Dataset Information

Expression and Clinical Significance of Origin Recognition Complex Subunit 6 in Breast Cancer - A Comprehensive Bioinformatics Analysis.

ABSTRACT:

Objective

We aimed to investigate the expression, diagnostic and prognostic values, and potential molecular mechanisms of the origin recognition complex (ORC) in breast cancer (BC).

Methods

Kaplan-Meier estimation was used to assess the prognostic value of ORC genes, and Oncomine, TCGA, GEO and ULCAN databases were used to analyze their expression in BC. Wilcoxon rank-sum tests were used to evaluate the relationship between ORC gene expression levels and BC clinicopathological features. Receiver operating characteristic (ROC) curves were used to assess the diagnostic value of ORC genes in BC. Survival analysis was performed using Kaplan-Meier estimation and Cox regression. A nomogram was constructed to predict 1-, 3-, and 5-year survival probabilities in BC. Gene set enrichment analysis (GSEA) and immune infiltration were used to investigate potential molecular mechanisms of the ORC.

Results

ORC1L and ORC6L were highly expressed in BC compared with healthy tissue, while ORC5L expression patterns were inconsistent; no significant differences in ORC2L, ORC3L or ORC4L expression were observed between BC and healthy tissues. ORC1L and ORC6L expression levels were significantly correlated with age, tumor (T) stage and molecular subtype; ORC5L expression was significantly correlated with age and number of nearby lymph nodes with cancer (N stage). ORC6L expression had the highest diagnostic value in BC and was an independent prognostic factor for poor overall survival (OS). ORC6L may be involved in cell cycle progression and may regulate cancer signaling pathways, including NF-κB, P53, and WNT, in BC. ORC6L expression was also associated with immune infiltration.

Conclusion

ORC1L and ORC6L are highly expressed in BC; ORC6L has a high diagnostic value and is an independent prognostic factor for poor OS. ORC6L may be involved in the initiation and progression of BC by regulating cell cycle progression, promoting cancer signaling pathway activation, and influencing tumor immune cell infiltration.

SUBMITTER: Chen S

PROVIDER: S-EPMC8684402 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundGastric cancer (GC) is one of the common gastrointestinal malignancy worldwide and exhibits a poor prognosis. Increasing studies have indicated that microRNAs play critical roles in the cancer progression and have shown great potential as useful biomarkers. The search for potential diagnostic and prognostic biomarkers of gastric cancer (GC) with integrated bioinformatics analyses has been undertaken in previous studies.MethodsIn this study, the robust rank aggregation (RRA) method was used to perform an integrated analysis of differentially expressed miRNAs (DEMs) from five microarray datasets in the Gene Expression Omnibus (GEO) database to find robust biomarkers for GC. Ultimately, seven miRNAs were filtered from fourteen primary miRNAs using the validation set of The Cancer Genome Atlas (TCGA) database. Based on these results, diagnostic and survival analyses were performed, and logistic regression and Cox regression were used to determine the clinicopathological characteristics of the DEM expression and overall survival.ResultsNine eligible miRNA datasets related to GC were selected from the GEO database for integrated analysis in this study. Diagnostic analysis implied that these miRNAs could be regarded as promising candidate diagnostic biomarkers in GC tissues, but whether the results of the tissue analysis are consistent with those of peripheral blood analysis requires further validation. The logistic regression indicated that the ectopic expression of these DEMs was relevant to the histological type, anatomical region, and pathological grade of GC. However, the survival and Cox regression analyses suggested that the poor prognosis of GC patients was not strongly dependent on the ectopic expression of the seven miRNAs, but rather, a poor prognosis was associated with age, metastasis, and histological grade.ConclusionsBased on the results presented in this study it can be concluded that these miRNAs (miR-455-3p, miR-135b-5p, let-7a-3p, miR-195-5p, miR-204-5p, miR-149-5p, and miR-143-3p) might be potential biomarkers for the early diagnosis of GC patients, but this finding should be regarded with caution. A large-scale, prospective, and multicenter cohort study should be performed.