Colorectal cancer risk factors, risk prediction and blood-based biomarker by tumor consensus molecular subtype

PLCO项目摘要 尽管有有效的筛查技术，但只有40%的结直肠癌（CRC）病例是 在疾病的局部阶段被诊断出来。这可能是由于多种因素的组合，包括筛选非- 依从性、筛查灵敏度和特异性的局限性以及CRC生物学的异质性。具体 存在更具侵袭性的肿瘤亚型，其可能具有较短的自然史， 筛查不足阻碍了我们发现更多早期疾病并进一步降低CRC发病率的能力 and mortality. 最近描述的CRC的共有分子亚型（CMS）包括更具侵袭性的， 间充质亚型，并提供分层风险评估，筛查建议和 预防干预。所鉴定的四种亚型具有不同的生物学和临床结果，表明 独特的风险因素，预防和筛查策略的可能性。具体而言，CMS 1（免疫，14%的 例）与高微卫星不稳定性（MSI）、BRAF突变和免疫浸润、CMS 2 （Canonical，37%）占肿瘤的最大百分比，其特征在于WNT和MYC的激活， CMS 3（代谢，13%）的特征在于低体细胞拷贝数改变、KRAS突变和肿瘤 代谢失调，CMS 4（间充质，23%）的特征在于基质浸润，TGF-β活化， 血管生成和更差的总体和无复发生存期（Nat Med.2015，21：1350）。本提案中的研究 利用CMS框架开发和测试风险预测工具，并测试CMS特定的性能， 经验证的基于血液的三标记物面板。 在我们的初步数据的基础上，使用高质量的纵向数据和肿瘤RNA， 前列腺癌、肺癌、结直肠癌和卵巢癌筛查试验，我们计划测试CMS与 诊断时的年龄、吸烟状况和肿瘤分期（目标1）。使用aim 1中的关联，我们计划建立 并测试CMS特定的CRC风险预测工具，以促进筛查和预防工作（目标2）。我们也 计划进一步测试我们经过验证的血液三标记物面板在CMS和 诊断前10年（目标3）。 CMS特异性风险预测工具和经验证的基于血液的生物标志物的组合具有 有可能大大提高CRC筛查依从性和早期发现，从而降低发病率 和CRC的死亡率。

PLCO Project Summary Despite the availability of effective screening techniques, only 40% of colorectal cancer (CRC) cases are diagnosed at a localized stage of disease. This is likely due to a combination of factors, including screening non- compliance, limitations in the screening sensitivity and specificity, and heterogeneity of CRC biology. Specifically the existence of more aggressive tumor subtypes, which may have a shorter natural history, combined with screening inadequacies hinder our ability to detect more early stage disease and further reduce CRC morbidity and mortality. The recently described consensus molecular subtypes (CMS) of CRC include a more aggressive, mesenchymal subtype and provide a framework for stratified risk assessment, screening recommendations and prevention interventions. The four subtypes identified have distinct biology and clinical outcomes, suggesting the possibility of unique risk factors, prevention, and screening strategies. Specifically, CMS1 (Immune, 14% of cases) is associated with high micro-satellite instability (MSI), BRAF mutations and immune infiltration, CMS2 (Canonical, 37%) accounts for the largest percent of tumors and is characterized by activation of WNT and MYC, CMS3 (Metabolic, 13%) is characterized by low somatic copy number alterations, KRAS mutations and tumor metabolic dysregulation, CMS4 (Mesenchymal, 23%) is characterized by stromal infiltration, TGF-β activation, angiogenesis and worse overall and relapse-free survival (Nat Med. 2015, 21:1350). The studies in this proposal utilize the CMS framework to develop and test a risk-prediction tool and test the CMS-specific performance of a validated blood-based three-marker panel. Building on our preliminary data and using the high-quality, longitudinal data and tumor RNA from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, we plan to test the associations of CMS with age, smoking status, and tumor stage at diagnosis (Aim 1). Using the associations from aim 1, we plan to build and test a CMS-specific CRC risk prediction tool to facilitate screening and prevention efforts (Aim 2). We also plan to further test the performance of our validated blood-based three-marker panel across CMS and in the years prior to diagnosis (Aim 3). The combination of a CMS-specific risk prediction tool and a validated blood-based biomarker has the potential to greatly improve CRC screening compliance and early detection, leading to a reduction in morbidity and mortality from CRC.