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Outcomes in AYA survivors of pediatric medulloblastoma.

小儿髓母细胞瘤 AYA 幸存者的结果。

基本信息

批准号：
10459011
负责人：
TRICIA Z KING
金额：
$ 51.24万
依托单位：
GEORGIA STATE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-05 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10459011
关键词：
Accounting Adaptive Behaviors Adolescent and Young Adult Age Algorithms Area Brain Neoplasms Caregivers Caring Cerebellum Characteristics Childhood Childhood Brain Neoplasm Childhood Medulloblastomas Clinical Clinical Markers Clinical Research Cognitive Collaborations DNA Sequence Alteration DNA sequencing Development Disease susceptibility Dose Drug Design Early identification Environmental Risk Factor Epigenetic Process Ethnic Origin Genes Genetic Genetic Markers Genetic Predisposition to Disease Genetic Transcription Genotype Health Heterogeneity Impaired cognition Individual Individual Differences Infrastructure Intervention Late Effects Literature Machine Learning Malignant Neoplasms Measures Methods Modeling Molecular Molecular Genetics Morbidity - disease rate Mutation NCI-Designated Cancer Center Neighborhoods Neuronal Plasticity Outcome Outcome Measure Oxidative Stress Pathway interactions Patient-Focused Outcomes Population Precision Medicine Initiative Prevention Proteins Quality of life RNA analysis Race Readiness Recording of previous events Regimen Research Research Design Resources Risk Risk Factors SHH gene Schools Severities Single Nucleotide Polymorphism Site Surveillance Modeling Survivors Tumor Subtype Variant Weight analysis pipeline base biopsychosocial caregiving chemoradiation childhood cancer survivor clinical risk clinically relevant cognitive ability cohort deprivation design disability experience family caregiving folic acid metabolism genetic variant health related quality of life high risk high standard improved indexing individualized medicine innovation interest medulloblastoma molecular subtypes neuroinflammation neurotoxic neurotransmission outcome prediction peer precision medicine preemptive intervention prevent preventive intervention prophylactic recruit repaired sex socioeconomic adversity standardize measure survivorship tool transcriptome sequencing treatment response tumor

项目摘要

Abstract This clinical research identifies the robust factors that contribute to cognitive outcomes in pediatric, adolescent, and young adult survivors (PAYAS) of medulloblastoma (MB) brain tumors located in the cerebellum. Pediatric brain tumor survivors are at increased risk of cognitive impairment (CI) and have substantial likelihood of poor health and disability relative to those who do not have a cancer history, and relative to survivors who did not have to undergo lifesaving neurotoxic chemoradiation treatment. However, individual differences in cognitive outcomes among PAYAS of MB are diverse and wide ranging, even when the most likely clinical contributors are the same (i.e., age at treatment, chemoradiation level of risk, MB tumor subtype). This led our team to examine genetic diatheses and other contributors that may explain the wide range of outcomes, from mild to severe CI. In addition to genetics, there is a need to fill important gaps in the research to date to identify both clinical risk factors and environmental resources that identify those at greatest risk of CI. This multisite project at NCI-designated cancer centers in GA, AL, and OH will examine multifactorial environmental resources (e.g., neighborhood socioeconomic adversity, material hardships, caregiving capacity, and school quality), clinical factors (e.g., age at treatment, chemoradiation level of risk, MB tumor type), and individual genetic diathesis (i.e., candidate single nucleotide polymorphism variants (SNPs)). First, in Aim 1, the study will examine each of the three domains independently using state of the art methods and innovative analyses to identify the best predictors of CI. In other populations, polygenetic risk scores (PRS) have provided a stronger prediction of outcomes than single SNPs alone. Therefore, within the genetic diathesis domain, we will examine targeted SNPs and neighboring interactive mutations to create a robust PRS utilizing machine learning tools that weights SNPs regulating RNA expression associated with CI, and incorporates known functional impact of epigenetics, transcriptions and proteins. Second, in Aim 2, we will create a multi-domain risk algorithm, using the most sensitive predictors of CI across the three domains (i.e., clinical risks, environmental resources, and genetic diathesis). This empirically derived risk algorithm will inform precision medicine, by identifying conditions for risk-adapted chemoradiation treatment and prophylactic interventions to prevent, mitigate and manage CI. Consistent with the STAR Act of 2018 and the Precision Medicine Initiative, these findings will allow for early identification of individuals at risk for CI and provide targets for treatments in order to improve overall quality of life and adaptive functioning in PAYAS of childhood cancer.

摘要