Profiling tumor selectivity of state- and paralog-selective RAS inhibitors through a signaling inhibition index (SII)

The landscape of RAS-directed therapies has rapidly advanced following the advent of mutant-selective KRAS(G12C) inhibitors, driving the development of additional RAS-targeting agents, including mutant-selective (e.g. KRAS(G12C), KRAS(G12D)), as well as paralog- and state-selective compounds. Non-mutant- specific RAS inhibition can currently be achieved through three strategies: (i) guanine nucleotide exchange-OFF inhibitors (panRAS-GEF(OFF)i) that indirectly inactivate RAS by targeting SHP2 or SOS1, (ii) KRAS-OFF inhibitors (panKRAS(OFF)i) that spare NRAS and HRAS, and (iii) active-state RAS(ON) inhibitors (panRAS(ON)i) that directly block binding of effector RAF. Although these therapeutic modalities have shown promise, their clinical effectiveness and tolerability ultimately depend on achieving a high therapeutic index, defined as potent inhibition of oncogenic signaling in tumor cells with minimal effects on normal cells. To more robustly quantify tumor selectivity in preclinical models, we introduce the signaling inhibition index (SII), which measures the differential suppression of oncogenic signaling between RAS(MUT) and RAS(WT) cells, providing a more structured metric of tumor selectivity that has previously been poorly defined. Here, we evaluated the SII for state- and paralog-selective RAS inhibitors across diverse RAS(MUT) and RAS(WT) models. PanRAS-GEF(OFF)i exhibited neutral or negative SII, reflecting reduced MAPK suppression in KRAS(G12X) cells compared to wild-type cells. KRAS(G13D) models, especially with NF1 loss, showed low sensitivity. Combining SHP2 and MEK inhibition resulted in low tumor-selectivity, while RAS(Q61X) models were resistant due to MEK inhibitor-induced NRAS reactivation and altered SHP2 conformations. Consistent with these findings, analysis of DepMap SHP2-inhibitor sensitivity and dependency datasets showed that RAS(MUT) cell lines are not more sensitive than RAS(WT) cells to SHP2 inhibition, further underscoring the limited tumor selectivity of panRAS-GEF(OFF)-based approaches. In parallel, we assessed panKRAS(OFF)i and panRAS(ON)i potency/selectivity across a panel of RAS(MUT) and RAS(WT) cell line models. KRAS(OFF) inhibitors demonstrated higher selectivity, whereas active-state RAS(ON) inhibitors showed broader activity but narrow selectivity. Comparative analyses of published datasets revealed correlated sensitivity patterns across RAS inhibitor classes, indicating that therapeutic activity is largely restricted to the same subset of RAS(MUT) cancers. These findings highlight the importance of systemic SII quantification for therapeutic selectivity and for guiding the rational design and clinical implementation of next-generation RAS-targeted therapies.