Evidence map›Paper›PMID 40100546›Full record

ArticleDiscover oncology2025

Unravelling the role of PRKCI and key-cancer related genes in breast cancer development and metastasis.

Hania Shah, Khushbukhat Khan, Yasmin Badshah, Janeen H Trembley, Naeem Mahmood Ashraf, Maria Shabbir, Tayyaba Afsar, Dara Aldisi, Dilawer Khan, Suhail Razak

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 citing papers in PubMed.

  1. Translational cancer research · 2026
    Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Hania ShahDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan.
Khushbukhat KhanDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan.
Yasmin BadshahDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan.
Janeen H TrembleyDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
Naeem Mahmood AshrafDepartment of Biochemistry and Biotechnology, University of Punjab, Lahore, Pakistan.
Maria ShabbirDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan.
Tayyaba AfsarDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Dara AldisiDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh, Saudi Arabia.
Dilawer KhanDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad, Pakistan.
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

backgroundBreast cancer is one of the most common causes of fatalities in females globally. Rising cases of drug resistance against existing chemotherapeutics are great problem. To address this issue, there is a need to find appropriate biomarker that could be used to detect cancer at early stages, so drug resistance development can be avoided. Protein Kinase C iota (PKCɩ), an AGC kinase, has an oncogenic role in cancers and its expression and Single nucleotide polymorphisms (SNPs) have been reported to be associated with the cancer development. So, the study aims were to examine the expression of PKCɩ, Protein Kinase B (AKT), Suppressor of cytokine signaling 3 (SOCS3), Vascular endothelial growth factor (VEGF), Krupple like factor 3 (KLF3), Tumor protein D52 (TPD52), Hypoxia inducible factor (HIF1α) and microRNA-124 (miR-124) in breast cancer and association of PKCɩ variants (G34W & F66Y) with breast cancer.

methodsGenetic expression assay was performed through real time Polymerase Chain reaction (PCR), whereas the genotypic association of PKCɩ SNPs with breast cancer was accomplished through Tetra-ARMS PCR.

resultsThe expression levels of PKCɩ, AKT, SOC3, VEGF, HIF1α and TPD52 were elevated in patients as compared to control whereas the expression levels of miR-124 and KLF3 were lowered in patients. Positive association of variant G34W (TT) of PKCɩ with breast cancer has been explored through ARM's PCR, while no association of variant F66Y with breast cancer was found.

conclusionHence, the results suggest that PKCɩ and related genes can have a role in breast cancer and after further verification can serve as the potential biomarkers for the early-diagnosis and prognosis of breast cancer.

Indexed as

AKTARM’s PCRCancerExpression analysisMutationPKCSNP

Identifiers

PMID40100546
PMCPMC11920535

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.