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LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer
BACKGROUND: Leucine-rich repeat sequence domains are known to mediate protein‒protein interactions. Recently, some studies showed that members of the leucine rich repeat containing (LRRC) protein superfamily may become new targets for the diagnosis and treatment of tumours. However, it is not known...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850808/ https://www.ncbi.nlm.nih.gov/pubmed/36653841 http://dx.doi.org/10.1186/s12920-023-01435-9 |
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author | Zhu, Xiaoying You, Shijing Du, Xiuzhen Song, Kejuan Lv, Teng Zhao, Han Yao, Qin |
author_facet | Zhu, Xiaoying You, Shijing Du, Xiuzhen Song, Kejuan Lv, Teng Zhao, Han Yao, Qin |
author_sort | Zhu, Xiaoying |
collection | PubMed |
description | BACKGROUND: Leucine-rich repeat sequence domains are known to mediate protein‒protein interactions. Recently, some studies showed that members of the leucine rich repeat containing (LRRC) protein superfamily may become new targets for the diagnosis and treatment of tumours. However, it is not known whether any of the LRRC superfamily genes is expressed in the stroma of ovarian cancer (OC) and is associated with prognosis. METHODS: The clinical data and transcriptional profiles of OC patients from the public databases TCGA (n = 427), GTEx (n = 88) and GEO (GSE40266 and GSE40595) were analysed by R software. A nomogram model was also generated through R. An online public database was used for auxiliary analysis of prognosis, immune infiltration and protein‒protein interaction (PPI) networks. Immunohistochemistry and qPCR were performed to determine the protein and mRNA levels of genes in high-grade serous ovarian cancer (HGSC) tissues of participants and the MRC-5 cell line induced by TGF-β. RESULTS: LRRC15 and LRRC32 were identified as differentially expressed genes from the LRRC superfamily by GEO transcriptome analysis. PPI network analysis suggested that they were most enriched in TGF-β signalling. The TCGA-GTEx analysis results showed that only LRRC15 was highly expressed in both cancer-associated fibroblasts (CAFs) and the tumour stroma of OC and was related to clinical prognosis. Based on this, we developed a nomogram model to predict the incidence of adverse outcomes in OC. Moreover, LRRC15 was positively correlated with CAF infiltration and negatively correlated with CD8 + T-cell infiltration. As a single indicator, LRRC15 had the highest accuracy (AUC = 0.920) in predicting the outcome of primary platinum resistance. CONCLUSIONS: The LRRC superfamily is related to the TGF-β pathway in the microenvironment of OC. LRRC15, as a stromal biomarker, can predict the clinical prognosis of HGSC and promote the immunosuppressive microenvironment. LRRC15 may be a potential therapeutic target for reversing primary resistance in OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01435-9. |
format | Online Article Text |
id | pubmed-9850808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-98508082023-01-20 LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer Zhu, Xiaoying You, Shijing Du, Xiuzhen Song, Kejuan Lv, Teng Zhao, Han Yao, Qin BMC Med Genomics Research BACKGROUND: Leucine-rich repeat sequence domains are known to mediate protein‒protein interactions. Recently, some studies showed that members of the leucine rich repeat containing (LRRC) protein superfamily may become new targets for the diagnosis and treatment of tumours. However, it is not known whether any of the LRRC superfamily genes is expressed in the stroma of ovarian cancer (OC) and is associated with prognosis. METHODS: The clinical data and transcriptional profiles of OC patients from the public databases TCGA (n = 427), GTEx (n = 88) and GEO (GSE40266 and GSE40595) were analysed by R software. A nomogram model was also generated through R. An online public database was used for auxiliary analysis of prognosis, immune infiltration and protein‒protein interaction (PPI) networks. Immunohistochemistry and qPCR were performed to determine the protein and mRNA levels of genes in high-grade serous ovarian cancer (HGSC) tissues of participants and the MRC-5 cell line induced by TGF-β. RESULTS: LRRC15 and LRRC32 were identified as differentially expressed genes from the LRRC superfamily by GEO transcriptome analysis. PPI network analysis suggested that they were most enriched in TGF-β signalling. The TCGA-GTEx analysis results showed that only LRRC15 was highly expressed in both cancer-associated fibroblasts (CAFs) and the tumour stroma of OC and was related to clinical prognosis. Based on this, we developed a nomogram model to predict the incidence of adverse outcomes in OC. Moreover, LRRC15 was positively correlated with CAF infiltration and negatively correlated with CD8 + T-cell infiltration. As a single indicator, LRRC15 had the highest accuracy (AUC = 0.920) in predicting the outcome of primary platinum resistance. CONCLUSIONS: The LRRC superfamily is related to the TGF-β pathway in the microenvironment of OC. LRRC15, as a stromal biomarker, can predict the clinical prognosis of HGSC and promote the immunosuppressive microenvironment. LRRC15 may be a potential therapeutic target for reversing primary resistance in OC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12920-023-01435-9. BioMed Central 2023-01-18 /pmc/articles/PMC9850808/ /pubmed/36653841 http://dx.doi.org/10.1186/s12920-023-01435-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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. |
spellingShingle | Research Zhu, Xiaoying You, Shijing Du, Xiuzhen Song, Kejuan Lv, Teng Zhao, Han Yao, Qin LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
title | LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
title_full | LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
title_fullStr | LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
title_full_unstemmed | LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
title_short | LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
title_sort | lrrc superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9850808/ https://www.ncbi.nlm.nih.gov/pubmed/36653841 http://dx.doi.org/10.1186/s12920-023-01435-9 |
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