Evidence map›Paper›PMID 37247279›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2023

Integrated Bioinformatics Analysis Identifies Crucial Biochemical Processes Shared between Pancreatitis and Pancreatic Ductal Adenocarcinoma.

Manoj M Wagle, Ananya Rao Kedige, Shama P Kabekkodu, Sandeep Mallya

Open access · goldAbstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 3 countries.

Manoj M WagleSchool of Mathematics and Statistics and Computational Systems Biology Group, Children's Medical Research Institute, University of Sydney, New South Wales, Australia.ORCID 0000-0001-5339-1453
Ananya Rao KedigeDepartment of Bioinformatics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, India.ORCID 0000-0002-5337-2209
Shama P KabekkoduDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, India.ORCID /0000-0002-4158-3893
Sandeep MallyaDepartment of Bioinformatics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, India.ORCID 0000-0001-6318-7165
Manipal Academy of Higher Education · INCEA Grenoble · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy associated with rapid progression and an abysmal prognosis. Previous research has shown that chronic pancreatitis can significantly increase the risk of developing PDAC. The overarching hypothesis is that some of the biological processes disrupted during the inflammatory stage tend to show significant dysregulation, even in cancer. This might explain why chronic inflammation increases the risk of carcinogenesis and uncontrolled proliferation. Here, we try to pinpoint such complex processes by comparing the expression profiles of pancreatitis and PDAC tissues.

methodsWe analyzed a total of six gene expression datasets retrieved from the EMBL-EBI ArrayExpress and NCBI GEO databases, which included 306 PDAC, 68 pancreatitis and 172 normal pancreatic samples. The disrupted genes identified were used to perform downstream analysis for ontology, interaction, enriched pathways, potential druggability, promoter methylation, and the associated prognostic value. Further, we performed expression analysis based on gender, patient's drinking habit, race, and pancreatitis status.

resultsOur study identified 45 genes with altered expression levels shared between PDAC and pancreatitis. Over-representation analysis revealed that protein digestion and absorption, ECM-receptor interaction, PI3k-Akt signaling, and proteoglycans in cancer pathways as significantly enriched. Module analysis identified 15 hub genes, of which 14 were found to be in the druggable genome category.

conclusionIn summary, we have identified critical genes and various biochemical processes disrupted at a molecular level. These results can provide valuable insights into certain events leading to carcinogenesis, and therefore help identify novel therapeutic targets to improve PDAC treatment in the future.

Indexed as

Carcinoma, Pancreatic DuctalPancreatic NeoplasmsPancreatitisBiomarkers, TumorComputational BiologyGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPhosphatidylinositol 3-KinasesSignal TransductionBiomarkers, TumorPhosphatidylinositol 3-Kinasesdifferentially expressed genesInflammationPancreatic cancerPDAC

Identifiers

PMID37247279
PMCPMC10495878
OpenAlexW4378716082

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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.