Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer
ObjectiveThe 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.MethodsThe Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx) databases were used to ext...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.967207/full |
| _version_ | 1818041639998849024 |
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| author | Yi-bo He Yi-bo He Lu-wei Fang Dan Hu Shi-liang Chen Shi-liang Chen Si-yu Shen Kai-li Chen Jie Mu Jun-yu Li Hongpan Zhang Liu Yong-lin Li Zhang |
| author_facet | Yi-bo He Yi-bo He Lu-wei Fang Dan Hu Shi-liang Chen Shi-liang Chen Si-yu Shen Kai-li Chen Jie Mu Jun-yu Li Hongpan Zhang Liu Yong-lin Li Zhang |
| author_sort | Yi-bo He |
| collection | DOAJ |
| description | ObjectiveThe 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.MethodsThe 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.ResultsThe 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.ConclusionNecroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors. |
| first_indexed | 2024-12-10T08:33:38Z |
| format | Article |
| id | doaj.art-7f6ef526695a4c2281ed817f9fd238f0 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-10T08:33:38Z |
| publishDate | 2022-07-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj.art-7f6ef526695a4c2281ed817f9fd238f02022-12-22T01:56:02ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-07-011210.3389/fonc.2022.967207967207Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancerYi-bo He0Yi-bo He1Lu-wei Fang2Dan Hu3Shi-liang Chen4Shi-liang Chen5Si-yu Shen6Kai-li Chen7Jie Mu8Jun-yu Li9Hongpan Zhang10Liu Yong-lin11Li Zhang12Department of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Clinical Lab, The Cixi Integrated Traditional Chinese and Western Medicine Medical and Health Group Cixi Red Cross Hospital, Cixi, ChinaDepartment of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, ChinaThe First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, ChinaDepartment of Pharmacy, Sanya Women and Children Hospital Managed by Shanghai Children’s Medical Center, Sanya, ChinaDepartment of Oncology, Affiliated Hospital of North Sichuan Medical College, Nanchong, ChinaReproductive Centre, Sanya Women and Children Hospital Managed by Shanghai Children’s Medical Center, Sanya, ChinaObstetrics and Gynaecology, The First Affiliated Hospital of Zhejiang Chinese Medical, Hangzhou, ChinaObjectiveThe 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.MethodsThe 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.ResultsThe 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.ConclusionNecroptosis-associated lncRNAs are reliable predictors of prognosis and can provide a treatment strategy by screening for hot tumors.https://www.frontiersin.org/articles/10.3389/fonc.2022.967207/fullovarian cancernecroptosisimmunotherapylong noncoding RNAsTCGA |
| spellingShingle | Yi-bo He Yi-bo He Lu-wei Fang Dan Hu Shi-liang Chen Shi-liang Chen Si-yu Shen Kai-li Chen Jie Mu Jun-yu Li Hongpan Zhang Liu Yong-lin Li Zhang Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer Frontiers in Oncology ovarian cancer necroptosis immunotherapy long noncoding RNAs TCGA |
| 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 | ovarian cancer necroptosis immunotherapy long noncoding RNAs TCGA |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.967207/full |
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