Jo Lynne Rokita

This study identifies miRNA programs in pediatric brain tumors linked to immune states and CAR T-cell therapy responses, highlighting miR-149 as a potential regulator.

MOSAIC learns graph node embeddings by analyzing dominant spectral components of diffusion operators, outperforming existing methods in biomedical graph tasks.

The paper identifies specific HLA class I and II alleles associated with increased risk of certain tumor types in NF1 patients using RNA-seq and DNA sequencing data.

The paper analyzes splicing in 729 pediatric brain tumors, identifies splicing-defined subgroups, and highlights CLK1 exon 4 as an oncofetal event linked to tumor prognosis.

The paper identifies a NRCAM proteoform with skipped microexons as a targetable surface antigen in pHGG and demonstrates its utility in immunotherapy.

The paper introduces OpenPedCan, a harmonized multi-omic dataset of pediatric cancer patients, providing integrated genomic, transcriptomic, and proteomic data for research and clinical applications.

This study identifies DLK1 as a potential immunotherapeutic target in neuroblastoma through integrative proteomic, transcriptomic, and epigenomic analysis.

AutoGVP classifies germline variants using ClinVar and modified InterVar criteria, enabling large-scale variant pathogenicity assessment in research.

This study identifies BARD1 germline variants associated with reduced BARD1 expression and DNA repair defects in neuroblastoma, showing haploinsufficiency and increased genomic instability.

OpenPBTA provides a collaborative platform to genomically characterize 1,074 pediatric brain tumors and 22 cell lines, offering analysis modules and somatic datasets for research and clinical applications.

annoFuse filters and prioritizes oncogenic gene fusions from RNA-Seq data, improving identification of clinically relevant fusions in cancer datasets.

The paper provides ChIP-Seq and ATAC-Seq data for MYCN, MYC, and histone marks in neuroblastoma cell lines to study gene regulation and enhancer dynamics.

This paper genomically characterizes 261 pediatric cancer patient-derived xenograft models to guide rational clinical trial design and drug development.