Lung Cancer Ion-Trap Vulnerability: Synthetic Virtual Screening and Hypothesis Falsification Dataset (Triple Trap)
Year: 2026
Type: preprint
Abstract: FREE SAMPLE INCLUDED. This record contains the full technical documentation and a free evaluation sample (336 rows covering 57 profiles), not the full dataset. The complete dataset (10,123 profiles, 81,024 screen outcomes, 8 Parquet files) is available here: https://sentineldata.com.ua/dataset/triple-trap-lung-cancer-ion-trap-vulnerability About the dataset: Triple Trap is a mechanistic cell-death dataset built around one engineering question: can a cancer cell's own ion-transport machinery be turned against it faster than it can route around the attack? A 9-state ODE model blocks four proton and lactate export valves (NHE1, MCT1/4, V-ATPase, CA9/CA12 bicarbonate import) while an independent metabolic trigger pushes the cell toward oxidative or disulfide-driven collapse. 123 real lung-cancer cell lines (DepMap 25Q3) plus 10,000 synthetic profiles are each run through all 8 treatment conditions (81,024 outcomes). Mixed evidence package: the real-data tests and the 123 real-cell-line expression rows are real DepMap data; every other row is an in silico model prediction, not experimental or patient data. Full description with tables is on the Wiki page of this project. Zenodo copy: https://doi.org/10.5281/zenodo.23984955
Source: OSF Preprints (OSF Preprints)
Author: Maksym Chekerskyi
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7225327333