Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis
Abstract Diagnosing low-grade and high-grade endometrial stromal sarcoma (LG-ESS and HG-ESS) is a challenge. This study aimed to identify biomarkers. 22 ESS cases were analyzed using Illumina microarrays. Differentially expressed genes (DEGs) were identified via Limma. DEGs were analyzed with String...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-47668-7 |
| _version_ | 1797363392248283136 |
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| author | Ruiqi Zhang Weilin Zhao Xingyao Zhu Yuhua Liu Qi Ding Caiyun Yang Hong Zou |
| author_facet | Ruiqi Zhang Weilin Zhao Xingyao Zhu Yuhua Liu Qi Ding Caiyun Yang Hong Zou |
| author_sort | Ruiqi Zhang |
| collection | DOAJ |
| description | Abstract Diagnosing low-grade and high-grade endometrial stromal sarcoma (LG-ESS and HG-ESS) is a challenge. This study aimed to identify biomarkers. 22 ESS cases were analyzed using Illumina microarrays. Differentially expressed genes (DEGs) were identified via Limma. DEGs were analyzed with String and Cytoscape. Core genes were enriched with GO and KEGG, their pan-cancer implications and immune aspects were studied. 413 DEGs were found by exome sequencing, 2174 by GSE85383 microarray. 36 common genes were identified by Venn analysis, and 10 core genes including RBFOX1, PCDH7, FAT1 were selected. Core gene GO enrichment included cell adhesion, T cell proliferation, and KEGG focused on related pathways. Expression was evaluated across 34 cancers, identifying immune DEGs IGF1 and AVPR1A. Identifying the DEGs not only helps improve our understanding of LG-ESS, HG-ESS but also promises to be potential biomarkers for differential diagnosis between LG-ESS and HG-ESS and new therapeutic targets. |
| first_indexed | 2024-03-08T16:20:44Z |
| format | Article |
| id | doaj.art-b9be1fe7a1ab4a10a8e154c8016a4a35 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-08T16:20:44Z |
| publishDate | 2024-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-b9be1fe7a1ab4a10a8e154c8016a4a352024-01-07T12:23:32ZengNature PortfolioScientific Reports2045-23222024-01-0114111110.1038/s41598-023-47668-7Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysisRuiqi Zhang0Weilin Zhao1Xingyao Zhu2Yuhua Liu3Qi Ding4Caiyun Yang5Hong Zou6Department of Pathology, The First Affiliated Hospital, Shihezi University School of MedicineDepartment of Pathology, Taihe Hospital, Hubei University of MedicineDepartment of Pathology, The Second Affiliated Hospital of Zhejiang University School of MedicineDepartment of Pathology, The First Affiliated Hospital, Shihezi University School of MedicineDepartment of Pathology, The First Affiliated Hospital, Shihezi University School of MedicineDepartment of Pathology, The First Affiliated Hospital, Shihezi University School of MedicineDepartment of Pathology, The Second Affiliated Hospital of Zhejiang University School of MedicineAbstract Diagnosing low-grade and high-grade endometrial stromal sarcoma (LG-ESS and HG-ESS) is a challenge. This study aimed to identify biomarkers. 22 ESS cases were analyzed using Illumina microarrays. Differentially expressed genes (DEGs) were identified via Limma. DEGs were analyzed with String and Cytoscape. Core genes were enriched with GO and KEGG, their pan-cancer implications and immune aspects were studied. 413 DEGs were found by exome sequencing, 2174 by GSE85383 microarray. 36 common genes were identified by Venn analysis, and 10 core genes including RBFOX1, PCDH7, FAT1 were selected. Core gene GO enrichment included cell adhesion, T cell proliferation, and KEGG focused on related pathways. Expression was evaluated across 34 cancers, identifying immune DEGs IGF1 and AVPR1A. Identifying the DEGs not only helps improve our understanding of LG-ESS, HG-ESS but also promises to be potential biomarkers for differential diagnosis between LG-ESS and HG-ESS and new therapeutic targets.https://doi.org/10.1038/s41598-023-47668-7 |
| spellingShingle | Ruiqi Zhang Weilin Zhao Xingyao Zhu Yuhua Liu Qi Ding Caiyun Yang Hong Zou Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis Scientific Reports |
| title | Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis |
| title_full | Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis |
| title_fullStr | Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis |
| title_full_unstemmed | Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis |
| title_short | Identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis |
| title_sort | identification of hub genes distinguishing subtypes in endometrial stromal sarcoma through comprehensive bioinformatics analysis |
| url | https://doi.org/10.1038/s41598-023-47668-7 |
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