Validating a prognostic plasma metabolomic biomarker to improve precision medicine in head and neck cancer patients

验证预后血浆代谢组生物标志物以改善头颈癌患者的精准医疗

• 批准号: 10576628
• 负责人: Ronald C Eldridge
• 金额: $ 7.83万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10576628
• 关键词: Adverse event; Age; Amino Acids; Anabolism; Apple; Bile Acids; Biological Markers; Blood; Bypass; Cancer Center; Cancer cell line; Categories; Characteristics; Chemotherapy and/or radiation; Clinical; Clinical Research; Clinical Trials; Coenzyme A; Cox Models; DNA sequencing; Data; Data Set; Development; Disease; Dose; Failure; Freezing; Future; Galactose Metabolism Pathway; Gene Expression; Genes; Genome; Glycolysis; Glycosaminoglycans; Goals; Grant; Head and Neck Cancer; Heterogeneity; Human Papillomavirus; In Vitro; Knowledge; Link; Lipids; Measures; Metabolic; Metabolism; Mitochondria; Mutation; Niacinamide; Oncogenes; Oncology; Oranges; Oropharyngeal; Outcome; Oxidative Phosphorylation; PIK3CA gene; Patient Recruitments; Patients; Phase III Clinical Trials; Plasma; Prognosis; Prognostic Marker; Publishing; Quality of life; Race; Regulation; Research; Resolution; Risk; Running; Signal Transduction; Site; Smoker; Smoking; Smoking History; Somatic Mutation; Source; TP53 gene; Taurine; Testing; The Cancer Genome Atlas; Toxic effect; Translating; Tryptophan; Tumor Tissue; Valine; Warburg Effect; amino acid metabolism; biomarker validation; cancer biomarkers; cancer clinical trial; cancer site; chemoradiation; clinically relevant; cohort; fatty acid biosynthesis; hazard; head and neck cancer patient; high risk; improved; in vivo; lipid biosynthesis; machine learning algorithm; male; metabolomics; multiple omics; novel; phase III trial; precision medicine; precision oncology; prognostic; prognostic of survival; prognostic value; programs; research clinical testing; sex; side effect; standard care; translational research program; treatment response; tumor; tumor metabolism

Over the past decade, precision medicine research in head and neck cancer (HNC) has been singularly focused on a single biomarker, human papillomavirus (HPV), to target low-risk patients for treatment de-intensification (i.e., reduce therapy to improve quality of life without sacrificing survival). De-intensification is vital since standard treatment involves toxic doses of chemoradiation that causes adverse events and debilitating long-term side effects in most patients. In 2019, however, two phase-III clinical trials confirmed that HPV was insufficient to target the most promising de-intensified therapy. This failure presents a timely opportunity to test new prognostic markers to target de-intensified therapy in the 41 existing clinical trials, but a lack of promising biomarkers hinders progress. HNC is a disease marked by extensive metabolic heterogeneity that is emerging as a rich source of novel prognostic biomarkers but has yet to be fully investigated. For instance, many of the somatic mutations in HNC that are associated with prognosis (e.g., TP53 and PIK3CA) are upstream regulators of key metabolic processes in glycolysis, lipids, amino acids, and cell signaling. Recent studies have showed that the Warburg effect, the atypical metabolic state in which a tumor upregulates glycolysis but bypasses mitochondrial oxidative phosphorylation (OXPHOS), is a key discriminating characteristic between HNC cell lines linked to prognosis. Most recently, five different studies in 2020 found that gene expression probes targeting metabolic regulating genes created signatures that can predict HNC patient survival. The evidence leads to one conclusion— metabolism is intimately involved in the development, progression, and survival of HNC. Thus, metabolomics may be the best approach to discover the translational biomarkers vital to the future of HNC precision medicine. However, the data required to investigate and validate an HNC metabolomic biomarker, particularly in a clinical setting, is severely lacking. My program of research aims to fill that gap. In my KL2 research, which includes 209 HNC patients with blood plasma metabolomics, I used machine learning algorithms to identify a pretreatment metabolomic endotype comprised of glycolysis, OXPHOS, lipid biosynthesis, and amino acid metabolites. The endotypes categorized patients into one of two distinct groups that were associated with overall survival (hazard ratio = 2.39, 95% CI: 1.19-4.78). Most importantly, the prognostic ability of the endotype was independent of relevant clinical factors such as HPV, smoking, age, sex, race, tumor site and stage, suggesting that it may succeed as an HNC biomarker where others have failed. The goal of this R03 is to validate my KL2 findings with an independent cohort (Aim 1) and investigate how the metabolomic endotype in blood is related to metabolism and metabolic characteristics in the tumor (Aim 2). Positive findings from this study will help me translate this biomarker to ongoing clinical trials data within NRG Oncology, a multisite cancer clinical trials consortium, to test whether the pretreatment metabolomic blood biomarker can identify HNC patients who will respond to de- intensified therapy and spare them the toxic effects of standard chemoradiotherapy.

在过去的十年中，头颈癌（HNC）的精准医学研究一直受到关注 单一生物标志物，人乳头瘤病毒（HPV），针对低风险患者进行治疗去强化 (i.e.,减少治疗以提高生活质量而不牺牲生存率）。去强化至关重要，因为标准 治疗涉及毒性剂量的放化疗，这会导致不良事件和使人衰弱的长期副作用。 对大多数患者有影响。然而，在2019年，两项III期临床试验证实HPV不足以 瞄准最有希望的去强化治疗这一失败提供了一个及时的机会，以测试新的预后 在现有的41项临床试验中，靶向去强化治疗的生物标志物，但缺乏有希望的生物标志物阻碍了 中求进工作总HNC是一种以广泛的代谢异质性为特征的疾病，其正在成为HNC的丰富来源。 新的预后生物标志物，但尚未得到充分研究。例如，许多体细胞突变， 与预后相关的HNC（例如，TP53和PIK3CA）是关键代谢酶的上游调节因子。 糖酵解、脂质、氨基酸和细胞信号传导过程。最近的研究表明，瓦尔堡 效应，非典型代谢状态，其中肿瘤上调糖酵解，但绕过线粒体氧化 磷酸化（OXPHOS）是与预后相关的HNC细胞系之间的关键区分特征。 最近，2020年的五项不同研究发现，靶向代谢调节的基因表达探针 基因产生的特征可以预测HNC患者的生存率。所有证据都指向一个结论- 代谢密切参与HNC的发展、进展和存活。因此，代谢组学 可能是发现对HNC精准医学的未来至关重要的翻译生物标志物的最佳方法。 然而，研究和验证HNC代谢组学生物标志物所需的数据，特别是在临床试验中， 设置，严重缺乏。我的研究计划旨在填补这一空白。在我的KL2研究中，包括209个 HNC患者的血浆代谢组学，我使用机器学习算法来识别预处理 代谢组学内型包括糖酵解、OXPHOS、脂质生物合成和氨基酸代谢物。的 内型将患者分为与总生存率相关的两个不同的组之一（风险 比值= 2.39，95%CI：1.19 - 4.78）。最重要的是，内型的预后能力独立于 相关的临床因素，如HPV，吸烟，年龄，性别，种族，肿瘤部位和阶段，表明它可能 成功地作为HNC生物标志物，而其他生物标志物则失败了。本R03的目标是验证我的KL2发现， 一个独立的队列（目的1），并研究如何代谢组学内型在血液中与代谢 和肿瘤的代谢特征（目的2）。这项研究的积极发现将有助于我翻译这一点 NRG Oncology（一个多中心癌症临床试验联盟）正在进行的临床试验数据的生物标志物，以测试 治疗前代谢组学血液生物标志物是否可以识别对去甲肾上腺素有反应的HNC患者， 强化治疗，避免标准放化疗的毒性作用。