Evidence map›Paper›PMID 33273524›Full record

ArticleScientific reports2020

MassArray analysis of genomic susceptibility variants in ovarian cancer.

Sonali Verma, Indu Sharma, Varun Sharma, Amrita Bhat, Ruchi Shah, Gh Rasool Bhat, Bhanu Sharma, Divya Bakshi, Ashna Nagpal, Ajay Wakhloo and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 54% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

12 authors at 5 institutions in 1 country.

Sonali VermaIndian Council of Medical Research-Centre for Advance Research, Shri Mata Vaishno Devi University, Katra, Jammu and Kashmir, India. Sonali.verma@smvdu.ac.in.
Indu SharmaAncient DNA Laboratory, Birbal Shani Institute of Paleo Sciences, Lucknow, Uttar Pradesh, India.
Varun SharmaAncient DNA Laboratory, Birbal Shani Institute of Paleo Sciences, Lucknow, Uttar Pradesh, India.
Amrita BhatSchool of Biotechnology, Shri Mata Vaishno Devi University, Katra, India.
Ruchi ShahDepartment of Biotechnology, Kashmir University, Srinagar, Jammu and Kashmir, India.
Gh Rasool BhatSchool of Biotechnology, Shri Mata Vaishno Devi University, Katra, India.
Bhanu SharmaSchool of Biotechnology, Shri Mata Vaishno Devi University, Katra, India.
Divya BakshiSchool of Biotechnology, Shri Mata Vaishno Devi University, Katra, India.
Ashna NagpalSchool of Biotechnology, Shri Mata Vaishno Devi University, Katra, India.
Ajay WakhlooDepartment of Obstetrics and Gynecology, Government Medical College, Jammu, Jammu and Kashmir, India.
Audesh BhatCentre for Molecular Biology, Central University of Jammu, Jammu, Jammu and Kashmir, India.
Rakesh KumarIndian Council of Medical Research-Centre for Advance Research, Shri Mata Vaishno Devi University, Katra, Jammu and Kashmir, India. drrakeshthusoo@gmail.com.
Shri Mata Vaishno Devi University · INCentral University of Jammu · INGovernment Medical College · INIndian Council of Medical Research · INUniversity of Kashmir · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ovarian cancer (OC), a multifaceted and genetically heterogeneous malignancy is one of the most common cancers among women. The aim of the study is to unravel the genetic factors associated with OC and the extent of genetic heterogeneity in the populations of Jammu and Kashmir (J&K).Using the high throughput Agena MassARRAY platform, present case control study was designed which comprises 200 histopathological confirmed OC patients and 400 age and ethnicity matched healthy controls to ascertain the association of previously reported eleven single nucleotide polymorphisms (SNPs) spread over ten genes (DNMT3A, PIK3CA, FGFR2, GSTP1, ERCC5, AKT1, CASC16, CYP19A1, BCL2 and ERCC1) within the OC population of Jammu and Kashmir, India. The association of each variant was estimated using logistic regression analyses. Out of the 11 SNPs the odds ratio observed for three SNPs; rs2699887 was (1.72 at 95% CI: 1.19-2.48, p = 0.004), rs1695 was (1.87 at 95% CI: 1.28-2.71, p = 0.001), and rs2298881 was (0.66 at 95% CI: 0.46-0.96, p = 0.03) were found significantly associated with the OC after correction with confounding factors i.e. age & BMI. Furthermore, the estimation of interactive analyses was performed and odds ratio observed was 2.44 (1.72-3.47), p value < 0. 001 suggests that there was a strong existence of interplay between the selected genetic variants in OC, which demonstrate that interactive analysis highlights the role of gene-gene interaction that provides an insight among multiple little effects of various polymorphisms in OC.

Indexed as

Genetic Predisposition to DiseaseGenetic VariationGenome, HumanOligonucleotide Array Sequence AnalysisAllelesCase-Control StudiesFemaleGene FrequencyHumansMiddle AgedMolecular Sequence AnnotationOvarian NeoplasmsPolymorphism, Single Nucleotide

Identifiers

PMID33273524
PMCPMC7713113
OpenAlexW3109264300

What OpenQuestion holds

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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 OpenQuestion graph.