Evidence map›Paper›PMID 39246994›Full record

ArticleCureus2024

In-Silico and In-Vitro Investigation of Key Long Non-coding RNAs Involved in 5-Fluorouracil Resistance in Colorectal Cancer Cells: Analyses Highlighting NEAT1 and MALAT1 as Contributors.

Roxana Sahebnasagh, Zahra Azizi, Tahereh Komeili-Movahhed, Kazem Zendehdel, Mohammad Hossein Ghahremani

Abstract read
In one paragraph

Article in Cureus, 2024. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

5 authors.

Roxana SahebnasaghDepartment of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, IRN.
Zahra AziziDepartment of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, IRN.
Tahereh Komeili-MovahhedCellular and Molecular Research Center, Qom University of Medical Sciences, Qom, IRN.
Kazem ZendehdelCancer Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, IRN.
Mohammad Hossein GhahremaniDepartment of Toxicology and Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, IRN.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Acquired resistance to 5-fluorouracil (5-FU) frequently results in chemotherapy failure and disease recurrence in advanced colorectal cancer (CRC) patients. Research has demonstrated that dysregulation of long non-coding RNAs (lncRNAs) mediates the development of chemotherapy resistance in cancerous cells. The present study aims to identify key lncRNAs associated with 5-FU resistance in CRC using bioinformatic and experimental validation approaches. Methods The Gene Expression Omnibus (GEO) dataset GSE119481, which contains miRNA expression profiles of the parental CRC HCT116 cell line (HCT116/P) and its in-vitro established 5-FU-resistant sub-cell line (HCT116/FUR), was downloaded. Firstly, differentially expressed microRNAs (DEmiRNAs) between the parental and 5-FU resistance cells were identified. LncRNAs and mRNAs were then predicted using online databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to uncover relevant biological mechanisms and pathways. Networks integrating lncRNAs, miRNAs, and mRNAs interactions were constructed, and topological analyses were used to identify key lncRNAs associated with 5-FU resistance. An in-vitro model of the HCT116/FUR sub-cell line was developed by exposing the HCT116/P cell line to increasing concentrations of 5-FU. Finally, real-time quantitative PCR (RT-qPCR) was performed on total RNA extracted from the HCT116/P cell line and the HCT116/FUR sub-cell line to validate the in-silico predictions of key lncRNAs. Results A total of 32 DEmiRNAs were identified. Enrichment analysis demonstrated that these DEmiRNAs were mainly enriched in several cancer hallmark pathways that regulate cell growth, cell cycle, cell survival, inflammation, immune response, and apoptosis. The predictive analysis identified 237 unique lncRNAs and 123 mRNAs interacting with these DEmiRNAs. The pathway analysis indicated that most of these predicted genes were enriched in the cellular response to starvation, protein polyubiquitination, chromatin remodeling, and negative regulation of gene expression. Topological analyses of the lncRNA-miRNA-mRNA network highlighted the nuclear enriched abundant transcript 1 (NEAT1), metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), and Opa interacting protein 5 antisense RNA 1 (OIP5-AS1) as central lncRNAs. Experimental analysis by RT-qPCR confirmed that the expression levels of NEAT1 and MALAT1 were significantly increased in HCT116/FUR cells compared to HCT116/P cells. However, no significant difference was observed in the OIP5-AS1 expression level between the two cells. Conclusion Our findings specifically highlight MALAT1 and NEAT1 as significant contributors to 5-FU resistance in CRC. These lncRNAs are promising biomarkers for diagnosing and predicting outcomes in CRC.

Indexed as

5-fu resistancecerna networkcolorectal cancerhct116long non-coding rnas

Identifiers

PMID39246994
PMCPMC11379344

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.