Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma

Zheng, Mingjun; Hu, Yuexin; Gou, Rui; Wang, Jing; Nie, Xin; Li, Xiao; Liu, Qing; Liu, Juanjuan; Lin, Bei

doi:10.18632/aging.102047

Cited by 23 publications

(16 citation statements)

References 30 publications

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“…More than 70% of cases are diagnosed in the advanced stage. The 5-year survival rate of disease is around one-fifth to one-third [4,5]. Consequently, the key molecule of forecasting and diagnosing OC is necessary to be determined.…”

Section: Introductionmentioning

confidence: 99%

Up-regulation of circ_LARP4 suppresses cell proliferation and migration in ovarian cancer by regulating miR-513b-5p/LARP4 axis

et al. 2020

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Background: Ovarian cancer (OC) is a common fatal malignant tumor of female reproductive system worldwide. Growing studies have proofed that circular RNAs (circRNAs) engage in the regulation of various types of cancers. However, the underlying biological functions and effect mechanism of circular RNA_LARP4 (circ_LARP4) in OC have not been explored. Methods: Quantitative real-time polymerase chain reaction (qRT-PCR) analysis was used to detect the expression of circ_LARP4 in OC cells. The function of circ_LARP4 was measured by cell counting kit-8 (CCK-8), colony formation assay and transwell assay. RNA immunoprecipitation (RIP) assay and luciferase reporter assays assessed the binding correlation between miR-513b-5p and circ_LARP4 (or LARP4). Results: The expression of circ_LARP4 in OC cells was much lower than that in human normal ovarian epithelial cells. Overexpressing circ_LARP4 impaired cell proliferation, invasion and migration abilities. Circ_LARP4 worked as a competing endogenous RNA (ceRNA) to sponge miR-513b-5p. Furthermore, LARP4 was indirectly modulated by circ_LARP4 as the downstream target of miR-513b-5p, as well as the host gene of circ_LARP4. Conclusion: Circ_LARP4 could hamper cell proliferation and migration by sponging miR-513b-5p to regulate the expression of LARP4. This research may provide some referential value to OC treatment.

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Section: Introductionmentioning

confidence: 99%

Up-regulation of circ_LARP4 suppresses cell proliferation and migration in ovarian cancer by regulating miR-513b-5p/LARP4 axis

et al. 2020

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“…Studies found that the abnormalities of DNA copy number and DNA methylation have important effects on the progression of sarcomas, and the two may also have co-regulatory effects [ 18 , 19 ]. However, so far, their potential relationship in sarcoma progression has not been studied.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of prognostic markers in sarcomas base on a multi-omics analysis

et al. 2021

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Background In sarcomas, the DNA copy number and DNA methylation exhibit genomic aberrations. Transcriptome imbalances play a driving role in the heterogeneous progression of sarcomas. However, it is still unclear whether abnormalities of DNA copy numbers are systematically related to epigenetic DNA methylation, thus, a comprehensive analysis of sarcoma occurrence and development from the perspective of epigenetic and genomics is required. Methods RNASeq, copy number variation (CNV), methylation data, clinical follow-up information were obtained from The Cancer Genome Atlas (TCGA) and GEO database. The association between methylation and CNV was analyzed to further identify methylation-related genes (MET-Gs) and CNV abnormality-related genes (CNV-Gs). Subsequently DNA copy number, methylation, and gene expression data associated with the MET-Gs and CNV-Gs were integrated to determine molecular subtypes and clinical and molecular characteristics of molecular subtypes. Finally, key biomarkers were determined and validated in independent validation sets. Results A total of 5354 CNV-Gs and 4042 MET-Gs were screened and showed a high degree of consistency. Four molecular subtypes (iC1, iC2, iC3, and iC4) with different prognostic significances were identified by multiomics cluster analysis, specifically, iC2 had the worst prognosis and iC4 indicated an immune-enhancing state. Three potential prognostic markers (ENO1, ACVRL1 and APBB1IP) were determined after comparing the molecular characteristics of the four molecular subtypes. The expression of ENO1 gene was significantly correlated with CNV, and was noticeably higher in iC2 subtype with the worst prognosis than any other subtypes. The expressions of ACVRL1 and APBB1IP were negatively correlated with methylation, and were high-expressed in the iC4 subtype with the most favorable prognosis. In addition, the number of silent/nonsilent mutations and neoantigens in iC2 subtype were significantly more than those in iC1/iC3/iC4 subtype, and the same trend was also observed in CNV Gain/Loss. Conclusion The current comprehensive analysis of genomic and epigenomic regulation provides new insights into multilayered pathobiology of sarcomas. Four molecular subtypes and three prognostic markers developed in this study improve the current understanding of the molecular mechanisms underlying sarcoma.

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“…Large and complicated biological data has been generated with the advent of high-throughput detection technology and bioinformatics development. The Cancer Genome Atlas (TCGA) database is one of the largest cancer genome program that provides researchers with multi-omics and standardized clinical data that can be used to design basic bioinformatics research [22,23]. The ESTIMATE algorithm can predict tumor purity by calculating the immune and stromal scores based on specific molecular biomarker expression in both immune and stromal cells [24].…”

Section: Introductionmentioning

confidence: 99%

A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer

Ding

Dong

Wang

et al. 2020

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Mounting evidence suggests that immune cell infiltration within the tumor microenvironment (TME) is a crucial regulator of carcinogenesis and therapeutic efficacy in ovarian cancer (OC). In this study, 593 OC patients from TCGA were divided into high and low score groups based on their immune/stromal scores resulting from analysis utilizing the ESTIMATE algorithm. Differential expression analysis revealed 294 intersecting genes that influencing both the immune and stromal scores. Further Cox regression analysis identified 34 differentially expressed genes (DEGs) as prognostic-related genes. Finally, the nine-gene signature was derived from the prognostic-related genes using a Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression. This nine-gene signature could effectively distinguish the high-risk patients in the training (TCGA database) and validation (GSE17260) cohorts (all p < 0.01). A time-dependent receiver operating characteristic (ROC) analysis showed that the nine-gene signature had a reasonable predictive accuracy (AUC = 0.707, AUC =0.696) in both cohorts. In addition, this nine-gene signature is associated with immune infiltration in TME by Gene Set Variation Analysis (GSVA), and can be used to predict the survival of patients with OC.

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Integrated multi-omics analysis of genomics, epigenomics, and transcriptomics in ovarian carcinoma

Cited by 23 publications

References 30 publications

Up-regulation of circ_LARP4 suppresses cell proliferation and migration in ovarian cancer by regulating miR-513b-5p/LARP4 axis

Up-regulation of circ_LARP4 suppresses cell proliferation and migration in ovarian cancer by regulating miR-513b-5p/LARP4 axis

Development and validation of prognostic markers in sarcomas base on a multi-omics analysis

A nine-gene signature related to tumor microenvironment predicts overall survival with ovarian cancer

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