对癌症微环境进行多组学分析显示出艾唑霉素联合标准治疗在MM的Ph1研究中的临床相关性。
Multi-omic analysis of the tumor microenvironment shows clinical correlations in Ph1 study of atezolizumab +/- SoC in MM.
发表日期:2023
作者:
Sandy Wong, Habib Hamidi, Luciano J Costa, Selma Bekri, Natalia Neparidze, Ravi Vij, Tina G Nielsen, Aparna Raval, Rajan Sareen, Elisabeth Wassner-Fritsch, Hearn J Cho
来源:
GENOMICS PROTEOMICS & BIOINFORMATICS
摘要:
多发性骨髓瘤(MM)至今仍无法治愈,复发/难治性疾病的治疗具有挑战性。该领域需要更多的精准靶向治疗方法。通过对骨髓瘤肿瘤和微环境进行深入的细胞和分子表型分析,可以为此类治疗提供指导。本研究(NCT02431208)评估了抗程序性死亡配体1嵌合单抗阿特伊珠单抗(Atezo)单独或与标准治疗(lenalidomide, pomalidomide和/或daratumumab)联合治疗复发/难治性多发性骨髓瘤(RRMM)患者的安全性和有效性。研究终点包括不良事件(AEs)发生率和总体反应率(ORR)。使用RNA测序、质谱细胞免疫表型和蛋白质组学技术对接受Atezo个体或Atezo + Dara方案治疗的患者的基线和治疗后骨髓样本进行新型无监督整合多组学分析。对预处理数据应用相似性网络融合(SNF)算法。共纳入了85名患者。2名患者出现治疗相关的死亡事件,但与研究治疗无关。ORR范围从11.1%(Atezo+Len组,n = 18)到83.3%(Atezo+Dara+Pom组,n = 6)。对肿瘤微环境的高维度多组学分析和整合SNF分析揭示了肿瘤和免疫微环境的细胞和分子特征之间的新型相关性,以及对患者选择标准和临床结果的影响。针对该患者群体,Atezo单药和标准治疗联合方案均安全,并显示出一定的临床疗效证据。高维基因组和免疫数据的整合分析确定了可能有助于指导骨髓瘤免疫治疗研究中患者选择标准和结果评估的新型临床相关性。© 2023 Wong, Hamidi, Costa, Bekri, Neparidze, Vij, Nielsen, Raval, Sareen, Wassner-Fritsch and Cho.
Multiple myeloma (MM) remains incurable, and treatment of relapsed/refractory (R/R) disease is challenging. There is an unmet need for more targeted therapies in this setting; deep cellular and molecular phenotyping of the tumor and microenvironment in MM could help guide such therapies. This phase 1b study (NCT02431208) evaluated the safety and efficacy of the anti-programmed death-ligand 1 monoclonal antibody atezolizumab (Atezo) alone or in combination with the standard of care (SoC) treatments lenalidomide (Len) or pomalidomide (Pom) and/or daratumumab (Dara) in patients with R/R MM. Study endpoints included incidence of adverse events (AEs) and overall response rate (ORR). A novel unsupervised integrative multi-omic analysis was performed using RNA sequencing, mass cytometry immunophenotyping, and proteomic profiling of baseline and on-treatment bone marrow samples from patients receiving Atezo monotherapy or Atezo+Dara. A similarity network fusion (SNF) algorithm was applied to preprocessed data. Eighty-five patients were enrolled. Treatment-emergent deaths occurred in 2 patients; both deaths were considered unrelated to study treatment. ORRs ranged from 11.1% (Atezo+Len cohorts, n=18) to 83.3% (Atezo+Dara+Pom cohort, n=6). High-dimensional multi-omic profiling of the tumor microenvironment and integrative SNF analysis revealed novel correlations between cellular and molecular features of the tumor and immune microenvironment, patient selection criteria, and clinical outcome. Atezo monotherapy and SoC combinations were safe in this patient population and demonstrated some evidence of clinical efficacy. Integrative analysis of high dimensional genomics and immune data identified novel clinical correlations that may inform patient selection criteria and outcome assessment in future immunotherapy studies for myeloma.Copyright © 2023 Wong, Hamidi, Costa, Bekri, Neparidze, Vij, Nielsen, Raval, Sareen, Wassner-Fritsch and Cho.