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Artificial intelligence enhanced cancer cell classification based organelle morphology and topology

Award Number: R21CA274622
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/01/2022
PERIOD OF PERFORMANCE END DATE: 08/31/2025

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Artificial intelligence enhanced cancer cell classification based organelle morphology and topology - ABSTRACT Breast cancer is a highly heterogenous disease, both phenotypically and genetically. The quantity and subcellular location of cancer protein biomarkers are used to classify breast cancer types. Transcriptomics, multiplexed imaging, or mass cytometry have been used to classify breast tumor cell heterogeneity with varying success. Although genomics and proteomics have been successful in the identification of tumor cell populations involved in metastatic progression, the ability to determine whether patient tumors contain metastatic subpopulations is still lacking. Recently, organelle morphology and function has been used as a direct readout of the functional phenotypic state of an individual cancer cell. We propose to use the spatial context of organelles, specifically their subcellular location and inter-organelle relationships (topology), to classify novel and distinct metastatic cancer cell subpopulations. We developed an Organelle Topology-based Cell Classification Pipeline (OTCCP) to quantify, for the first time, the topological features of subcellular organelles, defined as the distance between each organelle object and all its neighbors within a cell. Under RFA-CA-21-013 (Development of Innovative Informatics Methods and Algorithms for Cancer Research and Management), we will adapt or develop Machine learning and Deep Learning methodologies to accelerate and automate OTCCP-based organelle- based topology cancer cell classification to identify subpopulations of metastatic cells within heterogeneous primary tumors with potential diagnostic and prognostic value. This approach will also have major impact as a discovery tool to advance our understanding of cancer cell biology on a subcellular level.


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 = -$898 )
2026	2023	ALBANY MEDICAL COLLEGE	47 NEW SCOTLAND AVE # A34	ALBANY	NY	12208	ALBANY	USA	Cancer Biology Research	000	2	1/6/2026	NON-COMPETING CONTINUATION	-$898
														Subtotal = -$898

Issue Date FY: 2023 ( Subtotal = $269,712 )
2023	2023	ALBANY MEDICAL COLLEGE	47 NEW SCOTLAND AVE	ALBANY	NY	12208	ALBANY	USA	Cancer Biology Research	001	2	9/13/2023	SUPPLEMENT FOR EXPANSION	$81,500
2023	2023	ALBANY MEDICAL COLLEGE	47 NEW SCOTLAND AVE	ALBANY	NY	12208	ALBANY	USA	Cancer Biology Research	000	2	8/31/2023	NON-COMPETING CONTINUATION	$188,212
														Subtotal = $269,712

Issue Date FY: 2022 ( Subtotal = $230,154 )
2022	2022	ALBANY MEDICAL COLLEGE	47 NEW SCOTLAND AVE	ALBANY	NY	12208	ALBANY	USA	Cancer Biology Research	000	1	9/1/2022	NEW	$230,154
														Subtotal = $230,154

Grand Total All Awards = $498,968

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Artificial intelligence enhanced cancer cell classification based organelle morphology and topology

Award Number: R21CA274622

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 09/01/2022

PERIOD OF PERFORMANCE END DATE: 08/31/2025

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