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

通过基于片段的化学蛋白质组学方法克服对 KRAS 抑制剂的耐药性

• 批准号: 10722113
• 负责人: ERIC B. HAURA
• 金额: $ 43.33万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-19 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10722113
• 关键词: Address; Adenocarcinoma; Affinity; Alkynes; Azides; Binding; Binding Sites; Biochemical; Biological; Biological Assay; Biology; Cancer Model; Cancer Patient; Cancer cell line; Cell Line; Cell Survival; Cell model; Cells; Chemicals; Chemistry; Clustered Regularly Interspaced Short Palindromic Repeats; Colon; Copper; DNA Sequence Alteration; Data; Databases; Dedications; Development; Diazomethane; Disease Progression; Dose; Drug resistance; Engineering; Epigenetic Process; Epithelial Cells; Epithelium; Future; Genetic; Genetic Transcription; Genomics; Histologic; Histology; Induction of Apoptosis; Informatics; KRAS2 gene; Lead; Libraries; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Mediating; Mesenchymal; Mining; Modeling; Mutation; Outcome; Parents; Pathway interactions; Patients; Pharmaceutical Chemistry; Pharmaceutical Preparations; Phase I/II Clinical Trial; Phenotype; Proteomics; RNA Interference; Reporting; Research; Resistance; Signal Transduction; Structure; Testing; Time; Translations; Validation; Western Blotting; Work; analog; cancer therapy; cell type; chemoproteomics; cycloaddition; cytotoxic; drug discovery; drug-like compound; drug-sensitive; functional group; in vivo; inhibitor; lung cancer cell; mutant; non-genomic; novel; novel strategies; novel therapeutics; rare cancer; resistance mechanism; response; scaffold; screening; small molecule; tool; transcriptional reprogramming; tumor; tumor progression

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.

抽象的 近年来，主要的突破是针对Krasg12c的选择性抑制剂的发展 在肺，结肠和其他稀有癌症典型中发现的突变。 Sotorasib和Adagrasib的响应率为 KRASG12C突变肺癌的近40％。尽管有这一进步，但仍有两个主要问题 地址。首先，一组大量的患者没有肿瘤回归。第二，回答是 瞬态，抗性的出现导致肿瘤进展。而基因组机制具有 已确定驱动获得的抗性，一组相当大的肿瘤缺乏明显的基因组机制 并似乎依靠转录重编程或表观遗传机制。我们已经生成了细胞系 概括了抗性的非基因组机制的模型（i）确定与 抗性和（ii）开发铅化合物，以在未来的药物发现工作中服务。确定两个新目标 和铅化合物，我们将利用一种新的基于片段的化学蛋白质组学方法。片段状探针 由于其尺寸较小，并且具有更大的装饰类药物分子的优势，并且 （ii）更简单的结构可以吸引目标绑定位点，这些结合位点无法访问更加发达和复杂的结构 分子。因此，碎片样分子是识别新靶标和未知生物学的独特工具 目标空间。我们在Sotorasib抗性细胞模型中的初步数据表明该屏幕的能力识别 与药物敏感的父母相比，抗性细胞活性增强的片段。另外，使用 一组功能化的20个片段，我们在Krasg12c突变体H1792细胞中证明了鉴定能力 这些碎片的靶标使用化学蛋白质组学。 AIM 1将测试我们可以识别的假设 与未经治疗的药物敏感细胞相比，sotorasib抗性细胞活性增强的片段。 我们将利用Sotorasib抗性的其他细胞系模型，并使用非Krasg12c突变肺癌 模型和非肿瘤肺上皮细胞以提高选择性。目的2我们将检验目标的假设 可以通过化学蛋白质组学识别抗性表型。我们将评估20的目标 官能化的片段以及评估我们较大片段筛选中确定的目标。通过使用 这种方法可以探索更大的生物学目标空间，我们希望确定独特的 KRASG12C抑制剂耐药细胞的靶标。同时，我们的方法将确定化学铅的吸引力 这些目标是未来专门的药物发现项目。