Evaluating prostate cancer phenotype and genotype classification from circulating tumor DNA as biomarkers for predicting treatment outcomes

项目总结/摘要 前列腺癌是男性癌症死亡的第二大常见原因。这些死亡中的大多数 是由于对雄激素剥夺治疗的抵抗和进展到致命的去势抵抗性前列腺 癌症（CRPC）。靶向AR信号传导轴的新一代雄激素受体信号传导抑制剂（ARSI） 已用于CRPC环境;然而，大多数患者仍产生耐药性。最近， 前列腺特异性膜抗原（PSMA）已成为正电子发射断层扫描的一个有前途的靶点 成像（PSMA-PET）和靶向治疗，例如最近FDA批准的用于治疗癌症的放射性配体（PSMA-RL）。 ARSI治疗期间进展的CRPC患者。尽管PSMA-RL疗法有生存益处， 改善的结果是适度的，只有一半的患者表现出良好的反应。耐药性的出现 ARSI和PSMA-RL可能通过肿瘤表型的变化而产生，例如从 前列腺癌（ARPC）转化为治疗相关的小细胞神经内分泌前列腺癌（NEPC）， AR活性丧失的其他表型。目前的方法需要活检来诊断肿瘤组织学， 由于伴随发病率的侵入性手术和一些肿瘤不可接近， 或者具有差的样品质量。此外，肿瘤异质性是治疗抗性的主要贡献者， 使用单个转移部位的活组织检查来识别是特别具有挑战性的。这些挑战是重大的 CRPC男性患者当前治疗策略和精准医学的局限性。 作为无细胞DNA（cfDNA）从肿瘤细胞释放到血液中的循环肿瘤DNA（ctDNA）是非肿瘤性的。 侵入性“液体活检”解决方案，可解决组织可及性方面的挑战。目前的研究和临床 努力集中在从ctDNA测序中检测基因突变作为潜在的生物标志物; 然而，这些并不能完全解释治疗失败的原因。本提案的目的是制定和评估 用于从ctDNA分类侵袭性CRPC基因型和表型的创新方法， 肿瘤异质性的挑战。研究人员假设ctDNA可以用于肿瘤分类， CRPC中的亚型，这可以用来预测治疗结果。在目标1中，他们将研究肿瘤 接受快速尸检的男性中的异质性，以评估ctDNA分类器用于预测 尸体血浆中的异质表型。在目标2中，他们将确定ctDNA用于 预测接受ARSI治疗的前瞻性队列患者的前列腺癌治疗结局 通过PSMA-PET筛选并接受PSMA-RL治疗的患者。他们将评估ctDNA分类器 作为生物标志物工具，帮助PSMA-RL治疗的初始分配，并告知早期治疗指征 阻力在目标3中，他们将开发ctDNA方法的扩展，以推断基因表达和肿瘤 使用临床前小鼠PDX模型，包括体内， 表型混合物的工程化。

PROJECT SUMMARY/ABSTRACT Prostate cancer is the second most common cause of cancer mortality among men. The majority of these deaths are due to resistance to androgen deprivation therapy and progression to lethal castration-resistant prostate cancer (CRPC). New generation androgen receptor signaling inhibitors (ARSI) that target the AR signaling axis have been used in the CRPC setting; however, the majority of patients still develop resistance. Recently, prostate-specific membrane antigen (PSMA) has become a promising target for positron-emission tomography imaging (PSMA-PET) and targeted therapies, such as the recently FDA-approved radioligand (PSMA-RL) for CRPC patients who progressed on ARSI treatment. Despite a survival benefit for PSMA-RL therapy, the improved outcome is modest and only half the patients show favorable responses. The emergence of resistance to ARSI and PSMA-RL may arise through changes in tumor phenotype, such as trans-differentiation from prostate adenocarcinoma (ARPC) into treatment-related small-cell neuroendocrine prostate cancer (NEPC) and other phenotypes with loss of AR activity. Current methods require a biopsy to diagnose tumor histology, which can be challenging due to invasive procedures accompanied by morbidity and some tumors are not accessible or have poor sample quality. Furthermore, tumor heterogeneity is a major contributor to therapy resistance and is particularly challenging to identify using a biopsy of a single metastatic site. These challenges exemplify major limitations of current treatment strategies and precision medicine for men with CRPC. Circulating tumor DNA (ctDNA) released from tumor cells into the blood as cell-free DNA (cfDNA) is a non- invasive “liquid biopsy” solution for addressing challenges in tissue accessibility. Current research and clinical efforts have focused on the detection of genetic mutations from ctDNA sequencing as potential biomarkers; however, these do not fully explain why treatments fail. The objective of this proposal is to develop and evaluate innovative methods for classifying aggressive CRPC genotypes and phenotypes from ctDNA, overcoming challenges of tumor heterogeneity. The investigators hypothesize that ctDNA can be used to classify tumor subtypes in CRPC and that this can be used to predict treatment outcomes. In Aim 1, they will study tumor heterogeneity in men who have undergone rapid autopsy to evaluate the ctDNA classifiers for predicting heterogeneous phenotypes from post-mortem plasma. In Aim 2, they will determine the utility of ctDNA for predicting prostate cancer treatment outcomes in a prospective cohort of patients treated with ARSI and a subset of patients screened by PSMA-PET and treated with PSMA-RL therapy. They will evaluate the ctDNA classifiers as biomarker tools to aid in the initial allocation of PSMA-RL therapy and inform early indications of treatment resistance. In Aim 3, they will develop extensions to ctDNA methods that infer gene expression and tumor aggressiveness in prostate cancer phenotypes using preclinical mouse PDX models, including in vivo engineering of phenotype mixtures.