Possible prognostic impact of PKCι genetic variants in prostate cancer.

Molecular dynamic simulations PKCι Pathways Prostate cancer

Journal

Cancer cell international
ISSN: 1475-2867
Titre abrégé: Cancer Cell Int
Pays: England
ID NLM: 101139795

Informations de publication

Date de publication:
10 Jan 2024
Historique:
received: 08 10 2023
accepted: 17 12 2023
medline: 11 1 2024
pubmed: 11 1 2024
entrez: 10 1 2024
Statut: epublish

Résumé

Single nucleotide polymorphisms (SNPs) have been linked with prostate cancer (PCa) and have shown potential as prognostic markers for advanced stages. Loss of function mutations in PKCι have been linked with increased risk of malignancy by enhancing tumor cell motility and invasion. We have evaluated the impact of two coding region SNPs on the PKCι gene (PRKCI) and their prognostic potential. Genotypic association of non-synonymous PKCι SNPs rs1197750201 and rs1199520604 with PCa was determined through tetra-ARMS PCR. PKCι was docked with interacting partner Par-6 to determine the effect of these variants on PKCι binding capabilities. Molecular dynamic simulations of PKCι docked with Par-6 were performed to determine variant effects on PKCι protein interactions. The possible impact of changes in PKCι protein interactions on epithelial cell polarity was hypothesized. PKCι rs1199520604 mutant genotype TT showed association with PCa (p = 0.0055), while rs1197750201 mutant genotype AA also showed significant association with PCa (P = 0.0006). The binding interaction of PKCι with Par-6 was altered for both variants, with changes in Van der Waals energy and electrostatic energy of docked structures. Genotypic analysis of two non-synonymous PKCι variants in association with PCa prognosis was performed. Both variants in the PB1 domain showed potential as a prognostic marker for PCa. In silico analysis of the effect of the variants on PKCι protein interactions indicated they may be involved in PCa progression through aberration of epithelial cell polarity pathways.

Sections du résumé

BACKGROUND BACKGROUND
Single nucleotide polymorphisms (SNPs) have been linked with prostate cancer (PCa) and have shown potential as prognostic markers for advanced stages. Loss of function mutations in PKCι have been linked with increased risk of malignancy by enhancing tumor cell motility and invasion. We have evaluated the impact of two coding region SNPs on the PKCι gene (PRKCI) and their prognostic potential.
METHODS METHODS
Genotypic association of non-synonymous PKCι SNPs rs1197750201 and rs1199520604 with PCa was determined through tetra-ARMS PCR. PKCι was docked with interacting partner Par-6 to determine the effect of these variants on PKCι binding capabilities. Molecular dynamic simulations of PKCι docked with Par-6 were performed to determine variant effects on PKCι protein interactions. The possible impact of changes in PKCι protein interactions on epithelial cell polarity was hypothesized.
RESULTS RESULTS
PKCι rs1199520604 mutant genotype TT showed association with PCa (p = 0.0055), while rs1197750201 mutant genotype AA also showed significant association with PCa (P = 0.0006). The binding interaction of PKCι with Par-6 was altered for both variants, with changes in Van der Waals energy and electrostatic energy of docked structures.
CONCLUSION CONCLUSIONS
Genotypic analysis of two non-synonymous PKCι variants in association with PCa prognosis was performed. Both variants in the PB1 domain showed potential as a prognostic marker for PCa. In silico analysis of the effect of the variants on PKCι protein interactions indicated they may be involved in PCa progression through aberration of epithelial cell polarity pathways.

Identifiants

pubmed: 38200472
doi: 10.1186/s12935-023-03182-4
pii: 10.1186/s12935-023-03182-4
doi:

Types de publication

Journal Article

Langues

eng

Pagination

24

Informations de copyright

© 2024. The Author(s).

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Auteurs

Amna Hafeez (A)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Maria Shabbir (M)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan. mshabbir@asab.nust.edu.pk.

Khushbukhat Khan (K)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Janeen H Trembley (JH)

Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA.
Minneapolis VA Health Care System Research Service, Minneapolis, MN, USA.

Yasmin Badshah (Y)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Sameen Zafar (S)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Kanza Shahid (K)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Hania Shah (H)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Naeem Mahmood Ashraf (NM)

Department of Biochemistry and Biotechnology, University of Gujrat, Hafiz Hayat Campus, Gujrat, 50700, Punjab, Pakistan.

Arslan Hamid (A)

University of Bonn, LIMES Institute (AG-Netea), Carl-Troll-Str. 31, 53115, Bonn, Germany.

Tayyaba Afsar (T)

Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.

Ali Almajwal (A)

Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.

Afifa Marium (A)

Department of Healthcare Biotechnology, Rahman School of Applied Biosciences, National University of Sciences and Technology, Atta-Ur, Islamabad, Pakistan.

Suhail Razak (S)

Department of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia. smarazi@ksu.edu.sa.

Classifications MeSH