In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment

Prostate cancer is one of the world’s leading causes of cancer-related mortalities. There are several diagnostic tools and treatment plans readily available, such as prostate-specific antigen (PSA) tests and androgen deprivation therapy (ADT). However, these all come with their setbacks. Therefore,...

Full description

Saved in:
Bibliographic Details
Main Authors: Trevor Kenneth Wilson, Oliver Tendayi Zishiri
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Current Issues in Molecular Biology
Subjects:
Online Access:https://www.mdpi.com/1467-3045/47/4/292
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849714328377229312
author Trevor Kenneth Wilson
Oliver Tendayi Zishiri
author_facet Trevor Kenneth Wilson
Oliver Tendayi Zishiri
author_sort Trevor Kenneth Wilson
collection DOAJ
description Prostate cancer is one of the world’s leading causes of cancer-related mortalities. There are several diagnostic tools and treatment plans readily available, such as prostate-specific antigen (PSA) tests and androgen deprivation therapy (ADT). However, these all come with their setbacks. Therefore, alternatives must be developed to assist those patients for whom standardised treatment does not work. There are many genes whose mutations lead to prostate cancer development and progression. These mutations may also lead to higher resistance/vulnerability to specific therapies. In this in silico study, four genes, AR, ATM, PTEN, and TP53, were assessed, and mutations were chosen for qPCR primer and probe design. A total of 28 mutations were selected from the four genes, with PTEN (13) making up the majority of the mutations, followed by TP53 (six), then ATM (five), and finally, AR (four). All primer/probe combinations fall within the desired ranges for this study and provide valuable additions to prostate cancer’s diagnostic/prognostic landscape. These assays will require further experimental validation, but they are the first step toward a better future in the fight against this horrible disease.
format Article
id doaj-art-c77c8a3e34604cb69661c577e70978ad
institution DOAJ
issn 1467-3037
1467-3045
language English
publishDate 2025-04-01
publisher MDPI AG
record_format Article
series Current Issues in Molecular Biology
spelling doaj-art-c77c8a3e34604cb69661c577e70978ad2025-08-20T03:13:44ZengMDPI AGCurrent Issues in Molecular Biology1467-30371467-30452025-04-0147429210.3390/cimb47040292In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised TreatmentTrevor Kenneth Wilson0Oliver Tendayi Zishiri1Discipline of Genetics, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban 4000, South AfricaDiscipline of Genetics, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Durban 4000, South AfricaProstate cancer is one of the world’s leading causes of cancer-related mortalities. There are several diagnostic tools and treatment plans readily available, such as prostate-specific antigen (PSA) tests and androgen deprivation therapy (ADT). However, these all come with their setbacks. Therefore, alternatives must be developed to assist those patients for whom standardised treatment does not work. There are many genes whose mutations lead to prostate cancer development and progression. These mutations may also lead to higher resistance/vulnerability to specific therapies. In this in silico study, four genes, AR, ATM, PTEN, and TP53, were assessed, and mutations were chosen for qPCR primer and probe design. A total of 28 mutations were selected from the four genes, with PTEN (13) making up the majority of the mutations, followed by TP53 (six), then ATM (five), and finally, AR (four). All primer/probe combinations fall within the desired ranges for this study and provide valuable additions to prostate cancer’s diagnostic/prognostic landscape. These assays will require further experimental validation, but they are the first step toward a better future in the fight against this horrible disease.https://www.mdpi.com/1467-3045/47/4/292prostate cancerdiagnosisprognosispersonalised treatmentgenetic mutationsqPCR assay
spellingShingle Trevor Kenneth Wilson
Oliver Tendayi Zishiri
In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment
Current Issues in Molecular Biology
prostate cancer
diagnosis
prognosis
personalised treatment
genetic mutations
qPCR assay
title In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment
title_full In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment
title_fullStr In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment
title_full_unstemmed In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment
title_short In Silico Design of Quantitative Polymerase Chain Reaction (qPCR) Assay Probes for Prostate Cancer Diagnosis, Prognosis, and Personalised Treatment
title_sort in silico design of quantitative polymerase chain reaction qpcr assay probes for prostate cancer diagnosis prognosis and personalised treatment
topic prostate cancer
diagnosis
prognosis
personalised treatment
genetic mutations
qPCR assay
url https://www.mdpi.com/1467-3045/47/4/292
work_keys_str_mv AT trevorkennethwilson insilicodesignofquantitativepolymerasechainreactionqpcrassayprobesforprostatecancerdiagnosisprognosisandpersonalisedtreatment
AT olivertendayizishiri insilicodesignofquantitativepolymerasechainreactionqpcrassayprobesforprostatecancerdiagnosisprognosisandpersonalisedtreatment