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Integrating multi-modal label-free single cell technology to target radiation resistance in pediatric diffuse midline glioma

Award Number: K00CA294265
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/01/2024
PERIOD OF PERFORMANCE END DATE: 06/30/2030

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Integrating multi-modal label-free single cell technology to target radiation resistance in pediatric diffuse midline glioma - PROJECT SUMMARY Diffuse midline gliomas with the H3K27M mutation (DMG-H3K27M) are the leading cause of pediatric brain tumor-associated deaths. All DMG-H3K27M becomes resistant to radiation, the standard of care, and most children succumb to their disease within two years of diagnosis. A pool of radiation resistant cells (RRGCs) persist after radiation therapy and are the primary cause of poor prognosis. RRGCs vary genetically within a tumor and across patients limiting the efficacy of standard universal chemotherapies. There are 2 main reasons clinical progress has been slow; lack of an efficient RRGC targeted therapy and the difficulty of delivering drug past the blood brain barrier (BBB). New treatment solutions are urgently needed. Extracellular vesicles, subcellular lipid bilayer particles, represent a way to penetrate the BBB and selectively target tumor cells of interest. Traditional targeting of RRGCs based off antigens is difficult because of widespread intra and inter-tumor heterogeneity. Therefore, accurate identification based on a method that integrates molecular identifiers and iteratively learns whether cells are radiation resistant would improve upon current solutions. The overall objective of this project is to predict, identify, and target RRGCs by utilizing a microfluidic based approach to single cell characterization that integrates multi-layer molecular phenotypes into biophysical characteristics. The central hypothesis of the proposed research is that RRGCs have unique morphological and biophysical properties that are linked to differential radiation response and can be selectively targeted using engineered extracellular vesicles to promote radiosensitization. The rationale for my proposed research is that it will provide a novel method of RRGC identification and targeted EV therapy. The hypothesis will be tested by pursuing two specific aims: 1) Define biophysical and morphological signatures of radiation response with machine learning on single cells using a suspended microchannel resonator (SMR) platform and 2) Engineer extracellular vesicles to selectively target radiation resistant tumor cell states and promote radiosensitization. The first aim will involve building a brightfield and SMR platform that will be used to train a machine learning model and predict radiation response. The second aim will shift to targeting RRGCs based on chemical modifications of EVs loaded with a panel of common radiosensitizers. The research proposed in this application is significant because it will establish a targeted therapy that integrates multiple molecular phenotypes and can bypass the difficulty of developing a universal therapeutic strategy based off heterogenous genetic profiling.


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: 2026 ( Subtotal = $90,820 )
2026	2026	MASSACHUSETTS INSTITUTE OF TECHNOLOGY	77 MASSACHUSETTS AVE	CAMBRIDGE	MA	02139	MIDDLESEX	USA	Cancer Cause and Prevention Research	000	3	8/17/2026	EXTENSION WITH OR WITHOUT FUNDS	$90,820
														Subtotal = $90,820

Grand Total All Awards = $90,820

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Integrating multi-modal label-free single cell technology to target radiation resistance in pediatric diffuse midline glioma

Award Number: K00CA294265

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 09/01/2024

PERIOD OF PERFORMANCE END DATE: 06/30/2030

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