Evidence map›Paper›PMID 40847033›Full record

ArticleScientific reports2025

"In silico analysis of human TLR3 missense single nucleotide polymorphisms and their potential association with cancer".

Mohini Agarwal, Manish Kumar, Sarthak Dahiya, Anoop Kumar, Rupal Tripathi, Kumud Bala

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Mohini AgarwalTherapeutics and Molecular Diagnostic Lab, J-3 Block, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India.
Manish KumarTherapeutics and Molecular Diagnostic Lab, J-3 Block, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India.
Sarthak DahiyaAmity Institute of Pharmacy, Amity University, Noida, India.
Anoop KumarNational Institute of Biologicals, A-32, Sector-62, Noida, Uttar Pradesh, India.
Rupal TripathiRajiv Gandhi Cancer Institute and Research Centre, Delhi, India.
Kumud BalaTherapeutics and Molecular Diagnostic Lab, J-3 Block, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India. kbala@amity.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer is a prevalent malignancy worldwide and represents a significant health burden for women. Toll-like receptors (TLRs) are crucial components of the innate immune system and play a vital role in recognizing pathogen-associated molecular patterns. Among the TLRs, TLR3 has been implicated in the defense against viral infections, including human papillomavirus (HPV), the primary etiological agent of cervical cancer. Missense single-nucleotide polymorphisms (SNPs) in the TLR3 gene can alter its protein structure and potentially influence its function, leading to variations in immune responses and disease susceptibility. This study aimed to investigate the impact of TLR3 missense SNPs on cervical cancer development through in silico methods. A comprehensive analysis was performed using various computational tools and databases to predict the functional consequences of identified TLR3 missense SNPs. The selection criteria for SNPs included their reported association with cervical cancer or their potential effects on TLR3 structure and function. Three extremely detrimental TLR-3 nsSNPs, namely N284I (rs5743316), C37R(rs752889035), and L360P(rs768091235), have been found among the 150 nsSNPs that have so far been reported in the dbSNP database. The in silico analysis suggests that these genetic variations may contribute to the development and progression of cervical cancer by modulating TLR3 function. Further experimental studies are warranted to validate these findings and elucidate the underlying mechanisms, which may aid in developing novel therapeutic strategies for cervical cancer prevention and treatment.

Indexed as

Genetic Predisposition to DiseaseMutation, MissensePolymorphism, Single NucleotideToll-Like Receptor 3Uterine Cervical NeoplasmsComputational BiologyComputer SimulationFemaleHumansTLR3 protein, humanToll-Like Receptor 3Cervical cancerHPVIn silico analysisMissense mutationnsSNPTLR-3

Identifiers

PMID40847033
PMCPMC12373945

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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.