A Gemma model helped discover a new potential cancer therapy pathway

Summary

We gave our new C2S-Scale 27B model a task: Find a drug that acts as a conditional amplifier, one that would boost the immune signal only in a specific “immune-context-positive” environment where low levels of interferon (a key immune-signaling protein) were already present, but inadequate to induce antigen presentation on their own. This required a level of conditional reasoning that appeared to be an emergent capability of scale; our smaller models could not resolve this context-dependent effect.To accomplish that, we designed a dual-context virtual screen to find this specific synergistic effect. The virtual screen involved two stages:Immune-Context-Positive: We provided the model with real-world patient samples with intact tumor-immune interactions and low-level interferon signaling.Immune-Context-Neutral: We provided the model with isolated cell line data with no immune context.We then simulated the effect of over 4,000 drugs across both contexts and asked the model to predict which drugs would only boost antigen presentation in the first context, to bias the screen towards the patient-relevant setting. Out of the many drug candidates highlighted by the model, a fraction (10-30%) of drug hits are already known in prior literature, while the remaining drugs are surprising hits with no prior known link to the screen.From prediction to experimental validationThe model's predictions were clear. It identified a striking “context split” for the kinase CK2 inhibitor called silmitasertib (CX-4945). The model predicted a strong increase in antigen presentation when silmitasertib was applied in the “immune-context-positive” setting, but little to no effect in the “immune-context-neutral” one. What made this prediction so exciting was that it was a novel idea. Although CK2 has been implicated in many cellular functions, including as a modulator of the immune system, inhibiting CK2 via silmitasertib has not been reported in the literature to explicitly enhance MHC-I expres...