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Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer
OBJECTIVE: As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancer (GC). LncRNAs have been revealed to participate in this process. In this study, we tried to develop a stemness-related lncRNA pair signature as guidance for...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482617/ https://www.ncbi.nlm.nih.gov/pubmed/34587919 http://dx.doi.org/10.1186/s12885-021-08798-1 |
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author | Jiang, Quan Chen, Hao Tang, Zhaoqing Sun, Jie Ruan, Yuanyuan Liu, Fenglin Sun, Yihong |
author_facet | Jiang, Quan Chen, Hao Tang, Zhaoqing Sun, Jie Ruan, Yuanyuan Liu, Fenglin Sun, Yihong |
author_sort | Jiang, Quan |
collection | PubMed |
description | OBJECTIVE: As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancer (GC). LncRNAs have been revealed to participate in this process. In this study, we tried to develop a stemness-related lncRNA pair signature as guidance for clinical decisions. METHODS: The analysis was initiated by collecting stemness-related lncRNAs in TCGA cohort. The differentially expressed stemness-related lncRNAs between normal and tumor tissues in GC patients from TCGA datasets were further collected to establish the signature based on Lasso and Cox regression analyses. The predictive efficacy of the signature for chemotherapy and immunotherapy was also tested. The practicality of this signature was also validated by Zhongshan cohort. RESULTS: A 13-DEsrlncRNA pair-based signature was established. The cutoff point acquired by the AIC algorithm divided the TCGA cohort into high and low risk groups. We found that the low-risk group presented with better survival (Kaplan-Meier analysis, p < 0.001). Cox regression analyse was also conducted to confirm the signature as an independent risk factor for GC {p < 0.001, HR = 1.300, 95% CI (1.231–1.373)]}. As for the practicality of this signature, the IC50 of cytotoxic chemotherapeutics was significantly higher in the high-risk group. The low-risk group also presented with higher immunophenoscore (IPS) in both the “CTLA4+ PD1+” (Mann-Whitney U test, p = 0.019) and “CTLA4- PD1+” (Mann-Whitney U test, p = 0.013) groups, indicating higher sensitivity to immunotherapy. The efficacy of the signature was also validated by Zhongshan cohort. CONCLUSIONS: This study could not only provide a stemness-related lncRNA signature for survival prediction in GC patients but also established a model with predictive potentials for GC patients’ sensitivity to chemotherapy and immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08798-1. |
format | Online Article Text |
id | pubmed-8482617 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84826172021-10-04 Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer Jiang, Quan Chen, Hao Tang, Zhaoqing Sun, Jie Ruan, Yuanyuan Liu, Fenglin Sun, Yihong BMC Cancer Research OBJECTIVE: As a critical feature of cancers, stemness is acknowledged as a contributor to the development of drug resistance in gastric cancer (GC). LncRNAs have been revealed to participate in this process. In this study, we tried to develop a stemness-related lncRNA pair signature as guidance for clinical decisions. METHODS: The analysis was initiated by collecting stemness-related lncRNAs in TCGA cohort. The differentially expressed stemness-related lncRNAs between normal and tumor tissues in GC patients from TCGA datasets were further collected to establish the signature based on Lasso and Cox regression analyses. The predictive efficacy of the signature for chemotherapy and immunotherapy was also tested. The practicality of this signature was also validated by Zhongshan cohort. RESULTS: A 13-DEsrlncRNA pair-based signature was established. The cutoff point acquired by the AIC algorithm divided the TCGA cohort into high and low risk groups. We found that the low-risk group presented with better survival (Kaplan-Meier analysis, p < 0.001). Cox regression analyse was also conducted to confirm the signature as an independent risk factor for GC {p < 0.001, HR = 1.300, 95% CI (1.231–1.373)]}. As for the practicality of this signature, the IC50 of cytotoxic chemotherapeutics was significantly higher in the high-risk group. The low-risk group also presented with higher immunophenoscore (IPS) in both the “CTLA4+ PD1+” (Mann-Whitney U test, p = 0.019) and “CTLA4- PD1+” (Mann-Whitney U test, p = 0.013) groups, indicating higher sensitivity to immunotherapy. The efficacy of the signature was also validated by Zhongshan cohort. CONCLUSIONS: This study could not only provide a stemness-related lncRNA signature for survival prediction in GC patients but also established a model with predictive potentials for GC patients’ sensitivity to chemotherapy and immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08798-1. BioMed Central 2021-09-29 /pmc/articles/PMC8482617/ /pubmed/34587919 http://dx.doi.org/10.1186/s12885-021-08798-1 Text en © The Author(s) 2021 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 Jiang, Quan Chen, Hao Tang, Zhaoqing Sun, Jie Ruan, Yuanyuan Liu, Fenglin Sun, Yihong Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer |
title | Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer |
title_full | Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer |
title_fullStr | Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer |
title_full_unstemmed | Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer |
title_short | Stemness-related LncRNA pair signature for predicting therapy response in gastric cancer |
title_sort | stemness-related lncrna pair signature for predicting therapy response in gastric cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482617/ https://www.ncbi.nlm.nih.gov/pubmed/34587919 http://dx.doi.org/10.1186/s12885-021-08798-1 |
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