Proteomic determinants of response to checkpoint blockade in malignant pleuralmesothelioma

恶性胸膜间皮瘤检查点阻断反应的蛋白质组决定因素

基本信息

批准号：
10321963
负责人：
Bryan Michael Burt
金额：
$ 50.87万
依托单位：
BAYLOR COLLEGE OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-01 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10321963
关键词：
Architecture Atlases Bioinformatics Biological Markers Biology Caring Cells Clinical Clinical Data Cytometry Data Disease Elements Formalin Foundations Frequencies Human Image Immune Immune checkpoint inhibitor Immunohistochemistry Immunologics Life Life Extension Lung Malignant - descriptor Malignant Neoplasms Malignant Pleural Mesothelioma Mass Spectrum Analysis Measures Nivolumab Operative Surgical Procedures PD-1 blockade Paraffin Embedding Patient Care Patients Peptides Pharmaceutical Preparations Phenotype Pleura Production Prospective cohort Protein Analysis Proteins Proteomics Radiation therapy Resistance Sampling Side Signal Transduction Specimen Structure T cell response T-Lymphocyte Techniques Testing Time Tissues Toxic effect Translating Triage Tumor Burden Validation abstracting anti-PD-1 base bioinformatics pipeline cancer therapy cell type chemotherapy clinical application clinical biomarkers clinical translation cohort cost cytokine design effective therapy exome sequencing high dimensionality human leukocyte antigen testing immune checkpoint blockade immunogenicity improved in silico indexing innovation malignant pleura tumor neoantigens novel novel marker predicting response predictive marker programmed cell death ligand 1 prospective prospective test responders and non-responders response side effect single cell analysis standard of care time use traditional therapy transcriptome sequencing tumor tumor heterogeneity tumor-immune system interactions

项目摘要

PROJECT SUMMARY / ABSTRACT Malignant pleural mesothelioma (MPM) is a fatal cancer of the lining of the lungs that has defeated standard therapies for decades. Immune checkpoint inhibitors (ICIs) are revolutionizing cancer treatment, and tumor- specific neoantigens are critical components of the vigorous anti-tumor T cell responses possible from these agents. Emerging clinical data show that ICIs result in meaningful extension of life in half of patients with MPM but are associated with immune-related side effects. There is no reliable biomarker for identifying MPM patients who will respond to ICIs. Such a test would avoid unnecessary toxicity, triage non-responders to potentially more effective treatment, and could even extend long-term survival. Our preliminary data show that MPM tumors from patients that respond favorably to ICIs are rich in 1) distinct cellular and tissue architectural features of MPM's unique immune contexture, and 2) abundant tumor neoantigens that are detected at the peptide level and expressed concomitantly with the specific HLA proteins that are required for their presentation to T cells. Our central hypothesis is that response to PD-1 blockade in MPM can be predicted by a clinically-applicable biomarker of its immunologic organization and requires neoantigen:MHC concordance. In Aim 1, we will apply the high dimensional platforms of time-of-flight mass cytometry (CyTOF) and imaging mass cytometry (IMC) to dissect the cellular networks and immuno-architectural features of MPM that govern response to nivolumab. Based on these features, we derived a novel score that predicts response to nivolumab in MPM and we have developed an innovative bioinformatics platform to abstract this score from standard formalin-fixed paraffin- embedded (FFPE) clinical tissue sections. In Aim 1, we will optimize and prospectively validate this score in patients with MPM. In Aim 2, we will perform mass spectrometry (MS) on HLA-typed tumors to investigate neoantigen biology and challenge the prevailing biomarker of neoantigen burden that is used clinically to predict response to ICIs in other tumors, but with low accuracy. This biomarker has relied exclusively on neoantigens predicted in silico and does not directly measure neoantigens in tumors. We found that high quantities of MHC- I and MHC-II neoantigens detected by MS in MPM tumors (termed neoantigen abundance) correlated with sensitivity to nivolumab. More interestingly, we found that the MPM tumors most likely to respond had high peptide level expression of neoantigens concordant with high protein level expression of the specific HLA proteins required for their presentation (termed neoantigen:MHC concordance). These novel metrics will be tested prospectively in Aim 2 where we will also validate the immunogenicity of MS-detected neoantigens and determine the phenotype of neoantigen-reactive T cells. Our results will define core elements of the immunoproteomic structure of MPM and result in the clinical translation of innovative biomarkers expected to directly improve the care of MPM patients. More broadly, completion of this project will advance our understanding of neoantigen biology and of mechanisms of response and resistance to ICIs in human cancer.

项目概要/摘要恶性胸膜间皮瘤 (MPM) 是一种致命的肺内膜癌症，已超过标准几十年来的治疗方法。免疫检查点抑制剂（ICIs）正在彻底改变癌症治疗和肿瘤治疗特定的新抗原是这些可能产生的强有力的抗肿瘤 T 细胞反应的关键组成部分代理。新的临床数据表明，ICIs 使一半 MPM 患者的生命得到有意义的延长但与免疫相关的副作用有关。没有可靠的生物标志物来识别 MPM 患者谁将对 ICI 作出回应。这样的测试将避免不必要的毒性，将无反应者分类为潜在的更多有效的治疗，甚至可以延长长期生存。我们的初步数据表明 MPM 肿瘤来自对 ICI 反应良好的患者富含 1) MPM 独特的细胞和组织结构特征独特的免疫环境，以及 2) 在肽水平上检测到的丰富的肿瘤新抗原与呈递给 T 细胞所需的特定 HLA 蛋白同时表达。我们的中心假设是 MPM 对 PD-1 阻断的反应可以通过临床适用的方法来预测其免疫组织的生物标志物，需要新抗原：MHC 一致性。在目标 1 中，我们将应用飞行时间质谱流式细胞术 (CyTOF) 和成像质谱流式细胞术 (IMC) 的高维平台剖析控制纳武单抗反应的 MPM 的细胞网络和免疫结构特征。基于这些特征，我们得出了一个新的评分来预测 MPM 中对纳武单抗的反应，我们有开发了一个创新的生物信息学平台，从标准福尔马林固定石蜡中提取该分数包埋（FFPE）临床组织切片。在目标 1 中，我们将优化并前瞻性地验证该分数 MPM 患者。在目标 2 中，我们将对 HLA 型肿瘤进行质谱 (MS) 来研究新抗原生物学并挑战临床上用于预测的新抗原负荷的流行生物标志物对其他肿瘤中 ICI 的反应，但准确性较低。该生物标志物完全依赖于新抗原计算机预测，并不直接测量肿瘤中的新抗原。我们发现大量的 MHC- MS 在 MPM 肿瘤中检测到的 I 和 MHC-II 新抗原（称为新抗原丰度）与对纳武利尤单抗的敏感性。更有趣的是，我们发现最有可能做出反应的 MPM 肿瘤具有高新抗原的肽水平表达与特定 HLA 的高蛋白水平表达一致其呈现所需的蛋白质（称为新抗原：MHC 一致性）。这些新颖的指标将在目标 2 中进行前瞻性测试，我们还将验证 MS 检测到的新抗原的免疫原性和确定新抗原反应性 T 细胞的表型。我们的结果将定义核心要素 MPM 的免疫蛋白质组结构，并导致创新生物标志物的临床转化，预计直接改善 MPM 患者的护理。更广泛地说，该项目的完成将推动我们了解新抗原生物学以及人类癌症对 ICI 的反应和耐药机制。