Identification of LncRNA Prognostic Markers for Ovarian Cancer by Integration of Co-expression and CeRNA Network

Liang, Huisheng; Bai, Yiping; Wang, Hailong; Yang, Xiangjun

doi:10.3389/fgene.2020.566497

Cited by 7 publications

(4 citation statements)

References 73 publications

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“…These results demonstrate that lncRNAs are promising prognostic markers in OC. An autophagy-related lncRNA prognostic signature for OC was constructed by Meng et al ( 35 ) and an immune-related lncRNA prognostic model for the prediction of survival in OC was established by Liang et al ( 36 ). However, it appears there is no evidence of a ferroptosis-related lncRNA prognostic signature in OC.…”

Section: Discussionmentioning

confidence: 99%

A ferroptosis-related lncRNA signature predicts prognosis in ovarian cancer patients

Peng¹,

Hu²,

Rao³

et al. 2021

Transl Cancer Res TCR

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Background: Ovarian cancer (OC) is a common gynecological malignant tumor with poor prognosis.Ferroptosis is an iron-dependent modality of regulated cell death. The purpose of this study was to determine the prognostic ability of ferroptosis-related long non-coding RNAs (lncRNAs) in OC patients and construct a ferroptosis-related lncRNA prognostic model. Methods: The Cancer Genome Atlas (TCGA) and FerrDb databases were used to collect RNA sequencing data of OC patients and ferroptosis-related genes, respectively. OC patients were randomly assigned to the training or testing set. Pearson correlation analysis was used to identify ferroptosis-related lncRNAs. Univariate Cox, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate regression analyses were performed in the training set to develop a predictive model. The model was validated in the testing set and entire set. Survival analysis, receiver operating characteristic curves, independent prognostic factor analysis, and correlation analysis with clinical features were performed to evaluate the predictive value of the model. A nomogram was established to predict the survivability of OC patients over 1, 3, and 5 years. The distribution of distinct groups was investigated using principal component analysis, and the underlying the biological functions were explored using gene set enrichment analysis. Results: Eleven ferroptosis-related lncRNAs were determined to establish the prognostic model. Patients in the high-risk group had poor prognosis compared with the low-risk group in the training, testing and entire sets. The area under the receiver operating characteristic curve corresponding to 1-, 3-, and 5-year survival were 0.731, 0.796, and 0.805 in the training set; 0.704, 0.597, and 0.655 in the testing set; and 0.715, 0.691, and 0.736, in the entire set, respectively. The risk score correlated with age and grade. The risk score was also an independent prognostic factor in OC. A nomogram with high C-index (0.68) was constructed. An intuitive observation of the principal component analysis revealed a distinction between high-and lowrisk groups, and gene set enrichment analysis indicated that cancer-related pathways were enriched in the high-risk group. Conclusions: The signature composed of 11 ferroptosis-related lncRNAs accurately predicted the prognosis of OC patients.

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Section: Discussionmentioning

confidence: 99%

A ferroptosis-related lncRNA signature predicts prognosis in ovarian cancer patients

Peng¹,

Hu²,

Rao³

et al. 2021

Transl Cancer Res TCR

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“…Thus, it is necessary to construct a prognostic model which can predict the prognosis and immunotherapy response based on immune-related lncRNAs in ovarian cancer. Liang et al [32] used weighted gene co-expression network analysis (WGCNA) and found that the expression levels of 4 lncRNAs could be used as independent immune prognostic factors for OC. Liu et al [33] identified 52 lncRNAs as ovarian cancer-specific immune lncRNA and redefined two different molecular subtypes.…”

Section: Discussionmentioning

confidence: 99%

Immune-Related Long Non-coding RNA Constructs a Prognostic Signature of Ovarian Cancer

Sun

et al. 2021

Biol Proced Online

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Background Since ovarian cancer leads to the poor prognosis in women all over the world, we aim to construct an immune-related lncRNAs signature to improve the survival of ovarian cancer patients. Methods Normal and cancer patient samples and corresponding clinical data of ovarian were obtained from The Genotype-Tissue Expression (GTEx) portal and The Cancer Genome Atlas (TCGA) database. The predictive signature was constructed by the lasso penalty Cox proportional hazard regression model. The division of different risk groups was accounting for the optimal critical value of the time-dependent Receiver Operating Characteristic (ROC) curve. Finally, we validated and evaluated the application of this prognostic signature based on the clinical factors, chemo-sensitivity and immune status of different risk groups. Results The signature was established from 145 DEirlncRNAs and can be shown as an independent prognostic risk factor with accurate prediction on overall survival in ovarian cancer patients. Further analysis on the application of the prognostic signature showed that patients with low-risk had a better sensitivity to chemotherapy and a higher immunogenicity. Conclusion We constructed and verified an effective signature based on DEirlncRNA pairs, which could predict the prognosis, drug sensitivity and immune status of ovarian cancer patients and promote the prognostic estimation and individualized treatment.

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“…After identifying the miRNAs that overlapped between the miRDB and miRWalk website, the Cytoscape software was used to visualize the lncRNA-miRNA-mRNA ceRNA network. Finally, the GenCLiP310 website 7 was used to perform functional enrichment analysis to explore the functions of the genes in this ceRNA network ( Liang et al, 2020 ).…”

Section: Methodsmentioning

confidence: 99%

A Potential Immune-Related Long Non-coding RNA Prognostic Signature for Ovarian Cancer

Pan

2021

Front. Genet.

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Ovarian cancer (OC), the most lethal gynecologic malignancy, ranks fifth in cancer deaths among women, largely because of late diagnosis. Recent studies suggest that the expression levels of immune-related long non-coding RNAs (lncRNAs) play a significant role in the prognosis of OC; however, the potential of immune-related lncRNAs as prognostic factors in OC remains unexplored. In this study, we aimed to identify a potential immune-related lncRNA prognostic signature for OC patients. We used RNA sequencing and clinical data from The Cancer Genome Atlas and the Gene Expression Omnibus database to identify immune-related lncRNAs that could serve as useful biomarkers for OC diagnosis and prognosis. Univariate Cox regression analysis was used to identify the immune-related lncRNAs with prognostic value. Functional annotation of the data was performed through the GenCLiP310 website. Seven differentially expressed lncRNAs (AC007406.4, AC008750.1, AL022341.2, AL133351.1, FAM74A7, LINC02229, and HOXB-AS2) were found to be independent prognostic factors for OC patients. The Kaplan-Meier curve indicated that patients in the high-risk group had a poorer survival outcome than those in the low-risk group. The receiver operating characteristic curve revealed that the predictive potential of the immune-related lncRNA signature for OC was robust. The prognostic signature of the seven lncRNAs was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the signature of the seven lncRNAs was an independent prognostic factor for OC patients. Finally, we constructed a nomogram model and a competing endogenous RNA network related to the lncRNA prognostic signature. In conclusion, our study reveals novel immune-related lncRNAs that may serve as independent prognostic factors in OC.

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Identification of LncRNA Prognostic Markers for Ovarian Cancer by Integration of Co-expression and CeRNA Network

Cited by 7 publications

References 73 publications

A ferroptosis-related lncRNA signature predicts prognosis in ovarian cancer patients

A ferroptosis-related lncRNA signature predicts prognosis in ovarian cancer patients

Immune-Related Long Non-coding RNA Constructs a Prognostic Signature of Ovarian Cancer

A Potential Immune-Related Long Non-coding RNA Prognostic Signature for Ovarian Cancer

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