Jason E. Farrar

Arkansas Children's Hospital

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Soheil Meshinchi

Fred Hutch Cancer Center

Rhonda E. Ries

Fred Hutch Cancer Center

Todd A. Alonzo

University of Southern California

Alan S. Gamis

Children's Mercy Hospital

Daniela S. Gerhard

National Institutes of Health

Tanja M. Davidsen

Center for Information Technology

Malcolm A. Smith

National Cancer Institute

Patee Gesuwan

National Cancer Institute

R.J. Arceci

Johns Hopkins University

Jaime M. Guidry Auvil

National Cancer Institute

Cooperative Institutions

National Institutes of Health

University of Arkansas for Medical Sciences

St. Jude Children's Research Hospital

Fred Hutch Cancer Center

University of Washington

Boston Children's Hospital

Arkansas Children's Hospital

Johns Hopkins University

Harvard University

National Human Genome Research Institute

Author Statistics

Papers

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Untangling the Phenotypic Heterogeneity of Diamond Blackfan Anemia

Seminars in Hematology (2011)

Jason E. Farrar Niklas Dahl

Diamond–Blackfan anemia

Ribosomal protein

Bone marrow failure

Lineage (genetic)

Genotype-phenotype distinction

10.1053/j.seminhematol.2011.02.003

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Citations (52)

Supplementary Tables from Comprehensive Transcriptome Profiling of Cryptic CBFA2T3–GLIS2 Fusion–Positive AML Defines Novel Therapeutic Options: A COG and TARGET Pediatric AML Study

Jenny L. Smith Rhonda E. Ries Tiffany Hylkema Todd A. Alonzo Robert B. Gerbing

Supplemental tables including clinical characteristics and differentially expressed gene lists.

Cog

10.1158/1078-0432.22473323

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Citations (0)

Integrated Methylation and Transcriptional Landscape and Evolution of Pediatric AML

Blood (2023)

Benjamin J. Huang Hamid Bolouri Colin Y. Smith Jim J. Wang Rhonda E. Ries

CEBPA

10.1182/blood-2023-187819

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Supplemental Figure 4 from Genomic Profiling of Pediatric Acute Myeloid Leukemia Reveals a Changing Mutational Landscape from Disease Diagnosis to Relapse

Jason E. Farrar Heather L. Schuback Rhonda E. Ries Daniel Wai Oliver Hampton

Clonal cluster analysis. Mutations were clustered using DBSCAN based on the VAF and graphed according to timepoint. Panels A-T illustrate possible scenarios of how individual mutations may originate, evolve, and resolve based on VAF.

10.1158/0008-5472.22410512

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Supplemental Figure 3 from Genomic Profiling of Pediatric Acute Myeloid Leukemia Reveals a Changing Mutational Landscape from Disease Diagnosis to Relapse

Jason E. Farrar Heather L. Schuback Rhonda E. Ries Daniel Wai Oliver Hampton

Clonal evolution of mutations from diagnosis to relapse. These graphs depict the Variant Allele Frequency (VAF) of each patient's mutations at diagnosis and relapse. Note: Mutations absent at diagnosis or relapse are depicted with VAF of zero. Gene names are noted to the left of each variant and are available in Supplemental Table 2.

10.1158/0008-5472.22410515

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Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia

Nature Communications (2022)

Benjamin J. Huang Jenny L. Smith Jason E. Farrar Yi‐Cheng Wang Masayuki Umeda

Abstract Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.

Risk Stratification

Predictive power

10.1038/s41467-022-33244-6

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Citations (31)

CSF3R mutations have a high degree of overlap with CEBPA mutations in pediatric AML

Blood (2016)

Julia E. Maxson Rhonda E. Ries Yi-Cheng Wang Robert B. Gerbing E. Anders Kolb

CEBPA

Childhood Cancer

10.1182/blood-2016-04-709899

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Citations (54)

Sensitive quantification of mosaicism using high density SNP arrays and the cumulative distribution function

Molecular Genetics and Metabolism (2011)

Thomas C. Markello Hannah Carlson-Donohoe Murat Sincan David R. Adams David M. Bodine

SNP

SNP array

Exome

10.1016/j.ymgme.2011.12.015

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Citations (17)

A NOVEL GERMLINE TP53 MUTATION IN A PATIENT WITH LI-FRAUMENI SYNDROME - RESOLVING A VARIANT OF UNCERTAIN SIGNIFICANCE

Authorea (Authorea) (2020)

David P. Douglass Kimo C. Stine Jason E. Farrar

Increasing availability of genomic testing poses new challenges to clinicians, particularly where variant interpretation from commercial sources may be equivocal. We report a patient with recurrent rhabdomyosarcoma and subsequent bilateral breast cancer who was found to harbor a previously undescribed germline TP53 sequence alteration annotated by the commercial laboratory as a variant of uncertain significance (VUS). By investigating publically available databases of aggregated normal germline and malignant somatic genomic sequences, we conclude that this missense variant, c.476C>T (p.A159V), is a novel, pathogenic Li-Fraumeni syndrome mutation, and illustrate the utility of these resources in clinical pediatric hematology and oncology practice.

Li–Fraumeni syndrome

Hematology

10.22541/au.159559952.27535364

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Citations (0)

SNP Array Genotyping Reveals Constitutional and Mosaic Losses of Ribosomal Protein Gene Regions In Patients with Diamond Blackfan Anemia without Ribosomal Protein Gene Mutations.

Blood (2010)

Jason E. Farrar Adrianna Vlachos Eva Atsidaftos Hannah Carlson-Donohoe Steven R. Ellis

Diamond–Blackfan anemia

SNP genotyping

SNP array

Comparative genomic hybridization

Proband

10.1182/blood.v116.21.1168.1168

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Citations (3)