Number: 1
Page Range: pp. 48-66
Keywords: prostate cancer, metastatic prostate cancer, random forest, principal component analysis, feature selection
Date: 2022
URI: https://ir.uitm.edu.my/id/eprint/70776
Edit Item
Edit Item

Download

[thumbnail of 70776.pdf] Text
70776.pdf

Download (726kB)

ID Number

70776

Indexing

Statistic

Statistic details