Matthew H. Bailey
A5051591843- Cancer Genomics and Diagnostics
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Pancreatic and Hepatic Oncology Research
- Bioinformatics and Genomic Networks
- Epigenetics and DNA Methylation
- Pancreatitis Pathology and Treatment
- Pancreatic function and diabetes
- Ferroptosis and cancer prognosis
- RNA modifications and cancer
- Genetic Associations and Epidemiology
- Genetic factors in colorectal cancer
- RNA Research and Splicing
- Cancer-related molecular mechanisms research
- Genomics and Chromatin Dynamics
- Cancer Cells and Metastasis
- Lung Cancer Treatments and Mutations
- Cancer-related Molecular Pathways
- Cancer Immunotherapy and Biomarkers
- Genetics, Bioinformatics, and Biomedical Research
- Alzheimer's disease research and treatments
- Genomics and Phylogenetic Studies
- Single-cell and spatial transcriptomics
- Folate and B Vitamins Research
- Genomics and Rare Diseases
Brigham Young University
2011-2025
Center for Cancer Research
2022-2025
James S. McDonnell Foundation
2016-2023
University of Utah
2019-2022
Huntsman Cancer Institute
2019-2022
RELX Group (United States)
2021
Auburn University
2021
Washington University in St. Louis
2015-2020
Alvin J. Siteman Cancer Center
2020
Dana-Farber Cancer Institute
2018
Highlights•Alteration map of 10 signaling pathways across 9,125 samples from 33 cancer types•Reusable, curated pathway templates that include a catalogue driver genes•57% tumors have at least one potentially actionable alteration in these pathways•Co-occurrence alterations suggests combination therapy opportunitiesSummaryGenetic control cell-cycle progression, apoptosis, and cell growth are common hallmarks cancer, but the extent, mechanisms, co-occurrence differ between individual tumor...
Abstract Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation this variation at whole-genome scale 1–3 . Here we report integrative analysis 2,658 whole-cancer genomes their matching normal tissues across 38 tumour types from Pan-Cancer Analysis Whole Genomes (PCAWG) Consortium International Genome (ICGC) The Atlas (TCGA). We describe generation PCAWG resource, facilitated international data sharing using compute clouds. On...
Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify now exist, but systematic attempts combine and optimize them on large datasets are few. We report a PanCancer PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) using 26 computational tools catalog driver genes mutations. 299 with implications regarding their anatomical sites cancer/cell types. Sequence- structure-based...
<h2>Summary</h2> DNA damage repair (DDR) pathways modulate cancer risk, progression, and therapeutic response. We systematically analyzed somatic alterations to provide a comprehensive view of DDR deficiency across 33 types. Mutations with accompanying loss heterozygosity were observed in over 1/3 genes, including <i>TP53</i> <i>BRCA1/2</i>. Other prevalent included epigenetic silencing the direct genes <i>EXO5</i>, <i>MGMT</i>, <i>ALKBH3</i> ∼20% samples. Homologous recombination (HRD) was...
The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling Multiple Cancers project, our effort to generate a comprehensive encyclopedia somatic mutation calls for TCGA enable robust cross-tumor-type analyses. Our approach accounts variance and batch effects introduced by rapid advancement DNA extraction,...
Highlights•An overview of PanCancer Atlas analyses on oncogenic molecular processes•Germline genome affects somatic genomic landscape in a pathway-dependent fashion•Genome mutations impact expression, signaling, and multi-omic profiles•Mutation burdens drivers influence immune-cell composition microenvironmentSummaryThe Cancer Genome (TCGA) has catalyzed systematic characterization diverse alterations underlying human cancers. At this historic junction marking the completion over 11,000...
Models that recapitulate the complexity of human tumors are urgently needed to develop more effective cancer therapies. We report a bank patient-derived xenografts (PDXs) and matched organoid cultures from represent greatest unmet need: endocrine-resistant, treatment-refractory metastatic breast cancers. leverage PDXs PDX-derived organoids (PDxO) for drug screening is feasible cost-effective with in vivo validation. Moreover, we demonstrate feasibility using these models precision oncology...
Abstract Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment propagation, affecting accuracy of modeling cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 matched patient (PT) samples from 509 models. CNA inferences based on DNA sequencing microarray data displayed substantially higher resolution...
Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying significant cis-effects and distal trans-effects quantified at RNA, protein, phosphoprotein levels. Salient observations include association point mutations copy-number alterations with rewiring protein interaction networks,...
We present a systematic analysis of the effects synchronizing large-scale, deeply characterized, multi-omic dataset to current human reference genome, using updated software, pipelines, and annotations. For each 5 molecular data platforms in The Cancer Genome Atlas (TCGA)—mRNA miRNA expression, single nucleotide variants, DNA methylation copy number alterations—comprehensive sample, gene, probe-level studies were performed, towards quantifying degree similarity between 'legacy' GRCh37 (hg19)...
Abstract Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established landscapes 536 patient-derived xenograft (PDX) models across 25 types, together mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared human tumors, PDXs typically higher purity fit dynamic driver events molecular properties via multiple...
Abstract Cancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as controlling biological processes. With them, we classify genes, unveiling roles mechanisms. To this end, present Moonlight, a tool that incorporates multiple -omics data to identify critical analyze 8000+ samples from 18 types, discovering 3310...
Abstract Purpose: Pure pancreatic acinar cell carcinomas (PACC) are rare malignancies with no established treatment. PACC demonstrates significant genetic intertumoral heterogeneity multiple pathways involved, suggesting using targeted cancer therapeutics to treat this disease. We aggregated one of the largest datasets pure examine genomic variability and explore patient-specific therapeutic targets. Experimental Design: specimens (n = 51) underwent next-generation sequencing DNA 29) or...
ABSTRACT Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene‐by‐gene (G × G), or gene‐by‐environment interaction. We propose a versatile likelihood ratio test allows joint testing for mean and ( LRT MV ) either effect alone M V in the presence of covariates. Using extensive simulations our method others, we found all parametric tests were sensitive to nonnormality regardless any trait...
Abstract The Cancer Genome Atlas (TCGA) and International Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) genome (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis Whole Genomes (PCAWG) Consortium, which aggregated data from 2,658 cancers across 38 tumour types, we compare WES WGS side-by-side 746 TCGA samples, finding that ~80% mutations overlap in covered exonic regions. We estimate low variant allele fraction (VAF <...
Abstract Non-coding mutations can create splice sites, however the true extent of how such somatic non-coding affect RNA splicing are largely unexplored. Here we use MiSplice pipeline to analyze 783 cancer cases with WGS data and 9494 WES data, discovering 562 that lead alterations. Notably, most these new exons. Introns associated exon creation significantly larger than genome-wide average intron size. We find some mutation-induced alterations located in genes important tumorigenesis ( ATRX...