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Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia

BACKGROUND: Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of ge...

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Autores principales: Walter, Wencke, Shahswar, Rabia, Stengel, Anna, Meggendorfer, Manja, Kern, Wolfgang, Haferlach, Torsten, Haferlach, Claudia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330044/
https://www.ncbi.nlm.nih.gov/pubmed/34340673
http://dx.doi.org/10.1186/s12885-021-08635-5
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author Walter, Wencke
Shahswar, Rabia
Stengel, Anna
Meggendorfer, Manja
Kern, Wolfgang
Haferlach, Torsten
Haferlach, Claudia
author_facet Walter, Wencke
Shahswar, Rabia
Stengel, Anna
Meggendorfer, Manja
Kern, Wolfgang
Haferlach, Torsten
Haferlach, Claudia
author_sort Walter, Wencke
collection PubMed
description BACKGROUND: Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified. METHODS: We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients. RESULTS: DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples. CONCLUSION: As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08635-5.
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spelling pubmed-83300442021-08-04 Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia Walter, Wencke Shahswar, Rabia Stengel, Anna Meggendorfer, Manja Kern, Wolfgang Haferlach, Torsten Haferlach, Claudia BMC Cancer Research BACKGROUND: Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified. METHODS: We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients. RESULTS: DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples. CONCLUSION: As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08635-5. BioMed Central 2021-08-02 /pmc/articles/PMC8330044/ /pubmed/34340673 http://dx.doi.org/10.1186/s12885-021-08635-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Walter, Wencke
Shahswar, Rabia
Stengel, Anna
Meggendorfer, Manja
Kern, Wolfgang
Haferlach, Torsten
Haferlach, Claudia
Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
title Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
title_full Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
title_fullStr Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
title_full_unstemmed Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
title_short Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
title_sort clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8330044/
https://www.ncbi.nlm.nih.gov/pubmed/34340673
http://dx.doi.org/10.1186/s12885-021-08635-5
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