Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes
Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the...
Ausführliche Beschreibung
Autor*in: |
Wang, Hong [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
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2018 |
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Anmerkung: |
© Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Übergeordnetes Werk: |
Enthalten in: Annals of hematology - Berlin : Springer, 1955, 97(2018), 11 vom: 06. Aug., Seite 2025-2038 |
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Übergeordnetes Werk: |
volume:97 ; year:2018 ; number:11 ; day:06 ; month:08 ; pages:2025-2038 |
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DOI / URN: |
10.1007/s00277-018-3464-9 |
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Katalog-ID: |
SPR003956741 |
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520 | |a Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. | ||
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650 | 4 | |a Predictors |7 (dpeaa)DE-He213 | |
700 | 1 | |a Li, Yan |4 aut | |
700 | 1 | |a Lv, Na |4 aut | |
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700 | 1 | |a Wang, Lili |4 aut | |
700 | 1 | |a Yu, Li |0 (orcid)0000-0001-6872-2665 |4 aut | |
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10.1007/s00277-018-3464-9 doi (DE-627)SPR003956741 (SPR)s00277-018-3464-9-e DE-627 ger DE-627 rakwb eng Wang, Hong verfasserin aut Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. Acute myeloid leukemia (dpeaa)DE-He213 Myelodysplastic syndromes (dpeaa)DE-He213 Hypomethylating agents (dpeaa)DE-He213 Predictors (dpeaa)DE-He213 Li, Yan aut Lv, Na aut Li, Yonghui aut Wang, Lili aut Yu, Li (orcid)0000-0001-6872-2665 aut Enthalten in Annals of hematology Berlin : Springer, 1955 97(2018), 11 vom: 06. Aug., Seite 2025-2038 (DE-627)253389852 (DE-600)1458429-3 1432-0584 nnns volume:97 year:2018 number:11 day:06 month:08 pages:2025-2038 https://dx.doi.org/10.1007/s00277-018-3464-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 97 2018 11 06 08 2025-2038 |
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10.1007/s00277-018-3464-9 doi (DE-627)SPR003956741 (SPR)s00277-018-3464-9-e DE-627 ger DE-627 rakwb eng Wang, Hong verfasserin aut Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. Acute myeloid leukemia (dpeaa)DE-He213 Myelodysplastic syndromes (dpeaa)DE-He213 Hypomethylating agents (dpeaa)DE-He213 Predictors (dpeaa)DE-He213 Li, Yan aut Lv, Na aut Li, Yonghui aut Wang, Lili aut Yu, Li (orcid)0000-0001-6872-2665 aut Enthalten in Annals of hematology Berlin : Springer, 1955 97(2018), 11 vom: 06. Aug., Seite 2025-2038 (DE-627)253389852 (DE-600)1458429-3 1432-0584 nnns volume:97 year:2018 number:11 day:06 month:08 pages:2025-2038 https://dx.doi.org/10.1007/s00277-018-3464-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 97 2018 11 06 08 2025-2038 |
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10.1007/s00277-018-3464-9 doi (DE-627)SPR003956741 (SPR)s00277-018-3464-9-e DE-627 ger DE-627 rakwb eng Wang, Hong verfasserin aut Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. Acute myeloid leukemia (dpeaa)DE-He213 Myelodysplastic syndromes (dpeaa)DE-He213 Hypomethylating agents (dpeaa)DE-He213 Predictors (dpeaa)DE-He213 Li, Yan aut Lv, Na aut Li, Yonghui aut Wang, Lili aut Yu, Li (orcid)0000-0001-6872-2665 aut Enthalten in Annals of hematology Berlin : Springer, 1955 97(2018), 11 vom: 06. Aug., Seite 2025-2038 (DE-627)253389852 (DE-600)1458429-3 1432-0584 nnns volume:97 year:2018 number:11 day:06 month:08 pages:2025-2038 https://dx.doi.org/10.1007/s00277-018-3464-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 97 2018 11 06 08 2025-2038 |
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10.1007/s00277-018-3464-9 doi (DE-627)SPR003956741 (SPR)s00277-018-3464-9-e DE-627 ger DE-627 rakwb eng Wang, Hong verfasserin aut Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. Acute myeloid leukemia (dpeaa)DE-He213 Myelodysplastic syndromes (dpeaa)DE-He213 Hypomethylating agents (dpeaa)DE-He213 Predictors (dpeaa)DE-He213 Li, Yan aut Lv, Na aut Li, Yonghui aut Wang, Lili aut Yu, Li (orcid)0000-0001-6872-2665 aut Enthalten in Annals of hematology Berlin : Springer, 1955 97(2018), 11 vom: 06. Aug., Seite 2025-2038 (DE-627)253389852 (DE-600)1458429-3 1432-0584 nnns volume:97 year:2018 number:11 day:06 month:08 pages:2025-2038 https://dx.doi.org/10.1007/s00277-018-3464-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 97 2018 11 06 08 2025-2038 |
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10.1007/s00277-018-3464-9 doi (DE-627)SPR003956741 (SPR)s00277-018-3464-9-e DE-627 ger DE-627 rakwb eng Wang, Hong verfasserin aut Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. Acute myeloid leukemia (dpeaa)DE-He213 Myelodysplastic syndromes (dpeaa)DE-He213 Hypomethylating agents (dpeaa)DE-He213 Predictors (dpeaa)DE-He213 Li, Yan aut Lv, Na aut Li, Yonghui aut Wang, Lili aut Yu, Li (orcid)0000-0001-6872-2665 aut Enthalten in Annals of hematology Berlin : Springer, 1955 97(2018), 11 vom: 06. Aug., Seite 2025-2038 (DE-627)253389852 (DE-600)1458429-3 1432-0584 nnns volume:97 year:2018 number:11 day:06 month:08 pages:2025-2038 https://dx.doi.org/10.1007/s00277-018-3464-9 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 97 2018 11 06 08 2025-2038 |
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Wang, Hong @@aut@@ Li, Yan @@aut@@ Lv, Na @@aut@@ Li, Yonghui @@aut@@ Wang, Lili @@aut@@ Yu, Li @@aut@@ |
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Wang, Hong |
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Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes Acute myeloid leukemia (dpeaa)DE-He213 Myelodysplastic syndromes (dpeaa)DE-He213 Hypomethylating agents (dpeaa)DE-He213 Predictors (dpeaa)DE-He213 |
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predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes |
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Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes |
abstract |
Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
abstractGer |
Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
abstract_unstemmed |
Abstract Azacitidine and decitabine, two hypomethylating agents, are known to be effective in the treatment of high-risk myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) patients who cannot endure intensive cytotoxic chemotherapy or are not eligible for transplantation. However, the treatment response rate is low. The molecular mechanisms underlying the resistance to demethylation therapy are unclear. Though a wide range of predictors of treatment response have been investigated, no consensus has been reached. It is imperative to identify certain parameters that can help distinguish between patients who will obtain a favorable outcome from demethylation therapy and those who will not. Here, we describe currently researched potential predictors based on clinical characteristics, DNA methylation, gene mutation, gene expression, microRNAs, and protein expression. Although these parameters are not currently used in clinical practice, this review provides new sights into available clinical and experimental research. Moreover, this paper provides useful information on AML/MDS management. © Springer-Verlag GmbH Germany, part of Springer Nature 2018 |
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Predictors of clinical responses to hypomethylating agents in acute myeloid leukemia or myelodysplastic syndromes |
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https://dx.doi.org/10.1007/s00277-018-3464-9 |
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Li, Yan Lv, Na Li, Yonghui Wang, Lili Yu, Li |
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Li, Yan Lv, Na Li, Yonghui Wang, Lili Yu, Li |
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2024-07-03T22:45:35.811Z |
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|
score |
7.401189 |