Discovery and validation of novel biomarkers for detection of cervical cancer

Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential...
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Autor*in:	Zigang Li [verfasserIn] Jianhua Chen [verfasserIn] Shaobo Zhao [verfasserIn] Yajun Li [verfasserIn] Jie Zhou [verfasserIn] Jianghong Liang [verfasserIn] Huifang Tang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	biomarker cervical cancer CRISP2 GEO KRT17

Übergeordnetes Werk:	In: Cancer Medicine - Wiley, 2012, 10(2021), 6, Seite 2063-2074
Übergeordnetes Werk:	volume:10 ; year:2021 ; number:6 ; pages:2063-2074

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1002/cam4.3799

Katalog-ID:	DOAJ051895390

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520			\|a Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer.
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653		0	\|a Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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700	0		\|a Jie Zhou \|e verfasserin \|4 aut
700	0		\|a Jianghong Liang \|e verfasserin \|4 aut
700	0		\|a Huifang Tang \|e verfasserin \|4 aut
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allfields	10.1002/cam4.3799 doi (DE-627)DOAJ051895390 (DE-599)DOAJ7ec6179e8099466ea8dd909359239ebd DE-627 ger DE-627 rakwb eng RC254-282 Zigang Li verfasserin aut Discovery and validation of novel biomarkers for detection of cervical cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer. biomarker cervical cancer CRISP2 GEO KRT17 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jianhua Chen verfasserin aut Shaobo Zhao verfasserin aut Yajun Li verfasserin aut Jie Zhou verfasserin aut Jianghong Liang verfasserin aut Huifang Tang verfasserin aut In Cancer Medicine Wiley, 2012 10(2021), 6, Seite 2063-2074 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:10 year:2021 number:6 pages:2063-2074 https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/article/7ec6179e8099466ea8dd909359239ebd kostenfrei https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2021 6 2063-2074
spelling	10.1002/cam4.3799 doi (DE-627)DOAJ051895390 (DE-599)DOAJ7ec6179e8099466ea8dd909359239ebd DE-627 ger DE-627 rakwb eng RC254-282 Zigang Li verfasserin aut Discovery and validation of novel biomarkers for detection of cervical cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer. biomarker cervical cancer CRISP2 GEO KRT17 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jianhua Chen verfasserin aut Shaobo Zhao verfasserin aut Yajun Li verfasserin aut Jie Zhou verfasserin aut Jianghong Liang verfasserin aut Huifang Tang verfasserin aut In Cancer Medicine Wiley, 2012 10(2021), 6, Seite 2063-2074 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:10 year:2021 number:6 pages:2063-2074 https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/article/7ec6179e8099466ea8dd909359239ebd kostenfrei https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2021 6 2063-2074
allfields_unstemmed	10.1002/cam4.3799 doi (DE-627)DOAJ051895390 (DE-599)DOAJ7ec6179e8099466ea8dd909359239ebd DE-627 ger DE-627 rakwb eng RC254-282 Zigang Li verfasserin aut Discovery and validation of novel biomarkers for detection of cervical cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer. biomarker cervical cancer CRISP2 GEO KRT17 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jianhua Chen verfasserin aut Shaobo Zhao verfasserin aut Yajun Li verfasserin aut Jie Zhou verfasserin aut Jianghong Liang verfasserin aut Huifang Tang verfasserin aut In Cancer Medicine Wiley, 2012 10(2021), 6, Seite 2063-2074 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:10 year:2021 number:6 pages:2063-2074 https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/article/7ec6179e8099466ea8dd909359239ebd kostenfrei https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2021 6 2063-2074
allfieldsGer	10.1002/cam4.3799 doi (DE-627)DOAJ051895390 (DE-599)DOAJ7ec6179e8099466ea8dd909359239ebd DE-627 ger DE-627 rakwb eng RC254-282 Zigang Li verfasserin aut Discovery and validation of novel biomarkers for detection of cervical cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer. biomarker cervical cancer CRISP2 GEO KRT17 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jianhua Chen verfasserin aut Shaobo Zhao verfasserin aut Yajun Li verfasserin aut Jie Zhou verfasserin aut Jianghong Liang verfasserin aut Huifang Tang verfasserin aut In Cancer Medicine Wiley, 2012 10(2021), 6, Seite 2063-2074 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:10 year:2021 number:6 pages:2063-2074 https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/article/7ec6179e8099466ea8dd909359239ebd kostenfrei https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2021 6 2063-2074
allfieldsSound	10.1002/cam4.3799 doi (DE-627)DOAJ051895390 (DE-599)DOAJ7ec6179e8099466ea8dd909359239ebd DE-627 ger DE-627 rakwb eng RC254-282 Zigang Li verfasserin aut Discovery and validation of novel biomarkers for detection of cervical cancer 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer. biomarker cervical cancer CRISP2 GEO KRT17 Neoplasms. Tumors. Oncology. Including cancer and carcinogens Jianhua Chen verfasserin aut Shaobo Zhao verfasserin aut Yajun Li verfasserin aut Jie Zhou verfasserin aut Jianghong Liang verfasserin aut Huifang Tang verfasserin aut In Cancer Medicine Wiley, 2012 10(2021), 6, Seite 2063-2074 (DE-627)71860153X (DE-600)2659751-2 20457634 nnns volume:10 year:2021 number:6 pages:2063-2074 https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/article/7ec6179e8099466ea8dd909359239ebd kostenfrei https://doi.org/10.1002/cam4.3799 kostenfrei https://doaj.org/toc/2045-7634 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2021 6 2063-2074
language	English
source	In Cancer Medicine 10(2021), 6, Seite 2063-2074 volume:10 year:2021 number:6 pages:2063-2074
sourceStr	In Cancer Medicine 10(2021), 6, Seite 2063-2074 volume:10 year:2021 number:6 pages:2063-2074
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	biomarker cervical cancer CRISP2 GEO KRT17 Neoplasms. Tumors. Oncology. Including cancer and carcinogens
isfreeaccess_bool	true
container_title	Cancer Medicine
authorswithroles_txt_mv	Zigang Li @@aut@@ Jianhua Chen @@aut@@ Shaobo Zhao @@aut@@ Yajun Li @@aut@@ Jie Zhou @@aut@@ Jianghong Liang @@aut@@ Huifang Tang @@aut@@
publishDateDaySort_date	2021-01-01T00:00:00Z
hierarchy_top_id	71860153X
id	DOAJ051895390
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ051895390</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230501184524.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2021 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1002/cam4.3799</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ051895390</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ7ec6179e8099466ea8dd909359239ebd</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC254-282</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Zigang Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Discovery and validation of novel biomarkers for detection of cervical cancer</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2021</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. 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callnumber-first	R - Medicine
author	Zigang Li
spellingShingle	Zigang Li misc RC254-282 misc biomarker misc cervical cancer misc CRISP2 misc GEO misc KRT17 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens Discovery and validation of novel biomarkers for detection of cervical cancer
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topic_title	RC254-282 Discovery and validation of novel biomarkers for detection of cervical cancer biomarker cervical cancer CRISP2 GEO KRT17
topic	misc RC254-282 misc biomarker misc cervical cancer misc CRISP2 misc GEO misc KRT17 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_unstemmed	misc RC254-282 misc biomarker misc cervical cancer misc CRISP2 misc GEO misc KRT17 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
topic_browse	misc RC254-282 misc biomarker misc cervical cancer misc CRISP2 misc GEO misc KRT17 misc Neoplasms. Tumors. Oncology. Including cancer and carcinogens
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title	Discovery and validation of novel biomarkers for detection of cervical cancer
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title_full	Discovery and validation of novel biomarkers for detection of cervical cancer
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author_browse	Zigang Li Jianhua Chen Shaobo Zhao Yajun Li Jie Zhou Jianghong Liang Huifang Tang
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title_sort	discovery and validation of novel biomarkers for detection of cervical cancer
callnumber	RC254-282
title_auth	Discovery and validation of novel biomarkers for detection of cervical cancer
abstract	Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer.
abstractGer	Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer.
abstract_unstemmed	Abstract Aims To investigate novel biomarker for diagnosis of cervical cancer, we analyzed the datasets in Gene Expression Omnibus (GEO) and confirmed the candidate biomarker in patient sample. Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. Such combined analysis is capable of improving diagnostic accuracy of cervical cancer.
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title_short	Discovery and validation of novel biomarkers for detection of cervical cancer
url	https://doi.org/10.1002/cam4.3799 https://doaj.org/article/7ec6179e8099466ea8dd909359239ebd https://doaj.org/toc/2045-7634
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author2	Jianhua Chen Shaobo Zhao Yajun Li Jie Zhou Jianghong Liang Huifang Tang
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doi_str	10.1002/cam4.3799
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up_date	2024-07-03T22:47:49.217Z
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Materials and methods We collected major datasets of cervical cancer in GEO, and analyzed the differential expression of normal and cancer samples online with GEO2R and tested the differences, then focus on the GSE63514 to screen the target genes in different histological grades by using the R‐Bioconductor package and R‐heatmap. Then human specimens from the cervix in different histological grades were used to confirm the top 8 genes expression by immunohistochemical staining using Ki67 as a standard control. Results We identified genes differentially expressed in normal and cervical cancer, 274 upregulated genes and 206 downregulated genes. After intersection with GSE63514, we found the obvious tendency in different histological grades. Then we screened the top 24 genes, and confirmed the top 8 genes in human cervix tissues. Immunohistochemical (IHC) results confirmed that keratin 17 (KRT17) was not expressed in normal cervical tissues and was over‐expressed in cervical cancer. Cysteine‐rich secretory protein‐2 (CRISP2) was less expressed in high‐grade squamous intraepithelial lesions (HSILs) than in other histological grades. Conclusion For the good repeatability and consistency of KRT17 and CRISP2, they may be good candidate biomarkers. Combined analysis of KRT17, CRISP2 expression at both genetic and protein levels can determine different histological grades of cervical squamous cell carcinoma. 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Including cancer and carcinogens</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jianhua Chen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Shaobo Zhao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yajun Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jie Zhou</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Jianghong Liang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Huifang Tang</subfield><subfield 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Discovery and validation of novel biomarkers for detection of cervical cancer

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