Evidence map›Paper›PMID 30150654›Full record

ArticleScientific reports2018

An interaction network driven approach for identifying biomarkers for progressing cervical intraepithelial neoplasia.

Shikha Suman, Ashutosh Mishra

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

2 authors.

Shikha SumanDivision of Applied Sciences, Indian Institute of Information Technology (IIIT), Allahabad, 211012, India. shikha.suman27@gmail.com.
Ashutosh MishraDivision of Applied Sciences, Indian Institute of Information Technology (IIIT), Allahabad, 211012, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Overlapping genes across high-grade squamous intraepithelial lesions (CIN2 and 3) and cancer may serve as potential biomarkers for this progressive disease. Differentially expressed genes (DEGs) of dysplastic (CIN2 and CIN3) and cancer cells were identified by microarray data analysis. Gene interaction network was constructed using the 98 common DEGs among the dysplastic and cancer cells and analysed for the identification of common modules, hubs and significant motifs. Two significant modules and 10 hubs of the common gene interaction network, with 125 nodes and 201 edges were found. DEGs namely NDC80, ZWINT, CDC7, MCM4, MCM2 and MCM6 were found to be common in both the significant modules as well as the hubs. Of these, ZWINT, CDC7, MCM4, MCM2 and MCM6 were further identified to be part of most significant motifs. This overlapping relationship provides a list of common disease related genes among pre-cancerous and cancer stages which could help in targeting the proliferating cancerous cells during onset. Capitalizing upon and targeting Minichromosome maintenance protein complex - specifically the MCM2, MCM4 and MCM6 subunits, ZWINT and CDC7 for experimental validation, may provide valuable insights in understanding and detection of progressing cervical neoplasia to cervical cancer at an early stage.

Indexed as

BiomarkersBiomarkers, TumorCell Cycle ProteinsCell Line, TumorFemaleGene Regulatory NetworksHumansUterine Cervical DysplasiaUterine Cervical NeoplasmsBiomarkersBiomarkers, TumorCell Cycle Proteins

Identifiers

PMID30150654
PMCPMC6110773

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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.