Identification of Genetic and Epigenetic Changes as Biomarkers and Therapeutic Targets in the Pathogenesis of Lymphomas

Transcription

1 Identification of Genetic and Epigenetic Changes as Biomarkers and Therapeutic Targets in the Pathogenesis of Lymphomas Mingyi Chen MD, PhD Associate Professor Department of Pathology and Laboratory Medicine University of California Davis Medical Center

2 Objectives There are more than 60 unique subtypes of lymphomas. Despite this diversity, the expedient development and application of novel therapeutic advances in lymphoma have been critically important. This lecture will focus on to tree topics: 1.Detection of viral infection and lymphomagenesis 2.Epigenetics modifier MMSET expression in DLBCL 3.Recent developments in lymphoma classification, molecular biology, diagnostic algorithms, testing modalities, and advances in target therapeutic.

3 Infection Associated Cancers Infection-associated cancers are increasing at an alarming rate worldwide. Approximately percent of cancers (about 1.5 million cases per year in the US) are linked to viral infection. Furthermore, etiologic links between identified infectious agents, such as Epstein-Barr Virus (EBV) in lymphoma had significant clinical implications. Given existing evidence linking lymphoma to viral etiologies, a comprehensive screening virus in lymphomagenesis is performed using the novel Lawrence Livermore Microbial Detection Array (LLMDA).

4 Why do viruses cause cancer? Highlights of the first century of human tumour virology. Patrick S. Moore & Yuan Chang Nature Reviews Cancer 10, (December 2010)

5 Two Home Runs In A Row by Drs. Patrick S. Moore and Yuan Chang Discovery of two of the seven known human cancer viruses. In 1994, they discovered Kaposi sarcoma-associated herpesvirus (KSHV/HHV8), and they identified Merkel cell polyomavirus in 2007 by digital transcriptome subtraction.

6 The common human cancer viruses Patrick S. Moore & Yuan Chang Nature Reviews Cancer 10, (December 2010)

7 Major human Oncogenic Viruses DNA Viruses Small DNA tumor viruses - Adenovirus - Polyomaviruses (SV40/JCV/BKV/MCV) - Human Papilloma virus (HPV) Herpesviruses (large) - Epstein Barr virus (EBV) - Kaposi s Sarcoma Herpesvirus (KSHV) Other - Hepatitis virus B RNA viruses Human T-cell Leukemia Virus 1 (HTLV1) Hepatitis virus C 7

8 The molecular evolution of a human tumour virus. Why do viruses cause cancer? Highlights of the first century of human tumour virology. Patrick S. Moore & Yuan Chang Nature Reviews Cancer 10, (December 2010)

9 Common cellular targets for tumour virus oncoproteins. Patrick S. Moore & Yuan Chang Nature Reviews Cancer 10, (December 2010)

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11 Lawrence Livermore Microbial Detection Array (LLMDA) Microarray Probes: 170,399 family-specific viral probes (x2) 7,864 all sequenced bacteria 1,278 human viral response genes 20,736 ViroChip probes (DeRisi) 12,342 unclassified viruses 1,846 amplicons for hemorrhagic fever viruses 2,651 negative controls 387,156 total probes Extensive bioinformatics analyses allow this metagenomic microarray to rapidly characterize complex unknown samples with up to 1.7M probes

12 Comprehensive analysis of microbial signatures for lymphomagenesis using a novel Microbial Detection (LLMDA) Array HHV4/EBV genome stain detected Epstein Barr virus was detected by LMDA and confirmed by EBER in situ hybridization in plasmablastic lymphoma from a HIV/AIDS patient. Tellez J, Jaing C, Wang J, Green R, Chen M. Biomark Res Dec 5;2(1):24.

13 HE EBER-ish NK/T cell lymphoma Plasmablastic lymphoma Tellez J, Jaing C, Wang J, Green R, Chen M. Biomark Res Dec 5;2(1):24.

14 PTLD-cHL Angioimmunoblastic T-cell lymphoma PTLD-Burkitt lymphoma Tellez J, Jaing C, Wang J, Green R, Chen M. Biomark Res Dec 5;2(1):24.

15 Detection of EBV by LLMDA We screened 106 human tissue using LLMDA. Five of 21 aggressive stage B cell lymphomas were EBER+, and all the indolent stage B cell lymphomas were EBER-. Both NKT cell lymphomas were EBER+, and the T cell lymphomas and benign tissues were EBER-. Five of the PTLD cases (4 B cell lymphomas and 1 NKT cell lymphoma) were EBER+ and 5 were EBER-. Tellez J, Jaing C, Wang J, Green R, Chen M. Biomark Res Dec 5;2(1):24.

16 Tellez J, Jaing C, Wang J, Green R, Chen M. Biomark Res Dec 5;2(1):24.

17 Unraveling the EBV-induced lymphomagenesis:

18 Types of Epstein-Barr virus latency. Enhance PD-L1/PD-L2 by inducing tolerogenic microenvironment with T-cell anergy and immune evasion. Constitutive activation of NF-kB

19 Survival of Non-Hodgkin Lymphoma patients 100% indolent 50% aggressive very aggressive Years since diagnosis

20 Conclusion LLMDA efficiently detected EBV in clinical casese of malignant lymphomas. The LLMDA technique provides a powerful and sensitive method for identifying viral pathogens associated with lymphomagenesis and may also prove useful for the discovery of novel tumor-associated viruses.

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23 Targeting hit-and-run cancer viruses Viruses that can invade host cells, initiate cancer and then flee from their own trail of destruction therefore, play either a triggering or an accessory role in cancergenesis. The hit-and-run hypothesis proposes that cumulative host mutations allow viral genomes lost entirely. Cancers remaining virus-positive represent only a fraction of life that infection contributes, with considerable implications for disease control by early vaccination. Transient acquisition of viral genomes induces permanent changes in the gene expression pattern/epigenetic changes of the host cell, resulting in malignant conversion.

24 Epigenetic protein families: acetylation and methylation of histones Proteins covalently attach acetyl /methyl groups Enzymes remove histone marks Proteins recognize histone modifications Nature Reviews Drug Discovery 11, (May 2012).

25 MMSET (WHSC1/NSD2) is a SET domain containing histone lysine methyltransferase which is overexpressed in 15%-20% of multiple myelomas with the t(4;14)(p16;q32) translocation associated with poor prognosis. MMSET switches global histone methylation and alters gene expression as a Reader and a Writer of the Histone Code MMSET is localized on chromosome 4 and targets genes that are SET domain dependent and critical for cell Growth and Proliferation. Cell Cycle Adhesion Apoptosis DNA repair DNA replication?

26 Aberrations of NSD/MMSET family of epigenetic regulators in human cancers NSD: Nuclear receptor binding, SET domain containing NSD1 NSD2 Soto; AML WHS; MM NSD3 AML SET Domain H3K36me2 H3K36 methylation mark is present in transcriptionally active genes.

27 MMSET/NSD2 is also overexpressed in many types of human cancers Prostate Cancer Breast Cancer Lung Cancer DLBCL Lymphoma MMSET is linked to the immunoglobulin (IgH) promoter/enhancer in t(4;14) translocations, found in 15%-20% of multiple myeloma. Chromosomal fusion leads to overexpression of MMSET and FGFR3 genes; however, approximately 30% of the patient samples overexpress only the MMSET gene, suggesting its pivotal role in the disease Myeloma t(4;14) Yang P. et al., MCB 2012 & unpublished

28 Experimental Design: The gene expression of MMSET was detected by RT-qPCR in frozen lymphoma tissue and control lymphoid tissues (traumatic spleen). Immunohistochemistry of MMSET on lymphoma tissue microarrays (TMA) was performed. Further validations of MMSET expression were carried out on independent, tumor-specific sets of TMAs for diffuse large B-cell lymphoma with corresponding clinicopathological follow-up.

29 q-rtpcr analysis of MMSET/NSD2 gene expression in fresh frozen tissue of selected cases of lymphoma Relative fold increase of MMSET expression

30 Detection of MMSET/NSD2 expression in lymphoma TMA FL DLBCL BL TCHRLBL PTCL MZL ALCL chl

31 MMSET overexpression in DLBCL and correlation with tumor aggressiveness (high ANCAA) MMSET/NSD2 ANCCA ANCCA is an AAA+ ATPase and a bromodomain-containing nuclear coactivator that is crucial for assembly of chromatin-modifying complexes and functions as a cell proliferation index marker similar to K-i-67.

32 MMSET/NSD2 Criteria of H-score MMSET/NSD2 and ANCCA protein expression For MMSET/NSD2 and ANCCA protein expression analysis, a composite scoring system was used. Briefly, score was calculated by multiplying the intensity (integer between 0 and 3) with the percentage of the cells having this intensity. Classification into four tiers: Score 0: negative Score 1-100: weak Score : moderate Score : strong ρ:correlation coefficient 0.86 ANCCA

33 Subgroups of diffuse large B-cell lymphoma defined by gene expression profiling Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Alizadeh AA, et al. Nature 2000; 403: Germinal centre B-like: good prognosis Activated B-like; bad prognosis

34 MMSET overexpression in ABC type of DLBCL ABC (n=45) N (%) GCB (n=64) N (%) p-value Mean TMA tertiles 0-2 >2 and <3 >=3 11 (24%) 11 (24%) 23 (51%) 19 (30%) 29 (45%) 16 (25%) Mean TMA median <=2.5 > (40%) 27 (60%) 41 (64%) 23 (36%) Table 2 shows the association between mean TMA category divided into tertiles and at the median with ABC/GCB status. Both are significantly associated with ABC/GCB status. Table 2. Mean TMA categories by ABC/GCB status. 119 patients have survival data available. 47 have died and 72 were alive at last contact. The median follow-up for the patients alive at last contact is 7.7 years and ranges from 0.5 to 12.0 years.

35 Proportion MMSET overexpression correlates with poor event free survival Event-free in ABC type Survival of DLBCL by Mean IHC, in ABC P: Test: p= Years meancat2 CENSOR FAIL TOTAL MEDIAN >

36 Conclusion MMSET is highly expressed in high grade B-cell lymphomas especially in non-gcb phenotype. In DLBCL, MMSET overexpression is correlated with tumor aggressiveness (high ANCAA/Ki-67), therefore it might qualify as a prognostic marker and a possible therapeutic target. The mechanism leading to high levels expression of MMSET in the DLBCL remains to be elucidated. The aberrant MMSET overexpression is either directly contributing to DLBCL development or is merely a marker of the transformed cells.

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38 Immunotherapy of lymphoma Monoclonal antibodies Anty-CD20 (Rituximab, Mabthera) Anty-CD52 (alemtuzumab, Campath) Anti-CD30 (Brentuximab-MMAE(Adcetris) Interferons Interleukin 2 Immunomodulating agents: Lenalidomide (Revlimid) and bortezomib (Velcade) Combination therapy CHOP+Rituximab Radioimmunotherapy Zevalin : antycd20+y-ibritumomab tiuxetan Bexxar: antycd20+ I-tositumomab - Immune checkpoint inhibitors: PDL1/CTLA-4 inhibitors - Adoptive CAR-T cell immunotherapy

39 2013 Oct 21;210(11):

40 Aging predisposes to acute inflammatory induced pathology after tumor immunotherapy Bouchlaka M, Sckisel GD, Chen M. et al. J Exp Med. Oct 21, 2013; 210(11):

41 Obesity associated proinflammatory environments Lean Obese (Osborn et al., 2012, Nat Med) 41

42 Pathology Score Obesity increases GI tract damage after immunotherapy Lean (BM) Obese (BM) Lean (BM+T) (BM+SP) Obese (BM+T) (BM+SP) 40X 4.0 * * Multifocal necrosis and lymphocytic infiltration was seen GI tract of obese mice post immunotherapy Lean (BM) Obese (BM) Lean (BM +T) Obese (BM+T) 2. Villi atrophy and thinning of the intestinal wall in obese mice

43 November 3, 2014, 211(12)

44 Increased adiposity results in systemic release of proinflammatory cytokines storm and organ damage after immunotherapy in young ob/ob and aged AL mice. Mirsoian A, Bouchlaka M, Gail D. Chen M et al. J Exp Med 2014;211:

45 pg/ml pg/ml Obesity increases serum TNF-α and IL-6 post immunotherapy IL-6 TNF-a **** * Lean Obese Lean Obese 0 Lean Obese Lean Obese BM BM+T BM BM+T Pai CC, Hsiao HH, Sun K, Chen M, Hagino T, Tellez J, Mall C, Blazar BR, Monjazeb A, Abedi M, Murphy WJ. Biol Blood Marrow Transplant Dec;20(12):

46 Calorie restriction confers protection by decreasing cytokine levels and immunotherapy-associated organ damage Mirsoian A, Bouchlaka M, Gail D. Chen M et al. J Exp Med 2014;211:

47 Impact of aging in cancer immunotherapy Bouchlaka MN, Murphy WJ. Oncoimmunology Dec 1;2(12)

48 Bouchlaka MN, Murphy WJ.Oncoimmunology Dec 1;2(12)

49 Have the courage to follow your heart and intuition --Stay Hungry, Stay Foolish - Steve Jobs

50 Acknowledgement: Collaborators: Dr. Ralph Green, UCDMC, Dept. of Pathology and Laboratory Medicine Dr. Crystal Jiang, LLNL, Group Leader of Applied Genomics Dr. William Murphy, UCDMC, Dept. of Dermatology Dr. Hongwu Chen, UCDMC, Dept. of Biochemistry Dr. Kai Fu, U. of Nebraska, Dept. of Pathology and Microbiology. Dr. Eric Kool, Stanford University, Dept. of Chemistry Grant support: American Cancer Society-UCD IRG Grant UC-LLNL Fitpatrick Cancer Center Grant California Cancer Research Coordinating Grant Subcontract NCI RO1 CA099572?