OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma

Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and event...
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Autor*in:	Yang An [verfasserIn] Qiang Wang [verfasserIn] Lu Zhang [verfasserIn] Fengjie Sun [verfasserIn] Guosen Zhang [verfasserIn] Huan Dong [verfasserIn] Yingkun Li [verfasserIn] Yanyu Peng [verfasserIn] Haojie Li [verfasserIn] Wan Zhu [verfasserIn] Shaoping Ji [verfasserIn] Yunlong Wang [verfasserIn] Xiangqian Guo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome

Übergeordnetes Werk:	In: Frontiers in Oncology - Frontiers Media S.A., 2012, 10(2020)
Übergeordnetes Werk:	volume:10 ; year:2020

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fonc.2020.01097

Katalog-ID:	DOAJ019825714

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520			\|a Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp.
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allfields	10.3389/fonc.2020.01097 doi (DE-627)DOAJ019825714 (DE-599)DOAJb324002ba5b54a94b5e95e11294c87f6 DE-627 ger DE-627 rakwb eng RC254-282 Yang An verfasserin aut OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome Neoplasms. Tumors. Oncology. Including cancer and carcinogens Qiang Wang verfasserin aut Lu Zhang verfasserin aut Fengjie Sun verfasserin aut Guosen Zhang verfasserin aut Huan Dong verfasserin aut Yingkun Li verfasserin aut Yanyu Peng verfasserin aut Haojie Li verfasserin aut Wan Zhu verfasserin aut Shaoping Ji verfasserin aut Yunlong Wang verfasserin aut Xiangqian Guo verfasserin aut In Frontiers in Oncology Frontiers Media S.A., 2012 10(2020) (DE-627)684965518 (DE-600)2649216-7 2234943X nnns volume:10 year:2020 https://doi.org/10.3389/fonc.2020.01097 kostenfrei https://doaj.org/article/b324002ba5b54a94b5e95e11294c87f6 kostenfrei https://www.frontiersin.org/article/10.3389/fonc.2020.01097/full kostenfrei https://doaj.org/toc/2234-943X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 10 2020
spelling	10.3389/fonc.2020.01097 doi (DE-627)DOAJ019825714 (DE-599)DOAJb324002ba5b54a94b5e95e11294c87f6 DE-627 ger DE-627 rakwb eng RC254-282 Yang An verfasserin aut OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome Neoplasms. Tumors. Oncology. Including cancer and carcinogens Qiang Wang verfasserin aut Lu Zhang verfasserin aut Fengjie Sun verfasserin aut Guosen Zhang verfasserin aut Huan Dong verfasserin aut Yingkun Li verfasserin aut Yanyu Peng verfasserin aut Haojie Li verfasserin aut Wan Zhu verfasserin aut Shaoping Ji verfasserin aut Yunlong Wang verfasserin aut Xiangqian Guo verfasserin aut In Frontiers in Oncology Frontiers Media S.A., 2012 10(2020) (DE-627)684965518 (DE-600)2649216-7 2234943X nnns volume:10 year:2020 https://doi.org/10.3389/fonc.2020.01097 kostenfrei https://doaj.org/article/b324002ba5b54a94b5e95e11294c87f6 kostenfrei https://www.frontiersin.org/article/10.3389/fonc.2020.01097/full kostenfrei https://doaj.org/toc/2234-943X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 10 2020
allfields_unstemmed	10.3389/fonc.2020.01097 doi (DE-627)DOAJ019825714 (DE-599)DOAJb324002ba5b54a94b5e95e11294c87f6 DE-627 ger DE-627 rakwb eng RC254-282 Yang An verfasserin aut OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome Neoplasms. Tumors. Oncology. Including cancer and carcinogens Qiang Wang verfasserin aut Lu Zhang verfasserin aut Fengjie Sun verfasserin aut Guosen Zhang verfasserin aut Huan Dong verfasserin aut Yingkun Li verfasserin aut Yanyu Peng verfasserin aut Haojie Li verfasserin aut Wan Zhu verfasserin aut Shaoping Ji verfasserin aut Yunlong Wang verfasserin aut Xiangqian Guo verfasserin aut In Frontiers in Oncology Frontiers Media S.A., 2012 10(2020) (DE-627)684965518 (DE-600)2649216-7 2234943X nnns volume:10 year:2020 https://doi.org/10.3389/fonc.2020.01097 kostenfrei https://doaj.org/article/b324002ba5b54a94b5e95e11294c87f6 kostenfrei https://www.frontiersin.org/article/10.3389/fonc.2020.01097/full kostenfrei https://doaj.org/toc/2234-943X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 10 2020
allfieldsGer	10.3389/fonc.2020.01097 doi (DE-627)DOAJ019825714 (DE-599)DOAJb324002ba5b54a94b5e95e11294c87f6 DE-627 ger DE-627 rakwb eng RC254-282 Yang An verfasserin aut OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome Neoplasms. Tumors. Oncology. Including cancer and carcinogens Qiang Wang verfasserin aut Lu Zhang verfasserin aut Fengjie Sun verfasserin aut Guosen Zhang verfasserin aut Huan Dong verfasserin aut Yingkun Li verfasserin aut Yanyu Peng verfasserin aut Haojie Li verfasserin aut Wan Zhu verfasserin aut Shaoping Ji verfasserin aut Yunlong Wang verfasserin aut Xiangqian Guo verfasserin aut In Frontiers in Oncology Frontiers Media S.A., 2012 10(2020) (DE-627)684965518 (DE-600)2649216-7 2234943X nnns volume:10 year:2020 https://doi.org/10.3389/fonc.2020.01097 kostenfrei https://doaj.org/article/b324002ba5b54a94b5e95e11294c87f6 kostenfrei https://www.frontiersin.org/article/10.3389/fonc.2020.01097/full kostenfrei https://doaj.org/toc/2234-943X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 10 2020
allfieldsSound	10.3389/fonc.2020.01097 doi (DE-627)DOAJ019825714 (DE-599)DOAJb324002ba5b54a94b5e95e11294c87f6 DE-627 ger DE-627 rakwb eng RC254-282 Yang An verfasserin aut OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp. low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome Neoplasms. Tumors. Oncology. Including cancer and carcinogens Qiang Wang verfasserin aut Lu Zhang verfasserin aut Fengjie Sun verfasserin aut Guosen Zhang verfasserin aut Huan Dong verfasserin aut Yingkun Li verfasserin aut Yanyu Peng verfasserin aut Haojie Li verfasserin aut Wan Zhu verfasserin aut Shaoping Ji verfasserin aut Yunlong Wang verfasserin aut Xiangqian Guo verfasserin aut In Frontiers in Oncology Frontiers Media S.A., 2012 10(2020) (DE-627)684965518 (DE-600)2649216-7 2234943X nnns volume:10 year:2020 https://doi.org/10.3389/fonc.2020.01097 kostenfrei https://doaj.org/article/b324002ba5b54a94b5e95e11294c87f6 kostenfrei https://www.frontiersin.org/article/10.3389/fonc.2020.01097/full kostenfrei https://doaj.org/toc/2234-943X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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_2014 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 10 2020
language	English
source	In Frontiers in Oncology 10(2020) volume:10 year:2020
sourceStr	In Frontiers in Oncology 10(2020) volume:10 year:2020
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container_title	Frontiers in Oncology
authorswithroles_txt_mv	Yang An @@aut@@ Qiang Wang @@aut@@ Lu Zhang @@aut@@ Fengjie Sun @@aut@@ Guosen Zhang @@aut@@ Huan Dong @@aut@@ Yingkun Li @@aut@@ Yanyu Peng @@aut@@ Haojie Li @@aut@@ Wan Zhu @@aut@@ Shaoping Ji @@aut@@ Yunlong Wang @@aut@@ Xiangqian Guo @@aut@@
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callnumber-first	R - Medicine
author	Yang An
spellingShingle	Yang An misc RC254-282 misc low-grade glioma misc prognostic biomarker misc gene expression profiling misc survival analysis misc survival outcome misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma
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topic_title	RC254-282 OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma low-grade glioma prognostic biomarker gene expression profiling survival analysis survival outcome
topic	misc RC254-282 misc low-grade glioma misc prognostic biomarker misc gene expression profiling misc survival analysis misc survival outcome misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_unstemmed	misc RC254-282 misc low-grade glioma misc prognostic biomarker misc gene expression profiling misc survival analysis misc survival outcome misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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title	OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma
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title_full	OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma
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title_sort	oslgg: an online prognostic biomarker analysis tool for low-grade glioma
callnumber	RC254-282
title_auth	OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma
abstract	Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp.
abstractGer	Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp.
abstract_unstemmed	Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at http://bioinfo.henu.edu.cn/LGG/LGGList.jsp.
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title_short	OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma
url	https://doi.org/10.3389/fonc.2020.01097 https://doaj.org/article/b324002ba5b54a94b5e95e11294c87f6 https://www.frontiersin.org/article/10.3389/fonc.2020.01097/full https://doaj.org/toc/2234-943X
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author2	Qiang Wang Lu Zhang Fengjie Sun Guosen Zhang Huan Dong Yingkun Li Yanyu Peng Haojie Li Wan Zhu Shaoping Ji Yunlong Wang Xiangqian Guo
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up_date	2024-07-04T01:06:08.142Z
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The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. 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OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma

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