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Mechanism-based combination therapy for cholangiocarcinoma

Mechanism-based combination therapy for cholangiocarcinoma
基于机制的胆管癌联合治疗
批准号:
10650049
负责人:
Karina J Yoon
金额:
$20.83万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-04-05 至 2025-03-31

项目摘要

项目成果

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中文摘要
翻译
项目摘要/摘要 胆管癌(CCA)是一种侵袭性胆道癌。在场的大多数患者都患有 晚期疾病并在一年内死亡。对于这些患者来说,化疗是主要的治疗选择。当前 治疗标准包括以吉西他滨为基础的方案,如吉西他滨+顺铂。然而,5年期 存活率几十年来没有提高;最初有反应的肿瘤变得耐药, 病人会复发。文献记载,DNA修复蛋白的过度表达与抗性有关 对DNA损伤剂,如吉西他滨和顺铂,目前用于CCA的一线药物。这项建议 寻求确定基于吉西他滨的组合,以克服耐药性并产生耐受性 CCA患者的缓解。 为了确定有效的治疗方案并描述导致化疗敏感性或 为了克服耐药性,我们开发了一组患者来源的异种移植(PDX)CCA模型:CCA1-5和吉西他滨- CCA1和CCA2的抗性对应物(CCA1.geR和CCA2.geR),在体内获得抗性。我们 建议使用这些模型来确定CCA的有效治疗方法。我们的数据支持这样一种假设 吉西他滨+BET抑制剂(Beti)+PARP抑制剂(PARPI)是治疗该肿瘤的有效药物 打字。溴结构域和末端外结构域(BET)蛋白调节转录关联 特定染色体上的组蛋白与乙酰化赖氨酸残基的复合体。β_1基因表达降低 表达依赖于BET的基因。多个Beti正在进行临床试验。 结果表明:1)Beti+PARPI和Beti+吉西他滨在体外具有协同作用; 新发现的GemR细胞对Beti+PARPI比吉西他滨+顺铂更敏感;以及3) 在CCA1中,Beti JQ1+吉西他滨比吉西他滨单独用药更有效。 活体模型(P<0.001)。此外,我们的数据表明,连续服用Beti→吉西他滨将 产生Beti介导的DNA修复蛋白表达的减少,并将吉西他滨的耐药性降至最低。 拟议的工作评估临床Beti OTX015+PARPI olaparib+的抗肿瘤效果 吉西他滨、顺铂或吉西他滨+顺铂在局部和转移性CCA模型中的应用。我们将确定是否 这些方案中的任何一个都优于目前的护理标准,并对所有患者进行全基因组测序 识别与抗性相关的遗传和分子特征的模型。我们还将生成 治疗肿瘤与对照肿瘤以及原发肿瘤与转移肿瘤的表达谱。这些数据将提供一个 为今后确定有助于药物的基因产物和途径的长期目标的工作奠定基础 CCA的耐药或转移,并利用靶向药物开发有效的治疗方案。
英文摘要
PROJECT SUMMARY/ABSTRACT Cholangiocarcinoma (CCA) is an aggressive bile duct cancer. A majority of patients present with advanced disease and die within a year. For these patients, chemotherapy is the main therapeutic option. Current standards of care include gemcitabine-based regimens such as gemcitabine + cisplatin. However, the 5-year survival rate has not been improved for several decades; tumors that respond initially become resistant, and patients relapse. The literature documents that overexpression of DNA repair proteins contributes to resistance to DNA damaging agents such as gemcitabine and cisplatin, current frontline agents for CCA. This proposal seeks to identify gemcitabine-based combinations that overcome drug resistance and produce durable remissions for patients with CCA. To identify effective regimens and characterize molecular events that contribute to chemosensitivity or resistance, we developed a panel of patient-derived xenograft (PDX) CCA models: CCA1-5 and gemcitabine- resistant counterparts of CCA1 and CCA2 (CCA1.gemR and CCA2.gemR), with resistance acquired in vivo. We propose to use these models to identify effective treatments for CCA. Our data support the hypothesis that gemcitabine + a BET inhibitor (BETi) + a PARP inhibitor (PARPi) comprises effective treatment for this tumor type. Bromodomain and extra-terminal domain (BET) proteins regulate the association of transcription complexes to acetylated lysine residues of histones at specific chromosomal loci. BETi decrease expression of genes whose expression is BET-dependent. Multiple BETi are in clinical trial. Our data demonstrate: 1) that BETi + PARPi and also that BETi + gemcitabine are synergistic in vitro; 2) the novel finding that gemR cells are more sensitive to BETi + PARPi than to gemcitabine + cisplatin; and 3) that the BETi JQ1 + gemcitabine was more effective than gemcitabine as a single agent in the CCA1.gemR PDX in vivo model (P<0.001). Further, our data suggest that sequential administration of BETi → gemcitabine will produce BETi-mediated decreases in expression of DNA repair proteins and minimize gemcitabine resistance. Proposed work evaluates the anti-tumor efficacy of the clinical BETi OTX015 + the PARPi olaparib + gemcitabine, cisplatin, or gemcitabine + cisplatin in models of local and metastatic CCA. We will determine if any of these regimens is superior to current standard of care, and perform whole genome sequencing of all models to identify genetic and molecular characteristics associated with resistance. We will also generate expression profiles of treated vs control tumors and of primary vs metastatic tumors. These data will provide a basis for future work toward long-term goals of identifying gene products and pathways that contribute to drug resistance or metastasis of CCA, and to develop effective treatment regimens using targeted agents.
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