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Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs

Pancreatic cancer is one major digestive malignancy with a poor prognosis. Given the clinical importance of lncRNAs, developing a novel molecular panel with lncRNAs for pancreatic cancer has great potential. As a result, an 8-lncRNA-based robust prognostic signature was constructed using a random su...

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Autores principales: Ma, Di, Yang, Yuchen, Cai, Qiang, Ye, Feng, Deng, Xiaxing, Shen, Baiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9515791/
https://www.ncbi.nlm.nih.gov/pubmed/36186449
http://dx.doi.org/10.3389/fgene.2022.973444
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author Ma, Di
Yang, Yuchen
Cai, Qiang
Ye, Feng
Deng, Xiaxing
Shen, Baiyong
author_facet Ma, Di
Yang, Yuchen
Cai, Qiang
Ye, Feng
Deng, Xiaxing
Shen, Baiyong
author_sort Ma, Di
collection PubMed
description Pancreatic cancer is one major digestive malignancy with a poor prognosis. Given the clinical importance of lncRNAs, developing a novel molecular panel with lncRNAs for pancreatic cancer has great potential. As a result, an 8-lncRNA-based robust prognostic signature was constructed using a random survival forest model after examing the expression profile and prognostic significance of lncRNAs in the PAAD cohort from TCGA. The efficacy and effectiveness of the lncRNA-based signature were thoroughly assessed. Patients with high- and low-risk defined by the signature underwent significantly distinct OS expectancy. Most crucially the training group’s AUCs of ROC approached 0.90 and the testing group similarly had the AUCs above 0.86. The lncRNA-based signature was shown to behave as a prognostic indicator of pancreatic cancer, either alone or simultaneously with other factors, after combined analysis with other clinical-pathological factors in Cox regression and nomogram. Additionally, using GSEA and CIBERSORT scoring methods, the immune landscape and variations in biological processes between high- and low-risk subgroups were investigated. Last but not least, drug databases were searched for prospective therapeutic molecules targeting high-risk patients. The most promising compound were Afatinib, LY-303511, and RO-90-7501 as a result. In conclusion, we developed a novel lncRNA based prognostic signature with high efficacy to stratify high-risk pancreatic cancer patients and screened prospective responsive drugs for targeting strategy.
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spelling pubmed-95157912022-09-29 Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs Ma, Di Yang, Yuchen Cai, Qiang Ye, Feng Deng, Xiaxing Shen, Baiyong Front Genet Genetics Pancreatic cancer is one major digestive malignancy with a poor prognosis. Given the clinical importance of lncRNAs, developing a novel molecular panel with lncRNAs for pancreatic cancer has great potential. As a result, an 8-lncRNA-based robust prognostic signature was constructed using a random survival forest model after examing the expression profile and prognostic significance of lncRNAs in the PAAD cohort from TCGA. The efficacy and effectiveness of the lncRNA-based signature were thoroughly assessed. Patients with high- and low-risk defined by the signature underwent significantly distinct OS expectancy. Most crucially the training group’s AUCs of ROC approached 0.90 and the testing group similarly had the AUCs above 0.86. The lncRNA-based signature was shown to behave as a prognostic indicator of pancreatic cancer, either alone or simultaneously with other factors, after combined analysis with other clinical-pathological factors in Cox regression and nomogram. Additionally, using GSEA and CIBERSORT scoring methods, the immune landscape and variations in biological processes between high- and low-risk subgroups were investigated. Last but not least, drug databases were searched for prospective therapeutic molecules targeting high-risk patients. The most promising compound were Afatinib, LY-303511, and RO-90-7501 as a result. In conclusion, we developed a novel lncRNA based prognostic signature with high efficacy to stratify high-risk pancreatic cancer patients and screened prospective responsive drugs for targeting strategy. Frontiers Media S.A. 2022-09-14 /pmc/articles/PMC9515791/ /pubmed/36186449 http://dx.doi.org/10.3389/fgene.2022.973444 Text en Copyright © 2022 Ma, Yang, Cai, Ye, Deng and Shen. 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 Genetics
Ma, Di
Yang, Yuchen
Cai, Qiang
Ye, Feng
Deng, Xiaxing
Shen, Baiyong
Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
title Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
title_full Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
title_fullStr Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
title_full_unstemmed Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
title_short Identification of a lncRNA based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
title_sort identification of a lncrna based signature for pancreatic cancer survival to predict immune landscape and potential therapeutic drugs
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9515791/
https://www.ncbi.nlm.nih.gov/pubmed/36186449
http://dx.doi.org/10.3389/fgene.2022.973444
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