DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia

Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from thre...
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Autor*in:	Li, Xueqian [verfasserIn] Qi, Jiaqian Song, Xiaofei Xu, Xiaoyan Pan, Tingting Wang, Hong Yang, Jingyi Han, Yue

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Acute myeloid leukemia Weighted gene co-expression network analysis Differential gene expression analysis DLC1 Machine learning

Anmerkung:	© The Author(s) 2022

Übergeordnetes Werk:	Enthalten in: Experimental hematology & oncology - London : Biomed Central, 2012, 11(2022), 1 vom: 18. Okt.
Übergeordnetes Werk:	volume:11 ; year:2022 ; number:1 ; day:18 ; month:10

Links:	Volltext

DOI / URN:	10.1186/s40164-022-00335-5

Katalog-ID:	SPR051070898

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520			\|a Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis.
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allfields	10.1186/s40164-022-00335-5 doi (DE-627)SPR051070898 (SPR)s40164-022-00335-5-e DE-627 ger DE-627 rakwb eng Li, Xueqian verfasserin aut DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. Acute myeloid leukemia (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Differential gene expression analysis (dpeaa)DE-He213 DLC1 (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Qi, Jiaqian aut Song, Xiaofei aut Xu, Xiaoyan aut Pan, Tingting aut Wang, Hong aut Yang, Jingyi aut Han, Yue (orcid)0000-0002-7560-7195 aut Enthalten in Experimental hematology & oncology London : Biomed Central, 2012 11(2022), 1 vom: 18. Okt. (DE-627)718833341 (DE-600)2669066-4 2162-3619 nnns volume:11 year:2022 number:1 day:18 month:10 https://dx.doi.org/10.1186/s40164-022-00335-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 1 18 10
spelling	10.1186/s40164-022-00335-5 doi (DE-627)SPR051070898 (SPR)s40164-022-00335-5-e DE-627 ger DE-627 rakwb eng Li, Xueqian verfasserin aut DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. Acute myeloid leukemia (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Differential gene expression analysis (dpeaa)DE-He213 DLC1 (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Qi, Jiaqian aut Song, Xiaofei aut Xu, Xiaoyan aut Pan, Tingting aut Wang, Hong aut Yang, Jingyi aut Han, Yue (orcid)0000-0002-7560-7195 aut Enthalten in Experimental hematology & oncology London : Biomed Central, 2012 11(2022), 1 vom: 18. Okt. (DE-627)718833341 (DE-600)2669066-4 2162-3619 nnns volume:11 year:2022 number:1 day:18 month:10 https://dx.doi.org/10.1186/s40164-022-00335-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 1 18 10
allfields_unstemmed	10.1186/s40164-022-00335-5 doi (DE-627)SPR051070898 (SPR)s40164-022-00335-5-e DE-627 ger DE-627 rakwb eng Li, Xueqian verfasserin aut DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. Acute myeloid leukemia (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Differential gene expression analysis (dpeaa)DE-He213 DLC1 (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Qi, Jiaqian aut Song, Xiaofei aut Xu, Xiaoyan aut Pan, Tingting aut Wang, Hong aut Yang, Jingyi aut Han, Yue (orcid)0000-0002-7560-7195 aut Enthalten in Experimental hematology & oncology London : Biomed Central, 2012 11(2022), 1 vom: 18. Okt. (DE-627)718833341 (DE-600)2669066-4 2162-3619 nnns volume:11 year:2022 number:1 day:18 month:10 https://dx.doi.org/10.1186/s40164-022-00335-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 1 18 10
allfieldsGer	10.1186/s40164-022-00335-5 doi (DE-627)SPR051070898 (SPR)s40164-022-00335-5-e DE-627 ger DE-627 rakwb eng Li, Xueqian verfasserin aut DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. Acute myeloid leukemia (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Differential gene expression analysis (dpeaa)DE-He213 DLC1 (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Qi, Jiaqian aut Song, Xiaofei aut Xu, Xiaoyan aut Pan, Tingting aut Wang, Hong aut Yang, Jingyi aut Han, Yue (orcid)0000-0002-7560-7195 aut Enthalten in Experimental hematology & oncology London : Biomed Central, 2012 11(2022), 1 vom: 18. Okt. (DE-627)718833341 (DE-600)2669066-4 2162-3619 nnns volume:11 year:2022 number:1 day:18 month:10 https://dx.doi.org/10.1186/s40164-022-00335-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 1 18 10
allfieldsSound	10.1186/s40164-022-00335-5 doi (DE-627)SPR051070898 (SPR)s40164-022-00335-5-e DE-627 ger DE-627 rakwb eng Li, Xueqian verfasserin aut DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2022 Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. Acute myeloid leukemia (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Differential gene expression analysis (dpeaa)DE-He213 DLC1 (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213 Qi, Jiaqian aut Song, Xiaofei aut Xu, Xiaoyan aut Pan, Tingting aut Wang, Hong aut Yang, Jingyi aut Han, Yue (orcid)0000-0002-7560-7195 aut Enthalten in Experimental hematology & oncology London : Biomed Central, 2012 11(2022), 1 vom: 18. Okt. (DE-627)718833341 (DE-600)2669066-4 2162-3619 nnns volume:11 year:2022 number:1 day:18 month:10 https://dx.doi.org/10.1186/s40164-022-00335-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2022 1 18 10
language	English
source	Enthalten in Experimental hematology & oncology 11(2022), 1 vom: 18. Okt. volume:11 year:2022 number:1 day:18 month:10
sourceStr	Enthalten in Experimental hematology & oncology 11(2022), 1 vom: 18. Okt. volume:11 year:2022 number:1 day:18 month:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Acute myeloid leukemia Weighted gene co-expression network analysis Differential gene expression analysis DLC1 Machine learning
isfreeaccess_bool	true
container_title	Experimental hematology & oncology
authorswithroles_txt_mv	Li, Xueqian @@aut@@ Qi, Jiaqian @@aut@@ Song, Xiaofei @@aut@@ Xu, Xiaoyan @@aut@@ Pan, Tingting @@aut@@ Wang, Hong @@aut@@ Yang, Jingyi @@aut@@ Han, Yue @@aut@@
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author	Li, Xueqian
spellingShingle	Li, Xueqian misc Acute myeloid leukemia misc Weighted gene co-expression network analysis misc Differential gene expression analysis misc DLC1 misc Machine learning DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia
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topic_title	DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia Acute myeloid leukemia (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Differential gene expression analysis (dpeaa)DE-He213 DLC1 (dpeaa)DE-He213 Machine learning (dpeaa)DE-He213
topic	misc Acute myeloid leukemia misc Weighted gene co-expression network analysis misc Differential gene expression analysis misc DLC1 misc Machine learning
topic_unstemmed	misc Acute myeloid leukemia misc Weighted gene co-expression network analysis misc Differential gene expression analysis misc DLC1 misc Machine learning
topic_browse	misc Acute myeloid leukemia misc Weighted gene co-expression network analysis misc Differential gene expression analysis misc DLC1 misc Machine learning
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title	DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia
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title_full	DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia
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title_sort	dlc1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia
title_auth	DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia
abstract	Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. © The Author(s) 2022
abstractGer	Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. © The Author(s) 2022
abstract_unstemmed	Abstract Acute myeloid leukemia (AML) is a complex, heterogeneous malignant hematologic disease. Although multiple prognostic-related genes gave been explored in previous studies, there are still many genes whose prognostic value remains unclear. In this study, a total of 1532 AML patients from three GEO databases were included, five genes with potential prognostic value (DLC1, NF1B, DENND5B, TANC2 and ELAVL4) were screened by weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE). Based on this, we conducted survival analysis of the above five genes through the TCGA database and found that low level of DLC1 was detrimental to the long-term prognosis of AML patients. We also performed external validation in 48 AML patients from our medical center to analyze the impact of DLC1 level on prognosis. In conclusion, DLC1 may be a potential marker affecting the prognosis of AML, and its deficiency is associated with poor prognosis. © The Author(s) 2022
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title_short	DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia
url	https://dx.doi.org/10.1186/s40164-022-00335-5
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author2	Qi, Jiaqian Song, Xiaofei Xu, Xiaoyan Pan, Tingting Wang, Hong Yang, Jingyi Han, Yue
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DLC1 deficiency at diagnosis predicts poor prognosis in acute myeloid leukemia

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