About Dr. Naresh

Dr. Kikkeri Naresh is an academic pathologist with over 30 years of experience in the field of Pathology and has been a professor for over 20 years. He has worked in centers of excellence across three continents (Asia, Europe, and North America) and undertaken research in Africa.

Dr. Kikkeri Naresh focuses primarily on translational research in hematological malignancies, particularly lymphomas. He also partners with colleagues in basic research to address questions of biological importance. The questions he has addressed include – pathogenesis and disease evolution using genomic and expression platforms, disease biomarkers, infectious agents, tumor microenvironment, disease classification and stratification, identification of new entities, diagnostic algorithms, epidemiology including molecular epidemiology and others.

Dr. Naresh combines his research with teaching and training including clinical academic training. His research supervision/mentorship has included PhD, MSc, MRes and BSc/MD(MBBS) students and clinical academic trainees. He works across wide national and international research networks including the World Health Organization (WHO).

Current Ongoing Projects

Lymphoma Classification

Lymphoma is not one disease or one cancer. It is a group of over 100 cancers arising from lymphoid cells or lymphocytes. Recognizing each of these cancers is crucial for optimal patient management and achieving high cure rates. Dr. Naresh is one of the 24 experts on the Editorial Board of the WHO classification of Haematolymphoid Tumours (5th ed.) {PMID: 35732831; 35732829}. Apart from being an Editor, he has authored/co-authored >30 sections (disease entities) of the WHO classification. Refining subsets of aggressive B-cell lymphoma based on genomics is an area of active research. Furthermore, our understanding of lymphomas is rapidly evolving, and our approaches to disease classification need to keep pace with this dynamism {PMID: 36467810} (Figure 1). Naresh’s early work contributed to understanding in-situ mantle cell neoplasia {PMID: 18184277; 22058203} and marginal zone lymphoma {PMID: 18269584}. Naresh’s earlier work has also made the classification system relevant to low and middle-income countries {PMID: 21718280; 27247372; 34725849}.

Lymphoma Disease Biomarkers & Precision Oncology

Even within a single lymphoma entity, there is heterogeneity in patient outcomes. Understanding the basis of this heterogeneity will help develop strategies to adapt treatment for individual patients. Currently, work is underway in follicular lymphoma, mantle cell lymphoma, and classic Hodgkin lymphoma to unravel the basis of this heterogeneity. Evaluating outcome data from 33,925 patients of follicular lymphoma in the SEER database, the group identified that the grade of the disease has a significant impact on outcome {PMID: 35973829} (Figure 2). Currently, determining disease grade has a significant element of subjectivity, work is underway to identify and validate more objective strategies with a biological underpinning. Similarly, mantle cell lymphoma is heterogeneous in clinical behavior, and outcomes range from primary refractory disease to progression-free survival beyond 7 years. 

Based on our earlier findings that the mantle cell lymphoma is heterogeneous in the proportion of cells in G2 and mitotic phases {PMID: 32873701}, we are currently evaluating dysregulation of the cell cycle in this lymphoma and its impact on outcomes (Figures 3 & 4). 

In collaboration with Dr. Jonathan Fromm at UW, the proportion of rosetted Hodgkin Reed-Sternberg cells as identified using multiparametric flow cytometric analysis could serve as an excellent disease biomarker in classic Hodgkin lymphoma {PMID: 36241372} (Figure 5), and work is ongoing to make this strategy applicable on paraffin section slides in classic Hodgkin lymphoma (Figure 6). 

In collaboration with Dr. Jonathan Fromm at UW, we have standardized the application of multiple antibodies using CODEX technology. We have developed a B-cell-centered panel of 25 antibodies that is currently being evaluated on a large cohort of B-cell lymphomas (Figure 7). We are also in the process of developing a similar large T-cell panel.

We also identified that disease mortality as a relative proportion to the incidence of some of the lymphomas appears to be higher in the Central regions of Washington State as compared to other regions. It is important to understand the scientific basis responsible for these differences to achieve equity of cure rates. We are exploring if there are significant differences in the types and proportions of patient’s’ immune cells within the lymphoma samples from different regions in Washington state, if such variability in immune cells (if present) could contribute to disparities in patient outcomes in the Washington state (Figures 8 & 9).

Lymphoma Epidemiology

Lymphoma incidence varies between the 13 counties in the Seattle Puget Sound region – the age-adjusted incidence rate (2014-2018) is lowest in San Juan (17.1) and highest in Grays Harbor (30.2 (Figure 10). Upon revisiting diagnoses of all lymphomas in the Seattle Puget Sound region, we have arrived at the age-adjusted incidence of individual lymphomas in the 13 counties in both males and females. The data suggest a higher incidence of certain lymphomas in some counties relative to the rest. We are currently evaluating whether there is a higher incidence of lymphoma precursors in these regions.

B-cell Biology

We are currently exploring the modulation of the cell cycle during B-cell maturation, particularly within peripheral lymphoid organs, and the impact of this understanding on lymphoma classification and stratification. We are evaluating cell cycle proteins in different B-cell subsets to evaluate how the cell cycle profiles (proportions of cells in different stages of the cell cycle) alter with maturational stages of normal B-cells (Figure 11). We will further explore how this is altered in neoplastic states in comparison to their normal counterparts. We are also exploring mechanisms that modulate the expression of certain transcription factors in B-cell lymphoma. PAX5 is a nuclear transcription factor essential in B-cell development and is expressed from the pro-B to the mature B-cell stage. In classic Hodgkin lymphoma, PAX5 expression is consistently at a low level, and in rare cases may be entirely negative. We are currently exploring mechanisms that underpin these changes initially using the RNAscope technology (Figure 12).

Digital Archive

We are creating a digital searchable database for pathology samples that will include appropriate identifiers, keywords, available archived material, information on the availability of whole slide images, key clinical presentation parameters, histological diagnosis, key aspects of the microscopic description and link these aspects to whole slide images uploaded on a server. As a pilot study, the database is being created for samples obtained from patients who experienced graft versus host disease following stem cell transplantation and for patients who had CAR-T cell treatment at Fred Hutch.

Immunopathology and Pathogenesis of Graft Versus Host Disease (GVHD)

Acute GVHD seen in the setting of allogeneic stem cell transplantation is the result of the attack of donor lymphocytes on host tissue that includes the gastrointestinal tract (GIT), skin, liver, and lungs. Histological diagnosis of GVHD and its severity is made mainly by assessing the presence and the extent of apoptosis, and tissue destruction; all the evaluations are undertaken on hematoxylin and eosin stained slides. These morphological features overlap with other pathological processes. Interobserver reproductivity in diagnosis and grading is suboptimal. We are exploring biomarkers that will help improve diagnostic precision and grading. We are also trying to understand the process of GVHD better from an immunological and microbiome perspective (Figure 13). 

Projects Being Planned Based on Results of Previous Studies

Infectious Agents in Lymphomas

A proportion of lymphomas and lymphoproliferative disorders (LPD) are associated with the Epstein-Barr virus (EBV). Previous studies by us {PMID: 28419429; 22406538; 20408873} and others implicate EBV in the pathogenesis of lymphomas and LPDs. We hypothesize that latent infection by EBV (seen in >95% of the world’s population) provides only a limited proliferation/survival ability to the lymphoid cell. Further alterations/mutations in the EBV genome lead to changes in cell proliferation, apoptosis, or immunogenicity ultimately resulting in lymphomas and LPDs. We aim to identify mutations across the EBV genome from a large cohort of EBV+ lymphomas/LPDs, and unique matched sets of pre-lymphoma and lymphoma specimens and link these mutations to exact steps in lymphomagenesis (Figure 14). As a functional correlate, we intend to test the hypothesis that lymphoma-associated EBV mutations influence tumor immunogenicity. Patients’ immune cells and corresponding tumor samples will be used to analyze the magnitudes, specificities, and characteristics of EBV-specific T cells in the context of lymphoma-specific EBV mutations. We are also interested in the discovery of infectious agents hitherto not implicated in the pathogenesis of lymphomas.

Understanding the Importance of Germinal Center B-cell (GCB) Subpopulations (Dark Zone vs. Light Zone) In GCB Lymphomas

Antigen-exposed B-cells migrate to primary follicles and differentiate into proliferative centroblasts initiating a germinal center (GC). GC centroblasts that mainly occupy the dark zone (DZ) are subject to somatic hypermutation (SHM) of the rearranged IG genes and class-switch recombination (CSR), and they are highly susceptible to apoptosis. Centroblasts further differentiate into centrocytes that are located predominantly in the light zone (LZ) of the GC. Furthermore, GCB cells rapidly shuttle between DZ and LZ before differentiating into memory B-cells or plasma cells and exiting the GC (Figure 15). The two most common B-cell lymphomas – follicular lymphoma (FL) and the diffuse large B-cell lymphoma, not otherwise specified (DLBCL; including those with an activated B-cell phenotype) are derived from the GCB cells. We will explore the relationship of DZ vs. LZ phenotype to the biology of GCB cells and two lymphomas arising from GCB cells (FL & DLBCL). We will explore the cell cycle and spatial dynamics of DZ and LZ GCB cells and their interactions with the microenvironment within the GC. Furthermore, we will apply the distinction of DZ vs. LZ phenotype as a disease biomarker in patients/samples of FL and DLBCL.

Pathogenesis and Biomarkers of Lymphomas Associated with Immune Deficiencies

We wish to address the question as to why the risk of developing lymphomas is still high in patients living with HIV (PLWH) despite the timely initiation of combination anti-retroviral therapy (ART). PLWH on ART who have adequate CD4 counts and have a very low/undetectable HIV viral load continue to be at a higher risk of developing lymphomas. Our central hypothesis is that HIV infection induces genetic and epigenetic changes in lymphoid cells that persist even after the control of the HIV infection, and the nature of these alterations makes such lymphoid cells susceptible to lymphomagenic events with Epstein Barr virus (EBV) being a key factor in lymphomagenesis. A similar increased risk for developing lymphomas persists in patients who have received stem cell or solid organ transplantation, many years following the transplantation; the association with EBV decreases over time. We are interested in investigating tissue samples of benign lymph nodes and lymphomas in immune-suppressed states and comparing them to those in the general population at genomic, epigenetic, and expression levels. Through these studies, we wish to identify unique disease biomarkers for susceptibility to developing lymphoma and to those that can predict disease outcomes in those who develop lymphomas.

Spatial Biology in Lymphoid Malignancies

We are interested in understanding interactions between neoplastic lymphoid cells (including their subpopulations) with the microenvironment (both stromal and cellular) and the impact such interactions have on disease biology and patient outcomes, especially asking these questions in the context of novel therapies. We would like to understand this both at the level of the transcriptome and protein expression. One example is chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/ SLL), which is a neoplasm composed of monomorphic small mature B cells. Most of the CLL cells in the peripheral blood, lymph nodes (LN), and bone marrow are in a resting state. The proliferation of the neoplastic cells occurs primarily in the LN; within microscopically identifiable compartments of the LNs known as proliferation centers (PC) (Figure 16). Within the PCs, CLL cells come in intimate contact with T-helper cells, CLL-associated macrophages called nurse-like cells (NLC), and another component essential for the proliferation and survival of CLL cells. Bruton tyrosine kinase (BTK) inhibitors have proven to show significant clinical activity in patients of CLL. In a proportion of cases, CLL cells develop resistance to BTK inhibitors. To understand the mechanisms of response and resistance related to the tumor microenvironment of the CLL within the PCs, we would like to undertake transcriptomic analysis in a spatial context. We will explore spatial transcriptomic differences in samples of CLL between patients who respond and those who do not respond to the BTK inhibitor, ibrutinib. We will explore how differences in the expression of cells in the microenvironment of the proliferation center and those of the tumor cells contribute to response and resistance to ibrutinib. This will pave way for more in-depth studies and novel therapies in CLL. We will take similar approaches in follicular lymphoma, diffuse large B-cell lymphoma, and other lymphomas in the context of novel therapies.