Predicting sensitivity and resistance in RET-driven cancers
预测 RET 驱动的癌症的敏感性和耐药性
基本信息
- 批准号:10210994
- 负责人:
- 金额:$ 40.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-04-01 至 2026-03-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAdoptionAdultAllelic ImbalanceBiologicalBiopsyBypassCatalogingClinicalClonalityCollectionCombined Modality TherapyComputer AnalysisComputing MethodologiesData SetDependenceDrug ApprovalEffectivenessEvolutionFDA approvedFutureGeneticGenomicsHistologicIn VitroKRAS2 geneKineticsLeadershipLesionLibrariesLifeLungMDM2 geneMalignant Childhood NeoplasmMalignant NeoplasmsMalignant neoplasm of lungMalignant neoplasm of thyroidMethodsModelingMolecularMutationNaturePathway interactionsPatient SelectionPatientsPharmaceutical PreparationsPharmacologyPhase I/II TrialPlasmaPre-Clinical ModelProgression-Free SurvivalsProtocols documentationRET inhibitionReceptor Protein-Tyrosine KinasesResistanceResistance developmentResourcesRoleSamplingSavingsSignal TransductionStructureTherapeuticTimeTissuesTreatment EfficacyTyrosine Kinase InhibitorValidationcell free DNAclinically relevantco-clinical trialcombinatorialdeep sequencingdisorder controlexome sequencingin vivoinhibitor/antagonistmodel developmentmutantneoplastic cellnext generationnon-genomicnovelnovel therapeutic interventionpatient biomarkerspatient derived xenograft modelpre-clinicalpreventprogramsprospectiveresistance mechanismresponders and non-respondersresponsetumortumor progression
项目摘要
Selpercatinib (LOXO-292) is a highly active selective RET inhibitor explored on an ongoing registrational
program (LIBRETTO-001 phase 1/2 trial) in RET-dependent cancers (US FDA approval in 2020 for RET
fusion-positive lung/thyroid cancer and RET-mutant thyroid cancer). Unfortunately, resistance is
uncharacterized and remains a liability. This proposal anticipates and addresses this unmet need by identifying
and functionally characterizing mechanisms of intrinsic and acquired genomic and non-genomic resistance to
selective RET inhibition in RET-dependent cancers. To accomplish this, we will leverage unique clinical,
computational, and translational resources at our disposal. Aim 1 will identify determinants of intrinsic
resistance to RET inhibition in RET-dependent cancers. Pre-treatment biopsies of selpercatinib responders
and non-responders will undergo targeted/whole exome sequencing. Computational analysis will explore the
role of clonality, allelic imbalance, and co-mutational signatures relative to selpercatinib response and
progression-free survival. Aim 2 will establish the mechanisms of acquired resistance to selective RET
inhibition. Paired pre-treatment and post-progression tumor biopsies and longitudinal cell-free (cf)DNA
(baseline, on-treatment, at/post- progression) from LIBRETTO-001 patients will be profiled. Utilizing paired
samples will allow for the identification of emergent genomic and non-genomic (including histologic/EMT
transformation) resistance mechanisms. In addition, plasma profiling will allow for a dynamic assessment of
selpercatinib resistance that captures the consequences of serial genomic evolution. Aim 3 will functionally
characterize resistance to selective RET inhibition. A unique and rich library of patient-derived models of
treatment-naïve and RET inhibitor resistant RET-dependent cancers will be augmented by ongoing prospective
collection and model development from LIBRETTO-001 and commercial use. In these models, on-target
(secondary RET mutations) and off-target (MET/PI3K/KRAS/MDM2 activation) resistance mechanisms will be
functionally characterized in terms of cell/tumor viability, receptor tyrosine kinase activation, and downstream
signaling dependencies. Novel therapeutic strategies, specifically RET tyrosine kinase inhibitor type switching
(on-target resistance) and combinatorial therapies (off-target resistance), will be explored in vitro and in vivo.
Optimal combination therapies will then be employed in compassionate use programs to confirm their
effectiveness and provide tailored, life-saving treatment to patients. In addition, patients with on-target
resistance will be treated on-protocol (Drilon PI) with the next-generation RET inhibitor, TPX-0046. This
proposal has both immediate and long-term relevance considering that about 400 patients have been treated
with selpercatinib around the world on trial and the potential approval and rapid adoption of this drug by
multiple regulatory agencies. These current and future patients are in dire need of strategies to re-establish
durable disease control after progression on selective RET inhibition.
Selpercatinib(LOXO-292)是一种高活性的选择性RET抑制剂,正在进行注册研究
RET依赖型癌症的计划(libretto-001阶段1/2试验)(美国FDA于2020年批准RET
融合阳性肺癌/甲状腺癌和RET突变甲状腺癌)。不幸的是,抵抗是
没有特征,仍然是一种负担。本提案通过确定以下内容来预测和解决这一未得到满足的需求
以及内在和获得性基因组和非基因组抗性的功能表征机制
RET依赖癌症中的选择性RET抑制。为了实现这一目标,我们将利用独特的临床、
我们可以使用计算和翻译资源。目标1将确定内在因素的决定因素
依赖RET的癌症患者对RET抑制的抵抗。赛培卡替尼应答者的治疗前活检
而无反应者将接受靶向/整个外显子组测序。计算分析将探索
克隆性、等位基因不平衡和共突变特征与Selpercatinib反应和
无进展生存。目标2将建立对选择性RET的获得性耐药机制
抑制力。配对治疗前后肿瘤活检和纵向无细胞(Cf)DNA
(基线、治疗中、进展中/进展后)将对libretto-001患者的情况进行分析。利用配对
样本将允许识别紧急基因组和非基因组(包括组织学/EMT
转化)抗性机制。此外,血浆分析将允许动态评估
赛培卡替尼抵抗,捕捉到一系列基因组进化的后果。Aim 3将在功能上
表征对选择性RET抑制的抗性。独特而丰富的患者衍生模型库
治疗-对RET耐药和RET抑制剂耐药的RET依赖癌症将因正在进行的前瞻性研究而增加
从libretto-001和商业用途收集和模型开发。在这些模型中,目标是
(继发性RET突变)和脱靶(MET/PI3K/KRAS/MDM2激活)抗性机制将是
根据细胞/肿瘤活性、受体酪氨酸激酶激活和下游的功能表征
信令依赖关系。新的治疗策略,特别是RET酪氨酸激酶抑制物类型转换
(靶上抵抗)和联合治疗(靶外抵抗),将在体外和体内进行探索。
然后,最佳组合疗法将被用于同情使用计划,以确认他们的
并为患者提供量身定做的挽救生命的治疗。此外,符合目标的患者
耐药性将按照协议(Drilon PI)使用下一代RET抑制剂TPX-0046进行治疗。这
考虑到大约400名患者已经接受了治疗,这项提议既有直接意义,也有长期意义
塞培卡替尼在世界各地处于试验阶段,该药物可能获得批准并迅速通过
多个监管机构。这些当前和未来的患者迫切需要策略来重建
选择性RET抑制进展后的持久疾病控制。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Alexander Drilon其他文献
Alexander Drilon的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Alexander Drilon', 18)}}的其他基金
Predicting sensitivity and resistance in RET-driven cancers
预测 RET 驱动的癌症的敏感性和耐药性
- 批准号:
10376881 - 财政年份:2021
- 资助金额:
$ 40.49万 - 项目类别:
Predicting sensitivity and resistance in RET-driven cancers
预测 RET 驱动的癌症的敏感性和耐药性
- 批准号:
10608125 - 财政年份:2021
- 资助金额:
$ 40.49万 - 项目类别:
Understanding tumor addiction to TRK fusions and sensitivity to TRK inhibition
了解肿瘤对 TRK 融合的成瘾性和对 TRK 抑制的敏感性
- 批准号:
9917755 - 财政年份:2018
- 资助金额:
$ 40.49万 - 项目类别:
Understanding tumor addiction to TRK fusions and sensitivity to TRK inhibition
了解肿瘤对 TRK 融合的成瘾性和对 TRK 抑制的敏感性
- 批准号:
10155443 - 财政年份:2018
- 资助金额:
$ 40.49万 - 项目类别:
相似海外基金
WELL-CALF: optimising accuracy for commercial adoption
WELL-CALF:优化商业采用的准确性
- 批准号:
10093543 - 财政年份:2024
- 资助金额:
$ 40.49万 - 项目类别:
Collaborative R&D
Investigating the Adoption, Actual Usage, and Outcomes of Enterprise Collaboration Systems in Remote Work Settings.
调查远程工作环境中企业协作系统的采用、实际使用和结果。
- 批准号:
24K16436 - 财政年份:2024
- 资助金额:
$ 40.49万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Unraveling the Dynamics of International Accounting: Exploring the Impact of IFRS Adoption on Firms' Financial Reporting and Business Strategies
揭示国际会计的动态:探索采用 IFRS 对公司财务报告和业务战略的影响
- 批准号:
24K16488 - 财政年份:2024
- 资助金额:
$ 40.49万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10107647 - 财政年份:2024
- 资助金额:
$ 40.49万 - 项目类别:
EU-Funded
Assessing the Coordination of Electric Vehicle Adoption on Urban Energy Transition: A Geospatial Machine Learning Framework
评估电动汽车采用对城市能源转型的协调:地理空间机器学习框架
- 批准号:
24K20973 - 财政年份:2024
- 资助金额:
$ 40.49万 - 项目类别:
Grant-in-Aid for Early-Career Scientists
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
- 批准号:
10106221 - 财政年份:2024
- 资助金额:
$ 40.49万 - 项目类别:
EU-Funded
Our focus for this project is accelerating the development and adoption of resource efficient solutions like fashion rental through technological advancement, addressing longer in use and reuse
我们该项目的重点是通过技术进步加快时装租赁等资源高效解决方案的开发和采用,解决更长的使用和重复使用问题
- 批准号:
10075502 - 财政年份:2023
- 资助金额:
$ 40.49万 - 项目类别:
Grant for R&D
Engage2innovate – Enhancing security solution design, adoption and impact through effective engagement and social innovation (E2i)
Engage2innovate — 通过有效参与和社会创新增强安全解决方案的设计、采用和影响 (E2i)
- 批准号:
10089082 - 财政年份:2023
- 资助金额:
$ 40.49万 - 项目类别:
EU-Funded
De-Adoption Beta-Blockers in patients with stable ischemic heart disease without REduced LV ejection fraction, ongoing Ischemia, or Arrhythmias: a randomized Trial with blinded Endpoints (ABbreviate)
在没有左心室射血分数降低、持续性缺血或心律失常的稳定型缺血性心脏病患者中停用β受体阻滞剂:一项盲法终点随机试验(ABbreviate)
- 批准号:
481560 - 财政年份:2023
- 资助金额:
$ 40.49万 - 项目类别:
Operating Grants
Collaborative Research: SCIPE: CyberInfrastructure Professionals InnoVating and brOadening the adoption of advanced Technologies (CI PIVOT)
合作研究:SCIPE:网络基础设施专业人员创新和扩大先进技术的采用 (CI PIVOT)
- 批准号:
2321091 - 财政年份:2023
- 资助金额:
$ 40.49万 - 项目类别:
Standard Grant