Evidence map›Paper›PMID 41162960›Full record

ArticleBMC cancer2025

Comprehensive computational analysis of PKCδ non-synonymous variants identifies rs1703863535 as a potential breast cancer biomarker.

Sameen Zafar, Yasmin Badshah, Maria Shabbir, Somia Khan, Amna Hafeez, Naeem Mahmood Ashraf, Janeen H Trembley, Tayyaba Afsar, Ali Almajwal, Suhail Razak

Abstract read
In one paragraph

Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Sameen ZafarDepartment of Biomedicine, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Yasmin BadshahDepartment of Biomedicine, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan. yasmeenb@asab.nust.edu.pk.
Maria ShabbirDepartment of Biomedicine, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Somia KhanDepartment of Biomedicine, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Amna HafeezDepartment of Biomedicine, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, 44000, Pakistan.
Naeem Mahmood AshrafSchool of Biochemistry and Biotechnology, University of the Punjab, Lahore, Pakistan.
Janeen H TrembleyDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
Tayyaba AfsarDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Ali AlmajwalDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Suhail RazakDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia. smarazi@ksu.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PKCδ is a key isoform in the PKC subgroup of AGC-kinase proteins, known to be involved in various cellular processes. Dysregulation of its expression has been linked to multiple malignancies. Notably, PKCδ overexpression has been associated with breast cancer progression and poor prognosis. Previous research has shown that PKCδ phosphorylates specific serine residues on target proteins, leading to tumorigenesis and metastasis. However, the molecular mechanisms of PKCδ-driven breast cancer pathogenesis remain incompletely understood. Single-nucleotide polymorphisms (SNPs), the most common genetic variants, can contribute to cancer susceptibility by causing structural and functional changes in proteins. This study aimed to identify oncogenic non-synonymous variants in PKCδ and assess their impact on protein structure, stability, conservation, dynamics, and interactions. Analyzing a dataset of 613 non-synonymous variants with various computational and in silico tools based on sequence and structure approaches, four variants, including V114G, C189R, C189Y, W608R, were identified as highly oncogenic. Molecular dynamics simulations showed increased structural deviations and flexibility in these variants compared to the native protein, potentially leading to changes in structure, stability, and biophysical properties. These variants disrupted normal PKCδ function by causing surface distortion, changing net charge, and perturbing intramolecular interactions with STAT3, which may activate PKCδ in a non-canonical manner. The study also found an association between the oncogenic non-synonymous SNP W608R, located within the highly conserved AGC kinase domain, and breast cancer, with the TT genotype significantly linked to increased risk (OR = 2.7; RR = 1.6, p < 0.0001). Although further functional validation in cellular models is necessary, this research provides a foundation for future studies on the impact of oncogenic PKCδ variants in breast cancer.

Indexed as

Biomarkers, TumorBreast NeoplasmsPolymorphism, Single NucleotideProtein Kinase C-deltaComputational BiologyFemaleGenetic Predisposition to DiseaseHumansMolecular Dynamics SimulationSTAT3 Transcription FactorBiomarkers, TumorPRKCD protein, humanProtein Kinase C-deltaSTAT3 protein, humanSTAT3 Transcription FactorCanceroncogenePKCSingle Nucleotide Polymorphisms

Identifiers

PMID41162960
PMCPMC12570629

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.