Research

The Administrative Core provides strategic planning, governance and day-to-day management for the SPORE program. It coordinates projects and cores across UT MD Anderson, Emory and participating institutions, with financial oversight, operational support and regulatory coordination to keep the research program aligned and compliant. The core strengthens productivity and synergy by maintaining clear decision-making processes and consistent communication through email and tele/video conferencing.

In this program, the core will

• Lead and administer the SPORE
• Integrate institutional resources and core functions across sites
• Drive strategic planning and progress evaluation with guidance from an External Advisory Board (EAB)

The overall programmatic impact of the core includes:

1. Program leadership and administration, to include:
   1. overseeing all projects and research cores
   2. setting priorities
   3. convening regular meetings (scientific, operational, and NCI-related)
   4. coordinatnig required reporting, 
   5. supporting clinical trial activities (protocol development, approvals, and regulatory compliance)
   6. maintaining fiscal stewardship through routine budget monitoring, account summaries and transparent resource allocation
2. Integration across institutions and shared resources, to include:
   1. ensuring coordinated interactions among Core 1 (community outreach and engagement), Core 2 (biospecimen and pathology), Core 3 (biostatistics and bioinformatics) and the projects, while facilitating access to relevant institutional resources (including NCI-supported infrastructure, as applicable)
   2. standardizing communication and coordination workflows to support consistent implementation across sites
3. Strategic planning, evaluation and issue resolution, to include: 
   1. With EAB input, implementing a structured planning and evaluation process, including annual written progress reports and an annual EAB review with formal recommendations
   2. supporting program refinement through defined decision pathways, including modification, integration or discontinuation of activities when warranted

Administrative management for the core is provided by Veronica Leautaud, Ph.D.

The overarching goals of the Community Outreach and Engagement Core are to facilitate research development and implementation between SPORE investigators and communities, build and sustain research partnerships, and strengthen investigator’s ability to recruit and retain patients in clinical studies. The core will comprehensively support bi-directional communication with the community, community advisors and community scientists for education and feedback on all SPORE Projects.

The core plays an integral role in this SPORE by:

1. Engaging patients and community stakeholders in SPORE and the Developmental Research Program (DRP) and leveraging the Community Advisory Board and local advisory panels
2. Building capacity of investigative teams in recruiting participants to clinical trials through training and patient/community engagement
3. Conducting regular needs assessments within the catchment area to thoroughly analyze the demographics, cancer burden and trial participation barriers; adapting and implementing multilevel, lymphoma-focused, evidence-based interventions to enhance participation and increase clinical trial enrollment
4. Disseminating best practices to increase clinical trial accrual rates and create policy recommendations for other trial networks
    

Histologic and molecular analysis of lymphoma specimens is central to each SPORE Project, enabling investigators to uncover drivers of disease and develop novel diagnostic and therapeutic strategies. The Biospecimens and Pathology Core provides critical infrastructure for accurate tissue collection pathology review and advanced analysis, including multiplex imaging, spatial transcriptomics, and the development of tissue derivatives and patient-derived xenografts. In collaboration with other SPORE Cores, Core 2 will digitize pathology slides, integrate clinical and biospecimen data, enabling efficient selection of samples with specific molecular, cytogenetic, immunophenotypic or clinical characteristics for translational studies.

The aims of the core are:

1. Develop and provide oversight for a unified SPORE-specific specimen bank and database that includes tissues, digitized slides and linked clinical data to facilitate sample selection and research collaboration
2. Provide hematopathology expertise to render an integrated diagnosis for all lymphoma specimens according to current World Health Organization and International Consensus Classifications
3. Perform multiparametric in situ immunophenotypic and molecular analysis of lymphomas from primary patient specimens, PDXs and genetically engineered mouse models, with computational integration

The Biostatistics and Bioinformatics Core provides essential data management, statistical analysis and bioinformatics support for the SPORE, with a focus on enabling cost-effective, high-dimensional data analysis and integration. Core 3 will manage and analyze complex multimodal datasets, including biological, clinical, pathology, genomic, and imaging data, to support all SPORE Projects as well as the Career Enhancement and Developmental Research Programs. Core 3 operates through a collaborative partnership between Weill Cornell Medicine and UT MD Anderson, leveraging the established infrastructure and institutional resources at both institutions to provide HIPAA-compliant data handling and advanced next-generation sequencing (NGS) pipelines. The Core 3 team brings comprehensive expertise in genomics, biostatistics, and the management of large-scale datasets from both clinical and basic science research projects. This partnership ensures comprehensive support for the SPORE projects, guiding the transition of basic science findings to clinical applications. With decades of experience in processing and analyzing multidimensional datasets for team science initiatives, the Biostatistics and Bioinformatics Core is positioned to drive impactful discoveries and enhance the overall research of the SPORE.

Project 1: Precision Targeting of Therapeutic Vulnerabilities Specific to African Ancestry Lymphoma Patients

Diffuse large B cell lymphomas (DLBCLs) are highly heterogeneous, with many patients remaining incurable, and survivors often facing long-term medical and financial challenges. Patients of African Ancestry (AA) more commonly develop DLBCL at a younger age and have worse outcomes, but little is known about differences in disease biology.

Our research found that AA DLBCLs exhibit a unique genetic profile, with mutations in genes like SETD2, ATM, and MGA that impair DNA damage sensing and repair, and lead to chemotherapy resistance and poor outcomes. We also found that these tumors have a unique microenvironment with inflammatory cells and cancer cells that display a senescence associated secretory phenotype (SASP). This phenotype promotes immune evasion and tumor progression. By targeting the SASP with drugs, we may be able to improve immune response and boost the effectiveness of existing therapies, such as standard chemoimmunotherapy (i.e., RCHOP) and novel immunotherapy approaches.

In Project 1 we aim to

1. Identify the mechanisms driving the SASP phenotype in AA-DLBCLs
2. Uncover how the lymphoma microenvironment of these tumors promotes immune evasion
3. Determine the effect of anti-SASP drugs on enhancing immunotherapy and standard-of-care chemotherapy and preventing relapse of AA-DLBCLs

The overall translational impact of this project includes:

1. Identifying a new subtype of DLBCL that is common in patients of African ancestry, defined by unique mutations ( e.g. SETD2, ATM, MGA) and a tumor microenvironment that promotes immune evasion
2. Providing the first description of SASP in DLBCL, a reversible, AICDA-driven process with unique features in AA DLBCL that enable immune evasion
3.  Uncovering immune mechanisms involving SASP-driven recruitment and exhaustion of CD4+ T cells influenced by cytokines such as IL-6, IL-10, and IL-20
4. Advancing precision therapies by developing novel biomarkers that reveal therapeutic vulnerabilities in AA DLBCL and creating the first SASP-targeted treatments. We also aim to translate the first SETD2 inhibitor into clinical use, informed by the specific SASP characteristics observed in AA DLBCL

Project 2: Translating Genomics to Practice to Improve Outcomes in Diffuse Large B-Cell Lymphoma (DLBCL) 

Patients with diffuse large B-cell lymphoma (DLBCL) experience widely variable outcomes. Although some patients are cured with initial therapy, about 40% see their cancer return and have a poor outlook. Investigation of biologic factors contributing to differences in outcomes have been hindered by limited representation of some groups even in the largest research studies and clinical trials. Our research team is uniquely equipped to address this challenge, given our access to

1. Large collaborative biorepositories that include patient samples and data from groups that reflect the composition of the U.S. population, and
2. Clinical trial networks that involve community cancer clinics where many patients receive care

In this project we will analyze genetic data from DLBCL patients to test whether current prediction tools work well for all patients with DLBCL. We will also expand our collection of patient-derived mouse tumor models, to better understand how DLBCL develops and responds to treatment across different patient groups with ancestry-related biologic characteristics. Finally, we will evaluate evidence-based strategies to promote enrollment to a DLBCL clinical trial that incorporates genetic information into selection of frontline chemoimmunotherapy regimen conducted in community practices.

By incorporating a cells-to-society approach, Project 2 will

1. Define specific molecular and immune features of DLBCLs and their microenvironment across populations
2. Directly test their therapeutic vulnerabilities using innovative, ancestry-specific model systems
3. Deploy diagnostic and treatment workflows geared for community practices

The overall translational impact of this project includes:

1. Developing the first genomic classification of DLBCL that takes ancestry into account: this will be the first study to define the prognostic impact of specific molecular and lymphoma microenvironment features of DLBCL in poor-risk populations
2. Developing the first in vivo model systems that address unique ancestry subtypes to test targeted therapies
3. Deploying the first clinical trial to assess how frontline treatment strategies informed by molecular pathology testing (RNA/DNA sequencing) affect outcomes of DLBCL patients in community settings

Project 3: AI Digital Pathology Tools to Improve Lymphoma Diagnosis and Classification 

Patients who receive a pathologic diagnosis of lymphoma at a community-based practice have been reported to be misdiagnosed 20% of the time, often with treatment-changing implications. Digitizing glass slides into whole-slide images (WSIs) allows diagnostic materials to be rapidly transmitted anywhere for consultation. However, electronic transmission of WSIs does not completely solve the problem. There are delays with consultations and the number of trained pathologists is decreasing, making it harder to keep up with demand.

Pathology is one of the most promising areas for artificial intelligence (AI) in medicine. AI tools have been developed for diagnostic, prognostic, and predictive classifications, primarily for use in solid tumors. However, hematopathology applications, particularly those for lymphomas, have not received as much attention due to a paucity of WSI datasets with clinical annotation, the complexity of diagnostic systems, and their reliance on extensive immunohistochemical staining. AI models that predict biomarkers from WSI of hematoxylin and eosin (H&E)-stained slides can provide an inexpensive screen to rule out or replace molecular testing for biomarkers, but developing clinical-grade models requires large datasets with high-quality clinical annotations for thousands of cases.

Our research team is uniquely equipped to address these challenges, given our expertise in digital pathology and AI tool development, experience integrating community and academic hematopathology practice, and access to the Lymphoma Epidemiology of Outcomes (LEO) cohorts. We will use LEO to develop and validate a diagnostic lymphoma classifier that provides highly accurate diagnosis from WSI of a simple H&E stain that can be performed in any pathology lab. We will also investigate how integrating data from novel spatial transcriptomic and multiplex imaging platforms with WSI can create more powerful H&E-based models to predict prognostic biomarkers of the microenvironment. These models will be built specifically to meet the needs of community-based practices.

In Project 3 we aim to:

• Develop a classifier for differential diagnosis of lymphomas that is optimized for use in community healthcare practices to improve lymphoma diagnosis
• Investigate the ability of AI models to identify microenvironmental biomarkers from H&E WSIs

The overall translational impact of this project includes:

1. Conducting the largest computational pathology study of lymphoma diagnosis with validation in patient populations historically less represented in prior research and those receiving care in community-based settings
2. Creating a pathology AI tool designed to meet the specific needs of patients and doctors working in community-based practices
3. Enhancing the value of H&E WSI through coordinated training with spatially resolved transcriptomic data