Cargando…
Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods
BACKGROUND: Alternative splicing (AS) is an important mechanism for regulating gene expression and proteome diversity. Tumor-alternative splicing can reveal a large class of new splicing-associated potential new antigens that may affect the immune response and can be used for immunotherapy. METHODS:...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527772/ https://www.ncbi.nlm.nih.gov/pubmed/33062405 http://dx.doi.org/10.7717/peerj.9174 |
_version_ | 1783589128250589184 |
---|---|
author | Liu, Jie Zhou, Miao Ouyang, Yangyang Du, Laifeng Xu, Lingbo Li, Hongyun |
author_facet | Liu, Jie Zhou, Miao Ouyang, Yangyang Du, Laifeng Xu, Lingbo Li, Hongyun |
author_sort | Liu, Jie |
collection | PubMed |
description | BACKGROUND: Alternative splicing (AS) is an important mechanism for regulating gene expression and proteome diversity. Tumor-alternative splicing can reveal a large class of new splicing-associated potential new antigens that may affect the immune response and can be used for immunotherapy. METHODS: The RNA-seq transcriptome data and clinical information of stomach adenocarcinoma (STAD) cohort were downloaded from The Cancer Genome Atlas (TCGA) database data portal, and data of splicing events were obtained from the SpliceSeq database. Predicting genes were validated by Asian cancer research group (ACRG) cohort and Oncomine database. RT-qPCR was used to analysis the expression of ECT2 in STAD. RESULTS: A total of 32,166 AS events were identified, among which 2,042 AS events were significantly associated with patients survival. Biological pathway analysis indicated that these genes play an important role in regulating gastric cancer-related processes such as GTPase activity and PI3K-Akt signaling pathway. Next, we derived a risk signature, using alternate acceptor, that is an independent prognostic marker. Moreover, high ECT2 expression was associated with poorer prognosis in STAD. Multivariate survival analysis demonstrated that high ECT2 expression was an independent risk factor for overall survival. Gene set enrichment analysis revealed that high ECT2 expression was enriched for hallmarks of malignant tumors. The ACRG cohort and Oncomine also showed that high ECT2 expression was associated with poorer prognosis in gastric cancer patients. Finally, RT-qPCR showed ECT2 expression was higher in STAD compared to the normal tissues. CONCLUSION: This study excavated the alternative splicing events in gastric cancer, and found ECT2 might be a biomarkers for diagnosis and prognosis. |
format | Online Article Text |
id | pubmed-7527772 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75277722020-10-13 Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods Liu, Jie Zhou, Miao Ouyang, Yangyang Du, Laifeng Xu, Lingbo Li, Hongyun PeerJ Bioinformatics BACKGROUND: Alternative splicing (AS) is an important mechanism for regulating gene expression and proteome diversity. Tumor-alternative splicing can reveal a large class of new splicing-associated potential new antigens that may affect the immune response and can be used for immunotherapy. METHODS: The RNA-seq transcriptome data and clinical information of stomach adenocarcinoma (STAD) cohort were downloaded from The Cancer Genome Atlas (TCGA) database data portal, and data of splicing events were obtained from the SpliceSeq database. Predicting genes were validated by Asian cancer research group (ACRG) cohort and Oncomine database. RT-qPCR was used to analysis the expression of ECT2 in STAD. RESULTS: A total of 32,166 AS events were identified, among which 2,042 AS events were significantly associated with patients survival. Biological pathway analysis indicated that these genes play an important role in regulating gastric cancer-related processes such as GTPase activity and PI3K-Akt signaling pathway. Next, we derived a risk signature, using alternate acceptor, that is an independent prognostic marker. Moreover, high ECT2 expression was associated with poorer prognosis in STAD. Multivariate survival analysis demonstrated that high ECT2 expression was an independent risk factor for overall survival. Gene set enrichment analysis revealed that high ECT2 expression was enriched for hallmarks of malignant tumors. The ACRG cohort and Oncomine also showed that high ECT2 expression was associated with poorer prognosis in gastric cancer patients. Finally, RT-qPCR showed ECT2 expression was higher in STAD compared to the normal tissues. CONCLUSION: This study excavated the alternative splicing events in gastric cancer, and found ECT2 might be a biomarkers for diagnosis and prognosis. PeerJ Inc. 2020-07-14 /pmc/articles/PMC7527772/ /pubmed/33062405 http://dx.doi.org/10.7717/peerj.9174 Text en ©2020 Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Liu, Jie Zhou, Miao Ouyang, Yangyang Du, Laifeng Xu, Lingbo Li, Hongyun Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
title | Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
title_full | Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
title_fullStr | Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
title_full_unstemmed | Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
title_short | Identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
title_sort | identification of potential biomarkers and their clinical significance in gastric cancer using bioinformatics analysis methods |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527772/ https://www.ncbi.nlm.nih.gov/pubmed/33062405 http://dx.doi.org/10.7717/peerj.9174 |
work_keys_str_mv | AT liujie identificationofpotentialbiomarkersandtheirclinicalsignificanceingastriccancerusingbioinformaticsanalysismethods AT zhoumiao identificationofpotentialbiomarkersandtheirclinicalsignificanceingastriccancerusingbioinformaticsanalysismethods AT ouyangyangyang identificationofpotentialbiomarkersandtheirclinicalsignificanceingastriccancerusingbioinformaticsanalysismethods AT dulaifeng identificationofpotentialbiomarkersandtheirclinicalsignificanceingastriccancerusingbioinformaticsanalysismethods AT xulingbo identificationofpotentialbiomarkersandtheirclinicalsignificanceingastriccancerusingbioinformaticsanalysismethods AT lihongyun identificationofpotentialbiomarkersandtheirclinicalsignificanceingastriccancerusingbioinformaticsanalysismethods |