Identifying gene regulation modules associated with tumor metastasis using a network decomposition approach and combinatorial fusion analysis
Aninda Astuti, Christina Schweikert, Chia-Wei Weng, Derbiau Frank Hsu, Ka-Lok Ng · 2026
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Description
Aninda Astuti and four colleagues break cancer networks into small regulatory teams to find the ones driving metastasis. Their 2026 study builds a bioinformatics framework around gene regulatory modules: tiny groups of genes acting together. Modules were extracted from molecular networks and ranked by a combinatorial fusion method. Kidney cancer metastasis cohorts supplied the test beds. The top-ranked modules were cross-examined against cancer hallmark lists, drug-target databases, and patient survival data.
The framework beat existing methods at flagging metastasis-linked modules. Its choices stayed stable across ten different feature combinations. Three-gene and four-gene module versions performed consistently as well. Spread, not the primary tumour, is what usually kills cancer patients. Modules that reliably mark spread could nominate both warning biomarkers and drug targets. Because the method reads coordination rather than single genes, it may catch drivers that one-gene-at-a-time hunts keep missing.
Catalog record
| CREATOR | Aninda Astuti, Christina Schweikert, Chia-Wei Weng, Derbiau Frank Hsu, Ka-Lok Ng |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 54196 |
| LICENSE | CC_BY |
| RIGHTS | CC BY |
| SOURCE | PLOS |