Overcoming resistance to KRAS inhibitors through a fragment-based chemoproteomics approach

点击翻译按钮获取中文摘要

Abstract A major breakthrough in recent years has been the development of selective inhibitors that target KRASG12C mutations found in lung, colon, and other rare cancer typ. Both sotorasib and adagrasib have response rates of nearly 40% in KRASG12C mutant lung cancer. Despite this advance, there remains two major problems to address. First, a substantial group of patients fail to have tumor regressions. Second, the responses are transient, with the emergence of resistance leading to tumor progression. While genomic mechanisms have been identified that drive acquired resistance, a sizeable group of tumors lack obvious genomic mechanisms and appear to rely on transcriptional reprogramming or epigenetic mechanisms. We have generated cell line models that recapitulate non-genomic mechanisms of resistance to (i) identify such targets associated with resistance and (ii) develop lead compounds to serve in future drug discovery efforts. To identify both new targets and lead compounds, we will leverage a new fragment based chemoproteomics approach. Fragment-like probes have the distinct advantage over larger, more decorated drug-like molecules because of their (i) smaller size and (ii) simpler structures that can engage target binding sites that are inaccessible to more developed and complicated molecules.Thus, fragment-like molecules are unique tools to identify novel targets and probe uncharted biological target space. Our preliminary data in Sotorasib resistant cell models indicates the ability of this screen to identify fragments with enhanced activity in the resistant cells compared to drug sensitive parent. In addition, using a group of functionalized 20 fragments, we demonstrate in the KRASG12C mutant H1792 cell the ability to identify targets of these fragments using chemical proteomics. Aim 1 will test the hypothesis that we can identify fragments that have enhanced activity in the Sotorasib resistant cells compared to untreated drug sensitive cells. We will leverage additional cell line models of Sotorasib resistance, and use non-KRASG12C mutant lung cancer models and non-tumor lung epithelial cells to enhance selectivity. Aim 2 we will test the hypothesis that targets that drive the resistant phenotype can be identified by chemoproteomics. We will assess targets in our 20 functionalized fragment library as well as assess targets identified in our larger fragment screening. By using this approach that enables probing a significantly larger biological target space, we expect to identify unique targets for KRASG12C inhibitor resistant cells. At the same time, our approach will identify chemical leads engaging these targets for future dedicated drug discovery projects.