Identification of Diagnostic and Prognostic Subnetwork Biomarkers for Women with Breast Cancer Using Integrative Genomic and Network-Based Analysis
Olfat Al-Harazi, Achraf El Allali, Namik Kaya, Dilek Colak, Stergios Boussios, Matin Sheriff · 2024
Read Identification of Diagnostic and Prognostic Subnetwork Biomarkers for Women with Breast Cancer Using Integrative Genomic and Network-Based Analysis by Olfat Al-Harazi, Achraf El Allali, Namik Kaya, Dilek Colak, Stergios Boussios, Matin Sheriff (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11641665.txt.
Description
Olfat Al-Harazi and co-authors hunt in 2024 for gene network markers that can both spot breast cancer and forecast its course in women. Breast cancer stays a top cause of cancer death in women, and early finding saves lives. Gene chips give deep views of tumor biology, but single gene lists can mislead.
The team merged gene activity data with maps of how proteins interact, and pulled out four significant subnetworks. Hub genes inside them include known cancer drivers and cell division players. In separate data sets, the subnetworks split patients from healthy controls cleanly, and a simple classifier scored high on accuracy and sensitivity. In a far larger patient set, the markers also carried survival signal. The authors argue that network level markers, not lone genes, may give steadier tools for diagnosis and prognosis.
Catalog record
| CREATOR | Olfat Al-Harazi, Achraf El Allali, Namik Kaya, Dilek Colak, Stergios Boussios, Matin Sheriff |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 21 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |