Deciphering Clonal Evolution in Hereditary Renal Cell Carcinomas

1背景：对推动癌症生长和进展的因素的进一步理解是 2改善癌症患者预后的基础。Von Hippel-Lindau（VHL） 3种疾病在其一生中发展为多种血管肿瘤，包括数百种恶性肿瘤。 4例囊肿和透明细胞肾细胞癌（ccRCC）。这些肿瘤的基因组镜像 5例散发性ccRCC，并显示不同的临床表型。分析多个独立肿瘤 6在相同的生殖系和宿主环境中出现的突变提供了一个内在控制的模型 7研究癌症演变和进展的潜在因素。我们将利用 临床中心的8个独特的VHL疾病患者临床队列，以研究分子如何 9景观（目标1），肿瘤微环境（TME）（目标2）和代谢组 10（目的3）促进或抑制癌生长。 11方法：本前瞻性队列研究将从泌尿肿瘤科招募受试者 国家癌症研究所的12个分支。将跟踪单个肿瘤的生长动力学 13放射学在采购过程中，肿瘤被识别并与成像相关联。我们将 14进行多参数分子分析，整合所有数据集，以实现我们的研究目标。 15使用下一代测序，我们将检测恶性肿瘤的基础事件。 16转化（目标1.1）和与差异生长动力学相关的分子事件 17（目标1.1）。我们将探讨与肾外部位肿瘤形成相关的事件 18（目标1.3）以及分子/环境变异如何影响可变表型渗透 19人为VHL亲属（目标1.4）。为了评估TME的作用，我们将使用基因组分析， 20评估新抗原景观（目标2.1）并使用免疫细胞谱系鉴定差异 21 RNA测序（目标2.2）。我们将用多重免疫组化来验证这些发现 22（IHC）方法。我们将利用转录组谱分析来评估受干扰的代谢组（目的 23 3.1），并进行试点研究，以评估基因组和转录组的变化与稳定的同位素- 从术中获得的VHL肿瘤组织获得24个分解代谢谱。 结论：这将是VHL中产生的癌症的最全面的分子谱分析。 26疾病它有可能解决有关进化癌症生物学的关键问题， 27识别肿瘤生长和进展的触发因素，从而识别预测或预后生物标志物 28可能与癌症有更广泛的相关性。它可能为新的治疗策略提供信息， 治疗和预防遗传性和散发性ccRCC。

1 Background: An improved understanding of the factors that drive cancer growth and progression is 2 fundamental for improving outcomes in patients with cancer. Individuals with Von Hippel-Lindau (VHL) 3 disease develop multiple vascular tumours in their lifetime including many hundreds of malignant 4 cysts and clear cell renal cell carcinoma (ccRCCs). These tumours are the genomic mirror image of 5 sporadic ccRCCs and display variable clinical phenotypes. Profiling multiple, independent tumours 6 that have arisen in an identical germline and host environment offers an intrinsically controlled model 7 to study the factors underlying cancer evolution and progression in general. We will leverage the 8 unique clinical cohort of patients with VHL Disease at the Clinical Centre to study how the molecular 9 landscape (Objective 1), the tumour microenvironment (TME) (Objective 2) and the metabolome 10 (Objective 3) promote or restrain cancer growth. 11 Methods: Subjects will be recruited to this prospective cohort study from the Urology Oncology 12 Branch at the National Cancer Institute. Growth kinetics of individual tumours will be tracked 13 radiologically. During procurement, tumours are identified and correlated with imaging. We will 14 perform multiparametric molecular profiling, integrating all datasets to achieve our study objectives. 15 Using next generation sequencing we will characterise the events that underlie malignant 16 transformation (Objective 1.1) and the molecular events associated with differential growth kinetics 17 (Objective 1.1). We will explore events associated with tumour fromation in extra-renal sites 18 (Objective 1.3) and how molecular/environmental variants influence variable phenotypic penetration 19 amongst VHL kindred (Objective 1.4). To assess the role of the TME, we will use genomic profiling to 20 assess the neoantigen landscape (Objective 2.1) and identify differential immune cell lineages using 21 RNA sequencing (Objective 2.2). We will validate these fidnings with multiplex immunohistochemistry 22 (IHC) approach. We will assess the perturbed metabolome utilising transcriptome profiling (Objective 23 3.1) and conduct a pilot study to assess genomic and transcriptomic changes with stable isotope- 24 resolved metabolic profiles obtained from VHL tumor tissue obtained intraoperatively. 25 Conclusion: This will be the most comprehensive molecular profiling of cancers arising in VHL 26 disease. It has the potential to address key questions regarding evolutionary cancer biology and to 27 identify the triggers for tumour growth and progression and hence predictive or prognostic biomarkers 28 which may have a wider relevance to cancer. It may inform novel therapeutic strategies for the 29 treatment and prevention of hereditary and sporadic ccRCC.