https://m2.mtmt.hu/ hun 2026-07-26 23:43 JournalArticle 33772189 VALIDATED true Export Date: 19 June 2023 CODEN: BCMAC Correspondence Address: Yu, B.; Department of Gastroenterology, China; email: yubp62@163.com Correspondence Address: Wang, W.; Department of Gastroenterology, China; email: 50248@hbuas.edu.cn 0 false 2023-06-19T14:53:32.376+0000 2023-04-25T13:49:49.122+0000 2023-04-25T13:46:21.252+0000 true 10022176 Laczik Cecilia /api/admin/10022176 Admin true 10022176 2023-10-19T15:32:13.446+0000 2023-04-25T13:49:49.494+0000 true 10022176 Laczik Cecilia /api/admin/10022176 Admin true 10022176 false false true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle true 10000059 Article true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle /api/subtype/10000059 Szakcikk SubType 101 true 10000059 true 1 /api/category/1 Category true 1 Hong, Kunqiao Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer true true /api/journal/10000700 REVIEWED true false 10000700 false 10000700 true 1471-2407 1471-2407 Journal FOREIGN 23 1 301 301 18 2023 BackgroundAs a common malignant tumor, esophageal carcinoma (ESCA) has a low early diagnosis rate and poor prognosis. This study aimed to construct the prognostic features composed of ZNF family genes to effectively predict the prognosis of ESCA patients.MethodsThe mRNA expression matrix and clinical data were downloaded from TCGA and GEO database. Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, and nomogram to evaluate the prognostic value within and across sets, separately and combined. We also validated the prognostic value of the six-gene signature using GSE53624 dataset. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). Finally, real-time quantitative PCR was used to detect the expression of six prognostic ZNF genes in twelve pairs of ESCA and adjacent normal tissues.ResultsA six prognosis-related ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225 was identified. Multivariable Cox regression analysis revealed that six prognosis-related ZNF family genes were independent prognostic factors for overall survival of ESCA patients in TCGA and GSE53624. Further, a prognostic nomogram including the riskScore, age, gender, T, stage was constructed, and TCGA/GSE53624-based calibration plots indicated its excellent predictive performance. Drug Sensitivity and ssGSEA analysis showed that the six genes model was closely related to immune cells infiltration and could be used as a potential predictor of chemotherapy sensitivity.ConclusionWe identified six prognosis-related ZNF family genes model of ESCA, which provide evidence for individualized prevention and treatment. 2023 true true true false false GOLD 2023-06-19 false http://www.biomedcentral.com/bmccancer/ 0 0 0 0 0 0 0 0 0 0 0 0 1 1 Q2 false false false false 2023-04-24T13:49:48.912+0000 14 47 0 6 0 true Language 10002 /api/language/10002 Angol English true 2 true PersonAuthorship 107465452 /api/authorship/107465452 1 0.16666667 true false false Hong Kunqiao true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 107465453 /api/authorship/107465453 2 0.16666667 false false false Yang Qian true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 107465454 /api/authorship/107465454 3 0.16666667 false false false Yin Haisen true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 107465455 /api/authorship/107465455 4 0.16666667 false false false Wei Na true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 107465456 /api/authorship/107465456 5 0.16666667 false false true Wang Wei true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PersonAuthorship 107465457 /api/authorship/107465457 6 0.16666667 false true true Yu Baoping true false false AuthorshipType 1 /api/authorshiptype/1 0 true 0 true false true PublicationIdentifier 23427890 /api/publicationidentifier/23427890 PlainSource 6 /api/publicationsource/6 PublicationSourceType 10001 /api/publicationsourcetype/10001 true true true DOI DOI https://doi.org/@@@ true true 6 true IDENTICAL 10.1186/s12885-023-10779-5 https://doi.org/10.1186/s12885-023-10779-5 false true PublicationIdentifier 23427891 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class="author-name" >Wei Na </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Wang Wei ✉ </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Yu Baoping ✉ </span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;33772189" target="_blank">Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer</a></div> <div> <span class="journal-title">BMC CANCER</span> <span class="journal-issn">(<a target="_blank" href="https://portal.issn.org/resource/ISSN/1471-2407">1471-2407</a> <a target="_blank" href="https://portal.issn.org/resource/ISSN/1471-2407">1471-2407</a>)</span>: <span class="journal-volume">23</span> <span class="journal-issue">1</span> <span class="page"> Paper 301. 18 p. </span> <span class="year">(2023)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a 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class="mtid"><span class="long-pub-mtid">Közlemény: 33772189</span> | <span class="status-data status-VALIDATED"> Egyeztetett </span> Idéző | <span class="type-subtype">Folyóiratcikk ( Szakcikk ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">WOS TAGGED</span> </div> <div class="lastModified">Utolsó módosítás: 2023.04.25. 15:49 Laczik Cecilia (SE_AOK_1Patológia_Admin5_LC, admin) </div> <pre class="comment" style="margin-top: 0; margin-bottom: 0;"><u>Megjegyzés</u>: Export Date: 19 June 2023 CODEN: BCMAC Correspondence Address: Yu, B.; Department of Gastroenterology, China; email: yubp62@163.com Correspondence Address: Wang, W.; Department of Gastroenterology, China; email: 50248@hbuas.edu.cn</pre> </div></div>