Evidence map›Paper›PMID 41483317›Full record

ArticleMolecular diversity2026

In-Silico identification and optimization of therapeutic peptides against breast cancer via transcriptomic profiling.

Hossam Kamli, Aisha Shubaili, Adil A Yousif, Mohamed O Andarawi, Magdi M Salih, Hassan M Otifi, Saleh M Al-Qahtani, Najeeb Ullah Khan

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

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

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

8 authors.

Hossam KamliDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, 61421, Saudi Arabia.
Aisha ShubailiDepartment of Medical Laboratory, King Khalid University Medical City, King Khalid University, Abha, Saudi Arabia.
Adil A YousifDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, 61421, Saudi Arabia.
Mohamed O AndarawiDepartment of Pathology, College of Medicine, King Khalid University Abha, Abha, 61421, Saudi Arabia.
Magdi M SalihCollege of Applied Medical Sciences, Department of Clinical Laboratory Sciences, Taif University, Taif, Kingdom of Saudi Arabia.
Hassan M OtifiDepartment of Pathology, College of Medicine, King Khalid University Abha, Abha, 61421, Saudi Arabia.
Saleh M Al-QahtaniDepartment of Child Health, College of Medicine, King Khalid University, Abha, 61421, Saudi Arabia.
Najeeb Ullah KhanInstitute of Biotechnology and Genetic Engineering, The University of Agriculture, Peshawar. 25130, Peshawar, Pakistan. najeebkhan@aup.edu.pk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study integrates transcriptomic, proteomic, and immunoinformatic analyses to identify peptide-based and repurposed drug candidates for Breast cancer therapy. Differential gene expression profiling across four independent datasets (GSE134938, GSE213481, GSE214054, and GSE148657) identified 455 significantly upregulated and 439 downregulated genes out of 6,124, with ANKFY1 (GSE134938) and ATE1 (GSE148657) emerging as robust markers. Functional clustering highlighted consistent upregulation of genes involved in extracellular matrix (ECM) remodeling, tumor invasion, and metabolic reprogramming (COL1A1, FN1, SPP1, MMPs, SCD), alongside downregulation of adhesion and mitochondrial genes, suggesting epithelial-mesenchymal transition (EMT) and metabolic vulnerabilities. Protein-protein interaction network analysis revealed ANKFY1, STARD4/5, and CADM1 as central hubs enriched in lipid metabolism, ECM regulation, and cytoskeletal signaling. Functional enrichment underscored cholesterol transport, steroid biosynthesis, and PPAR/AMPK signaling as key pathways in BC pathogenesis. Proteomic profiling of 21 breast cancer-associated proteins generated 28,732 human-specific peptides, prioritized using a composite scoring system integrating immunogenicity, physicochemical traits, and safety. Top peptides, including SCAMP2, CADM1, and FNBP1, exhibited high MHC binding affinity (IC50 < 30 nM), non-allergenic and non-toxic profiles, and favorable solubility, with motif analysis identifying conserved functional patterns across SCAMP2, CADM1, and FNBP1. Structural modeling and virtual screening validated these proteins as tractable targets, with nilotinib and tucatinib emerging as promising multitarget repurposed drug candidates. At the same time, terfenadine displayed strong binding but cardiotoxic potential. Collectively, these results highlight lipid-driven oncogenesis and ECM remodeling as central to BC biology and provide a translational framework for peptide-based immunotherapy and drug repurposing.

Indexed as

Antineoplastic AgentsBreast NeoplasmsGene Expression ProfilingPeptidesTranscriptomeComputer SimulationFemaleGene Expression Regulation, NeoplasticHumansProtein Interaction MapsProteomicsAntineoplastic AgentsPeptidesBreast cancerDrug repurposingPeptide therapeuticsProtein–protein interactionTranscriptomics

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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.