OncoTreat
Alvarez MJ, Subramaniam PS, Tang LH, Grunn A, Aburi M, Rieckhof G, Komissarova EV, Hagan EA, Bodei L, Clemons PA, Dela Cruz FS, Dhall D, Diolaiti D, Fraker DA, Ghavami A, Kaemmerer D, Karan C, Kidd M, Kim KM, Kim HC, Kunju LP, Langel Ü, Li Z, Lee J, Li H, LiVolsi V, Pfragner R, Rainey AR, Realubit RB, Remotti H, Regberg J, Roses R, Rustgi A, Sepulveda AR, Serra S, Shi C, Yuan X, Barberis M, Bergamaschi R, Chinnaiyan AM, Detre T, Ezzat S, Frilling A, Hommann M, Jaeger D, Kim MK, Knudsen BS, Kung AL, Leahy E, Metz DC, Milsom JW, Park YS, Reidy-Lagunes D, Schreiber S, Washington K, Wiedenmann B, Modlin I, Califano A
2018 · Cancer Discovery
Classical Level 2 proxy method. Estimates master-regulator activity with VIPER and ranks compounds by their ability to reverse that activity profile against perturbation atlases.
Abstract
From the original paper, Cancer Discovery · PubMed
We introduce and validate a new precision oncology framework for the systematic prioritization of drugs targeting mechanistic tumor dependencies in individual patients. Compounds are prioritized on the basis of their ability to invert the concerted activity of master regulator proteins that mechanistically regulate tumor cell state, as assessed from systematic drug perturbation assays. We validated the approach on a cohort of 212 gastroenteropancreatic neuroendocrine tumors (GEP-NETs), a rare malignancy originating in the pancreas and gastrointestinal tract. The analysis identified several master regulator proteins, including key regulators of neuroendocrine lineage progenitor state and immunoevasion, whose role as critical tumor dependencies was experimentally confirmed. Transcriptome analysis of GEP-NET-derived cells, perturbed with a library of 107 compounds, identified the HDAC class I inhibitor entinostat as a potent inhibitor of master regulator activity for 42% of metastatic GEP-NET patients, abrogating tumor growth in vivo. This approach may thus complement current efforts in precision oncology.
Summary
OncoTreat is the classical proxy inverse-design method. It estimates malignant master-regulator activity with VIPER and ranks compounds by their ability to reverse that activity profile against perturbation atlases such as LINCS L1000.
The score linking intervention to response is explicit, but the response is a compound signature proxy rather than a simulated regulatory trajectory. This places OncoTreat at Level 2 within the inverse-design fidelity taxonomy: an outcome term is in the objective, but the outcome comes from — a perturbation-atlas response map — rather than from a mechanistic model with explicit intervention semantics.
Why this level
Level 2 because the method instantiates the optimization form with the LINCS L1000 compound-response atlas serving as the empirical proxy response map. Representation family is signature / state-matching because the proxy operates over master-regulator signature space (VIPER activity profiles), not over a regulatory-network propagation graph.