Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer
Aberrant DNA methylation is significantly associated with breast cancer. In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA pattern...
Saved in:
| Published in | World journal of surgical oncology Vol. 19; no. 1; p. 29 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
BioMed Central Ltd
26.01.2021
BioMed Central BMC |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Aberrant DNA methylation is significantly associated with breast cancer.
In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis.
In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival.
Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. |
|---|---|
| AbstractList | Abstract
Background
Aberrant DNA methylation is significantly associated with breast cancer.
Methods
In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis.
Results
In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes,
ADCY4
,
CPXM1
,
DNM3
,
GNG4
,
MAST1
,
mir129-2
,
PRDM14
, and
ZNF177
were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (
ADCY4
,
CPXM1
,
DNM3
,
GNG4
,
MAST1
,
PRDM14
,
ZNF177
) was 0.9998 [95% CI 0.9994–1], and the AUC for the combined signature of 3 genes (
MAST1
,
PRDM14
, and
ZNF177
) was 0.9991 [95% CI 0.9976–1]. Results from additional validation analyses showed that
MAST1
,
PRDM14
, and
ZNF177
had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of
ADCY4
,
CPXM1
,
DNM3
,
PRDM14
,
PRKCB
, and
ZNF177
were significantly associated with better overall survival.
Conclusions
Methylation pattern of
MAST1
,
PRDM14
, and
ZNF177
may represent new diagnostic biomarkers for breast cancer, while methylation of
ADCY4
,
CPXM1
,
DNM3
,
PRDM14
,
PRKCB
, and
ZNF177
may hold prognostic potential for breast cancer. BACKGROUNDAberrant DNA methylation is significantly associated with breast cancer. METHODSIn this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. RESULTSIn this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. CONCLUSIONSMethylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. Aberrant DNA methylation is significantly associated with breast cancer. In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. Aberrant DNA methylation is significantly associated with breast cancer. In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. Results In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994–1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976–1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Conclusions Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. Results In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994-1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976-1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Conclusions Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. Keywords: Breast cancer, Methylation, Biomarkers, Diagnosis, Prognosis Abstract Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation biomarkers using a bioinformatics analysis approach that could have clinical value for breast cancer diagnosis and prognosis. Firstly, differentially methylated DNA patterns were detected in breast cancer samples by comparing publicly available datasets (GSE72245 and GSE88883). Methylation levels in 7 selected methylation biomarkers were also estimated using the online tool UALCAN. Next, we evaluated the diagnostic value of these selected biomarkers in two independent cohorts, as well as in two mixed cohorts, through ROC curve analysis. Finally, prognostic value of the selected methylation biomarkers was evaluated breast cancer by the Kaplan-Meier plot analysis. Results In this study, a total of 23 significant differentially methylated sites, corresponding to 9 different genes, were identified in breast cancer datasets. Among the 9 identified genes, ADCY4, CPXM1, DNM3, GNG4, MAST1, mir129-2, PRDM14, and ZNF177 were hypermethylated. Importantly, individual value of each selected methylation gene was greater than 0.9, whereas predictive value for all genes combined was 0.9998. We also found the AUC for the combined signature of 7 genes (ADCY4, CPXM1, DNM3, GNG4, MAST1, PRDM14, ZNF177) was 0.9998 [95% CI 0.9994–1], and the AUC for the combined signature of 3 genes (MAST1, PRDM14, and ZNF177) was 0.9991 [95% CI 0.9976–1]. Results from additional validation analyses showed that MAST1, PRDM14, and ZNF177 had high sensitivity, specificity, and accuracy for breast cancer diagnosis. Lastly, patient survival analysis revealed that high expression of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 were significantly associated with better overall survival. Conclusions Methylation pattern of MAST1, PRDM14, and ZNF177 may represent new diagnostic biomarkers for breast cancer, while methylation of ADCY4, CPXM1, DNM3, PRDM14, PRKCB, and ZNF177 may hold prognostic potential for breast cancer. |
| ArticleNumber | 29 |
| Audience | Academic |
| Author | Huang, Ping Zhang, Guo-Bing Ye, Zi-Qi Xuan, Zi-Xue Ye, Qiang Jiang, Jin-Ying Zhao, Hong-Ying Mao, Xiao-Hong Shao, Yan-Fei |
| Author_xml | – sequence: 1 givenname: Xiao-Hong surname: Mao fullname: Mao, Xiao-Hong organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China – sequence: 2 givenname: Qiang surname: Ye fullname: Ye, Qiang organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China – sequence: 3 givenname: Guo-Bing surname: Zhang fullname: Zhang, Guo-Bing organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China – sequence: 4 givenname: Jin-Ying surname: Jiang fullname: Jiang, Jin-Ying organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China – sequence: 5 givenname: Hong-Ying surname: Zhao fullname: Zhao, Hong-Ying organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China – sequence: 6 givenname: Yan-Fei surname: Shao fullname: Shao, Yan-Fei organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China – sequence: 7 givenname: Zi-Qi surname: Ye fullname: Ye, Zi-Qi organization: Department of Pharmacy, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China – sequence: 8 givenname: Zi-Xue orcidid: 0000-0002-6296-4062 surname: Xuan fullname: Xuan, Zi-Xue email: xuanzixue0222@163.com organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China. xuanzixue0222@163.com – sequence: 9 givenname: Ping surname: Huang fullname: Huang, Ping email: huangping1841@zjcc.org.cn organization: Department of Pharmacy, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China. huangping1841@zjcc.org.cn |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33499882$$D View this record in MEDLINE/PubMed |
| BookMark | eNptklFv0zAUhS00xLbCH-ABRUJCe8mw49ixX5CmiUGlSbzAs3Vr37QuqV3sFKn_HmfdRotQZMW5-e7J9cm5JGchBiTkLaPXjCn5MbNGi66mDZtW09byBblgbdfVnWL67Gh_Ti5zXlPacC74K3LOeau1Us0FWc8dhtH33sLoY6hiXznf95imKgzDvtrguNoPMKKrlhgwV5ALAssQ8-htBcFV2xSfHhc-biD9xJQnqUVCyGNlIVhMr8nLHoaMbx7vM_Lj7vP326_1_bcv89ub-9oK3Y6161yrlJQOpYaOU0tbrUTP0WouKQBVAnQnmQK6kLrRzComO0YbqZEKK_iMzA-6LsLabJMvA-1NBG8eCjEtDaQy64BGcsuRdUpwTlsOTjGFGrhmQqpFsapofTpobXeLDTpbXEkwnIievgl-ZZbxt-lUUVG6CFw9CqT4a4d5NBufLQ4DBIy7bJq2TC8oE01B3_-DruMuhWJVoTRrG1r--l9qCeUAPvSxfNdOouamCLWiMBN1_R-qXA433pYY9b7UTxo-HDWsEIZxleOwm0KRT8HmANoUc07YP5vBqJliaQ6xNCWS5iGWxeUZeXds43PLUw75H9Z_3NE |
| CitedBy_id | crossref_primary_10_3390_cancers13061375 crossref_primary_10_3390_cancers15215274 crossref_primary_10_1016_j_ijbiomac_2022_03_090 crossref_primary_10_3390_ijms23115962 crossref_primary_10_1002_cam4_5623 crossref_primary_10_1186_s12957_021_02387_z crossref_primary_10_1186_s12957_021_02363_7 crossref_primary_10_3892_ol_2022_13237 crossref_primary_10_1186_s12957_021_02301_7 crossref_primary_10_3390_ijms241612660 crossref_primary_10_1007_s40944_023_00783_9 crossref_primary_10_3390_cancers13071739 crossref_primary_10_2147_BCTT_S408711 crossref_primary_10_1186_s13148_022_01386_5 crossref_primary_10_3390_ijms241511913 crossref_primary_10_1016_j_bspc_2021_103009 crossref_primary_10_3390_cancers14215444 crossref_primary_10_1186_s12957_022_02667_2 crossref_primary_10_3389_fgene_2022_991706 crossref_primary_10_1016_j_heliyon_2024_e28162 crossref_primary_10_1186_s12957_022_02828_3 |
| Cites_doi | 10.1158/0008-5472.CAN-19-1019 10.1038/s41419-020-2532-y 10.1093/carcin/bgu197 10.1158/1078-0432.CCR-18-3277 10.1158/1078-0432.CCR-15-2346 10.1186/s13148-016-0282-6 10.1002/1878-0261.12309 10.1186/s13058-020-1250-9 10.1186/s12885-019-5403-0 10.1016/j.annonc.2019.11.014 10.1038/s41571-018-0004-4 10.3389/fgene.2020.00294 10.1016/j.tjog.2015.08.010 10.1016/j.neo.2017.05.002 10.1136/gutjnl-2016-313372 10.1186/s12864-019-6142-y 10.3892/ijo.2016.3607 10.1038/s41467-020-15042-0 10.1093/annonc/mdt303 10.1186/s41512-019-0065-6 10.3390/cancers11101598 10.1016/j.ygyno.2019.11.028 10.1158/0008-5472.CAN-15-3278 10.1016/j.ccell.2018.06.012 10.1007/978-3-030-22254-3_14 10.3322/caac.21492 |
| ContentType | Journal Article |
| Copyright | COPYRIGHT 2021 BioMed Central Ltd. 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Author(s) 2021 |
| Copyright_xml | – notice: COPYRIGHT 2021 BioMed Central Ltd. – notice: 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: The Author(s) 2021 |
| DBID | CGR CUY CVF ECM EIF NPM AAYXX CITATION 3V. 7QL 7QO 7X7 7XB 88E 8FD 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR C1K CCPQU DWQXO FR3 FYUFA GHDGH K9. M0S M1P P64 PIMPY PQEST PQQKQ PQUKI 7X8 5PM DOA |
| DOI | 10.1186/s12957-021-02124-6 |
| DatabaseName | Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed CrossRef ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts ProQuest_Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Technology Research Database Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central ProQuest Central Essentials ProQuest Central Environmental Sciences and Pollution Management ProQuest One Community College ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Health & Medical Complete (Alumni) Health & Medical Collection (Alumni Edition) PML(ProQuest Medical Library) Biotechnology and BioEngineering Abstracts ProQuest - Publicly Available Content Database ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition MEDLINE - Academic PubMed Central (Full Participant titles) Directory of Open Access Journals |
| DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) CrossRef Publicly Available Content Database Technology Research Database ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College Environmental Sciences and Pollution Management ProQuest Central Health Research Premium Collection Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) ProQuest Medical Library (Alumni) ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition Engineering Research Database ProQuest One Academic ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | CrossRef MEDLINE - Academic MEDLINE Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: DOA name: Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 4 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1477-7819 |
| EndPage | 29 |
| ExternalDocumentID | oai_doaj_org_article_63c3e178533043ad818e9a391568b353 A650451838 10_1186_s12957_021_02124_6 33499882 |
| Genre | Journal Article |
| GeographicLocations | China |
| GeographicLocations_xml | – name: China |
| GrantInformation_xml | – fundername: the major Project for Medical and Health Science and Technology of Zhejiang Province grantid: No. WKJ-ZJ-1716 – fundername: the General Project Funds from the Health Department of Zhejiang Province grantid: No. 2016KYB026 – fundername: the Project of Application on Public Welfare Technology in Zhejiang Province grantid: No. LGF18H160022 – fundername: ; grantid: No. WKJ-ZJ-1716 – fundername: ; grantid: No. LGF18H160022 – fundername: ; grantid: No. 2016KYB026 |
| GroupedDBID | --- -A0 0R~ 29R 2WC 3V. 53G 5VS 7X7 88E 8FI 8FJ AAFWJ AAJSJ ABDBF ABUWG ACGFO ACGFS ACIHN ACIWK ACPRK ACRMQ ADBBV ADINQ ADRAZ ADUKV AEAQA AENEX AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALIPV ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS BAPOH BAWUL BCNDV BENPR BFQNJ BMC BPHCQ BVXVI C24 C6C CCPQU CGR CS3 CUY CVF DIK DU5 E3Z EBD EBLON EBS ECM EIF ESX F5P FRP FYUFA GROUPED_DOAJ GX1 HMCUK IAO IHR IHW INH INR ITC KQ8 M1P M48 M~E NPM O5R O5S OK1 P2P PGMZT PIMPY PQQKQ PROAC PSQYO RBZ RNS ROL RPM RSV SMD SOJ TR2 TUS UKHRP W2D WOQ WOW XSB ~8M AAYXX CITATION AFGXO ABVAZ AFNRJ 7QL 7QO 7XB 8FD 8FK AZQEC C1K DWQXO FR3 K9. P64 PQEST PQUKI 7X8 5PM |
| ID | FETCH-LOGICAL-c594t-d7d48866de69a730c04985f3ec9360aa085a97618a0b69291c816710269e05c53 |
| IEDL.DBID | RPM |
| ISSN | 1477-7819 |
| IngestDate | Tue Oct 22 15:16:31 EDT 2024 Tue Sep 17 21:28:06 EDT 2024 Fri Oct 25 03:12:00 EDT 2024 Thu Oct 10 22:03:30 EDT 2024 Fri Feb 23 00:06:11 EST 2024 Tue Nov 12 22:32:47 EST 2024 Tue Aug 20 22:12:41 EDT 2024 Thu Sep 12 19:37:11 EDT 2024 Sat Sep 28 08:26:51 EDT 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | Biomarkers Breast cancer Prognosis Diagnosis Methylation |
| Language | English |
| License | Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c594t-d7d48866de69a730c04985f3ec9360aa085a97618a0b69291c816710269e05c53 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ORCID | 0000-0002-6296-4062 |
| OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7839189/ |
| PMID | 33499882 |
| PQID | 2491420118 |
| PQPubID | 42870 |
| PageCount | 1 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_63c3e178533043ad818e9a391568b353 pubmedcentral_primary_oai_pubmedcentral_nih_gov_7839189 proquest_miscellaneous_2481650152 proquest_journals_2491420118 gale_infotracmisc_A650451838 gale_infotracacademiconefile_A650451838 gale_healthsolutions_A650451838 crossref_primary_10_1186_s12957_021_02124_6 pubmed_primary_33499882 |
| PublicationCentury | 2000 |
| PublicationDate | 2021-01-26 |
| PublicationDateYYYYMMDD | 2021-01-26 |
| PublicationDate_xml | – month: 01 year: 2021 text: 2021-01-26 day: 26 |
| PublicationDecade | 2020 |
| PublicationPlace | England |
| PublicationPlace_xml | – name: England – name: London |
| PublicationTitle | World journal of surgical oncology |
| PublicationTitleAlternate | World J Surg Oncol |
| PublicationYear | 2021 |
| Publisher | BioMed Central Ltd BioMed Central BMC |
| Publisher_xml | – name: BioMed Central Ltd – name: BioMed Central – name: BMC |
| References | S Zhang (2124_CR11) 2018; 12 T Oishi (2124_CR25) 2017; 7 N Mahmood (2124_CR7) 2019; 1164 A Koch (2124_CR6) 2018; 15 YC Chen (2124_CR28) 2015; 54 DS Chandrashekar (2124_CR16) 2017; 19 2124_CR19 F Bray (2124_CR1) 2018; 68 BM Downs (2124_CR5) 2019; 25 TC de Ruijter (2124_CR12) 2020; 22 S Dong (2124_CR10) 2019; 79 L Lv (2124_CR18) 2020; 11 J Moss (2124_CR13) 2020; 31 X Chen (2124_CR4) 2019; 20 S Snellenberg (2124_CR27) 2014; 35 F Picardo (2124_CR9) 2019; 11 A Diaz-Lagares (2124_CR17) 2016; 22 X Yu (2124_CR24) 2020; 11 A Goldhirsch (2124_CR2) 2013; 24 X Sun (2124_CR20) 2020; 13 H Taniguchi (2124_CR26) 1974; 2019 L Barault (2124_CR15) 2018; 67 Q Tang (2124_CR3) 2016; 8 M Klutstein (2124_CR8) 2016; 76 M Nakakido (2124_CR29) 2016; 49 TC de Ruijter (2124_CR21) 2019; 3 A Sybirna (2124_CR22) 2020; 11 L Jin (2124_CR23) 2018; 34 A Sangtani (2124_CR14) 2020; 156 |
| References_xml | – volume: 79 start-page: 6101 year: 2019 ident: 2124_CR10 publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-19-1019 contributor: fullname: S Dong – volume: 11 start-page: 340 year: 2020 ident: 2124_CR24 publication-title: Cell Death Dis doi: 10.1038/s41419-020-2532-y contributor: fullname: X Yu – volume: 35 start-page: 2611 year: 2014 ident: 2124_CR27 publication-title: Carcinogenesis doi: 10.1093/carcin/bgu197 contributor: fullname: S Snellenberg – volume: 25 start-page: 6357 year: 2019 ident: 2124_CR5 publication-title: Clin Cancer Res doi: 10.1158/1078-0432.CCR-18-3277 contributor: fullname: BM Downs – volume: 13 start-page: 4 year: 2020 ident: 2124_CR20 publication-title: BMC Med Genet contributor: fullname: X Sun – volume: 7 start-page: 12 year: 2017 ident: 2124_CR25 publication-title: J Clin Transl Endocrinol contributor: fullname: T Oishi – volume: 22 start-page: 3361 year: 2016 ident: 2124_CR17 publication-title: Clin Cancer Res doi: 10.1158/1078-0432.CCR-15-2346 contributor: fullname: A Diaz-Lagares – volume: 8 start-page: 115 year: 2016 ident: 2124_CR3 publication-title: Clin Epigenetics doi: 10.1186/s13148-016-0282-6 contributor: fullname: Q Tang – volume: 12 start-page: 1047 year: 2018 ident: 2124_CR11 publication-title: Mol Oncol doi: 10.1002/1878-0261.12309 contributor: fullname: S Zhang – volume: 22 start-page: 13 year: 2020 ident: 2124_CR12 publication-title: Breast Cancer Res doi: 10.1186/s13058-020-1250-9 contributor: fullname: TC de Ruijter – ident: 2124_CR19 doi: 10.1186/s12885-019-5403-0 – volume: 31 start-page: 395 year: 2020 ident: 2124_CR13 publication-title: Ann Oncol doi: 10.1016/j.annonc.2019.11.014 contributor: fullname: J Moss – volume: 15 start-page: 459 year: 2018 ident: 2124_CR6 publication-title: Nat Rev Clin Oncol doi: 10.1038/s41571-018-0004-4 contributor: fullname: A Koch – volume: 11 start-page: 294 year: 2020 ident: 2124_CR18 publication-title: Front Genet doi: 10.3389/fgene.2020.00294 contributor: fullname: L Lv – volume: 54 start-page: 572 year: 2015 ident: 2124_CR28 publication-title: Taiwan J Obstet Gynecol doi: 10.1016/j.tjog.2015.08.010 contributor: fullname: YC Chen – volume: 19 start-page: 649 year: 2017 ident: 2124_CR16 publication-title: Neoplasia doi: 10.1016/j.neo.2017.05.002 contributor: fullname: DS Chandrashekar – volume: 67 start-page: 1995 year: 2018 ident: 2124_CR15 publication-title: Gut doi: 10.1136/gutjnl-2016-313372 contributor: fullname: L Barault – volume: 20 start-page: 823 year: 2019 ident: 2124_CR4 publication-title: BMC Genomics doi: 10.1186/s12864-019-6142-y contributor: fullname: X Chen – volume: 49 start-page: 868 year: 2016 ident: 2124_CR29 publication-title: Int J Oncol doi: 10.3892/ijo.2016.3607 contributor: fullname: M Nakakido – volume: 11 start-page: 1282 year: 2020 ident: 2124_CR22 publication-title: Nat Commun doi: 10.1038/s41467-020-15042-0 contributor: fullname: A Sybirna – volume: 24 start-page: 2206 year: 2013 ident: 2124_CR2 publication-title: Ann Oncol doi: 10.1093/annonc/mdt303 contributor: fullname: A Goldhirsch – volume: 3 start-page: 20 year: 2019 ident: 2124_CR21 publication-title: Diagn Progn Res doi: 10.1186/s41512-019-0065-6 contributor: fullname: TC de Ruijter – volume: 2019 start-page: 233 year: 1974 ident: 2124_CR26 publication-title: Methods Mol Biol contributor: fullname: H Taniguchi – volume: 11 start-page: 1598 year: 2019 ident: 2124_CR9 publication-title: Cancers (Basel) doi: 10.3390/cancers11101598 contributor: fullname: F Picardo – volume: 156 start-page: 387 year: 2020 ident: 2124_CR14 publication-title: Gynecol Oncol doi: 10.1016/j.ygyno.2019.11.028 contributor: fullname: A Sangtani – volume: 76 start-page: 3446 year: 2016 ident: 2124_CR8 publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-15-3278 contributor: fullname: M Klutstein – volume: 34 start-page: 315 year: 2018 ident: 2124_CR23 publication-title: Cancer Cell doi: 10.1016/j.ccell.2018.06.012 contributor: fullname: L Jin – volume: 1164 start-page: 179 year: 2019 ident: 2124_CR7 publication-title: Adv Exp Med Biol doi: 10.1007/978-3-030-22254-3_14 contributor: fullname: N Mahmood – volume: 68 start-page: 394 year: 2018 ident: 2124_CR1 publication-title: CA Cancer J Clin doi: 10.3322/caac.21492 contributor: fullname: F Bray |
| SSID | ssj0023353 |
| Score | 2.4294944 |
| Snippet | Aberrant DNA methylation is significantly associated with breast cancer.
In this study, we aimed to determine novel methylation biomarkers using a... Abstract Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation... Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation biomarkers... Aberrant DNA methylation is significantly associated with breast cancer. In this study, we aimed to determine novel methylation biomarkers using a... BACKGROUNDAberrant DNA methylation is significantly associated with breast cancer. METHODSIn this study, we aimed to determine novel methylation biomarkers... Abstract Background Aberrant DNA methylation is significantly associated with breast cancer. Methods In this study, we aimed to determine novel methylation... |
| SourceID | doaj pubmedcentral proquest gale crossref pubmed |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database |
| StartPage | 29 |
| SubjectTerms | Bioinformatics Biological markers Biomarkers Biomarkers, Tumor - genetics Breast cancer Breast Neoplasms - diagnosis Breast Neoplasms - genetics Care and treatment Datasets Deoxyribonucleic acid Development and progression Diagnosis DNA DNA Methylation Gene Expression Regulation, Neoplastic Genes Genetic aspects Health aspects Humans Identification and classification Kaplan-Meier Estimate Kinases Methylation Prognosis Survival |
| SummonAdditionalLinks | – databaseName: Directory of Open Access Journals dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lj9MwELbQHhAXxPIM7IKRkDigaJM4dpzjglitkJYTK-3NsmOHh6oUtd3D_nu-sZ2qEQcu3NrONGrm5W_SeTD2TjZOKeQNQG5Ol23AK90EWdYIjM556H2k55BXX9XldfvlRt4crPqimrA0HjgJ7kyJQQRaIU-Jt7AeB0zoLY01V9oJmeZ8Vv2cTOVUS4Ayt8hodbbFqSa7ksoRaKR5W6rFMRSn9f8dkw8OpWXB5MEJdPGIPczQkZ-nn3zM7oXpMbt_lf8cf8J-pabbMT-F4-uRz-tP4Mar1R2nddF3K6BLz79TjON2C5ZYa4drcjt5TvVa-S115lPxzmZLl3JUvb7jA1nJ5im7vvj87dNlmVcplIPs213pOw9PVcoH1Vs49YDEQMtRhKEXqrIWwMsCmNTaVk4BMdWDhrYAPlQfKjlI8YwdTespvGDcW1WNLoTOS48o6x0UU_dOtqrxQGNjwT7MkjW_08QMEzMNrUzSg4EOTNSDUQX7SMLfc9K06_gBbMBkGzD_soGCvSHVmdQ6uvdZcw742UoELV2w95GDvBYaHGxuPsAt0fyrBefJghPeNizJs3mY7O1bgxS2bglJgfx2T6ZvUgXbFNa3xAOJSoCvpmDPkzXtb1oI5J1IdQrWLexsIZUlZfr5I84C7wBwa92__B9ifMUeNNFF6rJRJ-xot7kNp4BcO_c6etcf1Rgk3Q priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Central dbid: BENPR link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3da9RAEB_0CuKL-G1q1RUEHyQ0yWY3mydppaUILSIW-rbsV6pyJPVyfeh_35lkExsE3-5u50Ky8_WbzXwAfBCFlRLjBkRuVqVlwE-qCCLN0TBa65HvDZ1Dnp7Jk_Py64W4iAdufUyrnGziYKh95-iMfB_DhLwkb6U-X_1JaWoUvV2NIzTuw06BkUK2gp3Do7Nv3-eQi3PBp1IZJfd79G6iSiktgVqbl6lcuKOha_-_tvmOc1omTt7xRMeP4VGEkOxg5PkTuBfap_DgNL4kfwa_x-LbJp7Gsa5h0xgUVOf1-obR2OibNaJMzy7J1jHTI8mQc4fXZKb1jPK24leq0Kcknk1Pl7KUxb5ljqRl8xzOj49-fDlJ40iF1Im63Ka-8qixUvoga4PK7TBAUKLhwdVcZsYgADMIUHJlMisROeVOIdcQhMg6ZMIJ_gJWbdeGV8C8kVljQ6i88GhtveVoK2orSll4RGVNAp-mndVXY-cMPUQcSuqRDxp5oAc-aJnAIW3-TEldr4cfus2ljkqkJXc85JWijNiSG49gI9SGWtxLZZHTCbwj1umxhHTWXX2AMLQUaLxUAh8HCtJe5KAzsQgBH4n6YC0o9xaUqHVuuTyJh45a3-u_MprA-3mZ_kmZbG3orokGd1QgCCsSeDlK0_zQnGP8iSFPAtVCzha7slxpf_0ceoJXCHRzVe_-_7Zew8NiEP48LeQerLab6_AGQdXWvo2acwumjx9d priority: 102 providerName: ProQuest – databaseName: Scholars Portal Open Access Journals dbid: M48 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1ba9RAFD7UCqUv4t1o1REEHyS6yVwyeRCpYilCfXKhb8Pc0ipLVrNbcP-950wuNNgn3zY7ZwI5t_lOci4Ar2XplMK4AZGb07mI-EuXUeYFOkbnAsq9ofeQZ9_U6VJ8PZfnezCOOxoYuLkxtKN5Ustu9e7P791HNPgPyeC1er_BM0tWOSUbUMNykatbcLsUGKlTKp-YviqUnEs-Fs7cuO8QDjjHGEDrcnZOpXb-_zrta6fWPKPy2hF1chfuDNiSHffKcA_2YnsfDs6Gr-cP4GdfldsMr-nYumHjfBS089Vqx2ie9G6F8DOwC3KCzG6QJCXj4T2ZbQOjhK7hkkr3Kbun29CtHKW3b5knNeoewvLky_fPp_kwayH3shbbPFQBTVmpEFVt0eo9Rg5aNjz6mquFtYjMLCKXQtuFUwipCq9RnIhOVB0X0kv-CPbbdRufAAtWLRoXYxVkQDccHAqiqJ0UqgwI15oM3o6cNb_6lhomhSJamV4kBsVhkkiMyuATMX-ipHbY6Y91d2EG6zKKex6LSlOqrOA2IAqJtaXe90o7FHoGL0l0pq8tnYzaHCM-FRK9ms7gTaIgRUMJejtUJ-AjUYOsGeXRjBLN0c-XR_UwozYbjHELQVALl19Ny7STUtzauL4iGuSoRHRWZvC416bpoUelzKCa6dmMK_OV9sdlahZeIQIudP30v3c-g8MymUiRl-oI9rfdVXyOQGzrXiTr-gvRwC6q priority: 102 providerName: Scholars Portal |
| Title | Identification of differentially methylated genes as diagnostic and prognostic biomarkers of breast cancer |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/33499882 https://www.proquest.com/docview/2491420118 https://search.proquest.com/docview/2481650152 https://pubmed.ncbi.nlm.nih.gov/PMC7839189 https://doaj.org/article/63c3e178533043ad818e9a391568b353 |
| Volume | 19 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1La9tAEB6SFEovJX2rSd0tFHooii2tdrU6xiEhFBxCaMD0suxLaYojB9s55N93ZiWZiN56EbZ3JKSdx34jfzML8FXkVkrMGxC5WZUWAT-pPIg0w8BorUe91_QecnYhz6-LH3Mx3wHR18JE0r6zt0fN4u6ouf0duZX3d27c88TGl7OTElf1TFXjXdhFA-1T9C7L4lzwvjpGyfEaFzRRpsREoG7mRUqbFnGOQF-pfLAYxZ79_0bmJ0vTkDb5ZB0624eXHYBkx-2NvoKd0LyG57PuL_I38Kctva27d3FsWbN-ExR05sXikdGm0Y8LxJie3VCkY2aNIpFxh9dkpvGMWFvdV6rPJwrPak2XssRh3zBHtrJ6C9dnpz9PztNuQ4XUiarYpL706K9S-iArgzPnMD1QoubBVVxOjEH4ZRCeZMpMrETclDmFOkMIIqswEU7wd7DXLJvwAZg3clLbEEovPMZabzlGisqKQuYeMVmdwPd-ZvV92zdDx3xDSd2qRKM6dFSJlglMafK3ktTzOv6wXN3oTvNacsdDViriwxbceIQaoTLU4F4qi0pP4DOpTrcFpFvP1ccIQguBoUsl8C1KkO-iBp3pShDwkagL1kDycCCJPueGw7156M7n1xoT2awgPIXDX7bDdCbx2JqwfCAZnFGBECxP4H1rTduH7o0ygXJgZ4NZGY6gg8SO4J1DfPzvMw_gRR5dJEtzeQh7m9VD-IRoa2NH6GPzcgTPpqcXl1ej-M4Cj7NC4fFq-msUve8v7q8skQ |
| link.rule.ids | 230,315,730,783,787,867,888,2109,12068,21400,24330,27936,27937,31731,31732,33756,33757,43322,43817,53804,53806 |
| linkProvider | National Library of Medicine |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1Lb9NAEB5BkaAXxBtDoUZC4oCsxl7ven1CBVEFaHpqpdxW-3ILiuw2Tg_998ys12ktJG5JdmLZO69v1vMA-MgLIwTGDYjcjMxKj59k4XmWo2E0xiHfGzqHXJyI-Vn5c8mX8cCtj2mVo00Mhtp1ls7IDzBMyEvyVvLL5VVGU6Po7WocoXEfHlAfLppgUC1vAy7GOBsLZaQ46NG38SqjpARqbF5mYuKMQs_-fy3zHdc0TZu844eOnsDjCCDTw4HjT-Geb5_Bw0V8Rf4c_gylt008i0u7Jh2HoKAyr1Y3KQ2NvlkhxnTpOVm6VPdIEjLu8Jqpbl1KWVvxK9XnUwrPuqdLGcph36SWZGX9As6Ovp9-m2dxoEJmeV1uMlc51FchnBe1RtW2GB5I3jBvayZmWiP80ghPcqlnRiBuyq1EniEEEbWfccvZS9hpu9a_htRpMWuM95XjDm2tMwwtRW14KQqHmKxJ4PO4s-py6JuhQrwhhRr4oJAHKvBBiQS-0uZvKanndfihW5-rqEJKMMt8XknKhy2Zdgg1fK2pwb2QBjmdwD6xTg0FpFvNVYcIQkuOpksm8ClQkO4iB62OJQj4SNQFa0K5N6FEnbPT5VE8VNT5Xt1KaAIftsv0T8pja313TTS4oxwhWJHAq0Gatg_NGEafGPAkUE3kbLIr05X290XoCF4hzM1l_eb_t7UPj-ani2N1_OPk11vYLYIi5Fkh9mBns7727xBebcz7oEN_AX9VIOg |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Lb9QwELagSBUXRHkGSmskJA4ozcOx4xxL21V5bNUDlXqz_Eop2mZXu9tD_z0zjrPaiBu3bDyJEo-_8TfZz2NCPvHSCAF5AzA3I9PKw5EsPU8LCIzGOPB7i98hpxfi_Kr6fs2vt7b6CqJ9a26PutndUXf7O2grF3c2G3Ri2eX0pIZZvZBNtnBt9pg8AczmYkjUY67FGGfDGhkpshVMa7xOUY-ANc2rFLcuYgzovpTlaEoKlfv_jc9bE9RYPLk1G02ek2eRRtLj_nH3yCPfvSC70_hH-Uvyp1-A28YvcnTe0mErFID0bPZAcevohxkwTUdvMN5RvQKToLuDe1LdOYrarfgTV-mjkGe5wlsZVLKvqcURs3xFriZnv07O07itQmp5U61TVztArRDOi0YDwC0kCZK3zNuGiVxrIGEaSEohdW4EsKfCSvAcEBHR-Jxbzl6TnW7e-beEOi3y1nhfO-4g4jrDIF40hleidMDM2oR8GXpWLfrqGSpkHVKo3iUK3KGCS5RIyFfs_I0lVr4OJ-bLGxX9rwSzzBe1RFVsxbQDwuEbjWXuhTTg9IQcoutUv4x0g191DFS04hDAZEI-BwtEMHjQ6rgQAV4Ja2GNLPdHloA8O24ehoeKyF8pSGeLClkVNH_cNOOVqGbr_PwebaBHORCxMiFv-tG0eelhUCakHo2zUa-MWwAmoS54hMW7_77ykOxenk7Uz28XP96Tp2VAS5GWYp_srJf3_gPQr7U5CED7C6KjK5s |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Identification+of+differentially+methylated+genes+as+diagnostic+and+prognostic+biomarkers+of+breast+cancer&rft.jtitle=World+journal+of+surgical+oncology&rft.au=Mao%2C+Xiao-hong&rft.au=Ye%2C+Qiang&rft.au=Zhang%2C+Guo-bing&rft.au=Jiang%2C+Jin-ying&rft.date=2021-01-26&rft.pub=BioMed+Central&rft.eissn=1477-7819&rft.volume=19&rft_id=info:doi/10.1186%2Fs12957-021-02124-6&rft_id=info%3Apmid%2F33499882&rft.externalDBID=PMC7839189 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1477-7819&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1477-7819&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1477-7819&client=summon |