Evidence map›Paper›PMID 36672978›Full record

ArticleGenes2023

Pathogenicity of PKCγ Genetic Variants-Possible Function as a Non-Invasive Diagnostic Biomarker in Ovarian Cancer.

Kanza Shahid, Khushbukhat Khan, Yasmin Badshah, Naeem Mahmood Ashraf, Arslan Hamid, Janeen H Trembley, Maria Shabbir, Tayyaba Afsar, Ali Almajwal, Ali Abusharha and 1 more

Open access · goldAbstract read
In one paragraph

Article in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. The Role of NQO1 in Ovarian Cancer.International journal of molecular sciences · 2023
    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

11 authors at 5 institutions in 4 countries.

Kanza ShahidDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44010, Pakistan.
Khushbukhat KhanDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44010, Pakistan.ORCID 0000-0002-9946-9057
Yasmin BadshahDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44010, Pakistan.
Naeem Mahmood AshrafSchool of Biochemistry and Biotechnology, University of the Punjab, Lahore 54590, Pakistan.
Arslan HamidLIMES Institute (AG-Netea), University of Bonn, Carl-Troll-Str. 31, 53115 Bonn, Germany.ORCID 0000-0002-2861-013X
Janeen H TrembleyMinneapolis VA Health Care System Research Service, Minneapolis, MN 55417, USA.ORCID 0000-0003-3597-2611
Maria ShabbirDepartment of Healthcare Biotechnology, Atta-Ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44010, Pakistan.ORCID 0000-0002-5685-3059
Tayyaba AfsarDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Ali AlmajwalDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Ali AbusharhaDepartment of Optometry, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
Suhail RazakDepartment of Community Health Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11362, Saudi Arabia.
King Saud University · SANational University of Sciences and Technology · PKUniversity of Bonn · DEUniversity of Minnesota · USUniversity of the Punjab · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer has the highest mortality rate among gynecologic malignancies, owing to its misdiagnosis or late diagnosis. Identification of its genetic determinants could improve disease outcomes. Conventional Protein Kinase C-γ (PKCγ) dysregulation is reported in several cancers. Similarly, its variant rs1331262028 is also reported to have an association with hepatocellular carcinoma. Therefore, the aim of the present study was to analyze the variant rs1331262028 association with ovarian cancer and to determine its impact on PKCγ's protein interactions. Association of variation was determined through genotyping PCR (cohort size:100). Protein-protein docking and molecular dynamic simulation were carried out to study the variant impact of PKCγ interactions. The study outcome indicated the positive association of variant rs1331262028 with ovarian cancer and its clinicopathological features. Molecular dynamics simulation depicted the potential influence of variation on PKCγ molecular signaling. Hence, this study provided the foundations for assessing variant rs1331262028 as a potential prognostic marker for ovarian cancer. Through further validation, it can be applied at the clinical level.

Indexed as

Ovarian NeoplasmsSignal TransductionBiomarkersFemaleHumansVirulenceBiomarkersmolecular dynamics simulationovarian cancerprotein kinase c-gamma (PKCγ)protein-protein docking

Identifiers

PMID36672978
PMCPMC9858858
OpenAlexW4316673432

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.