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：
10545173
负责人：
Bryan Michael Burt
金额：
$ 49.59万
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/10545173
关键词：
Acceleration Antigen Targeting Architecture Atlases Bioinformatics Biological Markers Biology Caring Cells Clinical Clinical Data Cytometry Data Disease Elements Formalin Frequencies Human Image Immune Immune checkpoint inhibitor Immunohistochemistry Immunologics Life Life Extension Lung MHC antigen 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 Signal Transduction Specimen Structure T cell response T-Lymphocyte Techniques Testing Time Tissues Toxic effect Translating Triage Tumor Burden Validation abstracting anti-PD-1 antigen detection 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.

项目摘要 /摘要恶性胸膜间皮瘤（MPM）是肺部内膜的致命癌症，它已经击败了标准疗法数十年。免疫检查点抑制剂（ICI）正在革新癌症治疗，肿瘤 - 特定的新抗原是从这些剧烈抗肿瘤T细胞反应的关键成分代理商。新兴的临床数据表明，ICIS导致一半MPM患者的生命有意义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患者谁会回应ICIS。这样的测试将避免不必要的毒性，分类无反应可能会更多有效的治疗，甚至可以延长长期生存。我们的初步数据表明，来自对ICI的反应的患者富含1）MPM的细胞和组织结构特征的不同独特的免疫环境和2）在肽水平上检测到的丰富的肿瘤新抗原和与特定的HLA蛋白同时表达，这些HLA蛋白将其呈现给T细胞所需。我们的中心假设是可以通过临床上适用的MPM中对PD-1封锁的反应预测其免疫组织的生物标志物，需要新抗原：MHC一致性。在AIM 1中，我们将申请飞行时间质量细胞术（CytoF）和成像质量细胞术（IMC）的高维平台至剖析了控制对nivolumab的反应的MPM的细胞网络和免疫构造特征。基于这些特征，我们得出了一个新的分数，该分数预测了MPM中对Nivolumab的反应，我们有开发了一个创新的生物信息学平台，可以从标准的福尔马林固定石蜡中抽象这一分数嵌入（FFPE）临床组织切片。在AIM 1中，我们将优化并前瞻性地验证该分数 MPM患者。在AIM 2中，我们将对HLA型肿瘤进行质谱（MS）进行研究新抗原生物学并挑战新抗原负担的现行生物标志物，该标志物在临床上用于预测对其他肿瘤中ICI的反应，但精度较低。该生物标志物仅依赖于新抗原在计算机中进行预测，不直接测量肿瘤中的新抗原。我们发现大量的MHC- I和MHC-II新抗原在MPM肿瘤（称为新抗原丰度）中检测到与对Nivolumab的敏感性。更有趣的是，我们发现最有可能反应的MPM肿瘤很高新抗原与特异性HLA的高蛋白水平表达一致的新抗原的肽水平表达其呈现所需的蛋白质（称为新抗原：MHC一致性）。这些新颖的指标将是在AIM 2中进行了前瞻性测试，我们还将验证MS检测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 MPM的免疫蛋白质组结构，并导致预期的创新生物标志物的临床翻译直接改善MPM患者的护理。更广泛地，完成该项目的完成将推动我们的了解新抗原生物学以及人类癌症中ICI的反应和抗性机制。