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Application of Gabriella Miller Kids First Pediatric Research Data to a Predictive Model of Neuroblastoma

Award Number: R03HD105079
ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

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Project Summary There is currently no diagnostic tool to accurately predict pediatric neuroblastoma disease outcome that is based on the mechanistic nature of the disease and genomic information of a child’s tumor. Neuroblastoma is a solid, cancerous tumor of the sympathetic nervous system (SNS) that accounts for half of all cancers in infants younger than 1 year. Uncertainties in the trajectory of disease progression has led to aggressive radiation and chemotherapy treatments that often result in long-term developmental disabilities for children. Determination of the critical drivers of neuroblastoma initiation and assessment of their interactions for an individual child would help target chemotherapy and limit over-treatment, possibly resulting in an increased quality of life and infant survival. Our solution to this problem is to develop a predictive artificial intelligence algorithm (PredictNeuroB) and use genomic input from a child’s tumor to test its predictive strengths to predict disease progression, identify critical disease drivers and compare results to current clinical statistical-based algorithms. PredictNeuroB is based on the network interactions of receptor tyrosine kinase (RTK) developmental signals and is supported by our discovery of a critical role for trkB and its ligand brain-derived neurotrophic factor (BDNF) during SNS development. Our published model’s prediction of early stage neuroblastoma (for infants 0-2yrs old) using genomic information of 77 children is more accurate than any current clinical prognostic (Kasemeier-Kulesa et al., 2018). In this study, we propose to strengthen the predictive capability of our model for a broader class of patient data (age, stage of disease, chromosome status, MYCN amplification) by applying Gabriella Miller Kids First neuroblastoma databases. Further, we will perform in silico perturbations of the algorithm to determine critical drivers capable of altering neuroblastoma outcome states. At the conclusion of our study, by using a larger set of patient-derived data with associated clinical and disease outcome information, we expect our PredictNeuroB model will prove highly predictive for a broad class of neuroblastoma patients and support clinical decision making in disease treatment and targeted drug therapies.


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: 2024 ( Subtotal = -$171,591 )
2024	2022	UNIVERSITY OF NOTRE DAME DU LAC	940 GRACE HALL	NOTRE DAME	IN	46556	ST JOSEPH	USA	Child Health and Human Development Extramural Research	001	3	7/15/2024	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$15,091
2024	2022	UNIVERSITY OF NOTRE DAME DU LAC	940 GRACE HALL	NOTRE DAME	IN	46556	ST JOSEPH	USA	Child Health and Human Development Extramural Research	002	3	8/27/2024	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	-$171,591
2024	2021	STOWERS INSTITUTE FOR MEDICAL RESEARCH	1000 E 50TH ST	KANSAS CITY	MO	64110	JACKSON	USA	Child Health and Human Development Extramural Research	000	1	7/15/2024	NEW	-$15,091
														Subtotal = -$171,591

Issue Date FY: 2023 ( Subtotal = -$8,500 )
2023	2022	UNIVERSITY OF NOTRE DAME DU LAC	940 GRACE HALL	NOTRE DAME	IN	46556	ST JOSEPH	USA	Child Health and Human Development Extramural Research	001	3	3/24/2023	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$156,500
2023	2022	STOWERS INSTITUTE FOR MEDICAL RESEARCH	1000 E 50TH ST	KANSAS CITY	MO	64110	JACKSON	USA	Child Health and Human Development Extramural Research	000	2	3/24/2023	NON-COMPETING CONTINUATION	-$165,000
														Subtotal = -$8,500

Issue Date FY: 2022 ( Subtotal = $165,000 )
2022	2022	STOWERS INSTITUTE FOR MEDICAL RESEARCH	1000 E 50TH	KANSAS CITY	MO	64110	JACKSON	USA	Child Health and Human Development Extramural Research	001	2	4/26/2022	NON-COMPETING CONTINUATION	$16,500
2022	2022	STOWERS INSTITUTE FOR MEDICAL RESEARCH	1000 E 50TH	KANSAS CITY	MO	64110	JACKSON	USA	Child Health and Human Development Extramural Research	000	2	4/7/2022	NON-COMPETING CONTINUATION	$148,500
														Subtotal = $165,000

Issue Date FY: 2021 ( Subtotal = $165,000 )
2021	2021	STOWERS INSTITUTE FOR MEDICAL RESEARCH	1000 E 50TH	KANSAS CITY	MO	64110	JACKSON	USA	Child Health and Human Development Extramural Research	000	1	3/16/2021	NEW	$165,000
														Subtotal = $165,000

Grand Total All Awards = $149,909

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Application of Gabriella Miller Kids First Pediatric Research Data to a Predictive Model of Neuroblastoma

Award Number: R03HD105079

ORGANIZATION: NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

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