Cancer Survivorship Community

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Apr 15, 2022

The Cancer Survivorship Community shares high quality genomic, clinical, and patient-reported data from survivors of pediatric cancer. To accelerate the rate of discovery in survivorship research we have developed this SJLIFE Survivorship Portal, a data-sharing platform for genomic and clinical data from the St. Jude Lifetime Cohort hosted on the St. Jude Cloud. The Portal features the Clinical Data Browser, GenomePaint, a genetic variant browser, for browsing, visualizing and analyzing clinical and genetic data integratively. Additionally, the Survivorship Portal will serve as a site for an expanding portfolio of risk-prediction tools developed using the SJLIFE cohort, including the recently developed Cumulative Burden Risk-Prediction Tool.

Reference: Epigenetic Age Acceleration and Chronic Health Conditions among Adult Survivors of Childhood Cancer. JNCI 2021

About the Data

The SJLIFE Study cohort was established in 2007 to address knowledge deficits about the health of 5-year survivors of cancer diagnosed during childhood and adolescence and treated at St. Jude Children Research Hospital. As part of the study, detailed demographic, diagnostic, and treatment are available for all participants.

Additional detailed follow-up and clinically assessed outcomes are available for all patients who completed an on campus visit. Whole-genome sequence (30x) has been completed on the initial 3006 participants and serve as the population available on the initial version of the St. Jude Survivorship Portal. Access the raw genomics data.

St. Jude Survivorship Portal

The portal enables interactive exploration of 1) Cancer-related variables such as diagnosis and treatment 2) Demographic variables, and 3) Outcomes, including severity-graded chronic health conditions using a modified version of the Common Terminology Classification for Adverse Events, and subsequent cancers.

Dictionary terms from these categories are arranged hierarchically from general to specific, allowing a user to traverse the dictionary tree and view patient distributions by user selected terms as customizable barcharts, or perform cross-tabulation between two terms.