4.6 Article

Necroptosis-associated long noncoding RNAs can predict prognosis and differentiate between cold and hot tumors in ovarian cancer

期刊

FRONTIERS IN ONCOLOGY
卷 12, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2022.967207

关键词

ovarian cancer; necroptosis; immunotherapy; long noncoding RNAs; TCGA

类别

资金

  1. Research Projects of Zhejiang Chinese Medicine University [2022JKZKTS26, 2022JKJNTZ16]
  2. Zhejiang young and middle-aged clinical famous Chinese medicine talents project [1S22228]
  3. Hainan Province Health Industry Scientific Research Project [21A200333]
  4. Medical Institutions Special Science and Technology Project [2021GXYL29]
  5. Hainan Province Clinical Medical Center
  6. Sanya Maternal and Child Health Hospital Golden Coconut Seeds [JYZZ201903]
  7. Sanya Special Science and Technology Program for Universities and Medical Institutions [2021GXYL29]
  8. Hainan Health Science Education Project [21A200333]
  9. Sanya University

向作者/读者索取更多资源

In this study, necroptosis-associated lncRNAs were identified as reliable prognostic predictors in ovarian cancer. The risk model established can predict patient prognosis and provide treatment strategies.
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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据