Riaz Gillani

The paper identifies clustered structural variant hotspots in osteosarcoma, linking them to oncogenic addiction and plasticity through transcriptional changes and clinical detectability.

This study identifies conserved neuronal-like and secretory programs in GEP-NETs and links them to spatial microenvironmental niches and metastatic potential.

This paper shows that Ewing sarcoma cells have reduced POLθ expression and MMEJ activity due to EWS-FLI1 or EWSR1 disruption, making them sensitive to inhibitors of FA, NHEJ, or HR pathways.

This study identifies a loss of osteoblastic lineage fidelity in metastatic osteosarcoma through single-nucleus RNA sequencing, linking it to disease progression and potential therapeutic targets.

The paper identifies polygenic risk factors and rare variants in unexplained familial cancers using whole genome sequencing and family history data.

This study identifies rare germline structural variants as risk factors for pediatric solid tumors, particularly neuroblastoma, by analyzing genome sequencing data from affected children and controls.

This study analyzes structural variants in melanoma subtypes, identifying distinct genomic properties and molecular drivers that may inform therapeutic strategies.

This study identifies germline rare variants associated with clear and non-clear cell RCC, accounting for population stratification, and finds distinct risk patterns and somatic associations.

FusionInspector identifies and characterizes biologically relevant fusion transcripts from RNA-seq data in tumor and normal tissues using clustering and machine learning.

This study uses low-pass whole genome sequencing to impute variants and construct polygenic risk scores for breast cancer in an underrepresented Arab population, finding associations with family history and age of presentation.

This study identifies inherited pathogenic variants in DNA damage repair genes as a distinct germline risk factor for Ewing sarcoma, with FANCC showing significant enrichment.