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Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma
PURPOSE: Kidney renal papillary cell carcinoma (KIRP) is a highly heterogeneous malignancy and current systemic therapeutic strategies are difficult to achieve a satisfactory outcome for advanced disease. Meanwhile, there is a lack of effective biomarkers to predict the prognosis of KIRP. METHODS: U...
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/PMC10067223/ https://www.ncbi.nlm.nih.gov/pubmed/37004005 http://dx.doi.org/10.1186/s12894-023-01218-5 |
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author | Liu, Yifu Cheng, Xiaofeng Xi, Ping Zhang, Zhicheng Sun, Ting Gong, Binbin |
author_facet | Liu, Yifu Cheng, Xiaofeng Xi, Ping Zhang, Zhicheng Sun, Ting Gong, Binbin |
author_sort | Liu, Yifu |
collection | PubMed |
description | PURPOSE: Kidney renal papillary cell carcinoma (KIRP) is a highly heterogeneous malignancy and current systemic therapeutic strategies are difficult to achieve a satisfactory outcome for advanced disease. Meanwhile, there is a lack of effective biomarkers to predict the prognosis of KIRP. METHODS: Using TCGA, GTEx, UALCAN, TIMER, TIMER 2.0 and STRING databases, we analyzed the relationship of SNHG6 with KIRP subtypes, tumor-infiltrating immune cells and potential target mRNAs. Based on TCGA data, ROC curves, Kaplan–Meier survival analysis and COX regression analysis were performed to evaluate the diagnostic and prognostic value of SNHG6 in KIRP. Nomogram was used to predict 3- and 5-year disease-specific survival in KIRP patients. In addition, with the help of Genetic ontology and Gene set enrichment analysis, the biological processes and signalling pathways that SNHG6 may be involved in KIRP were initially explored. RESULTS: In patients with KIRP, SNHG6 was significantly upregulated and associated with a more aggressive subtype (lymph node involvement, pathological stage IV, CIMP phenotype) and poor prognosis. The ROC curve showed good diagnostic efficacy (AUC value: 0.828) and the C-index of the Nomogram for predicting DSS at 3 and 5 years was 0.920 (0.898–0.941). In the immune microenvironment of KIRP, SNHG6 expression levels were negatively correlated with macrophage abundance and positively correlated with cancer-associated fibroblasts. Furthermore, SNHG6 may promote KIRP progression by regulating the expression of molecules such as AURKB, NDC80, UBE2C, NUF2, PTTG1, CENPH, SPC25, CDCA3, CENPM, BIRC5, TROAP, EZH2. Last, GSEA suggests that SNHG6 may be involved in the regulation of the PPAR signalling pathway and the SLIT/ROBO signalling pathway. CONCLUSIONS: Our analysis suggests that a high SNHG6 expression status in KIRP is associated with a poorer prognosis for patients, and also elucidates some potential mechanisms contributing to this poorer outcome. This may provide new insights into the treatment and management of KIRP in the foreseeable future. |
format | Online Article Text |
id | pubmed-10067223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100672232023-04-03 Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma Liu, Yifu Cheng, Xiaofeng Xi, Ping Zhang, Zhicheng Sun, Ting Gong, Binbin BMC Urol Research PURPOSE: Kidney renal papillary cell carcinoma (KIRP) is a highly heterogeneous malignancy and current systemic therapeutic strategies are difficult to achieve a satisfactory outcome for advanced disease. Meanwhile, there is a lack of effective biomarkers to predict the prognosis of KIRP. METHODS: Using TCGA, GTEx, UALCAN, TIMER, TIMER 2.0 and STRING databases, we analyzed the relationship of SNHG6 with KIRP subtypes, tumor-infiltrating immune cells and potential target mRNAs. Based on TCGA data, ROC curves, Kaplan–Meier survival analysis and COX regression analysis were performed to evaluate the diagnostic and prognostic value of SNHG6 in KIRP. Nomogram was used to predict 3- and 5-year disease-specific survival in KIRP patients. In addition, with the help of Genetic ontology and Gene set enrichment analysis, the biological processes and signalling pathways that SNHG6 may be involved in KIRP were initially explored. RESULTS: In patients with KIRP, SNHG6 was significantly upregulated and associated with a more aggressive subtype (lymph node involvement, pathological stage IV, CIMP phenotype) and poor prognosis. The ROC curve showed good diagnostic efficacy (AUC value: 0.828) and the C-index of the Nomogram for predicting DSS at 3 and 5 years was 0.920 (0.898–0.941). In the immune microenvironment of KIRP, SNHG6 expression levels were negatively correlated with macrophage abundance and positively correlated with cancer-associated fibroblasts. Furthermore, SNHG6 may promote KIRP progression by regulating the expression of molecules such as AURKB, NDC80, UBE2C, NUF2, PTTG1, CENPH, SPC25, CDCA3, CENPM, BIRC5, TROAP, EZH2. Last, GSEA suggests that SNHG6 may be involved in the regulation of the PPAR signalling pathway and the SLIT/ROBO signalling pathway. CONCLUSIONS: Our analysis suggests that a high SNHG6 expression status in KIRP is associated with a poorer prognosis for patients, and also elucidates some potential mechanisms contributing to this poorer outcome. This may provide new insights into the treatment and management of KIRP in the foreseeable future. BioMed Central 2023-04-01 /pmc/articles/PMC10067223/ /pubmed/37004005 http://dx.doi.org/10.1186/s12894-023-01218-5 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 Liu, Yifu Cheng, Xiaofeng Xi, Ping Zhang, Zhicheng Sun, Ting Gong, Binbin Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
title | Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
title_full | Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
title_fullStr | Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
title_full_unstemmed | Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
title_short | Bioinformatic analysis highlights SNHG6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
title_sort | bioinformatic analysis highlights snhg6 as a putative prognostic biomarker for kidney renal papillary cell carcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067223/ https://www.ncbi.nlm.nih.gov/pubmed/37004005 http://dx.doi.org/10.1186/s12894-023-01218-5 |
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