Table · dataset · 2026
<b>Interpretable AI Fusion Prioritizes Nomilin-Responsive Targets and PI3K/Akt/</b><b>Cyclin D1</b><b> Signaling in Triple-Negative Breast Cancer</b>
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<p dir="ltr">Triple-negative breast cancer (TNBC) remains difficult to treat because of its molecular heterogeneity, aggressive progression, and limited actionable targets.
Description
Nomilin, a citrus-derived limonoid, has shown potential antitumor activity, but its target network and mechanism in TNBC remain incompletely characterized. This study developed an interpretable artificial intelligence (AI)-assisted multi-source evidence fusion framework to prioritize nomilin-responsive targets and validate their biological relevance.
In Stage I, transcriptomic dysregulation, weighted gene co-expression modules, disease-target evidence, compound-target evidence, protein-protein interaction topology, graph embedding, pathway context, and molecular docking were integrated into a positive-unlabeled (PU) ensemble target-ranking framework with an independent held-out reference set. In Stage II, molecular dynamics simulation, MM/GBSA binding free energy, proteome microarray, cellular thermal shift assay, microscale thermophoresis (MST), single-cell mapping, immune deconvolution, cellular assays, Akt rescue, and xenograft validation were used as independent post-ranking evidence.
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Among 221 candidate nomilin-TNBC targets, PARP1, EGFR, HSP90AA1, BCL2, CASP3, CCND1, KRAS, and TNF were prioritized as high-priority targets. SHAP analysis showed that graph-derived features, transcriptomic relevance, docking plausibility, and PI3K/Akt pathway context contributed substantially to ranking. Independent held-out evaluation yielded,, and.
An external curcumin-colorectal-cancer benchmark showed a smaller but consistent advantage of the PU-XGBoost framework over GraphSAGE and random forest. Post-ranking validation supported protein-level binding signals and selected cellular target engagement. Orthogonal MST measurements supported measurable nomilin binding to several prioritized proteins, whereas TNF showed weak, non-saturating binding within the tested concentration range.
Functionally, nomilin inhibited TNBC cell proliferation and migration, induced mitochondria-dependent apoptosis, and suppressed xenograft growth. SC79-mediated Akt activation partially reversed nomilin-induced inhibition of cell viability and Cyclin D1 expression, supporting the involvement of PI3K/Akt/Cyclin D1 signaling. These findings support further investigation of nomilin as a multi-target natural product candidate in TNBC models.</p>
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Where it is published
- DOI doi.org/10.6084/m9.figshare.33653113.v1 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
- From keywords
- Artificial intelligence · Astronomy & Astrophysics · Biological network analysis · Chemistry · Computer Science & AI · Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Medicine & Health · Ocean & Atmospheric Science · Proteomics and metabolomics · Social Science
- Inferred from text
- Cancer 75% · Simulation 75%
Provenance · 1 source records, 21 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| figshare | oai:figshare.com:article/33653113 | 4 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · figshare com | connector:figshare_com@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · figshare com | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:field:310202 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Biological network analysis'] |
| concepts[field].anzsrc:field:310205 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Proteomics and metabolomics'] |
| concepts[field].anzsrc:group:4602 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['artificial intelligence'] |
| concepts[field].local:field:astronomy | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:engineering | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:humanities | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:ocean-atmospheric | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:social-science | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · figshare com | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/description |
| license | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/rights |
| publication_date | source · figshare com | connector:figshare_com@1.0.0 | |
| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |