U01CA294514
Cooperative Agreement
Overview
Grant Description
Center for Human Lymphoma Spatiotemporal Atlas (HULYMSTA) - Summary
Non-Hodgkin lymphomas (NHL) represent about 90% of all lymphomas diagnosed each year and is classified based on cell type - B cell, T cell and natural killer (NK) cell types, location - nodal or extra nodal, and the tumor grade - aggressive (high grade) and indolent (low grade).
Follicular lymphoma (FL) is the most common indolent B-cell lymphoma but remains a largely incurable malignancy.
The most clinically challenging aspect of FL is the transformation into diffuse large B-cell lymphomas (DLBCL), characterized by the emergence of more aggressive subclones, loss of the follicular growth spatial architecture, and resistance to treatment, leading to a much-shortened survival period, typically less than 2 years.
Among T-cell lymphomas, angioimmunoblastic T-cell lymphoma (AITL) is one of the most common subtypes characterized by a tumor with follicular helper phenotype surrounded by an inflammatory microenvironment, arborizing vasculature, and progression with dramatic changes in spatial architecture.
Although the discovery of FL transformation and AITL tumor evolution was initially documented over 50 years ago, the biological mechanisms and clinical implications remain poorly understood.
No biomarkers exist to predict or therapies to prevent its metastases or progression to highly aggressive lymphomas.
Both of these tumors hijack normal follicle biology to escape immune surveillance and potentially develop resistance clones.
Yale HTAN Center aims to leverage the latest development in single-cell and spatial omics technologies to construct a spatiotemporal atlas of human FL transformation to DLBCL and AITL evolution.
Specifically, we will apply high-plex immunofluorescence protein imaging to map all major cell types and spatial whole transcriptome sequencing to link cell type to mutational landscape, clonal evolution, and spatial interaction within the tumor microenvironment.
We will further integrate spatial omics data with single nucleus RNA sequencing to identify cell subtypes and niches across tissue samples over various disease stages to construct a complete cell atlas associated with tumor transformation for different genders and racial/ethnic groups and then computationally model the spatiotemporal evolutionary dynamics.
Finally, we will apply and integrate spatial-epigenome-transcriptome co-profiling to unveil epigenetic mechanisms underlying such transformation and potentially discover earliest events to predict the progression.
The proposed spatiotemporal lymphoma atlas represents a valuable resource to test a range of hypotheses such as how different tumor clones emerge, interact, compete or cooperate in the spatial tissue context to drive lymphomagenesis, how T cells recognize and interact with different mutant clones, how the microenvironment co-evolves with tumor cells, and how to predict the likelihood of transformation and therapeutic stratification of patients.
Single-cell spatial omics techniques and computational models can be applied to other types of human tumors within the HTAN consortium.
Non-Hodgkin lymphomas (NHL) represent about 90% of all lymphomas diagnosed each year and is classified based on cell type - B cell, T cell and natural killer (NK) cell types, location - nodal or extra nodal, and the tumor grade - aggressive (high grade) and indolent (low grade).
Follicular lymphoma (FL) is the most common indolent B-cell lymphoma but remains a largely incurable malignancy.
The most clinically challenging aspect of FL is the transformation into diffuse large B-cell lymphomas (DLBCL), characterized by the emergence of more aggressive subclones, loss of the follicular growth spatial architecture, and resistance to treatment, leading to a much-shortened survival period, typically less than 2 years.
Among T-cell lymphomas, angioimmunoblastic T-cell lymphoma (AITL) is one of the most common subtypes characterized by a tumor with follicular helper phenotype surrounded by an inflammatory microenvironment, arborizing vasculature, and progression with dramatic changes in spatial architecture.
Although the discovery of FL transformation and AITL tumor evolution was initially documented over 50 years ago, the biological mechanisms and clinical implications remain poorly understood.
No biomarkers exist to predict or therapies to prevent its metastases or progression to highly aggressive lymphomas.
Both of these tumors hijack normal follicle biology to escape immune surveillance and potentially develop resistance clones.
Yale HTAN Center aims to leverage the latest development in single-cell and spatial omics technologies to construct a spatiotemporal atlas of human FL transformation to DLBCL and AITL evolution.
Specifically, we will apply high-plex immunofluorescence protein imaging to map all major cell types and spatial whole transcriptome sequencing to link cell type to mutational landscape, clonal evolution, and spatial interaction within the tumor microenvironment.
We will further integrate spatial omics data with single nucleus RNA sequencing to identify cell subtypes and niches across tissue samples over various disease stages to construct a complete cell atlas associated with tumor transformation for different genders and racial/ethnic groups and then computationally model the spatiotemporal evolutionary dynamics.
Finally, we will apply and integrate spatial-epigenome-transcriptome co-profiling to unveil epigenetic mechanisms underlying such transformation and potentially discover earliest events to predict the progression.
The proposed spatiotemporal lymphoma atlas represents a valuable resource to test a range of hypotheses such as how different tumor clones emerge, interact, compete or cooperate in the spatial tissue context to drive lymphomagenesis, how T cells recognize and interact with different mutant clones, how the microenvironment co-evolves with tumor cells, and how to predict the likelihood of transformation and therapeutic stratification of patients.
Single-cell spatial omics techniques and computational models can be applied to other types of human tumors within the HTAN consortium.
Awardee
Funding Goals
TO PROVIDE SUPPORT FOR INITIATIVES FUNDED UNDER THE 21ST CENTURY CURES ACT TO SUPPORT CANCER RESEARCH, SUCH AS THE DEVELOPMENT OF CANCER VACCINES, THE DEVELOPMENT OF MORE SENSITIVE DIAGNOSTIC TESTS FOR CANCER, IMMUNOTHERAPY AND THE DEVELOPMENT OF COMBINATION THERAPIES, AND RESEARCH THAT HAS THE POTENTIAL TO TRANSFORM THE SCIENTIFIC FIELD, THAT HAS INHERENTLY HIGHER RISK, AND THAT SEEKS TO ADDRESS MAJOR CHALLENGES RELATED TO CANCER.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
New Haven,
Connecticut
065118959
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 404% from $1,018,682 to $5,130,804.
Yale Univ was awarded
Transformative Spatiotemporal Atlas for Lymphoma Evolution
Cooperative Agreement U01CA294514
worth $5,130,804
from National Cancer Institute in September 2024 with work to be completed primarily in New Haven Connecticut United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.353 21st Century Cures Act - Beau Biden Cancer Moonshot.
The Cooperative Agreement was awarded through grant opportunity Human Tumor Atlas (HTA) Research Centers (U01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 9/26/25
Period of Performance
9/1/24
Start Date
8/31/29
End Date
Funding Split
$5.1M
Federal Obligation
$0.0
Non-Federal Obligation
$5.1M
Total Obligated
Activity Timeline
Transaction History
Modifications to U01CA294514
Additional Detail
Award ID FAIN
U01CA294514
SAI Number
U01CA294514-3883485404
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75NC00 NIH National Cancer Institute
Funding Office
75NC00 NIH National Cancer Institute
Awardee UEI
FL6GV84CKN57
Awardee CAGE
4B992
Performance District
CT-03
Senators
Richard Blumenthal
Christopher Murphy
Christopher Murphy
Modified: 9/26/25