Identification and validation of a five-lncRNA signature for predicting survival with targeted drug candidates in ovarian cancer

Lin, Jia‐zhe; Tanaka, Yoshiaki; Sun, Pingnan; Zhou, Xiaoling

doi:10.1080/21655979.2021.1946632

Cited by 24 publications

(23 citation statements)

References 47 publications

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“…Wang et al found that NRAV can mediate the activation of the Wnt/bcatenin signaling pathway to promote the proliferation and invasion of hepatocellular carcinoma (41). Lin et al discovered that BMPR1B-DT is a prognostic marker of ovarian cancer and is associated with drug sensitivity (42). The role of OLMALINC in osteosarcoma was confirmed by He et al, who found that it was highly correlated with the immune microenvironment of osteosarcoma and could assess patient outcomes (43).…”

Section: Discussionmentioning

confidence: 97%

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The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

Chen

Zhu

et al. 2022

Front. Oncol.

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BackgroundOne of the most common diseases that have a negative impact on women’s health is endometrial carcinoma (EC). Advanced endometrial cancer has a dismal prognosis and lacks solid prognostic indicators. IFN-γ is a key cytokine in the inflammatory response, and it has also been suggested that it has a role in the tumor microenvironment. The significance of IFN-γ-related genes and long non-coding RNAs in endometrial cancer, however, is unknown.MethodsThe Cancer Genome Atlas (TCGA) database was used to download RNA-seq data from endometrial cancer tissues and normal controls. Genes associated with IFN-γ were retrieved from the gene set enrichment analysis (GSEA) website. Co-expression analysis was performed to find lncRNAs linked to IFN-γ gene. The researchers employed weighted co-expression network analysis (WGCNA) to find lncRNAs that were strongly linked to survival. The prognostic signature was created using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The training cohort, validation cohort, and entire cohort of endometrial cancer patients were then split into high-risk and low-risk categories. To investigate variations across different risk groups, we used survival analysis, enrichment analysis, and immune microenvironment analysis. The platform for analysis is R software (version X64 3.6.1).ResultsBased on the transcript expression of IFN-γ-related lncRNAs, two distinct subgroups of EC from TCGA cohort were formed, each with different outcomes. Ten IFN-γ-related lncRNAs were used to build a predictive signature using Cox regression analysis and the LASSO regression, including CFAP58, LINC02014, UNQ6494, AC006369.1, NRAV, BMPR1B-DT, AC068134.2, AP002840.2, GS1-594A7.3, and OLMALINC. The high-risk group had a considerably worse outcome (p < 0.05). In the immunological microenvironment, there were also substantial disparities across different risk categories.ConclusionOur findings give a reference for endometrial cancer prognostic type and immunological status assessment, as well as prospective molecular markers for the disease.

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Section: Discussionmentioning

confidence: 97%

“…Lin et al. discovered that BMPR1B-DT is a prognostic marker of ovarian cancer and is associated with drug sensitivity ( 42 ). The role of OLMALINC in osteosarcoma was confirmed by He et al., who found that it was highly correlated with the immune microenvironment of osteosarcoma and could assess patient outcomes ( 43 ).…”

Section: Discussionmentioning

confidence: 99%

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

Chen

Zhu

et al. 2022

Front. Oncol.

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“…Considering that only about 1.5% of the human genome encodes proteins, and most of the genome is transcribed, non-coding RNAs such as lncRNAs may play crucial roles in biological processes ( 7 ). Researchers have increasingly found that lncRNAs play an important role in tumor biology ( 5 , 32 ). Herein, we investigated the role of LINC00467 in LUAD and demonstrated that DNA copy amplification and hypomethylation were two vital mechanisms of LINC00467 upregulation and were associated with poor prognosis.…”

Section: Discussionmentioning

confidence: 99%

LINC00467 Is Upregulated by DNA Copy Number Amplification and Hypomethylation and Shows ceRNA Potential in Lung Adenocarcinoma

Wang

Liang

et al. 2022

Front. Endocrinol.

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Lung adenocarcinoma (LUAD) is the most common histological lung cancer, and it is the leading cause of cancer-related deaths worldwide. Long noncoding RNAs (lncRNAs) have been implicated in tumorigenesis. LINC00467 is a novel lncRNA that is abnormally expressed in several cancer types including LUAD. However, its function and regulatory mechanism in LUAD progression remain unclear. In this study, based on The Cancer Genome Atlas data mining, we demonstrated that DNA copy number amplification and hypomethylation was positively correlated with LINC00467 expression in LUAD. In addition, DNA copy number amplification was significantly associated with distant metastasis, immune infiltration and poor survival. Microarray analysis demonstrated that LINC00467 knockdown in the LUAD A549 cell line led to a distinct microRNA expression profile that impacted various target genes involved in multiple biological processes. This finding suggests that LINC00467 may regulate LUAD progression by functioning as a competing endogenous RNA (ceRNA). Finally, we constructed a ceRNA network that included two microRNAs (hsa-miR-1225-5p, hsa-miR-575) and five mRNAs (BARX2, BCL9, KCNK1, KIAA1324, TMEM182) specific to LINC00467 in LUAD. Subsequent Kaplan-Meier survival analysis in both The Cancer Genome Atlas and Gene Expression Omnibus databases revealed that two genes, BARX2 and BCL9, were potential prognostic biomarkers for LUAD patients. In conclusion, our data provide possible mechanisms underlying the abnormal upregulation of LINC00467 as well as a comprehensive view of the LINC00467-mediated ceRNA network in LUAD, thereby highlighting its potential role in diagnosis and therapy.

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“…12 necroptosis-related lncRNAs highly associated with OS in glioma patients were identified by lasso and univariate and multifactorial Cox regression, and risk prognostic models were constructed by risk score (i.e., AC025857.2, AC092718.4, AL513534.1, AC083864.2, ZNF236-DT, AC099850.3, AL590094.1, AC010226.1, POLR2J4, AC023024.1, SLC25A21-AS1, and AC109439.2). In these lncRNAs, AC092718.4 has been reported to be highly correlated with ovarian cancer as a predictive signature [22]. AC099850.3 has been found to promote proliferation and invasion in hepatocellular carcinoma via the PRR11/PI3K/AKT pathway and is also a major participant in prognostic models for squamous cell carcinoma of the tongue and non-small-cell lung cancer [23][24][25].…”

Section: Discussionmentioning

confidence: 99%

Construction and Validation of a Necroptosis-Related lncRNA Signature in Prognosis and Immune Microenvironment for Glioma

Jiang

Zhan

Yang

et al. 2022

Journal of Oncology

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Background. Glioma is the most common primary brain tumor, representing approximately 80.8% of malignant tumors. Necroptosis triggers and enhances antitumor immunity and is expected to be a new target for tumor immunotherapy. The effectiveness of necroptosis-related lncRNAs as potential therapeutic targets for glioma has not been elucidated. Methods. We acquired RNA-seq data sets from LGG and GBM samples, and the corresponding clinical characteristic information is from TCGA. Normal brain tissue data is from GTEX. Based on TCGA and GTEx, we used univariate Cox regression to sort out survival-related lncRNAs. Lasso regression models were then built. Then, we performed a separate Kaplan-Meier analysis of the lncRNAs used for modeling. We validated different risk groups via OS, DFS, enrichment analysis, comprehensive immune analysis, and drug sensitivity. Results. We constructed a 12 prognostic lncRNAs model after bioinformatic analysis. Subsequently, the risk score of every glioma patient was calculated based on correlation coefficients and expression levels, and the patients were split into low- and high-risk groups according to the median value of the risk score. A nomogram was established for every glioma patient to predict prognosis. Besides, we found significant differences in OS, DFS, immune infiltration and checkpoints, and immune therapy between different risk subgroups. Conclusion. Predictive models of 12 necroptosis-related lncRNAs can facilitate the assessment of the prognosis and molecular characteristics of glioma patients and improve treatment modalities.

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Identification and validation of a five-lncRNA signature for predicting survival with targeted drug candidates in ovarian cancer

Cited by 24 publications

References 47 publications

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

LINC00467 Is Upregulated by DNA Copy Number Amplification and Hypomethylation and Shows ceRNA Potential in Lung Adenocarcinoma

Construction and Validation of a Necroptosis-Related lncRNA Signature in Prognosis and Immune Microenvironment for Glioma

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