A5016023354- Cancer Genomics and Diagnostics
- Sarcoma Diagnosis and Treatment
- Cancer-related molecular mechanisms research
- RNA modifications and cancer
- RNA Research and Splicing
- Molecular Biology Techniques and Applications
- Single-cell and spatial transcriptomics
- Genetic factors in colorectal cancer
- Listeria monocytogenes in Food Safety
- Cancer Cells and Metastasis
- Microbial Inactivation Methods
- Genomics and Chromatin Dynamics
- Food Drying and Modeling
- RNA and protein synthesis mechanisms
- Radiomics and Machine Learning in Medical Imaging
- Cancer Research and Treatments
- Helicobacter pylori-related gastroenterology studies
- Bacillus and Francisella bacterial research
The Ohio State University
2005-2023
Nationwide Children's Hospital
2020-2023
Janssen (United States)
2022-2023
Johnson & Johnson (United States)
2022
Abstract Background Tumors are complex tissues containing collections of phenotypically diverse malignant and nonmalignant cells. We know little the mechanisms that govern heterogeneity tumor cells nor role plays in overcoming stresses, such as adaptation to different microenvironments. Osteosarcoma is an ideal model for studying these mechanisms—it exhibits widespread inter- intra-tumoral heterogeneity, predictable patterns metastasis, a lack clear targetable driver mutations. Understanding...
Osteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNA) are the genetic drivers disease. Models around instability conflict-it unclear whether osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization fitness landscape or early catastrophic event followed stable maintenance abnormal genome. We address this question...
Abstract Background Tumors are complex tissues containing collections of phenotypically diverse malignant and nonmalignant cells. We know little the mechanisms that govern heterogeneity tumor cells nor role plays in overcoming stresses, such as adaptation to different microenvironments. Osteosarcoma is an ideal model for studying these mechanisms—it exhibits widespread inter- intra-tumoral heterogeneity, predictable patterns metastasis, a lack clear targetable driver mutations. Understanding...
Abstract Osteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNAs) are the genetic drivers disease. Models around instability conflict - it unclear if osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization fitness landscape or early catastrophic event followed stable maintenance abnormal genome. We address this...
Abstract Four decades of intense multinational efforts to improve outcomes for children and teenagers with osteosarcoma have failed. Today, we still treat patients a regimen first developed in 1982. The same 35-40% young people diagnosed die from their disease, almost always complications related lung metastasis. Believing that therapies targeting metastasis could dramatically outcomes, sought understand the mechanisms drive colonization this disease. We previously found interactions...
<p>Cell count and fraction of clones</p>
<p>CHISEL output plots</p>
<p>Bulk data genome SCNA plots by patient</p>
<p>Fraction of altered genome density plots</p>
<p>CHISEL plot for SJOS003939 samples</p>
<p>Proportion of identically assigned SCNAs between samples</p>
<p>TP53 copy number in single-cell data</p>
<div><p>Osteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNA) are the genetic drivers disease. Models around instability conflict—it unclear whether osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization fitness landscape or early catastrophic event followed stable maintenance abnormal genome. We...
<p>Ploidy plots</p>
<p>Bulk data genome SCNA plots by patient</p>
<p>Proportion of identically assigned SCNAs between samples</p>
<p>TP53 copy number in single-cell data</p>
<p>Ploidy plots</p>
<p>CHISEL output plots</p>