Evidence map›Paper›PMID 39690926›Full record

ArticleCancer reports (Hoboken, N.J.)2024

Comprehensive Multi-Omics Analysis Reveals NPC2 and ITGAV Genes as Potential Prognostic Biomarkers in Gastrointestinal Cancers.

Moein Piroozkhah, Mohammadreza Zabihi, Pooya Jalali, Zahra Salehi

Abstract read
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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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

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Moein PiroozkhahBasic and Molecular Epidemiology of Gastrointestinal Disorders Research Centre, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammadreza ZabihiInstitute of Biochemistry and Biophysics (IBB), Department of Bioinformatics, Laboratory of Complex Biological Systems and Bioinformatics (CBB), University of Tehran, Tehran, Iran.ORCID 0000-0002-9357-2942
Pooya JalaliBasic and Molecular Epidemiology of Gastrointestinal Disorders Research Centre, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Zahra SalehiHematology, Oncology and Stem Cell Transplantation Research Center, Research Institute for Oncology, Hematology and Cell Therapy, Tehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-0839-2729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGastrointestinal cancers (GICs) continue to dominate in terms of both incidence and mortality worldwide. Due to the absence of efficient and accurate prognostic biomarkers, the prognosis and treatment outcomes of many GICs are poor. Identifying biomarkers to predict individual clinical outcomes efficiently is a fundamental challenge in clinical oncology. Although several biomarkers have been continually discovered, their predictive accuracy is relatively modest, and their therapeutic use is restricted. In light of this, the discovery of reliable biomarkers for predicting prognosis and outcome in GIC is urgently required. MATERIALS AND

methodsWe evaluated the Human Protein Atlas dataset and identified NPC Intracellular Cholesterol Transporter 2 (NPC2) and Integrin Subunit Alpha V (ITGAV) as probable poor predictive genes for these cancers. In addition, we used the GEPIA2, cBioPortal, UALCAN, LinkedOmics, STRING, Enrichr, TISDB, TIMER2.0, hTFTarget, miRTarBase, circBank, and drug-gene interaction database databases to conduct a comprehensive and systematic analysis of the NPC2 and ITGAV genes.

resultOur results found high expression levels of NPC2 and ITGAV in most GICs. The aforementioned gene expressions were linked to several clinicopathological characteristics of GICs as well as poorer prognosis in LIHC and STAD. The most common alteration type of NPC2 was amplification, and for ITGAV was deep deletion. Significant promotor hypermethylation was also seen in NPC2 and ITGAV in PAAD and COAD, respectively. For the immunologic significance, NPC2 and ITGAV were positively correlated with the abundance of tumor-infiltrating lymphocytes and macrophages. Furthermore, various immunomodulators showed strong correlations with the expression of these genes. There were currently 10 small molecule drugs targeting ITGAV.

conclusionConsequently, our bioinformatics analysis showed that NPC2 and ITGAV might be used as potential biomarkers to determine the prognosis of various GICs and are also related to immune infiltration.

Indexed as

Biomarkers, TumorGastrointestinal NeoplasmsComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMultiomicsPrognosisVesicular Transport ProteinsBiomarkers, TumorNPC2 protein, humanVesicular Transport Proteinsbioinformaticsgastrointestinal cancerITGAVmultiomicsNPC2prognostic factors

Identifiers

PMID39690926
PMCPMC11652787

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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 Socratic graph.