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

Yi-Bo He; Lu-Wei Fang; Dan Hu; Shi-Liang Chen; Si-Yu Shen; Kai-Li Chen; Jie Mu; Jun-Yu Li; Hongpan Zhang; Liu Yong-Lin; Li Zhang

doi:10.3389/fonc.2022.967207

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

Front Oncol. 2022 Jul 28:12:967207. doi: 10.3389/fonc.2022.967207. eCollection 2022.

Authors

Yi-Bo He^{1

2}, Lu-Wei Fang², Dan Hu³, Shi-Liang Chen^{1

2}, Si-Yu Shen², Kai-Li Chen², Jie Mu², Jun-Yu Li⁴, Hongpan Zhang⁵, Liu Yong-Lin⁶, Li Zhang⁷

Affiliations

¹ Department of Clinical Lab, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China.
² The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
³ Department of Clinical Lab, The Cixi Integrated Traditional Chinese and Western Medicine Medical and Health Group Cixi Red Cross Hospital, Cixi, China.
⁴ Department of Pharmacy, Sanya Women and Children Hospital Managed by Shanghai Children's Medical Center, Sanya, China.
⁵ Department of Oncology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
⁶ Reproductive Centre, Sanya Women and Children Hospital Managed by Shanghai Children's Medical Center, Sanya, China.
⁷ Obstetrics and Gynaecology, The First Affiliated Hospital of Zhejiang Chinese Medical, Hangzhou, China.

Abstract

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.

Keywords: TCGA; immunotherapy; long noncoding RNAs; necroptosis; ovarian cancer.