Evidence map›Paper›PMID 41296246›Full record

ArticleDiscover oncology2025

Exploring the TRIM15 protein interaction network as a drug target using machine learning in pancreatic cancer.

Kübra Sena Bas Topcu, Kubra Temiz, Ercan Cacan

Abstract read
In one paragraph

Article in Discover oncology, 2025. 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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0cells of the map it votes in
0citing 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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

3 authors.

Kübra Sena Bas TopcuDepartment of Molecular Biology and Genetics, Faculty of Science, Bartin University, Bartin, Türkiye.
Kubra TemizDepartment of Biotechnology, Faculty of Science, Bartin University, Bartin, Türkiye. ktemiz@bartin.edu.tr.
Ercan CacanDepartment of Molecular Biology and Genetics, Faculty of Science and Art, Tokat Gaziosmanpasa University, Tokat, Türkiye. ercan.cacan@gop.edu.tr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is among the most lethal cancers with a 5-year survival rate of only 13%. Due to its late-stage diagnosis and high metastatic potential, there is a critical need to better understand its molecular mechanisms to develop effective treatments. Tripartite motif containing 15 (TRIM15), a member of the TRIM protein family, plays a role in tumor progression, immune evasion, and lipid metabolism reprogramming, but its role in apoptosis and immune-related pathways remains unclear. Moreover, immune checkpoint proteins such as PD-L1 and VISTA have been associated with cancer progression and poor survival by contributing significantly to the tumor microenvironment. In this context, in order to better understand the effects of TRIM15 and its neighboring genes on pancreatic cancer, other genes interacting with these genes were obtained from NCBI and BioGRID databases. In the topological analysis of the protein-protein interaction network, 191 proteins in which TRIM15 is involved were identified and the expression profiles of these proteins in pancreatic cancer were analyzed using the Expression Atlas database. These analyses revealed 73 differentially expressed proteins compared to normal individuals, and high accuracy (> 0.90) was achieved with machine learning algorithms. These proteins were identified as drug targets and 50 drug candidates were identified through the L1000CSD2 database. As a result of the TF-IDF calculations performed for innovation, impartozole with a TF-IDF value of 0 was selected as a potential drug candidate for the treatment of pancreatic cancer. Importin-β1, which is overexpressed in many cancers, is associated with tumor progression and its inhibitor, importazole, exhibits antitumor activity by inducing G2/M cell cycle arrest and apoptosis. Here, TRIM15 regulation, apoptosis mechanism and immune checkpoint mechanisms were investigated to reveal the role of importazole on the underlying mechanisms of pancreatic cancer progression. The findings show that importazole administration suppressed the expression level of TRIM15 and VISTA in AsPC-1 pancreatic cancer cells and triggered the apoptosis mechanism. These results suggest that importazole may be a potential therapeutic target for TRIM15 and VISTA in pancreatic cancer and may contribute to the development of innovative strategies for cancer treatment.

Indexed as

Immune checkpointImportazoleMachine learningPancreatic cancerProtein-protein interaction networkTRIM15

Identifiers

PMID41296246
PMCPMC12662958

What Socratic holds

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Registered trials

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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.