PO.CL07.02 · 临床研究
通过信号抑制指数(SII)剖析状态选择性和旁系同源物选择性RAS抑制剂的肿瘤选择性
Profiling tumor selectivity of state- and paralog-selective RAS inhibitors through a signaling inhibition index (SII)
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
随着突变选择性KRAS(G12C)抑制剂的问世,RAS导向疗法的格局迅速推进,推动了更多RAS靶向药物的开发,包括突变选择性(如KRAS(G12C)、KRAS(G12D))以及旁系同源物选择性和状态选择性化合物。非突变特异性RAS抑制目前可通过三种策略实现:(i)鸟嘌呤核苷酸交换-OFF抑制剂(panRAS-GEF(OFF)i),通过靶向SHP2或SOS1间接使RAS失活,(ii)保留NRAS和HRAS的KRAS-OFF抑制剂(panKRAS(OFF)i),以及(iii)直接阻断效应器RAF结合的活性状态RAS(ON)抑制剂(panRAS(ON)i)。尽管这些治疗模式已显示出前景,但其临床有效性和耐受性最终取决于实现高治疗指数,即对肿瘤细胞中致癌信号的强效抑制而对正常细胞影响最小。为在临床前模型中更稳健地量化肿瘤选择性,我们引入信号抑制指数(SII),其测量RAS(MUT)和RAS(WT)细胞之间致癌信号的差异性抑制,为此前定义不清的肿瘤选择性提供了更结构化的指标。在此,我们评估了状态选择性和旁系同源物选择性RAS抑制剂在多种RAS(MUT)和RAS(WT)模型中的SII。PanRAS-GEF(OFF)i表现出中性或负性SII,反映了KRAS(G12X)细胞相比野生型细胞的MAPK抑制减弱。KRAS(G13D)模型,尤其是伴NF1缺失者,显示低敏感性。联合SHP2和MEK抑制导致低肿瘤选择性,而RAS(Q61X)模型因MEK抑制剂诱导的NRAS再激活和SHP2构象改变而耐药。与这些发现一致,对DepMap SHP2抑制剂敏感性和依赖性数据集的分析表明,RAS(MUT)细胞系对SHP2抑制并不比RAS(WT)细胞更敏感,进一步凸显了基于panRAS-GEF(OFF)方法的有限肿瘤选择性。同时,我们在一组RAS(MUT)和RAS(WT)细胞系模型中评估了panKRAS(OFF)i和panRAS(ON)i的效力/选择性。KRAS(OFF)抑制剂显示出更高的选择性,而活性状态RAS(ON)抑制剂显示出更广泛的活性但狭窄的选择性。对已发表数据集的比较分析揭示了RAS抑制剂各类别间相关的敏感性模式,表明治疗活性在很大程度上局限于相同的RAS(MUT)癌症亚群。这些发现凸显了系统性SII量化对治疗选择性以及指导下一代RAS靶向疗法的合理设计和临床实施的重要性。
查看英文原文 English abstract
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.
利益披露 Disclosure
B. Baars, None..
A. Orive-Ramos, None..
M. Emmett, None..
B. Gaire, None..
M. Desaunay, None..
Z. Kou, None..
G. Li, None..
C. Adamopoulos, None..
S. A. Aaronson, None..
S. Wang, None.
W. R. Sellers,
Pierre Fabre Other, Consulting.
Delphia Therapeutics Other, Consulting.
Red Ridge Bio Other, Consulting.
Atavistik Bio Other, Consulting.
CJ Biosciences Other, Consulting.
Ideaya Biosciences Other, Consulting.
Astex Pharmaceuticals Other, Consulting.
Scorpion Therapeutics Other, Consulting.
2seventy bio Other, Consulting.
Servier Pharmaceuticals ).
Pfizer ).
Boehringer Ingelheim ).
Bayer Pharmaceuticals ).
Novartis Pharmaceuticals ).
Merck Pharmaceuticals ).
Ridgeline Discovery ).
Calico Life Sciences ).
Bristol Myers Squibb ).
T. Martin, None.
E. Gavathiotis,
BaxGen Therapeutics Other, Consulting.
Life Biosciences Other, Consulting.
Stelexis Biosciences Other, Consulting.
BeanPod Biosciences Other, Consulting.
Comorin Therapeutics Other, Consulting.
P. I. Poulikakos,
Verastem Oncology ), Consulting.
Enliven Therapeutics ).
Nuvalent Other, Consulting.
Fore Biotherapeutics Other, Consulting.
Belharra Therapeutics Other, Consulting.