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Daniel A. King

Donald & Barbara Zucker School of Medicine at Hofstra/Northwell

ORCID: 0000-0001-6451-712X

Publishes on Pancreatic and Hepatic Oncology Research, Cancer Genomics and Diagnostics, Genomics and Rare Diseases. 176 papers and 4.8k citations.

176Publications
4.8kTotal Citations

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Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data
Cited by 789Open Access

BACKGROUND: Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. METHODS: The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. FINDINGS: Around 80,000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. INTERPRETATION: Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene-phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. FUNDING: Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health.

Immunotherapy and Targeted Therapy for Advanced Gastroesophageal Cancer: ASCO Guideline
Manish A. Shah, Erin B. Kennedy, Ashley E. Alarcon-Rozas et al.|Journal of Clinical Oncology|2023
Cited by 199Open Access

PURPOSE: To develop recommendations involving targeted therapies for patients with advanced gastroesophageal cancer. METHODS: The American Society of Clinical Oncology convened an Expert Panel to conduct a systematic review of relevant studies and develop recommendations for clinical practice. RESULTS: Eighteen randomized controlled trials met the inclusion criteria for the systematic review. RECOMMENDATIONS: For human epidermal growth factor receptor 2 (HER2)-negative patients with gastric adenocarcinoma (AC) and programmed death-ligand 1 (PD-L1) combined positive score (CPS) ≥ 5, first-line therapy with nivolumab and chemotherapy (CT) is recommended. For HER2-negative patients with esophageal or gastroesophageal junction (GEJ) AC and PD-L1 CPS ≥ 5, first-line therapy with nivolumab and CT is recommended. First-line therapy with pembrolizumab and CT is recommended for HER2-negative patients with esophageal or GEJ AC and PD-L1 CPS ≥ 10. For patients with esophageal squamous cell carcinoma and PD-L1 tumor proportion score ≥ 1%, nivolumab plus CT, or nivolumab plus ipilimumab is recommended; for patients with esophageal squamous cell carcinoma and PD-L1 CPS ≥ 10, pembrolizumab plus CT is recommended. For patients with HER2-positive gastric or GEJ previously untreated, unresectable or metastatic AC, trastuzumab plus pembrolizumab is recommended, in combination with CT. For patients with advanced gastroesophageal or GEJ AC whose disease has progressed after first-line therapy, ramucirumab plus paclitaxel is recommended. For HER2-positive patients with gastric or GEJ AC who have progressed after first-line therapy, trastuzumab deruxtecan is recommended. In all cases, participation in a clinical trial is recommended as it is the panel's expectation that targeted treatment options for gastroesophageal cancer will continue to evolve.Additional information is available at www.asco.org/gastrointestinal-cancer-guidelines.

Pan-UK Biobank GWAS improves discovery, analysis of genetic architecture, and resolution into ancestry-enriched effects
Cited by 171Open Access

Summary Large biobanks, such as the UK Biobank (UKB), enable massive phenome by genome-wide association studies that elucidate genetic etiology of complex traits. However, individuals from diverse genetic ancestry groups are often excluded from association analyses due to concerns about population structure introducing false positive associations. Here, we generate mixed model associations and meta-analyses across genetic ancestry groups, inclusive of a larger fraction of the UKB than previous efforts, to produce freely-available summary statistics for 7,266 traits. We build a quality control and analysis framework informed by genetic architecture. Overall, we identify 14,676 significant loci (p < 5 x 10 -8 ) in the meta-analysis that were not found in the EUR genetic ancestry group alone, including novel associations for example between CAMK2D and triglycerides. We also highlight associations from ancestry-enriched variation, including a known pleiotropic missense variant in G6PD associated with several biomarker traits. We release these results publicly alongside FAQs that describe caveats for interpretation of results, enhancing available resources for interpretation of risk variants across diverse populations.