With the remarkable improvement in cure rates of childhood cancer over the last several decades, over 80% of
children in the U.S. with cancer today become long-term (5+ years) survivors. This growing population of
survivors, currently over 400,000 nationwide, reflects a highly vulnerable group of individuals with a high
probability of experiencing adverse health-related and quality-of-life outcomes. To provide proper care for this
population and inform the design of future treatment regimens, it is imperative to gain sound understanding of
their long-term morbidity/mortality associated with specific therapeutic exposures, genetic profiles, sex and
other demographic characteristics, and co-morbid medical conditions. Growing body of published literature
exists addressing specific adverse outcomes and their associations with specific therapeutic exposures. While
these association studies have provided key evidence utilized to develop follow-up care guidelines such as
those of Children's Oncology Group, recognizing “associations” (differences) is not sufficient for provision of
individually-tailored follow-up care. Ability to “predict” (prognose) is required to expand the impact of
survivorship-based research and allow translation of observational research toward individualized-precision
survivorship care. Capitalizing on existing strengths of the well-established and highly productive survivorship-
based research program at St. Jude Children's Research Hospital, with currently available late effects
outcomes data from direct clinical assessments and whole genome sequencing of germline DNA, the
proposed project will apply state-of-the-art methods to construct and independently validate outcome-specific
prediction models, based on a phenotype pathway/modeling framework for each outcome, incorporating
genetic predictors with laboratory-based functional validation. We will undertake an aggressive program of
survivorship focused research to address NCI's Provocative Question PPQ-7: How can prediction models be
developed and used to identify patients at highest risk of treatment-related complications? By not restricting the
proposed research to a small number of late effects outcomes or a specific diagnosis of childhood cancer, our
aims are ambitiously set to extensively contribute to and meaningfully impact clinical practice. Our specific
aims are to: (1) build individual-risk prediction models that have clinically-appropriate degrees of precision, for
the following 11 late effects outcomes: meningioma; basal cell carcinoma; multiple subsequent neoplasms;
cardiomyopathy; obstructive lung disease; restrictive lung disease; diabetes mellitus; oligo/azoospermia;
primary hypogonadism; memory deficit; and executive function deficit; (2) validate them with independent
validation cohorts; and (3) functionally/biologically validate the genetic elements in the risk prediction models.
Upon completion of (1)-(3), we extend the model building, validation, and functional/biological validation work
to 9 additional late effects: stroke; arrhythmia; growth hormone deficiency; hypothyroidism; central
hypogonadism; processing speed deficits; attention deficits; hearing loss; and bone mineral density deficits.
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