Orathai Promsuwicha, Weerapat Owattanapanich, Supattra Kankhaw, Theera Ruchutrakool, Smith Kungwankiattichai
{"title":"流式细胞术免疫分型能否预测急性髓系白血病的细胞遗传学异常？骨髓增生异常相关细胞遗传学异常的研究","authors":"Orathai Promsuwicha, Weerapat Owattanapanich, Supattra Kankhaw, Theera Ruchutrakool, Smith Kungwankiattichai","doi":"10.1111/ijlh.14546","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The European LeukemiaNet (ELN) 2022 classification introduced significant modifications to acute myeloid leukemia (AML) categorization, including refined criteria for AML with myelodysplasia-related cytogenetic abnormalities (AML-MRC). While cytogenetic analysis is essential for a definitive diagnosis, the question remains whether flow cytometry can aid in the initial identification of this AML subgroup. This study aimed to characterize the immunophenotypic profiles of AML-MRC and validate previously reported immunophenotypic patterns of AML with t(8;21) and inv(16) using flow cytometry.</p><p><strong>Methods: </strong>This retrospective study analyzed 911 non-acute promyelocytic leukemia (APL) AML cases. Flow cytometric immunophenotyping was performed using a comprehensive panel of 23 markers. Statistical analysis included univariate and multivariate logistic regression to identify discriminatory markers.</p><p><strong>Results: </strong>Among 911 patients, 241 (26.5%) were classified as AML-MRC. AML-MRC patients were significantly older (mean age: 55.9 vs. 47.9 years, p < 0.001) and presented with lower WBC counts (median: 8.9 vs. 24.2 × 10^9/L, p < 0.001) compared to non-MRC cases. AML-MRC demonstrated higher expression of CD34 (75.9% vs. 57.6%, p < 0.001), CD41a (10.8% vs. 4.5%, p = 0.002) and CD235a (5.8% vs. 1.2%, p < 0.001), with CD235a showing the highest discriminatory power (OR 4.458, 95% CI 1.720-11.552). For core-binding factor AML, AML with t(8;21) exhibited characteristic expression of CD19 (46.3% vs. 9.4%, p < 0.001) and CD56 (72.5% vs. 34.5%, p < 0.001), while AML with inv(16) showed distinctive CD34 (88.9% vs. 61.7%, p = 0.004) and CD14 (59.3% vs. 18.1%, p < 0.001) expression patterns.</p><p><strong>Conclusion: </strong>This study identifies markers that distinguish AML-MRC, including CD235a, CD41a, and CD34. This suggests that acute erythroid leukemia and acute megakaryocytic leukemia are subsets within the AML-MRC category. Additionally, the study validates previously reported immunophenotypic characteristics of AML with t(8;21) and inv(16).</p>","PeriodicalId":94050,"journal":{"name":"International journal of laboratory hematology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can Flow Cytometry Immunophenotyping Predict Cytogenetic Abnormalities in Acute Myeloid Leukemia? A Focus on Myelodysplasia-Related Cytogenetic Abnormalities.\",\"authors\":\"Orathai Promsuwicha, Weerapat Owattanapanich, Supattra Kankhaw, Theera Ruchutrakool, Smith Kungwankiattichai\",\"doi\":\"10.1111/ijlh.14546\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>The European LeukemiaNet (ELN) 2022 classification introduced significant modifications to acute myeloid leukemia (AML) categorization, including refined criteria for AML with myelodysplasia-related cytogenetic abnormalities (AML-MRC). While cytogenetic analysis is essential for a definitive diagnosis, the question remains whether flow cytometry can aid in the initial identification of this AML subgroup. This study aimed to characterize the immunophenotypic profiles of AML-MRC and validate previously reported immunophenotypic patterns of AML with t(8;21) and inv(16) using flow cytometry.</p><p><strong>Methods: </strong>This retrospective study analyzed 911 non-acute promyelocytic leukemia (APL) AML cases. Flow cytometric immunophenotyping was performed using a comprehensive panel of 23 markers. Statistical analysis included univariate and multivariate logistic regression to identify discriminatory markers.</p><p><strong>Results: </strong>Among 911 patients, 241 (26.5%) were classified as AML-MRC. AML-MRC patients were significantly older (mean age: 55.9 vs. 47.9 years, p < 0.001) and presented with lower WBC counts (median: 8.9 vs. 24.2 × 10^9/L, p < 0.001) compared to non-MRC cases. AML-MRC demonstrated higher expression of CD34 (75.9% vs. 57.6%, p < 0.001), CD41a (10.8% vs. 4.5%, p = 0.002) and CD235a (5.8% vs. 1.2%, p < 0.001), with CD235a showing the highest discriminatory power (OR 4.458, 95% CI 1.720-11.552). For core-binding factor AML, AML with t(8;21) exhibited characteristic expression of CD19 (46.3% vs. 9.4%, p < 0.001) and CD56 (72.5% vs. 34.5%, p < 0.001), while AML with inv(16) showed distinctive CD34 (88.9% vs. 61.7%, p = 0.004) and CD14 (59.3% vs. 18.1%, p < 0.001) expression patterns.</p><p><strong>Conclusion: </strong>This study identifies markers that distinguish AML-MRC, including CD235a, CD41a, and CD34. This suggests that acute erythroid leukemia and acute megakaryocytic leukemia are subsets within the AML-MRC category. Additionally, the study validates previously reported immunophenotypic characteristics of AML with t(8;21) and inv(16).</p>\",\"PeriodicalId\":94050,\"journal\":{\"name\":\"International journal of laboratory hematology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of laboratory hematology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/ijlh.14546\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of laboratory hematology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/ijlh.14546","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Can Flow Cytometry Immunophenotyping Predict Cytogenetic Abnormalities in Acute Myeloid Leukemia? A Focus on Myelodysplasia-Related Cytogenetic Abnormalities.
Introduction: The European LeukemiaNet (ELN) 2022 classification introduced significant modifications to acute myeloid leukemia (AML) categorization, including refined criteria for AML with myelodysplasia-related cytogenetic abnormalities (AML-MRC). While cytogenetic analysis is essential for a definitive diagnosis, the question remains whether flow cytometry can aid in the initial identification of this AML subgroup. This study aimed to characterize the immunophenotypic profiles of AML-MRC and validate previously reported immunophenotypic patterns of AML with t(8;21) and inv(16) using flow cytometry.
Methods: This retrospective study analyzed 911 non-acute promyelocytic leukemia (APL) AML cases. Flow cytometric immunophenotyping was performed using a comprehensive panel of 23 markers. Statistical analysis included univariate and multivariate logistic regression to identify discriminatory markers.
Results: Among 911 patients, 241 (26.5%) were classified as AML-MRC. AML-MRC patients were significantly older (mean age: 55.9 vs. 47.9 years, p < 0.001) and presented with lower WBC counts (median: 8.9 vs. 24.2 × 10^9/L, p < 0.001) compared to non-MRC cases. AML-MRC demonstrated higher expression of CD34 (75.9% vs. 57.6%, p < 0.001), CD41a (10.8% vs. 4.5%, p = 0.002) and CD235a (5.8% vs. 1.2%, p < 0.001), with CD235a showing the highest discriminatory power (OR 4.458, 95% CI 1.720-11.552). For core-binding factor AML, AML with t(8;21) exhibited characteristic expression of CD19 (46.3% vs. 9.4%, p < 0.001) and CD56 (72.5% vs. 34.5%, p < 0.001), while AML with inv(16) showed distinctive CD34 (88.9% vs. 61.7%, p = 0.004) and CD14 (59.3% vs. 18.1%, p < 0.001) expression patterns.
Conclusion: This study identifies markers that distinguish AML-MRC, including CD235a, CD41a, and CD34. This suggests that acute erythroid leukemia and acute megakaryocytic leukemia are subsets within the AML-MRC category. Additionally, the study validates previously reported immunophenotypic characteristics of AML with t(8;21) and inv(16).
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