An Approach to Solving the Complex Clinicogenomic Data Landscape in Precision Oncology: Learnings From the Design of WAYFIND-R, a Global Precision Oncology Registry.

Precision oncology, where patients are given therapies based on their genomic profile and disease trajectory, is rapidly evolving to become a pivotal part of cancer management, supported by regulatory approvals of biomarker-matched targeted therapies and cancer immunotherapies. However, next-generation sequencing (NGS)-based technologies have revealed an increasing number of molecular-based cancer subtypes with rare patient populations, leading to difficulties in executing/recruiting for traditional clinical trials. Therefore, approval of novel therapeutics based on traditional interventional studies may be difficult and time consuming, with delayed access to innovative therapies.

Gene-environment interactions and the complexity of human genetic diseases.

In the assessment of mortality and morbidity risk, the ability of family history and genetic test results to predict the age of occurrence, severity, and long-term prognosis of 'genetic' diseases is important. An increasing number of gene-gene and gene-environment interactions have been demonstrated in a number of monogenic Mendelian diseases. These interactions can significantly modify the clinical presentation (disease phenotype) of diseases previously regarded purely as 'genetic.

Promoter choice determines splice site selection in protocadherin alpha and gamma pre-mRNA splicing.

A family of mammalian protocadherin (Pcdh) proteins is encoded by three closely linked gene clusters (alpha, beta, and gamma). Multiple alpha and gamma Pcdh mRNAs are expressed in distinct patterns in the nervous system and are generated by alternative pre-mRNA splicing between different "variable" exons and three "constant" exons within each cluster. We show that each Pcdh variable exon is preceded by a promoter and that promoter choice determines which variable exon is included in a Pcdh mRNA.