Utilising multi-modal data-driven network analysis to identify monotherapy and combinational therapy targets in SOX2-dependent squamous cell lung cancer
Woochang Hwang, Daniel Kottmann, Wenrui Guo, Méabh MacMahon, Lucia Correia, Sherine Ahmed, Rebecca Harris, Frank McCaughan, Namshik Han · 2025
Read Utilising multi-modal data-driven network analysis to identify monotherapy and combinational therapy targets in SOX2-dependent squamous cell lung cancer by Woochang Hwang, Daniel Kottmann, Wenrui Guo, Méabh MacMahon, Lucia Correia, Sherine Ahmed, Rebecca Harris, Frank McCaughan, Namshik Han (2025) 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-12717043.txt.
Description
Woochang Hwang and eight colleagues built a data-integration pipeline to find drug targets in a lung cancer addicted to one gene. Squamous cell lung cancer makes up about a quarter of cases and lacks targeted treatments. Half its tumors amplify SOX2, a gene that sustains the cancer's identity. Their pipeline, iPANDDA, fuses omics, disease, and pathway data into networks that nominate targets. Predictions were then tested in cells.
Blocking AKT or mTOR complexes worked as single and combination strategies against SOX2-dependent cells. The analysis also mapped combination routes for attacking the SOX2 program indirectly, since SOX2 itself is hard to drug. The twenty twenty-five study demonstrates a general recipe: integrate every data type available, rank network nodes, and validate the shortlist experimentally, instead of betting on single-dataset hunches.
Catalog record
| CREATOR | Woochang Hwang, Daniel Kottmann, Wenrui Guo, Méabh MacMahon, Lucia Correia, Sherine Ahmed, Rebecca Harris, Frank McCaughan, Namshik Han |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 88 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |