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Record W4321210045 · doi:10.1186/s12931-023-02366-w

A literature review of microRNA and gene signaling pathways involved in the apoptosis pathway of lung cancer

2023· review· en· W4321210045 on OpenAlexaff
Hanie Abolfathi, Mohadeseh Arabi, Mojgan Sheikhpour

Bibliographic record

VenueRespiratory Research · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsUniversité Laval
FundersPasteur Institute of Iran
KeywordsmicroRNAPTENXIAPKRASSignal transductionBiologyProtein kinase BCancer researchKEGGPI3K/AKT/mTOR pathwayCancerLung cancerBioinformaticsApoptosisGeneMedicineProgrammed cell deathGene expressionGeneticsCaspasePathologyColorectal cancerTranscriptome

Abstract

fetched live from OpenAlex

BACKGROUND: Lung cancer is one of the leading causes of death in the world and the deadliest of all cancers. Apoptosis is a key pathway in regulating the cell growth rate, proliferation, and occurrence of lung cancer. This process is controlled by many molecules, such as microRNAs and their target genes. Therefore, finding new medical approaches such as exploring diagnostic and prognostic biomarkers involved in apoptosis is needed for this disease. In the present study, we aimed to identify key microRNAs and their target genes that could be used in the prognosis and diagnosis of lung cancer. METHODS: Signaling pathways, genes, and microRNAs involved in the apoptotic pathway were identified by bioinformatics analysis and recent clinical studies. Bioinformatics analysis was performed on databases including NCBI, TargetScan, UALCAN, UCSC, KEGG, miRPathDB, and Enrichr, and clinical studies were extracted from PubMed, web of science, and SCOPUS databases. RESULTS: NF-κB, PI3K/AKT, and MAPK pathways play critical roles in the regulation of apoptosis. MiR-146b, 146a, 21, 23a, 135a, 30a, 202, and 181 were identified as the involved microRNAs in the apoptosis signaling pathway, and IRAK1, TRAF6, Bcl-2, PTEN, Akt, PIK3, KRAS, and MAPK1 were classified as the target genes of the mentioned microRNAs respectively. The essential roles of these signaling pathways and miRNAs/target genes were approved through both databases and clinical studies. Moreover, surviving, living, BRUCE, and XIAP was the main inhibitor of apoptosis which act by regulating the apoptosis-involved genes and miRNAs. CONCLUSION: Identifying the abnormal expression and regulation of miRNAs and signaling pathways in apoptosis of lung cancer can represent a novel class of biomarkers that can facilitate the early diagnosis, personalized treatment, and prediction of drug response for lung cancer patients. Therefore, studying the mechanisms of apoptosis including signaling pathways, miRNAs/target genes, and the inhibitors of apoptosis are advantageous for finding the most practical approach and reducing the pathological demonstrations of lung cancer.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.692
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.133
GPT teacher head0.409
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations38
Published2023
Admission routes1
Has abstractyes

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