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Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature
Endometrial carcinoma (EC) is one of the common gynecological cancers with increasing incidence and revived mortality recently. Given the heterogeneity of tumors and the complexity of lncRNAs, a panel of lncRNA biomarkers might be more precise and stable for prognosis. In the present study, we devel...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8844015/ https://www.ncbi.nlm.nih.gov/pubmed/35178403 http://dx.doi.org/10.3389/fcell.2021.814456 |
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author | Ding, Hongmei Jiang, Fei Deng, Lifeng Wang, Juan Wang, Ping Ji, Mintao Li, Jie Shi, Weiqiang Pei, Yufang Li, Jiafu Zhang, Yue Zhang, Zengli Chen, Youguo Li, Bingyan |
author_facet | Ding, Hongmei Jiang, Fei Deng, Lifeng Wang, Juan Wang, Ping Ji, Mintao Li, Jie Shi, Weiqiang Pei, Yufang Li, Jiafu Zhang, Yue Zhang, Zengli Chen, Youguo Li, Bingyan |
author_sort | Ding, Hongmei |
collection | PubMed |
description | Endometrial carcinoma (EC) is one of the common gynecological cancers with increasing incidence and revived mortality recently. Given the heterogeneity of tumors and the complexity of lncRNAs, a panel of lncRNA biomarkers might be more precise and stable for prognosis. In the present study, we developed a new lncRNA model to predict the prognosis of patients with EC. EC-associated differentially expressed long noncoding RNAs (lncRNAs) were identified from The Cancer Genome Atlas (TCGA). Univariate COX regression and least absolute shrinkage and selection operator (LASSO) model were selected to find the 8-independent prognostic lncRNAs of EC patient. Furthermore, the risk score of the 3-lncRNA signature for overall survival (OS) was identified as CTD-2377D24.6 expression × 0.206 + RP4-616B8.5 × 0.341 + RP11-389G6.3 × 0.343 by multivariate Cox regression analysis. According to the median cutoff value of this prognostic signature, the EC samples were divided into two groups, high-risk set (3-lncRNAs at high levels) and low-risk set (3-lncRNAs at low levels), and the Kaplan–Meier survival curves demonstrated that the low-risk set had a higher survival rate than the high-risk set. In addition, the 3-lncRNA signature was closely linked with histological subtype (p = 0.0001), advanced clinical stage (p = 0.011), and clinical grade (p < 0.0001) in EC patients. Our clinical samples also confirmed that RP4-616B8.5, RP11-389G6.3, and CTD-2377D24.6 levels were increased in tumor tissues by qRT-PCR and in situ hybridization. Intriguingly, the p-value of combined 3-lncRNAs was lower than that of each lncRNA, indicating that the 3-lncRNA signature also showed higher performance in EC tissue than paracancerous. Functional analysis revealed that cortactin might be involved in the mechanism of 3-lncRNA signatures. These findings provide the first hint that a panel of lncRNAs may play a critical role in the initiation and metastasis of EC, indicating a new signature for early diagnosis and therapeutic strategy of uterine corpus endometrial carcinoma. |
format | Online Article Text |
id | pubmed-8844015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88440152022-02-16 Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature Ding, Hongmei Jiang, Fei Deng, Lifeng Wang, Juan Wang, Ping Ji, Mintao Li, Jie Shi, Weiqiang Pei, Yufang Li, Jiafu Zhang, Yue Zhang, Zengli Chen, Youguo Li, Bingyan Front Cell Dev Biol Cell and Developmental Biology Endometrial carcinoma (EC) is one of the common gynecological cancers with increasing incidence and revived mortality recently. Given the heterogeneity of tumors and the complexity of lncRNAs, a panel of lncRNA biomarkers might be more precise and stable for prognosis. In the present study, we developed a new lncRNA model to predict the prognosis of patients with EC. EC-associated differentially expressed long noncoding RNAs (lncRNAs) were identified from The Cancer Genome Atlas (TCGA). Univariate COX regression and least absolute shrinkage and selection operator (LASSO) model were selected to find the 8-independent prognostic lncRNAs of EC patient. Furthermore, the risk score of the 3-lncRNA signature for overall survival (OS) was identified as CTD-2377D24.6 expression × 0.206 + RP4-616B8.5 × 0.341 + RP11-389G6.3 × 0.343 by multivariate Cox regression analysis. According to the median cutoff value of this prognostic signature, the EC samples were divided into two groups, high-risk set (3-lncRNAs at high levels) and low-risk set (3-lncRNAs at low levels), and the Kaplan–Meier survival curves demonstrated that the low-risk set had a higher survival rate than the high-risk set. In addition, the 3-lncRNA signature was closely linked with histological subtype (p = 0.0001), advanced clinical stage (p = 0.011), and clinical grade (p < 0.0001) in EC patients. Our clinical samples also confirmed that RP4-616B8.5, RP11-389G6.3, and CTD-2377D24.6 levels were increased in tumor tissues by qRT-PCR and in situ hybridization. Intriguingly, the p-value of combined 3-lncRNAs was lower than that of each lncRNA, indicating that the 3-lncRNA signature also showed higher performance in EC tissue than paracancerous. Functional analysis revealed that cortactin might be involved in the mechanism of 3-lncRNA signatures. These findings provide the first hint that a panel of lncRNAs may play a critical role in the initiation and metastasis of EC, indicating a new signature for early diagnosis and therapeutic strategy of uterine corpus endometrial carcinoma. Frontiers Media S.A. 2022-02-01 /pmc/articles/PMC8844015/ /pubmed/35178403 http://dx.doi.org/10.3389/fcell.2021.814456 Text en Copyright © 2022 Ding, Jiang, Deng, Wang, Wang, Ji, Li, Shi, Pei, Li, Zhang, Zhang, Chen and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Ding, Hongmei Jiang, Fei Deng, Lifeng Wang, Juan Wang, Ping Ji, Mintao Li, Jie Shi, Weiqiang Pei, Yufang Li, Jiafu Zhang, Yue Zhang, Zengli Chen, Youguo Li, Bingyan Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature |
title | Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature |
title_full | Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature |
title_fullStr | Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature |
title_full_unstemmed | Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature |
title_short | Prediction of Clinical Outcome in Endometrial Carcinoma Based on a 3-lncRNA Signature |
title_sort | prediction of clinical outcome in endometrial carcinoma based on a 3-lncrna signature |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8844015/ https://www.ncbi.nlm.nih.gov/pubmed/35178403 http://dx.doi.org/10.3389/fcell.2021.814456 |
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