Molecular diagnosis and outcome prediction in lymphoma

淋巴瘤的分子诊断和结果预测

• 批准号: 10014502
• 负责人: Louis Staudt
• 金额: $ 141.83万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10014502
• 关键词: Affect; B-Cell Lymphomas; B-Lymphocytes; Behavior; Biological; Biopsy; Cell Line; Cells; Characteristics; Chronic; Classification; Clinical; Clinical Trials; DNA Sequence Alteration; DNA analysis; DNA copy number; Diagnosis; Diagnostic; Diagnostic Procedure; Disease; Drug Combinations; Drug Targeting; Endothelial Cells; Enrollment; Epigenetic Process; Formalin; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic; Genomics; Goals; Heterogeneity; Human; Immuno-Chemotherapy; Inferior; Investigation; Laboratories; Laboratory Study; Length; Lymphoma; Malignant lymphoid neoplasm; Mediastinal; Methods; Modeling; Molecular; Molecular Abnormality; Molecular Diagnosis; Molecular Profiling; Monoclonal Antibody CD20; Mutation; Myelogenous; NF-kappa B; Neoplasms in Vascular Tissue; Oncogenic; Outcome; Paraffin Embedding; Pathogenesis; Pathway interactions; Patients; Phase II Clinical Trials; Phenotype; Primary Neoplasm; Progression-Free Survivals; Protein Isoforms; Receptor Signaling; Receptors, Antigen, B-Cell; Recurrence; Refractory; Regimen; Relapse; Role; Signal Pathway; Signal Transduction; Somatic Mutation; Structure of germinal center of lymph node; Survival Rate; Taxonomy; Technology; Testing; Therapeutic Clinical Trial; Tissue Embedding; Trisomy 3; Tumor Biology; Tumor Suppressor Proteins; addiction; angiogenesis; anti-CD20; base; biological heterogeneity; chemotherapy; clinical practice; clinically relevant; cohort; companion diagnostics; comparative genomic hybridization; density; digital; genomic platform; histiocyte; improved; large cell Diffuse non-Hodgkin' s lymphoma; lenalidomide; lymphoid neoplasm; molecular diagnostics; nano-string; novel; outcome forecast; outcome prediction; patient response; patient subsets; precision medicine clinical trials; predicting response; prognostic; response; rituximab; scaffold; targeted agent; therapeutic target; therapy outcome; tool; treatment response; tumor; tumor microenvironment

On the basis of gene expression profiling, the laboratory proposed that the most common form of lymphoma, diffuse large B cell lymphoma (DLBCL), is a composite of three molecularly distinct diseases that are indistinguishable by standard diagnostic methods. These diseases, termed germinal center B cell-like (GCB) DLBCL, activated B cell-like (ABC) DLBCL, and primary mediastinal B cell lymphoma (PMBL), arise from B lymphocytes at different stages of differentiation by distinct oncogenic pathways. The curative response of patients with DLBCL to chemotherapy is highly variable, and the DLBCL subtype distinction accounts, in part, for this heterogeneity. With CHOP multi-agent chemotherapy, the 5-year survival rates of ABC DLBCL and GCB DLBCL are 60% and 30%, respectively. This clinical disparity likely reflects the host of genetic differences between these DLBCL subtypes. A recurring theme that emerges from our molecular profiling efforts in lymphoma is that the curative response to treatment and the length of survival following diagnosis are dictated by molecular features of the tumors at diagnosis. In DLBCL, we developed a multivariate model of therapeutic outcome based on gene expression signatures, which quantitatively reflected distinct aspects of tumor biology. This study was performed in the era of CHOP chemotherapy for DLBCL, which has subsequently been supplanted by regimens that add the anti-CD20 monoclonal antibody Rituximab (R-CHOP). We therefore created a new gene expression model that was strongly associated with both overall and progression-free survival in the CHOP and R-CHOP cohorts as well as in a third CHOP cohort. The gene expression-based survival model could divide the patients in the R-CHOP cohort into quartile groups that had 3-year progression-free survival rates of 84%, 69%, 61% and 34%, respectively, indicating that the model captures much of the heterogeneity in therapeutic response. The germinal center B cell signature mirrored the distinction between GCB and ABC DLBCL and therefore reflects the myriad genetic and epigenetic differences that exist between these two subtypes. On the other hand, the stromal-1 and stromal-2 signatures reflected different aspects of the tumor microenvironment. The stromal-1 signature, which was associated with favorable outcome, identified tumors that were fibrotic and rich in histiocytic cells of the myeloid lineage. The stromal-2 signature, which was associated with poor outcome, included a host of genes that are characteristically expressed in endothelial cells and was correlated with increased tumor blood vessel density, revealing an unanticipated role for angiogenesis in DLBCL. Array-based comparative genomic hybridization was used to identify genomic changes in copy number that influenced survival. Two genomic alterations that occurred exclusively in ABC DLBCL were deletion of the INK4a/ARF tumor suppressor locus and trisomy 3. These genetic aberrations, considered separately and together, identified a subset of patients with ABC DLBCL with inferior prognosis relative to other patients with this DLBCL subtype. This ABC DLBCL subset was also characterized by oncogenic mutations that activate various survival signaling pathways. These include mutations in the CARD11 gene, which encodes a scaffold molecule required for NF-kB signaling downstream of the B cell receptor. Mutations in the B cell receptor components CD79A and CD79B potentiate ongoing B cell receptor signaling. Mutations in the signaling adapter MYD88 create spontaneously active isoforms. Each of these mutations contribute to constitutive NF-kB activity in ABC DLBCLs in which they have been acquired. We are currently investigating several platforms to deliver the molecular diagnostic and prognostic distinction to patients with lymphoma. The goal is to utilize formalin-fixed and paraffin-embedded tissue for these analyses since most lymphoma biopsies are routinely stored in this fashion. The Nanostring platform for digital gene expression analysis has proved highly effective in distinguishing ABC and GCB DLBCL. This technology has been licensed by Nanostring and is currently being used to develop a companion diagnostic for the use of lenalidomide to treat ABC DLBCL. Most recently, we have been conducting genomic analysis of patients enrolled in therapeutic clinical trials. In a phase 2 trial of ibrutinib in relapsed/refractory DLBCL, we used gene expression profiling to subdivide the cases into ABC and GCB subtypes. The response rate in ABC DLBCL was significantly greater than in GCB DLBCL (37% vs. 5%), as predicted by our laboratory studies showing addiction to chronic active B cell receptor (BCR) signaling and ibrutinib sensitivity in cell line models of ABC DLBCL. Analysis of recurrent mutations in ABC DLBCL revealed a higher response rate in tumors with mutations affecting the BCR subunit CD79B and especially in tumors with both CD79B and MYD88 mutations. This suggests that ABC DLBCL can be usefully subdivided further based on genetic abnormalities in order to predict response to targeted agents. To test this, we undertook a multi-platform genomic analysis of 574 DLBCL tumors and integrated gene expression profiling with analysis of DNA copy number alterations, translocations, and mutations, resulting in a genetic taxonomy of DLBCL that has provided unexpected biological and clinical insights1. Tumors were classified into the same genetic subtype if they shared multiple recurrent genetic alterations. This approach yielded four DLBCL genetic subtypes - termed MCD, BN2, N1, and EZB - that refine and extend the gene expression-based classification of DLBCL1. MCD and N1 tumors are primarily subsets of ABC DLBCL and EZB is a subset of GCB DLBCL, but BN2 tumors are drawn from ABC, GCB and Unclassified DLBCL. Strong support for the biological and clinical relevance of the DLBCL genetic subtypes came from analysis of responses to immunochemotherapy1. The MCD and N1 subtypes had a substantially better overall survival than the BN2 and EZB genetic subtypes. The 5-year survival fractions in MCD, N1, BN2 and EZB DLBCL were 26%, 36%, 65%, 68%, respectively. Within ABC DLBCL, the survival of MCD and N1 patients was inferior to the survival of BN2 patients. Within GCB DLBCL, the survival of EZB patients was inferior to other GCB patients. Thus, the prognostic information provided by the genetic subtype distinction extends and improves upon the prognostic differences provided by gene expression profiling. One implication of these findings is that patients with MCD DLBCL should consider clinical trials of a novel agent(s) combined with immunochemotherapy, given the relative low 5-year survival in this group following chemotherapy alone. A second implication is that clinical trials in which R-CHOP is combined with a novel agent should ascertain which DLBCL genetic subtypes were enrolled, given the striking differences in outcome following R-CHOP alone among these subtypes. Current efforts aim to develp a clinically feasible and useful tool to classify DLBCL tumors into genetic subtypes and to deploy these methods in precision medicine clinical trials.

在基因表达分析的基础上，实验室提出，淋巴瘤弥漫性大B细胞淋巴瘤（DLBCL）最常见的形式是三种分子不同疾病的复合物，这些疾病是由标准诊断方法无法区分的。这些疾病称为生殖中心B细胞（GCB）DLBCL，激活的B细胞样（ABC）DLBCL和原发性纵隔B细胞淋巴瘤（PMBL），是由B淋巴细胞在不同阶段在不同阶段通过不同的致癌途径在不同阶段的B淋巴细胞引起的。 DLBCL患者对化学疗法的治疗反应高度可变，而DLBCL亚型的区别部分则部分是这种异质性。通过CHOP多药化疗，ABC DLBCL和GCB DLBCL的5年生存率分别为60％和30％。这种临床差异可能反映了这些DLBCL亚型之间的遗传差异。我们在淋巴瘤中的分子分析工作中产生的一个反复出现的主题是，诊断后对治疗的治疗反应和诊断后的生存时间由诊断时肿瘤的分子特征决定。在DLBCL中，我们基于基因表达特征开发了一种多元治疗结果模型，该模型定量反映了肿瘤生物学的不同方面。这项研究是在DLBCL的CHOP化疗时代进行的，DLBCL随后被添加抗CD20单克隆抗体利妥昔单抗（R-CHOP）的方案所取代。因此，我们创建了一个新的基因表达模型，该模型与CHOP和R-CHOP同类群以及第三个CHOP队列中的整体和无进展生存密切相关。基于基因表达的生存模型可以将R-CHOP队列中的患者分为四分之一的无进展生存率，分别为84％，69％，61％和34％，表明该模型在治疗反应中捕获了许多异质性。生发中心B细胞特征反映了GCB和ABC DLBCL之间的区别，因此反映了这两个亚型之间存在的无数遗传和表观遗传差异。另一方面，基质-1和Stromal-2特征反映了肿瘤微环境的不同方面。与良好结果相关的基质-1特征确定了纤维化且富含髓样谱系的组织细胞细胞的肿瘤。与预后不良有关的基质-2特征包括许多在内皮细胞中特征表达的基因，并且与肿瘤血管密度的增加相关，揭示了在DLBCL中血管生成的意外作用。基于阵列的比较基因组杂交用于确定影响生存的拷贝数的基因组变化。 ABC DLBCL中仅发生的两种基因组改变是INK4A/ARF肿瘤抑制基因座和三体肌3的缺失。这些遗传像差被认为分别和一起识别为ABC DLBCL患者的一部分，与此DLBCL亚型相对于其他患者，ABC DLBCL患者的预后较低。该ABC DLBCL子集的特征在于激活各种存活信号通路的致癌突变。这些包括在Card11基因中的突变，该突变编码了B细胞受体下游NF-KB信号所需的支架分子。 B细胞受体成分CD79A和CD79B中的突变增强了持续的B细胞受体信号。信号适配器MyD88中的突变会产生自发的活性同工型。这些突变中的每一个都导致其获得的ABC DLBCL中的构型NF-KB活性。我们目前正在研究几个平台，以向淋巴瘤患者提供分子诊断和预后区别。目的是利用福尔马林固定和石蜡包裹的组织进行这些分析，因为大多数淋巴瘤活检通常以这种方式储存。事实证明，用于区分ABC和GCB DLBCL的数字基因表达分析的纳米弦平台非常有效。这项技术已获得纳米串许可，目前正在用于开发使用Lenalidomide来治疗ABC DLBCL的伴侣诊断。最近，我们一直在对参加治疗临床试验的患者进行基因组分析。在复发/难治性DLBCL中ibrutinib的2期试验中，我们使用基因表达分析将病例细分为ABC和GCB亚型。正如我们的实验室研究所预测的那样，ABC DLBCL的反应率明显大于GCB DLBCL（37％vs. 5％），这表明对ABC DLBCL的细胞系模型中对慢性活性B细胞受体（BCR）信号的成瘾和Ibrutinib敏感性。 ABC DLBCL中复发突变的分析表明，肿瘤的缓解率更高，突变影响BCR亚基CD79B，尤其是CD79B和MYD88突变的肿瘤。这表明可以根据遗传异常来进一步细分ABC DLBCL，以预测对靶向剂的反应。为了测试这一点，我们对574种DLBCL肿瘤进行了多平台基因组分析，并通过对DNA拷贝数改变，易位和突变的分析进行了综合基因表达分析，从而导致了DLBCL的遗传分类法，从而提供了意外的生物学和临床见解1。如果肿瘤具有多种复发遗传改变，则将其分类为相同的遗传亚型。这种方法产生了四种DLBCL遗传亚型 - 称为MCD，BN2，N1和EZB-，可完善并扩展基于基因表达的DLBCL1分类。 MCD和N1肿瘤主要是ABC DLBCL的子集，EZB是GCB DLBCL的子集，但BN2肿瘤是从ABC，GCB和未分类的DLBCL中绘制的。 DLBCL遗传亚型的生物学和临床相关性的强烈支持来自对免疫化学疗法的反应的分析。 MCD和N1亚型的总生存率比BN2和EZB遗传亚型要好得多。 MCD，N1，BN2和EZB DLBCL的5年生存部分分别为26％，36％，65％，68％。在ABC DLBCL中，MCD和N1患者的存活率不如BN​​2患者的存活率。在GCB DLBCL中，EZB患者的存活率不如其他GCB患者。因此，遗传亚型区别提供的预后信息扩展并改善了基因表达分析所提供的预后差异。这些发现的一个含义是，鉴于仅在化学疗法后，该组相对低的5年生存率，因此患有MCD DLBCL的患者应考虑一种与免疫化学疗法相结合的新型药物的临床试验。第二个暗示是，鉴于这些亚型仅在R-Chop之后的结果存在明显的差异，其中R-Chop与新药结合的临床试验应确定哪些DLBCL遗传亚型被招募。当前的努力旨在开发一种可行的可行且有用的工具，以将DLBCL肿瘤分类为遗传亚型，并将这些方法部署在Precision Medicine临床试验中。