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Development of machine learning software to quantitatively map telomere induced senescence in tissue sections during aging

Award Number: UH3CA268103
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: COOPERATIVE AGREEMENT
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/21/2021
PERIOD OF PERFORMANCE END DATE: 07/31/2026

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Development of machine learning software to quantitatively map telomere induced senescence in tissue sections during aging - PROJECT SUMMARY/ABSTRACT Cellular senescence is a pillar of aging, acting as a key driver of aging and age-related diseases. Telomeres play a major role in cellular senescence. When telomeres become critically short or damaged, they elicit a DNA damage response (DDR) that drives senescence. Our laboratory developed sophisticated methods to detect senescent cells in tissues based on the co-localization between telomeres and the DDR. Furthermore, we recently developed SenoQuant, a software that simplifies the measure of Telomere associated foci (TAF), reducing quantification time from weeks to hours. We now propose to apply emerging technologies such as machine learning and deep learning to map TAF more accurately and robustly in human tissue sections. This will address several challenges inherent to TAF analysis, including nuclei detection, staining artifacts, and quantification time. Furthermore, in collaboration with the Tissue Mapping Centers we will tailor SenoQuant to the analysis of specific human tissues. Finally, we propose to integrate TAF with multiplexed imaging methods such as Imaging Mass Cytometry (IMC), allowing the detection of multiple senescence markers in tissues simultaneously. We anticipate that this technology will greatly advance the spatially-resolved mapping of senescent cells in human tissues and will be a great resource for the aging and cell senescence community.


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 = $200,000 )
2025	2025	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Trans-NIH Research Support	001	4	9/3/2025	SUPPLEMENT FOR EXPANSION	$200,000
2025	2024	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Trans-NIH Research Support	002	4	9/23/2025	NON-COMPETING CONTINUATION	$0
2025	2024	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Trans-NIH Research Support	000	4	7/11/2025	NON-COMPETING CONTINUATION	$0
														Subtotal = $200,000

Issue Date FY: 2024 ( Subtotal = $722,010 )
2024	2024	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Trans-NIH Research Support	001	4	9/6/2024	NON-COMPETING CONTINUATION	$722,010
2024	2023	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Trans-NIH Research Support	000	3	3/20/2024	EXTENSION WITH OR WITHOUT FUNDS	$0
														Subtotal = $722,010

Issue Date FY: 2023 ( Subtotal = $722,010 )
2023	2023	MAYO CLINIC	200 1ST ST SW	ROCHESTER	MN	55905	OLMSTED	USA	Trans-NIH Research Support	000	3	9/1/2023	EXTENSION WITH OR WITHOUT FUNDS	$722,010
														Subtotal = $722,010

Grand Total All Awards = $1,644,020

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Development of machine learning software to quantitatively map telomere induced senescence in tissue sections during aging

Award Number: UH3CA268103

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: COOPERATIVE AGREEMENT

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

PERIOD OF PERFORMANCE START DATE: 09/21/2021

PERIOD OF PERFORMANCE END DATE: 07/31/2026

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