Evidence map›Paper›PMID 33444474›Full record

ArticleIET systems biology2019

MicroRNAs and their target mRNAs as potential biomarkers among smokers and non-smokers with lung adenocarcinoma.

Sumaria Malik, Rehan Zafar Paracha, Maryam Khalid, Maryum Nisar, Amnah Siddiqa, Zamir Hussain, Raheel Nawaz, Amjad Ali, Jamil Ahmad

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Article in IET systems biology, 2019. 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 57% 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

9 authors at 2 institutions in 2 countries.

Sumaria MalikResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
Rehan Zafar ParachaResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
Maryam KhalidResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
Maryum NisarResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
Amnah SiddiqaResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
Zamir HussainResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
Raheel NawazSchool of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, GM459 Geoffrey Manton Building, Manchester, England.
Amjad AliAtta-ur-Rahman School of Applied Biosciences - ASAB, National University of Sciences and Technology (NUST), Sector H- 12, Islamabad, Pakistan.
Jamil AhmadResearch Center For Modeling & Simulation (RCMS), National University of Sciences and Technology (NUST), Sector H-12, Islamabad, Pakistan.
National University of Sciences and Technology · PKManchester Metropolitan University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung adenocarcinoma is one of the major causes of mortality. Current methods of diagnosis can be improved through identification of disease specific biomarkers. MicroRNAs are small non-coding regulators of gene expression, which can be potential biomarkers in various diseases. Thus, the main objective of this study was to gain mechanistic insights into genetic abnormalities occurring in lung adenocarcinoma by implementing an integrative analysis of miRNAs and mRNAs expression profiles in the case of both smokers and non-smokers. Differential expression was analysed by comparing publicly available lung adenocarcinoma samples with controls. Furthermore, weighted gene co-expression network analysis is performed which revealed mRNAs and miRNAs significantly correlated with lung adenocarcinoma. Moreover, an integrative analysis resulted in identification of several miRNA-mRNA pairs which were significantly dysregulated in non-smokers with lung adenocarcinoma. Also two pairs (miR-133b/Protein Kinase C Zeta (PRKCZ) and miR-557/STEAP3) were found specifically dysregulated in smokers. Pathway analysis further revealed their role in important signalling pathways including cell cycle. This analysis has not only increased the authors' understanding about lung adenocarcinoma but also proposed potential biomarkers. However, further wet laboratory studies are required for the validation of these potential biomarkers which can be used to diagnose lung adenocarcinoma.

Indexed as

cancerdisease specific biomarkersgenetic abnormalitiesgeneticsintegrative analysislunglung adenocarcinomamedical diagnostic computingmicroRNAsmiRNAs expression profilesmolecular biophysicsmolecular configurationsmRNAs expression profilesnoncoding regulatorsnonsmokerspatient diagnosisproteinsRNAsmokerstumoursweighted gene coexpression network analysis

Identifiers

PMID33444474
PMCPMC8687273
OpenAlexW2894385852

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.