Evidence map›Paper›PMID 41348314›Full record

ArticleBiochemical genetics2026

Candidate Prognostic LncRNAs Including C2orf49-DT, CAPN10-DT, LOC105371795 as Potential Biomarkers for Colorectal Cancer.

Ali Karimi, Zeynab Ashari, Soheil Momeni, Shahla Kamarei, Atefeh Zamani, Mohammad Mahdevar

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Article in Biochemical genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

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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.

Ali Karimi *Genius Gene, Genetics and Biotechnology Company, Isfahan, Iran.
Zeynab Ashari *Genius Gene, Genetics and Biotechnology Company, Isfahan, Iran.
Soheil Momeni *Genius Gene, Genetics and Biotechnology Company, Isfahan, Iran.
Shahla KamareiGenius Gene, Genetics and Biotechnology Company, Isfahan, Iran.
Atefeh ZamaniGenius Gene, Genetics and Biotechnology Company, Isfahan, Iran. atefeh.zamani20@gmail.com.
Mohammad MahdevarGenius Gene, Genetics and Biotechnology Company, Isfahan, Iran. mahdevar416@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) have regulatory functions and are linked to various disorders, including cancer. In this study, we investigated signature lncRNAs that may be associated with the pathogenesis of colorectal cancer (CRC) and could serve as diagnostic and prognostic biomarkers. The relationship between lncRNA expression and patient mortality rates was identified using data from The Cancer Genome Atlas. Next, linear models determined the differential expression of lncRNAs in cancer and healthy samples. The association of lncRNA expression with patient prognosis was examined using a Cox regression test, and the risk model was constructed using a subset of lncRNAs. The co-expression network was analyzed to identify the pathways associated with candidate lncRNAs. The expression levels of specific lncRNAs were examined in 35 tumor samples from the Iranian Tumor Bank to validate the in-silico analyses. RNAs were extracted using TRIzol, and their quality was assessed. The qRT-PCR method determined candidate gene expression levels after cDNA synthesis. Our findings showed that C2orf49-DT, CAPN10-DT, and LOC105371795 levels were higher in CRC samples and linked to patients with poor prognoses. The co-expression network data demonstrated that the examined lncRNAs were connected to crucial genes involved in cell proliferation, like E2F3. The RT-qPCR results showed a significant increase in C2orf49-DT, CAPN10-DT, and LOC105371795 compared to healthy tissue samples. We found a significant correlation between the levels of the mentioned lncRNAs and E2F3 expression in the ex vivo data. Our findings suggest that elevated levels of C2orf49-DT, CAPN10-DT, and LOC105371795 may be associated with increased mortality rates in CRC patients. These non-coding RNAs are associated with pathways that promote cell proliferation and are proposed as potential biomarkers for diagnosing and predicting CRC.

Indexed as

Biomarkers, TumorCalpainColorectal NeoplasmsRNA, Long NoncodingFemaleGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisBiomarkers, TumorCalpaincalpain 10RNA, Long NoncodingBioinformaticsColorectal cancerGene expressionLncRNAqRT-PCR

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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.