Cargando…
Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer
OBJECTIVE: The mortality rate of ovarian cancer (OC) is the highest among all gynecologic cancers. To predict the prognosis and the efficacy of immunotherapy, we identified new biomarkers. METHODS: The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used t...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9366220/ https://www.ncbi.nlm.nih.gov/pubmed/35965557 http://dx.doi.org/10.3389/fonc.2022.967207 |
_version_ | 1784765513570713600 |
---|---|
author | He, Yi-bo Fang, Lu-wei Hu, Dan Chen, Shi-liang Shen, Si-yu Chen, Kai-li Mu, Jie Li, Jun-yu Zhang, Hongpan Yong-lin, Liu Zhang, Li |
author_facet | He, Yi-bo Fang, Lu-wei Hu, Dan Chen, Shi-liang Shen, Si-yu Chen, Kai-li Mu, Jie Li, Jun-yu Zhang, Hongpan Yong-lin, Liu Zhang, Li |
author_sort | He, Yi-bo |
collection | PubMed |
description | OBJECTIVE: The mortality rate of ovarian cancer (OC) is the highest among all gynecologic cancers. To predict the prognosis and the efficacy of immunotherapy, we identified new biomarkers. METHODS: The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used to extract ovarian cancer transcriptomes. By performing the co-expression analysis, we identified necroptosis-associated long noncoding RNAs (lncRNAs). We used the least absolute shrinkage and selection operator (LASSO) to build the risk model. The qRT-PCR assay was conducted to confirm the differential expression of lncRNAs in the ovarian cancer cell line SK-OV-3. Gene Set Enrichment Analysis, Kaplan-Meier analysis, and the nomogram were used to determine the lncRNAs model. Additionally, the risk model was estimated to evaluate the efficacy of immunotherapy and chemotherapy. We classified necroptosis-associated IncRNAs into two clusters to distinguish between cold and hot tumors. RESULTS: The model was constructed using six necroptosis-associated lncRNAs. The calibration plots from the model showed good consistency with the prognostic predictions. The overall survival of one, three, and five-year areas under the ROC curve (AUC) was 0.691, 0.678, and 0.691, respectively. There were significant differences in the IC50 between the risk groups, which could serve as a guide to systemic treatment. The results of the qRT-PCR assay showed that AL928654.1, AL133371.2, AC007991.4, and LINC00996 were significantly higher in the SK-OV-3 cell line than in the Iose-80 cell line (P < 0.05). The clusters could be applied to differentiate between cold and hot tumors more accurately and assist in accurate mediation. Cluster 2 was more vulnerable to immunotherapies and was identified as the hot tumor. CONCLUSION: Necroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors. |
format | Online Article Text |
id | pubmed-9366220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93662202022-08-12 Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer He, Yi-bo Fang, Lu-wei Hu, Dan Chen, Shi-liang Shen, Si-yu Chen, Kai-li Mu, Jie Li, Jun-yu Zhang, Hongpan Yong-lin, Liu Zhang, Li Front Oncol Oncology OBJECTIVE: The mortality rate of ovarian cancer (OC) is the highest among all gynecologic cancers. To predict the prognosis and the efficacy of immunotherapy, we identified new biomarkers. METHODS: The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used to extract ovarian cancer transcriptomes. By performing the co-expression analysis, we identified necroptosis-associated long noncoding RNAs (lncRNAs). We used the least absolute shrinkage and selection operator (LASSO) to build the risk model. The qRT-PCR assay was conducted to confirm the differential expression of lncRNAs in the ovarian cancer cell line SK-OV-3. Gene Set Enrichment Analysis, Kaplan-Meier analysis, and the nomogram were used to determine the lncRNAs model. Additionally, the risk model was estimated to evaluate the efficacy of immunotherapy and chemotherapy. We classified necroptosis-associated IncRNAs into two clusters to distinguish between cold and hot tumors. RESULTS: The model was constructed using six necroptosis-associated lncRNAs. The calibration plots from the model showed good consistency with the prognostic predictions. The overall survival of one, three, and five-year areas under the ROC curve (AUC) was 0.691, 0.678, and 0.691, respectively. There were significant differences in the IC50 between the risk groups, which could serve as a guide to systemic treatment. The results of the qRT-PCR assay showed that AL928654.1, AL133371.2, AC007991.4, and LINC00996 were significantly higher in the SK-OV-3 cell line than in the Iose-80 cell line (P < 0.05). The clusters could be applied to differentiate between cold and hot tumors more accurately and assist in accurate mediation. Cluster 2 was more vulnerable to immunotherapies and was identified as the hot tumor. CONCLUSION: Necroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors. Frontiers Media S.A. 2022-07-28 /pmc/articles/PMC9366220/ /pubmed/35965557 http://dx.doi.org/10.3389/fonc.2022.967207 Text en Copyright © 2022 He, Fang, Hu, Chen, Shen, Chen, Mu, Li, Zhang, Yong-lin and Zhang 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 | Oncology He, Yi-bo Fang, Lu-wei Hu, Dan Chen, Shi-liang Shen, Si-yu Chen, Kai-li Mu, Jie Li, Jun-yu Zhang, Hongpan Yong-lin, Liu Zhang, Li Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
title | Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
title_full | Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
title_fullStr | Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
title_full_unstemmed | Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
title_short | Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
title_sort | necroptosis-associated long noncoding rnas can predict prognosis and differentiate between cold and hot tumors in ovarian cancer |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9366220/ https://www.ncbi.nlm.nih.gov/pubmed/35965557 http://dx.doi.org/10.3389/fonc.2022.967207 |
work_keys_str_mv | AT heyibo necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT fangluwei necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT hudan necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT chenshiliang necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT shensiyu necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT chenkaili necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT mujie necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT lijunyu necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT zhanghongpan necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT yonglinliu necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer AT zhangli necroptosisassociatedlongnoncodingrnascanpredictprognosisanddifferentiatebetweencoldandhottumorsinovariancancer |