A simplified approach using Taqman low-density array for medulloblastoma subgrouping

Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Cruzeiro, Gustavo Alencastro Veiga [verfasserIn] Salomão, Karina Bezerra de Biagi Jr, Carlos Alberto Oliveira Baumgartner, Martin Sturm, Dominik Lira, Régia Caroline Peixoto de Almeida Magalhães, Taciani Baroni Milan, Mirella da Silva Silveira, Vanessa Saggioro, Fabiano Pinto de Oliveira, Ricardo Santos dos Santos Klinger, Paulo Henrique Seidinger, Ana Luiza Yunes, José Andrés de Paula Queiroz, Rosane Gomes Oba-Shinjo, Sueli Mieko Scrideli, Carlos Alberto Nagahashi, Suely Marie Kazue Tone, Luiz Gonzaga Valera, Elvis Terci

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Medulloblastoma Molecular subgroups Brazilian cohort Real-time PCR

Anmerkung:	© The Author(s). 2019

Übergeordnetes Werk:	Enthalten in: Acta Neuropathologica Communications - London : Biomed Central, 2013, 7(2019), 1 vom: 04. März
Übergeordnetes Werk:	volume:7 ; year:2019 ; number:1 ; day:04 ; month:03

Links:	Volltext

DOI / URN:	10.1186/s40478-019-0681-y

Katalog-ID:	SPR036514772

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520			\|a Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making.
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allfields	10.1186/s40478-019-0681-y doi (DE-627)SPR036514772 (SPR)s40478-019-0681-y-e DE-627 ger DE-627 rakwb eng Cruzeiro, Gustavo Alencastro Veiga verfasserin (orcid)0000-0002-0005-3984 aut A simplified approach using Taqman low-density array for medulloblastoma subgrouping 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. Medulloblastoma (dpeaa)DE-He213 Molecular subgroups (dpeaa)DE-He213 Brazilian cohort (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 Salomão, Karina Bezerra aut de Biagi Jr, Carlos Alberto Oliveira aut Baumgartner, Martin aut Sturm, Dominik aut Lira, Régia Caroline Peixoto aut de Almeida Magalhães, Taciani aut Baroni Milan, Mirella aut da Silva Silveira, Vanessa aut Saggioro, Fabiano Pinto aut de Oliveira, Ricardo Santos aut dos Santos Klinger, Paulo Henrique aut Seidinger, Ana Luiza aut Yunes, José Andrés aut de Paula Queiroz, Rosane Gomes aut Oba-Shinjo, Sueli Mieko aut Scrideli, Carlos Alberto aut Nagahashi, Suely Marie Kazue aut Tone, Luiz Gonzaga aut Valera, Elvis Terci aut Enthalten in Acta Neuropathologica Communications London : Biomed Central, 2013 7(2019), 1 vom: 04. März (DE-627)746066465 (DE-600)2715589-4 2051-5960 nnns volume:7 year:2019 number:1 day:04 month:03 https://dx.doi.org/10.1186/s40478-019-0681-y kostenfrei 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_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 7 2019 1 04 03
spelling	10.1186/s40478-019-0681-y doi (DE-627)SPR036514772 (SPR)s40478-019-0681-y-e DE-627 ger DE-627 rakwb eng Cruzeiro, Gustavo Alencastro Veiga verfasserin (orcid)0000-0002-0005-3984 aut A simplified approach using Taqman low-density array for medulloblastoma subgrouping 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. Medulloblastoma (dpeaa)DE-He213 Molecular subgroups (dpeaa)DE-He213 Brazilian cohort (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 Salomão, Karina Bezerra aut de Biagi Jr, Carlos Alberto Oliveira aut Baumgartner, Martin aut Sturm, Dominik aut Lira, Régia Caroline Peixoto aut de Almeida Magalhães, Taciani aut Baroni Milan, Mirella aut da Silva Silveira, Vanessa aut Saggioro, Fabiano Pinto aut de Oliveira, Ricardo Santos aut dos Santos Klinger, Paulo Henrique aut Seidinger, Ana Luiza aut Yunes, José Andrés aut de Paula Queiroz, Rosane Gomes aut Oba-Shinjo, Sueli Mieko aut Scrideli, Carlos Alberto aut Nagahashi, Suely Marie Kazue aut Tone, Luiz Gonzaga aut Valera, Elvis Terci aut Enthalten in Acta Neuropathologica Communications London : Biomed Central, 2013 7(2019), 1 vom: 04. März (DE-627)746066465 (DE-600)2715589-4 2051-5960 nnns volume:7 year:2019 number:1 day:04 month:03 https://dx.doi.org/10.1186/s40478-019-0681-y kostenfrei 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_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 7 2019 1 04 03
allfields_unstemmed	10.1186/s40478-019-0681-y doi (DE-627)SPR036514772 (SPR)s40478-019-0681-y-e DE-627 ger DE-627 rakwb eng Cruzeiro, Gustavo Alencastro Veiga verfasserin (orcid)0000-0002-0005-3984 aut A simplified approach using Taqman low-density array for medulloblastoma subgrouping 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. Medulloblastoma (dpeaa)DE-He213 Molecular subgroups (dpeaa)DE-He213 Brazilian cohort (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 Salomão, Karina Bezerra aut de Biagi Jr, Carlos Alberto Oliveira aut Baumgartner, Martin aut Sturm, Dominik aut Lira, Régia Caroline Peixoto aut de Almeida Magalhães, Taciani aut Baroni Milan, Mirella aut da Silva Silveira, Vanessa aut Saggioro, Fabiano Pinto aut de Oliveira, Ricardo Santos aut dos Santos Klinger, Paulo Henrique aut Seidinger, Ana Luiza aut Yunes, José Andrés aut de Paula Queiroz, Rosane Gomes aut Oba-Shinjo, Sueli Mieko aut Scrideli, Carlos Alberto aut Nagahashi, Suely Marie Kazue aut Tone, Luiz Gonzaga aut Valera, Elvis Terci aut Enthalten in Acta Neuropathologica Communications London : Biomed Central, 2013 7(2019), 1 vom: 04. März (DE-627)746066465 (DE-600)2715589-4 2051-5960 nnns volume:7 year:2019 number:1 day:04 month:03 https://dx.doi.org/10.1186/s40478-019-0681-y kostenfrei 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_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 7 2019 1 04 03
allfieldsGer	10.1186/s40478-019-0681-y doi (DE-627)SPR036514772 (SPR)s40478-019-0681-y-e DE-627 ger DE-627 rakwb eng Cruzeiro, Gustavo Alencastro Veiga verfasserin (orcid)0000-0002-0005-3984 aut A simplified approach using Taqman low-density array for medulloblastoma subgrouping 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. Medulloblastoma (dpeaa)DE-He213 Molecular subgroups (dpeaa)DE-He213 Brazilian cohort (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 Salomão, Karina Bezerra aut de Biagi Jr, Carlos Alberto Oliveira aut Baumgartner, Martin aut Sturm, Dominik aut Lira, Régia Caroline Peixoto aut de Almeida Magalhães, Taciani aut Baroni Milan, Mirella aut da Silva Silveira, Vanessa aut Saggioro, Fabiano Pinto aut de Oliveira, Ricardo Santos aut dos Santos Klinger, Paulo Henrique aut Seidinger, Ana Luiza aut Yunes, José Andrés aut de Paula Queiroz, Rosane Gomes aut Oba-Shinjo, Sueli Mieko aut Scrideli, Carlos Alberto aut Nagahashi, Suely Marie Kazue aut Tone, Luiz Gonzaga aut Valera, Elvis Terci aut Enthalten in Acta Neuropathologica Communications London : Biomed Central, 2013 7(2019), 1 vom: 04. März (DE-627)746066465 (DE-600)2715589-4 2051-5960 nnns volume:7 year:2019 number:1 day:04 month:03 https://dx.doi.org/10.1186/s40478-019-0681-y kostenfrei 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_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 7 2019 1 04 03
allfieldsSound	10.1186/s40478-019-0681-y doi (DE-627)SPR036514772 (SPR)s40478-019-0681-y-e DE-627 ger DE-627 rakwb eng Cruzeiro, Gustavo Alencastro Veiga verfasserin (orcid)0000-0002-0005-3984 aut A simplified approach using Taqman low-density array for medulloblastoma subgrouping 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. Medulloblastoma (dpeaa)DE-He213 Molecular subgroups (dpeaa)DE-He213 Brazilian cohort (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213 Salomão, Karina Bezerra aut de Biagi Jr, Carlos Alberto Oliveira aut Baumgartner, Martin aut Sturm, Dominik aut Lira, Régia Caroline Peixoto aut de Almeida Magalhães, Taciani aut Baroni Milan, Mirella aut da Silva Silveira, Vanessa aut Saggioro, Fabiano Pinto aut de Oliveira, Ricardo Santos aut dos Santos Klinger, Paulo Henrique aut Seidinger, Ana Luiza aut Yunes, José Andrés aut de Paula Queiroz, Rosane Gomes aut Oba-Shinjo, Sueli Mieko aut Scrideli, Carlos Alberto aut Nagahashi, Suely Marie Kazue aut Tone, Luiz Gonzaga aut Valera, Elvis Terci aut Enthalten in Acta Neuropathologica Communications London : Biomed Central, 2013 7(2019), 1 vom: 04. März (DE-627)746066465 (DE-600)2715589-4 2051-5960 nnns volume:7 year:2019 number:1 day:04 month:03 https://dx.doi.org/10.1186/s40478-019-0681-y kostenfrei 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_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 7 2019 1 04 03
language	English
source	Enthalten in Acta Neuropathologica Communications 7(2019), 1 vom: 04. März volume:7 year:2019 number:1 day:04 month:03
sourceStr	Enthalten in Acta Neuropathologica Communications 7(2019), 1 vom: 04. März volume:7 year:2019 number:1 day:04 month:03
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Medulloblastoma Molecular subgroups Brazilian cohort Real-time PCR
isfreeaccess_bool	true
container_title	Acta Neuropathologica Communications
authorswithroles_txt_mv	Cruzeiro, Gustavo Alencastro Veiga @@aut@@ Salomão, Karina Bezerra @@aut@@ de Biagi Jr, Carlos Alberto Oliveira @@aut@@ Baumgartner, Martin @@aut@@ Sturm, Dominik @@aut@@ Lira, Régia Caroline Peixoto @@aut@@ de Almeida Magalhães, Taciani @@aut@@ Baroni Milan, Mirella @@aut@@ da Silva Silveira, Vanessa @@aut@@ Saggioro, Fabiano Pinto @@aut@@ de Oliveira, Ricardo Santos @@aut@@ dos Santos Klinger, Paulo Henrique @@aut@@ Seidinger, Ana Luiza @@aut@@ Yunes, José Andrés @@aut@@ de Paula Queiroz, Rosane Gomes @@aut@@ Oba-Shinjo, Sueli Mieko @@aut@@ Scrideli, Carlos Alberto @@aut@@ Nagahashi, Suely Marie Kazue @@aut@@ Tone, Luiz Gonzaga @@aut@@ Valera, Elvis Terci @@aut@@
publishDateDaySort_date	2019-03-04T00:00:00Z
hierarchy_top_id	746066465
id	SPR036514772
language_de	englisch
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author	Cruzeiro, Gustavo Alencastro Veiga
spellingShingle	Cruzeiro, Gustavo Alencastro Veiga misc Medulloblastoma misc Molecular subgroups misc Brazilian cohort misc Real-time PCR A simplified approach using Taqman low-density array for medulloblastoma subgrouping
authorStr	Cruzeiro, Gustavo Alencastro Veiga
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topic_title	A simplified approach using Taqman low-density array for medulloblastoma subgrouping Medulloblastoma (dpeaa)DE-He213 Molecular subgroups (dpeaa)DE-He213 Brazilian cohort (dpeaa)DE-He213 Real-time PCR (dpeaa)DE-He213
topic	misc Medulloblastoma misc Molecular subgroups misc Brazilian cohort misc Real-time PCR
topic_unstemmed	misc Medulloblastoma misc Molecular subgroups misc Brazilian cohort misc Real-time PCR
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title	A simplified approach using Taqman low-density array for medulloblastoma subgrouping
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title_full	A simplified approach using Taqman low-density array for medulloblastoma subgrouping
author_sort	Cruzeiro, Gustavo Alencastro Veiga
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author_browse	Cruzeiro, Gustavo Alencastro Veiga Salomão, Karina Bezerra de Biagi Jr, Carlos Alberto Oliveira Baumgartner, Martin Sturm, Dominik Lira, Régia Caroline Peixoto de Almeida Magalhães, Taciani Baroni Milan, Mirella da Silva Silveira, Vanessa Saggioro, Fabiano Pinto de Oliveira, Ricardo Santos dos Santos Klinger, Paulo Henrique Seidinger, Ana Luiza Yunes, José Andrés de Paula Queiroz, Rosane Gomes Oba-Shinjo, Sueli Mieko Scrideli, Carlos Alberto Nagahashi, Suely Marie Kazue Tone, Luiz Gonzaga Valera, Elvis Terci
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title_sort	simplified approach using taqman low-density array for medulloblastoma subgrouping
title_auth	A simplified approach using Taqman low-density array for medulloblastoma subgrouping
abstract	Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. © The Author(s). 2019
abstractGer	Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. © The Author(s). 2019
abstract_unstemmed	Abstract Next-generation sequencing platforms are routinely used for molecular assignment due to their high impact for risk stratification and prognosis in medulloblastomas. Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. A simplified method using six genes and restricting the final stratification into SHH, WNT and non-SHH/non-WNT appears to be a very interesting approach for rapid clinical decision-making. © The Author(s). 2019
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title_short	A simplified approach using Taqman low-density array for medulloblastoma subgrouping
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Yet, low and middle-income countries still lack an accurate cost-effective platform to perform this allocation. TaqMan Low Density array (TLDA) assay was performed using a set of 20 genes in 92 medulloblastoma samples. The same methodology was assessed in silico using microarray data for 763 medulloblastoma samples from the GSE85217 study, which performed MB classification by a robust integrative method (Transcriptional, Methylation and cytogenetic profile). Furthermore, we validated in 11 MBs samples our proposed method by Methylation Array 450 K to assess methylation profile along with 390 MB samples (GSE109381) and copy number variations. TLDA with only 20 genes accurately assigned MB samples into WNT, SHH, Group 3 and Group 4 using Pearson distance with the average-linkage algorithm and showed concordance with molecular assignment provided by Methylation Array 450 k. Similarly, we tested this simplified set of gene signatures in 763 MB samples and we were able to recapitulate molecular assignment with an accuracy of 99.1% (SHH), 94.29% (WNT), 92.36% (Group 3) and 95.40% (Group 4), against 97.31, 97.14, 88.89 and 97.24% (respectively) with the Ward.D2 algorithm. t-SNE analysis revealed a high level of concordance (k = 4) with minor overlapping features between Group 3 and Group 4. Finally, we condensed the number of genes to 6 without significantly losing accuracy in classifying samples into SHH, WNT and non-SHH/non-WNT subgroups. Additionally, we found a relatively high frequency of WNT subgroup in our cohort, which requires further epidemiological studies. TLDA is a rapid, simple and cost-effective assay for classifying MB in low/middle income countries. 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A simplified approach using Taqman low-density array for medulloblastoma subgrouping

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