Genomic adaptability of the tumor cells is the major obstacle in achieving successful cancer treatment. We have studied both tumor cells and their microenvironment in multiple myeloma (MM), a plasma cell malignancy. The immune microenvironment in MM exhibit considerable dysfunction1. In our previous work, we showed that dysfunctional regulatory T helper cells (Tregs)2, iNKT cells3, and elevated Th17 cells and IL-17A, increase MM cell growth and survival and suppress immune responses and induce bone disease4,5. Also, by targeting IL-17A in myeloma using a human anti-IL-17A monoclonal antibody (AIN457) we showed significant inhibition of MM cell growth5. However, the vast genomic changes in MM cells provide them the ability to survive and adapt to the therapeutic and immune micro-environmental influences. Our recent study has defined the mutational spectrum in MM at the time of initial diagnosis and found heterogeneity across patients6. We have recently identified biologically distinct mutations (APOBEC signature) responsible for tumor evolution and heterogeneity6. This clonal evolution is driven by a combination of factors, leads to both clonal selection and formation of new clones. We hypothesize that a combination of micro-environmental influences along with evolving genomic changes drives the tumor clone leading to progressive disease. In this regards, having studied immune status and function in previous funding period, we will now focus on identifying and validating mechanisms driving clonal changes in myeloma along with evaluation of the impact of immune microenvironment on these mechanisms. Towards this goal, we will pursue following specific Aims:
Specific Aim 1 : To identify molecular markers of progression in MM by investigating mutational signatures, expression profile and APOBEC activity in paired diagnosis and relapse samples We hypothesize that continued acquisition of mutational changes, driven by specific mutational processes, underlies progression of disease in myeloma from newly-diagnosed disease to relapsed state. We will analyze genome sequencing data from archived paired MM cell samples collected at the time of diagnosis and then at relapse following initial therapy, for overall mutational spectrum, types of mutational signatures inducing mutations at diagnosis and then driving the evolution, as well as overall clonal dynamics to identify patterns associated with progression. Based on our preliminary data, we will also evaluate if APOBEC activity and expression in these samples correlates with specific genomic signatures, overall genomic instability and/or progression.
Specific Aim 2 : To functionally evaluate the role of APOBECs in driving genomic instability in MM. We hypothesize that dysregulated APOBEC activity may be in part responsible for acquisition of new mutational changes associated with progression in myeloma. We will therefore perform loss- and gain-of-function studies using MM cell lines to investigate immediate and long term effects on genomic integrity, ongoing genomic instability, mutational changes/signatures, genes and genomic regions affected and activation/inactivation of genome maintenance, cell cycle and apoptosis pathways, proliferation rate and ability of cells to migrate.
Specific Aim 3 : To investigate the impact of immune components of the BM on APOBEC activity and genomic stability in myeloma. We hypothesize, that abnormal immune components including B cell subsets and soluble factors may affect APOBEC activity and drive clonal evolution. We will evaluate the impact of B cell subsets, mature and immature DCs, Th17 cells and soluble factors including IFN-? and ?, IL-17A and IL-6 on APOBEC expression and activity, and evaluate changes in genome using our standard assays.
Multiple myeloma (MM) is a B-cell malignancy whose incidence and prevalence are increasing with age. The median age at the diagnosis is 70 years and African Americans are affected at twice the rate of Caucasians. The elderly patient population at the VA Medical Center has increased risk of developing MM. Moreover, its relationship to Agent Orange increases its importance in veteran population. In a direct review of VA records over 4,000 patients with MM were seen in the VA in 2012. The effective therapy for MM is high-dose chemotherapy with bone marrow transplantation for which most of the veterans are not eligible due to their age, performance status, state of the disease or co-morbidities. The proposed studies on evolution of tumor cell genome from diagnosis to the time of the relapse, identifying the impact of immune components in tumor microenvironment on the clonal evolution in MM has great therapeutic implications. These mutational determinants with neo-antigenicity to MM will lead to a new treatment modality at any age in veterans.
|Szalat, R; Samur, M K; Fulciniti, M et al. (2018) Nucleotide excision repair is a potential therapeutic target in multiple myeloma. Leukemia 32:111-119|
|Amodio, Nicola; Stamato, Maria Angelica; Juli, Giada et al. (2018) Drugging the lncRNA MALAT1 via LNA gapmeR ASO inhibits gene expression of proteasome subunits and triggers anti-multiple myeloma activity. Leukemia 32:1948-1957|
|Bolli, Niccolò; Maura, Francesco; Minvielle, Stephane et al. (2018) Genomic patterns of progression in smoldering multiple myeloma. Nat Commun 9:3363|
|Gullà, A; Hideshima, T; Bianchi, G et al. (2018) Protein arginine methyltransferase 5 has prognostic relevance and is a druggable target in multiple myeloma. Leukemia 32:996-1002|
|Kumar, Subodh; Talluri, Srikanth; Pal, Jagannath et al. (2018) Role of apurinic/apyrimidinic nucleases in the regulation of homologous recombination in myeloma: mechanisms and translational significance. Blood Cancer J 8:92|
|Samur, Mehmet Kemal; Minvielle, Stephane; Gulla, Annamaria et al. (2018) Long intergenic non-coding RNAs have an independent impact on survival in multiple myeloma. Leukemia 32:2626-2635|
|Bolli, N; Biancon, G; Moarii, M et al. (2017) Analysis of the genomic landscape of multiple myeloma highlights novel prognostic markers and disease subgroups. Leukemia :|
|Cleynen, A; Szalat, R; Kemal Samur, M et al. (2017) Expressed fusion gene landscape and its impact in multiple myeloma. Nat Commun 8:1893|
|Cetin, Arif E; Stevens, Mark M; Calistri, Nicholas L et al. (2017) Determining therapeutic susceptibility in multiple myeloma by single-cell mass accumulation. Nat Commun 8:1613|
|Fulciniti, Mariateresa; Martinez-Lopez, Joaquin; Senapedis, William et al. (2017) Functional role and therapeutic targeting of p21-activated kinase 4 in multiple myeloma. Blood 129:2233-2245|
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