Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities
Acute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:e2a5950c46fd43f79855962125a2e5322021-11-05T06:20:28ZDatabase-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities2234-943X10.3389/fonc.2021.746951https://doaj.org/article/e2a5950c46fd43f79855962125a2e5322021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fonc.2021.746951/fullhttps://doaj.org/toc/2234-943XAcute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective of the present study was to assess whether a Compass database-guided analysis can be used to achieve rapid and accurate diagnoses. We conducted this study to determine whether this method could be employed to pilote the genetic and molecular tests and to objectively identify different-from-normal (DfN) patterns to improve measurable residual disease follow-up in AML. Three Compass databases were built using Infinicyt 2.0 software, including normal myeloid-committed hematopoietic precursors (n = 20) and AML blasts harboring the most frequent recurrent genetic abnormalities (n = 50). The diagnostic accuracy of the Compass database-guided analysis was evaluated in a prospective validation study (125 suspected AML patients). This method excluded AML associated with the following genetic abnormalities: t(8;21), t(15;17), inv(16), and KMT2A translocation, with 92% sensitivity [95% confidence interval (CI): 78.6%–98.3%] and a 98.5% negative predictive value (95% CI: 90.6%–99.8%). Our data showed that the Compass database-guided analysis could identify phenotypic differences between AML groups, representing a useful tool for the identification of DfN patterns.Carmen-Mariana AaneiRichard Veyrat-MassonCristina SeliceanCristina SeliceanMirela MarianLauren RigolletAdrian Pavel TrifaAdrian Pavel TrifaCiprian TomuleasaCiprian TomuleasaAdrian SerbanMohamad CherryPascale Flandrin-GrestaEmmanuelle Tavernier TardyDenis GuyotatLydia Campos CatafalFrontiers Media S.A.articleacute myeloid leukemia with recurrent genetic abnormalitiesmulticolor flow cytometryCompass database-guided analysisdifferent-from-normal (DfN) approachmeasurable (minimal) residual diseaseNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENFrontiers in Oncology, Vol 11 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
acute myeloid leukemia with recurrent genetic abnormalities multicolor flow cytometry Compass database-guided analysis different-from-normal (DfN) approach measurable (minimal) residual disease Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 |
| spellingShingle |
acute myeloid leukemia with recurrent genetic abnormalities multicolor flow cytometry Compass database-guided analysis different-from-normal (DfN) approach measurable (minimal) residual disease Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Carmen-Mariana Aanei Richard Veyrat-Masson Cristina Selicean Cristina Selicean Mirela Marian Lauren Rigollet Adrian Pavel Trifa Adrian Pavel Trifa Ciprian Tomuleasa Ciprian Tomuleasa Adrian Serban Mohamad Cherry Pascale Flandrin-Gresta Emmanuelle Tavernier Tardy Denis Guyotat Lydia Campos Catafal Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities |
| description |
Acute myeloid leukemias (AMLs) are hematologic malignancies with varied molecular and immunophenotypic profiles, making them difficult to diagnose and classify. High-dimensional analysis algorithms might increase the utility of multicolor flow cytometry for AML diagnosis and follow-up. The objective of the present study was to assess whether a Compass database-guided analysis can be used to achieve rapid and accurate diagnoses. We conducted this study to determine whether this method could be employed to pilote the genetic and molecular tests and to objectively identify different-from-normal (DfN) patterns to improve measurable residual disease follow-up in AML. Three Compass databases were built using Infinicyt 2.0 software, including normal myeloid-committed hematopoietic precursors (n = 20) and AML blasts harboring the most frequent recurrent genetic abnormalities (n = 50). The diagnostic accuracy of the Compass database-guided analysis was evaluated in a prospective validation study (125 suspected AML patients). This method excluded AML associated with the following genetic abnormalities: t(8;21), t(15;17), inv(16), and KMT2A translocation, with 92% sensitivity [95% confidence interval (CI): 78.6%–98.3%] and a 98.5% negative predictive value (95% CI: 90.6%–99.8%). Our data showed that the Compass database-guided analysis could identify phenotypic differences between AML groups, representing a useful tool for the identification of DfN patterns. |
| format |
article |
| author |
Carmen-Mariana Aanei Richard Veyrat-Masson Cristina Selicean Cristina Selicean Mirela Marian Lauren Rigollet Adrian Pavel Trifa Adrian Pavel Trifa Ciprian Tomuleasa Ciprian Tomuleasa Adrian Serban Mohamad Cherry Pascale Flandrin-Gresta Emmanuelle Tavernier Tardy Denis Guyotat Lydia Campos Catafal |
| author_facet |
Carmen-Mariana Aanei Richard Veyrat-Masson Cristina Selicean Cristina Selicean Mirela Marian Lauren Rigollet Adrian Pavel Trifa Adrian Pavel Trifa Ciprian Tomuleasa Ciprian Tomuleasa Adrian Serban Mohamad Cherry Pascale Flandrin-Gresta Emmanuelle Tavernier Tardy Denis Guyotat Lydia Campos Catafal |
| author_sort |
Carmen-Mariana Aanei |
| title |
Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities |
| title_short |
Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities |
| title_full |
Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities |
| title_fullStr |
Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities |
| title_full_unstemmed |
Database-Guided Analysis for Immunophenotypic Diagnosis and Follow-Up of Acute Myeloid Leukemia With Recurrent Genetic Abnormalities |
| title_sort |
database-guided analysis for immunophenotypic diagnosis and follow-up of acute myeloid leukemia with recurrent genetic abnormalities |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/e2a5950c46fd43f79855962125a2e532 |
| work_keys_str_mv |
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