Thursday, January 2, 2025 1/2/2025

Modeling Dynamic Immune Cell Modulation in a 3-D Tissue Engineered Platform to Enhance Patient-specific Immunotherapy for Lung Cancer

Award Number: R21CA263365
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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PROJECT SUMMARY/ABSTRACT Immune suppression and resistance to immune checkpoint inhibitors (ICI) are major obstacles for successful immunotherapy for non small cell lung cancer (NSCLC). In NSCLC, the density and diversity of tumor-infiltrating immune cells in the tumor microenvironment (TME) are closely related to prognosis, prediction of treatment efficacy of frontline combination therapies with ICI and favorable survival. The patient heterogeneity in the immune cell composition within the TME indicates that mapping the composition of immune infiltrates and their functional state within the TME is important for diagnosing and designing treatment strategies and for predicting biomarkers. The central objective of this project is to utilize our novel three dimensional human tissue model (3D-LTB) that recapitulates tissue dimensionality and microenvironment of human lung tumors to test the hypothesis that modulation of tumor-stromal crosstalk and sphingolipid signaling pathways that influence infiltration of immune suppressive myeloid-derived suppressor cells (MDSCs) in the lung TME alters the spatial dynamics of resident and recruited effector cells to enhance response to immune targeted therapies for NSCLC. In Aim1, patient-derived tumors and cutting edge GeoMx Digital Spatial Profiling platform will be utilized to define the dynamics and spatial profiles of effector T cells within the 3D-LTBs in response to immunotherapy. Studies in Aim 2 will determine if pharmacological targeting of sphingolipid rheostat alters tumor-stromal crosstalk and enhances response to immunotherapy using the same platform described in Aim 1. To our knowledge, this is the first fully developed 3D model of NSCLC that fully recapitulate lung cancer-immune interactions. Our studies have the power to define patient heterogeneity and identify spatially informed biomarkers in response to ICI in NSCLC. This optimized model system mimics extrapolatable growth characteristics and molecular signatures of resistance mechanisms in the human disease.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = -$3,018 )
2025	2023	UNIVERSITY OF ALABAMA AT BIRMINGHAM	701 S 20TH STREET	BIRMINGHAM	AL	35294	JEFFERSON	USA	Cancer Treatment Research	000	2	10/17/2024	NON-COMPETING CONTINUATION	-$3,018
														Subtotal = -$3,018

Issue Date FY: 2023 ( Subtotal = $170,089 )
2023	2023	UNIVERSITY OF ALABAMA AT BIRMINGHAM	701 S 20TH ST	BIRMINGHAM	AL	35294	JEFFERSON	USA	Cancer Treatment Research	000	2	6/7/2023	NON-COMPETING CONTINUATION	$170,089
														Subtotal = $170,089

Issue Date FY: 2022 ( Subtotal = $208,271 )
2022	2022	UNIVERSITY OF ALABAMA AT BIRMINGHAM	701 S 20TH ST	BIRMINGHAM	AL	35294	JEFFERSON	USA	Cancer Treatment Research	000	1	7/27/2022	NEW	$208,271
														Subtotal = $208,271

Grand Total All Awards = $375,342

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Modeling Dynamic Immune Cell Modulation in a 3-D Tissue Engineered Platform to Enhance Patient-specific Immunotherapy for Lung Cancer

Award Number: R21CA263365

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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