A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia

As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML)....

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Published inNature communications Vol. 12; no. 1; p. 2474
Main Authors Docking, T. Roderick, Parker, Jeremy D. K., Jädersten, Martin, Duns, Gerben, Chang, Linda, Jiang, Jihong, Pilsworth, Jessica A., Swanson, Lucas A., Chan, Simon K., Chiu, Readman, Nip, Ka Ming, Mar, Samantha, Mo, Angela, Wang, Xuan, Martinez-Høyer, Sergio, Stubbins, Ryan J., Mungall, Karen L., Mungall, Andrew J., Moore, Richard A., Jones, Steven J. M., Birol, İnanç, Marra, Marco A., Hogge, Donna, Karsan, Aly
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 30.04.2021
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Abstract As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2 , demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy. Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors generate an AML prognostic score from RNA-seq data of patients, which successfully stratifies AML patients and which may provide guidance for therapeutic strategies.
AbstractList As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2, demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors generate an AML prognostic score from RNA-seq data of patients, which successfully stratifies AML patients and which may provide guidance for therapeutic strategies.
As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2 , demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy.
Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors generate an AML prognostic score from RNA-seq data of patients, which successfully stratifies AML patients and which may provide guidance for therapeutic strategies.
As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for risk stratification. Here, we develop and validate a clinical transcriptome-based assay for stratification of acute myeloid leukemia (AML). Comparison of ribonucleic acid sequencing (RNA-Seq) to whole genome and exome sequencing reveals that a standalone RNA-Seq assay offers the greatest diagnostic return, enabling identification of expressed gene fusions, single nucleotide and short insertion/deletion variants, and whole-transcriptome expression information. Expression data from 154 AML patients are used to develop a novel AML prognostic score, which is strongly associated with patient outcomes across 620 patients from three independent cohorts, and 42 patients from a prospective cohort. When combined with molecular risk guidelines, the risk score allows for the re-stratification of 22.1 to 25.3% of AML patients from three independent cohorts into correct risk groups. Within the adverse-risk subgroup, we identify a subset of patients characterized by dysregulated integrin signaling and RUNX1 or TP53 mutation. We show that these patients may benefit from therapy with inhibitors of focal adhesion kinase, encoded by PTK2 , demonstrating additional utility of transcriptome-based testing for therapy selection in myeloid malignancy. Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors generate an AML prognostic score from RNA-seq data of patients, which successfully stratifies AML patients and which may provide guidance for therapeutic strategies.
ArticleNumber 2474
Author Docking, T. Roderick
Jones, Steven J. M.
Chiu, Readman
Swanson, Lucas A.
Duns, Gerben
Wang, Xuan
Chang, Linda
Nip, Ka Ming
Stubbins, Ryan J.
Hogge, Donna
Mo, Angela
Marra, Marco A.
Chan, Simon K.
Mar, Samantha
Mungall, Karen L.
Mungall, Andrew J.
Pilsworth, Jessica A.
Moore, Richard A.
Birol, İnanç
Karsan, Aly
Jiang, Jihong
Martinez-Høyer, Sergio
Parker, Jeremy D. K.
Jädersten, Martin
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Snippet As more clinically-relevant genomic features of myeloid malignancies are revealed, it has become clear that targeted clinical genetic testing is inadequate for...
Several genomic features have been found for acute myeloid leukaemia (AML) but targeted clinical genetic testing fails to predict prognosis. Here, the authors...
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Acute myeloid leukemia
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Cell Line, Tumor
Cohort Studies
Core Binding Factor Alpha 2 Subunit - genetics
Core Binding Factor Alpha 2 Subunit - metabolism
Female
Focal adhesion kinase
Gene deletion
Gene expression
Gene Expression Regulation, Neoplastic - genetics
Gene Fusion
Gene sequencing
Genetic screening
Genomics
Humanities and Social Sciences
Humans
INDEL Mutation
Insertion
Integrins - genetics
Integrins - metabolism
Kinases
Leukemia
Leukemia, Myeloid, Acute - diagnosis
Leukemia, Myeloid, Acute - genetics
Leukemia, Myeloid, Acute - metabolism
Male
Malignancy
Medicin och hälsovetenskap
multidisciplinary
Mutation
Myeloid leukemia
Nucleotides
p53 Protein
Patients
Polymorphism, Single Nucleotide
Prognosis
Prospective Studies
Ribonucleic acid
Risk
Risk Factors
Risk groups
RNA
RNA-Seq
Runx1 protein
Science
Science (multidisciplinary)
Signal Transduction - genetics
Subgroups
Survival Analysis
Therapy
Transcriptome
Transcriptomes
Tumor Suppressor Protein p53 - genetics
Tumor Suppressor Protein p53 - metabolism
Whole Exome Sequencing
Whole Genome Sequencing
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Title A clinical transcriptome approach to patient stratification and therapy selection in acute myeloid leukemia
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Volume 12
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