Identification of Family with Sequence Similarity 110 Member C (FAM110C) as a Candidate Diagnostic and Prognostic Biomarker for Glioma
Background: Gliomas are the most frequent and dangerous primary cerebral tumors. Therefore, there is a need to develop molecular targets for the diagnosis and treatment for glioma. Methods: In September 2020, we retrieved the expression matrix of glioblastoma (GBM) sufferers and pertinent clinical d...
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Veröffentlicht in: | Iranian journal of public health 2023-10, Vol.52 (10), p.2117-2127 |
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description | Background: Gliomas are the most frequent and dangerous primary cerebral tumors. Therefore, there is a need to develop molecular targets for the diagnosis and treatment for glioma. Methods: In September 2020, we retrieved the expression matrix of glioblastoma (GBM) sufferers and pertinent clinical data from the TCGA (The Cancer Genome Atlas) database. Prognostic differences between various families with sequence similarity 110 member C (FAM110C) expression groups were assessed by Kaplan-Meier with log-rank test. The R platform get used to assess the accuracy of FAM110C delivery in predicting the prognosis of PDAC using a time-dependent receptor operating characteristic (ROC) curve. The delivery level of FAM110C was determined by qRT-PCR and western blot. Gene set enrichment investigated possible mechanisms between different FAM110C expression groups in GBM (GSEA). The impact of FAM110C on glioma cell movement was discovered using migration test. The drug's gene-targeting impact was validated by the CCK8 test. Results: A total of 173 GBM samples were obtained from the TCGA database, with 148 including information on IDH1 mutations and 151 containing information on overall survival. The mRNA expression level of FAM110C was greater in wild-type GBM, according to qRT-PCR data. The connection between FAM110C expression and Hallmark, GO, and KEGG pathway gene sets was investigated using GSEA software. We used migration test to assess the impact of FAM110C on glioma motility in order to confirm the findings of the GSEA analysis. Conclusion: FAM110C might get used as a possible diagnostic and prognostic biomarker for wild-type GBM, and its inhibition could be used to prevention and treatment wild-type GBM. |
doi_str_mv | 10.18502/ijph.v52i10.13850 |
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Therefore, there is a need to develop molecular targets for the diagnosis and treatment for glioma. Methods: In September 2020, we retrieved the expression matrix of glioblastoma (GBM) sufferers and pertinent clinical data from the TCGA (The Cancer Genome Atlas) database. Prognostic differences between various families with sequence similarity 110 member C (FAM110C) expression groups were assessed by Kaplan-Meier with log-rank test. The R platform get used to assess the accuracy of FAM110C delivery in predicting the prognosis of PDAC using a time-dependent receptor operating characteristic (ROC) curve. The delivery level of FAM110C was determined by qRT-PCR and western blot. Gene set enrichment investigated possible mechanisms between different FAM110C expression groups in GBM (GSEA). The impact of FAM110C on glioma cell movement was discovered using migration test. The drug's gene-targeting impact was validated by the CCK8 test. Results: A total of 173 GBM samples were obtained from the TCGA database, with 148 including information on IDH1 mutations and 151 containing information on overall survival. The mRNA expression level of FAM110C was greater in wild-type GBM, according to qRT-PCR data. The connection between FAM110C expression and Hallmark, GO, and KEGG pathway gene sets was investigated using GSEA software. We used migration test to assess the impact of FAM110C on glioma motility in order to confirm the findings of the GSEA analysis. Conclusion: FAM110C might get used as a possible diagnostic and prognostic biomarker for wild-type GBM, and its inhibition could be used to prevention and treatment wild-type GBM.</description><identifier>ISSN: 2251-6085</identifier><identifier>EISSN: 2251-6093</identifier><identifier>DOI: 10.18502/ijph.v52i10.13850</identifier><language>eng</language><publisher>Tehran: Tehran University of Medical Sciences</publisher><subject>Biomarkers ; Brain tumors ; Cell migration ; Gene expression ; Genomes ; Glioblastoma ; Glioma ; Glioma cells ; Medical prognosis ; Nucleotide sequence ; Original ; Rank tests ; Similarity</subject><ispartof>Iranian journal of public health, 2023-10, Vol.52 (10), p.2117-2127</ispartof><rights>2023. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Copyright © 2023 Ren et al. Published by Tehran University of Medical Sciences. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612548/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10612548/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids></links><search><creatorcontrib>Ren, Deshuai</creatorcontrib><creatorcontrib>Zhuang, Xiaoyu</creatorcontrib><creatorcontrib>Lv, Yanxin</creatorcontrib><creatorcontrib>Zhang, Yun</creatorcontrib><creatorcontrib>Xu, Jiazhi</creatorcontrib><creatorcontrib>Gao, Fengquan</creatorcontrib><creatorcontrib>Chen, Dagang</creatorcontrib><creatorcontrib>Wang, Yu</creatorcontrib><title>Identification of Family with Sequence Similarity 110 Member C (FAM110C) as a Candidate Diagnostic and Prognostic Biomarker for Glioma</title><title>Iranian journal of public health</title><description>Background: Gliomas are the most frequent and dangerous primary cerebral tumors. Therefore, there is a need to develop molecular targets for the diagnosis and treatment for glioma. Methods: In September 2020, we retrieved the expression matrix of glioblastoma (GBM) sufferers and pertinent clinical data from the TCGA (The Cancer Genome Atlas) database. Prognostic differences between various families with sequence similarity 110 member C (FAM110C) expression groups were assessed by Kaplan-Meier with log-rank test. The R platform get used to assess the accuracy of FAM110C delivery in predicting the prognosis of PDAC using a time-dependent receptor operating characteristic (ROC) curve. The delivery level of FAM110C was determined by qRT-PCR and western blot. Gene set enrichment investigated possible mechanisms between different FAM110C expression groups in GBM (GSEA). The impact of FAM110C on glioma cell movement was discovered using migration test. The drug's gene-targeting impact was validated by the CCK8 test. Results: A total of 173 GBM samples were obtained from the TCGA database, with 148 including information on IDH1 mutations and 151 containing information on overall survival. The mRNA expression level of FAM110C was greater in wild-type GBM, according to qRT-PCR data. The connection between FAM110C expression and Hallmark, GO, and KEGG pathway gene sets was investigated using GSEA software. We used migration test to assess the impact of FAM110C on glioma motility in order to confirm the findings of the GSEA analysis. Conclusion: FAM110C might get used as a possible diagnostic and prognostic biomarker for wild-type GBM, and its inhibition could be used to prevention and treatment wild-type GBM.</description><subject>Biomarkers</subject><subject>Brain tumors</subject><subject>Cell migration</subject><subject>Gene expression</subject><subject>Genomes</subject><subject>Glioblastoma</subject><subject>Glioma</subject><subject>Glioma cells</subject><subject>Medical prognosis</subject><subject>Nucleotide sequence</subject><subject>Original</subject><subject>Rank tests</subject><subject>Similarity</subject><issn>2251-6085</issn><issn>2251-6093</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpdkd1OGzEQha2qSKWhL9ArS72hFwH_7s9VRbcEkEBUAq6t2bWXTLq7Tu0NVV6A58ZJIFK5sufz-OjMHEK-cnbCC83EKS6W85MnLXBDZEIfyKEQmk8zVsqP-3uhP5HPMS4YU5nQ-SF5vrJuGLHFBkb0A_UtnUGP3Zr-w3FO79zflRsaR-8wQQg4rinnjN64vnaBVvR4dnaTQPWdQqRAKxgsWhgd_YXwOPg4YkMTo7-Dfyt_ou8h_EnfWx_oRbcpj8hBC110X17PCXmYnd9Xl9Pr24ur6ux62khdjlPNtFWlrqWWmVaW1YxDnQNIpnXumG1Vqwqb5zoh0SgmlVBc2kzlUnFonZyQHzvd5arunW3S7AE6swyYLK2NBzT_vww4N4_-yXCWcaFVkRSOXxWCT7uJo-kxNq7rYHB-FY0oCsULyZLFCfn2rnXhV2FI86WuvOQ5Z-VGUOy6muBjDK7du-HMbMM1m3DNLlyzDVe-AMxsmGk</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Ren, Deshuai</creator><creator>Zhuang, Xiaoyu</creator><creator>Lv, Yanxin</creator><creator>Zhang, Yun</creator><creator>Xu, Jiazhi</creator><creator>Gao, Fengquan</creator><creator>Chen, Dagang</creator><creator>Wang, Yu</creator><general>Tehran University of Medical Sciences</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>M0S</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20231001</creationdate><title>Identification of Family with Sequence Similarity 110 Member C (FAM110C) as a Candidate Diagnostic and Prognostic Biomarker for Glioma</title><author>Ren, Deshuai ; Zhuang, Xiaoyu ; Lv, Yanxin ; Zhang, Yun ; Xu, Jiazhi ; Gao, Fengquan ; Chen, Dagang ; Wang, Yu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-505d495b353654d0b01ab7aa30557e0df4f48d775aa32c40342413d647341afe3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Biomarkers</topic><topic>Brain tumors</topic><topic>Cell migration</topic><topic>Gene expression</topic><topic>Genomes</topic><topic>Glioblastoma</topic><topic>Glioma</topic><topic>Glioma cells</topic><topic>Medical prognosis</topic><topic>Nucleotide sequence</topic><topic>Original</topic><topic>Rank tests</topic><topic>Similarity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ren, Deshuai</creatorcontrib><creatorcontrib>Zhuang, Xiaoyu</creatorcontrib><creatorcontrib>Lv, Yanxin</creatorcontrib><creatorcontrib>Zhang, Yun</creatorcontrib><creatorcontrib>Xu, Jiazhi</creatorcontrib><creatorcontrib>Gao, Fengquan</creatorcontrib><creatorcontrib>Chen, Dagang</creatorcontrib><creatorcontrib>Wang, Yu</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Iranian journal of public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ren, Deshuai</au><au>Zhuang, Xiaoyu</au><au>Lv, Yanxin</au><au>Zhang, Yun</au><au>Xu, Jiazhi</au><au>Gao, Fengquan</au><au>Chen, Dagang</au><au>Wang, Yu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of Family with Sequence Similarity 110 Member C (FAM110C) as a Candidate Diagnostic and Prognostic Biomarker for Glioma</atitle><jtitle>Iranian journal of public health</jtitle><date>2023-10-01</date><risdate>2023</risdate><volume>52</volume><issue>10</issue><spage>2117</spage><epage>2127</epage><pages>2117-2127</pages><issn>2251-6085</issn><eissn>2251-6093</eissn><abstract>Background: Gliomas are the most frequent and dangerous primary cerebral tumors. Therefore, there is a need to develop molecular targets for the diagnosis and treatment for glioma. Methods: In September 2020, we retrieved the expression matrix of glioblastoma (GBM) sufferers and pertinent clinical data from the TCGA (The Cancer Genome Atlas) database. Prognostic differences between various families with sequence similarity 110 member C (FAM110C) expression groups were assessed by Kaplan-Meier with log-rank test. The R platform get used to assess the accuracy of FAM110C delivery in predicting the prognosis of PDAC using a time-dependent receptor operating characteristic (ROC) curve. The delivery level of FAM110C was determined by qRT-PCR and western blot. Gene set enrichment investigated possible mechanisms between different FAM110C expression groups in GBM (GSEA). The impact of FAM110C on glioma cell movement was discovered using migration test. The drug's gene-targeting impact was validated by the CCK8 test. Results: A total of 173 GBM samples were obtained from the TCGA database, with 148 including information on IDH1 mutations and 151 containing information on overall survival. The mRNA expression level of FAM110C was greater in wild-type GBM, according to qRT-PCR data. The connection between FAM110C expression and Hallmark, GO, and KEGG pathway gene sets was investigated using GSEA software. We used migration test to assess the impact of FAM110C on glioma motility in order to confirm the findings of the GSEA analysis. Conclusion: FAM110C might get used as a possible diagnostic and prognostic biomarker for wild-type GBM, and its inhibition could be used to prevention and treatment wild-type GBM.</abstract><cop>Tehran</cop><pub>Tehran University of Medical Sciences</pub><doi>10.18502/ijph.v52i10.13850</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biomarkers Brain tumors Cell migration Gene expression Genomes Glioblastoma Glioma Glioma cells Medical prognosis Nucleotide sequence Original Rank tests Similarity |
title | Identification of Family with Sequence Similarity 110 Member C (FAM110C) as a Candidate Diagnostic and Prognostic Biomarker for Glioma |
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