Molecular diagnosis and outcome prediction in lymphoma

淋巴瘤的分子诊断和结果预测

基本信息

批准号：
10926109
负责人：
Louis Staudt
金额：
$ 144.57万
依托单位：
DIVISION OF BASIC SCIENCES - NCI
依托单位国家：
美国
项目类别：
财政年份：
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/10926109
关键词：
Affect Age Algorithms B cell differentiation B-Cell Antigen Receptor B-Cell Lymphomas B-Lymphocytes Behavior Biological Biopsy Biopsy Specimen Cell Line Central Nervous System Lymphoma Chronic Classification Clinic Clinical Clinical Trials DNA analysis DNA copy number Data Data Analyses Data Set Diagnosis Diagnostic Procedure Disease Disease-Free Survival Disparity Drug Combinations Drug Targeting Enrollment Extranodal Formalin Gene Expression Gene Expression Profile Gene Expression Profiling Genetic Genomics Genotype Goals Heterogeneity Human Immuno-Chemotherapy In complete remission Investigation Laboratories Laboratory Study Length Licensing Lymphoma Malignant lymphoid neoplasm Mediastinal Methods Modeling Molecular Molecular Abnormality Molecular Diagnosis Molecular Profiling Mutation NF-kappa B Newly Diagnosed Oncogenic Outcome PIK3CG gene Paraffin Embedding Pathogenesis Pathway interactions Patients Phenotype Primary Neoplasm Probability Process Randomized Receptor Signaling Recurrence Refractory Regimen Relapse Signal Transduction Site Somatic Mutation Structure of germinal center of lymph node Survival Rate Taxonomy Technology Testing Therapeutic Clinical Trial Tissue Embedding Tumor Biology activated B cell like addiction biological heterogeneity chemotherapy clinical practice clinically relevant diagnostic platform digital platform genomic platform improved insight large cell Diffuse non-Hodgkin&apos s lymphoma leukemia/lymphoma lymphoid neoplasm nano-string novel outcome prediction participant enrollment patient response phase II trial phase III trial predicting response response targeted agent targeted treatment therapeutic target therapy outcome transcription factor treatment response tumor tumor microenvironment web site

项目摘要

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. To bring these findings into the clinic, we investigated methods to utilize formalin-fixed and paraffin-embedded tissue for gene expression profiling since most lymphoma biopsies are routinely stored in this fashion. Together with collaborators in the Lymphoma/Leukemia Molecular Profiling Project (LLMPP), we developed a 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 Veracyte, which has applied to the FDA for approval to aid in the diagnosis of DLBCL. 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. These two mutations are also recurrent in aggressive lymphomas involving certain extranodal sites, such as primary central nervous system lymphoma (PCNSL). This clinical finding suggested that 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 insights. Tumors were classified into the same genetic subtype if they shared multiple recurrent genetic alterations. This approach initially yielded four DLBCL genetic subtypes - termed MCD, BN2, N1, and EZB - that refine and extend the gene expression-based classification of DLBCL. 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. More recently, we have extended our analysis of this dataset with a new algorithm, LymphGen, which provides a probability that a lymphoma belongs to a particular genetic subtype. This effort led to the discovery of 2 new genetic subtypes, termed ST2 and A53, and the subdivision of the EZB subtype into an EZB-MYC+ and an EZB-MYC- subtype. Strong support for the biological and clinical relevance of the DLBCL genetic subtypes came from analysis of responses to immunochemotherapy. Within ABC DLBCL, the outcomes following R-CHOP chemotherapy were significantly different, with adverse 5-year overall survival rates in the MCD (37%), A53 (33%) and N1 subtypes (22%) compared with a more favorable survival rate in BN2 (76%). Within GCB DLBCL, favorable 5-year survival rates were observed in ST2 (81%), EZB-MYC- (82%), A53(100%), and BN2 (100%) compared with EZB-MYC+ tumors (48%). Each genetic subtype was also characterized by the expression of distinct gene expression signatures, indicating striking differences between the subtypes with respect to B cell differentiation stage and transcription factors, oncogenic signaling mechanisms and the tumor microenvironment, emphasizing that view that this genetic taxonomy identify tumors with shared pathobiological processes. One implication of these findings 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. To this end, we have implemented the LymphGen algorithm on a publicly accessible web site. The genetic abnormalities and gene expression signatures that characterize the DLBCL genetic subtype suggest that they will respond differentially to targeted therapy. The MCD and BN2 subtypes are enriched for genetic changes in the BCR-dependent NF-kB pathway, and cell line models of these subtypes are heavily reliant on this oncogenic signaling for survival. The EZB genetic subtype does not rely on this pathway but instead engages PI3 kinase signaling to maintain viability. These distinctions are apparent in our clinical trials. As mentioned above, in relapsed/refractory ABC DLBCL, tumors of the MCD genotype frequently responded to ibrutinib. In a clinical trial in primary central nervous system lymphoma, which belongs to the MCD subtype, we showed that ibrutinib induced objective response in 94% of cases as monotherapy, and together with chemotherapy induced complete responses in 83% of patients. Our phase II trial of ibrutinib monotherapy in relapsed/refractory DLBCL led to a randomized phase III trial ("Phoenix") of ibrutinib plus R-CHOP chemotherapy in newly diagnosed non-GCB DLBCL, which LYMB colleague Wyndham Wilson and I co-led together with Anas Younes and Janssen colleagues. The trial showed an ibrutinib benefit in younger patients (age60), resulting in a 12.3% improvement in 3-year overall survival. To understand the biological basis for this ibrutinib benefit, we applied our LymphGen genetic classifier to data from Phoenix biopsy samples, allowing us to distinguish three main subtypes: MCD, N1 and BN2. Younger patients with the MCD and N1 subtypes had a 100% 3-year event-free survival with ibrutinib plus R-CHOP but only 43% and 50% survival, respectively, with R-CHOP alone. MCD and N1 acquire mutations targeting the BCR-dependent NF-kB pathways in 91% and 57% of cases, respectively, consistent with their sensitivity to ibrutinib. Our findings demonstrate that the survival benefit of ibrutinib in younger non-GCB patients on the Phoenix trial has a strong biological basis, supporting the view that an ibrutinib-containing regimen should be considered for such patients.

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。为了将这些发现带入诊所，我们研究了利用福尔马林固定和石蜡包含的组织进行基因表达分析的方法，因为大多数淋巴瘤活检通常以这种方式存储。我们与淋巴瘤/白血病分子分析项目（LLMPP）的合作者一起开发了用于数字基因表达分析的纳米弦平台，已证明在区分ABC和GCB DLBCL方面非常有效。该技术已获得纳米弦和Veracyte的许可，该技术已申请FDA批准以帮助诊断DLBCL。我们一直在进行接受治疗临床试验的患者的基因组分析。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。这两个突变也在涉及某些旋转外部位的侵袭性淋巴瘤中复发，例如原发性中枢神经系统淋巴瘤（PCNSL）。这一临床发现表明，DLBCL可以根据遗传异常进一步细分，以预测对靶向剂的反应。为了测试这一点，我们对574个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，该分类学提供了意外的生物学和临床见解。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。这种方法最初产生了四个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DLBCL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。最近，我们已经使用一种新算法淋巴扩展了对该数据集的分析，该算法提供了淋巴瘤属于特定遗传亚型的概率。这项工作导致发现了2种新的遗传亚型，称为ST2和A53，并将EZB亚型的细分划分为EZB-MYC+和EZB-MYC-亚型。 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。在ABC DLBCL中，R-CHOP化疗之后的结果显着差异，MCD的5年总生存率不良（37％），A53（33％）和N1亚型（22％），而BN2（76％）的存活率更高。在GCB DLBCL中，与EZB-MYC+肿瘤（48％）相比，在ST2（81％），EZB-MYC-（82％），A53（100％）和BN2（100％）中观察到了有利的5年生存率。每种遗传亚型还以不同的基因表达特征的表达表达，表明亚型在B细胞分化阶段和转录因子，致癌信号传导机制和肿瘤微环境方面的显着差异，强调了这种遗传分类学鉴定具有共享病态学物理学过程的遗传分类法。这些发现的一个含义是，鉴于仅在这些子类型中，仅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。为此，我们已经在公共访问的网站上实现了淋巴算法。表征DLBCL遗传亚型的遗传异常和基因表达特征表明它们将对靶向治疗有所不同。 MCD和BN2亚型富含BCR依赖性NF-KB途径的遗传变化，这些亚型的细胞系模型在很大程度上依赖于这种致癌信号传导以生存。 EZB遗传亚型不依赖于这一途径，而是接合PI3激酶信号传导以保持生存能力。这些区别在我们的临床试验中很明显。如上所述，在复发/难治性ABC DLBCL中，MCD基因型的肿瘤经常对伊布鲁替尼有反应。在属于MCD亚型的原发性中枢神经系统淋巴瘤中的一项临床试验中，我们表明ibrutinib在94％的病例中作为单一疗法诱导了客观反应，并且与化学疗法一起诱导了83％的患者的完全反应。我们对复发/难治性DLBCL进行Ibrutinib单一疗法的II期试验导致了Ibrutinib加上III期的随机试验（“ Phoenix”），以及新诊断的非GCB DLBCL的R-Chop化学疗法，LYMB同事Wyndham Wilson和I与AnaseAsea anas Younes Younes ancorea coute in non-GCB DLBCL中。该试验显示，年轻患者（60岁）的ibrutinib受益，三年制总生存率提高了12.3％。为了了解这种依鲁替尼的生物学基础，我们将淋巴遗传分类器应用于凤凰活检样品的数据，从而使我们能够区分三个主要亚型：MCD，N1和BN2。 MCD和N1亚型的年轻患者与Ibrutinib加R-Chop的100％无事件生存期为100％，但单独使用R-Chop的患者分别只有43％和50％的生存率。 MCD和N1在91％和57％的病例中获取针对BCR依赖性NF-KB途径的突变，这与它们对Ibrutinib的敏感性一致。我们的发现表明，在凤凰城试验中，伊布鲁替尼在年轻的非GCB患者中的生存益处具有很强的生物学基础，支持这样一种患者应考虑含伊布鲁替尼治疗方案的观点。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Defining, Identifying, and Understanding "Exceptional Responders" in Oncology Using the Tools of Precision Medicine.

使用精准医学工具定义、识别和理解肿瘤学中的“特殊反应者”。

DOI：
10.1097/ppo.0000000000000392
发表时间：
2019
期刊：
Cancer journal (Sudbury, Mass.)
影响因子：
0
作者：
Tsimberidou,ApostoliaM;Said,Rabih;Staudt,LouisM;Conley,BarbaraA;Takebe,Naoko
通讯作者：
Takebe,Naoko

Activating mutations of STAT5B and STAT3 in lymphomas derived from γδ-T or NK cells.

DOI：
10.1038/ncomms7025
发表时间：
2015-01-14
期刊：
Nature communications
影响因子：
16.6
作者：
Küçük C;Jiang B;Hu X;Zhang W;Chan JK;Xiao W;Lack N;Alkan C;Williams JC;Avery KN;Kavak P;Scuto A;Sen E;Gaulard P;Staudt L;Iqbal J;Zhang W;Cornish A;Gong Q;Yang Q;Sun H;d'Amore F;Leppä S;Liu W;Fu K;de Leval L;McKeithan T;Chan WC
通讯作者：
Chan WC

Integrating genomic alterations in diffuse large B-cell lymphoma identifies new relevant pathways and potential therapeutic targets.

DOI：
10.1038/leu.2017.251
发表时间：
2018-03
期刊：
Leukemia
影响因子：
11.4
作者：
Karube K;Enjuanes A;Dlouhy I;Jares P;Martin-Garcia D;Nadeu F;Ordóñez GR;Rovira J;Clot G;Royo C;Navarro A;Gonzalez-Farre B;Vaghefi A;Castellano G;Rubio-Perez C;Tamborero D;Briones J;Salar A;Sancho JM;Mercadal S;Gonzalez-Barca E;Escoda L;Miyoshi H;Ohshima K;Miyawaki K;Kato K;Akashi K;Mozos A;Colomo L;Alcoceba M;Valera A;Carrió A;Costa D;Lopez-Bigas N;Schmitz R;Staudt LM;Salaverria I;López-Guillermo A;Campo E
通讯作者：
Campo E

MHC class II transactivator CIITA is a recurrent gene fusion partner in lymphoid cancers.

DOI：
10.1038/nature09754
发表时间：
2011-03-17
期刊：
NATURE
影响因子：
64.8
作者：
Steidl, Christian;Shah, Sohrab P.;Woolcock, Bruce W.;Rui, Lixin;Kawahara, Masahiro;Farinha, Pedro;Johnson, Nathalie A.;Zhao, Yongjun;Telenius, Adele;Ben Neriah, Susana;McPherson, Andrew;Meissner, Barbara;Okoye, Ujunwa C.;Diepstra, Arjan;van den Berg, Anke;Sun, Mark;Leung, Gillian;Jones, Steven J.;Connors, Joseph M.;Huntsman, David G.;Savage, Kerry J.;Rimsza, Lisa M.;Horsman, Douglas E.;Staudt, Louis M.;Steidl, Ulrich;Marra, Marco A.;Gascoyne, Randy D.
通讯作者：
Gascoyne, Randy D.

Aggressive lymphomas.