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Background. Several studies have been conducted to investigate the role of cell division cycle-associated 5 (CDCA5) in cancer. Its role in breast cancer, however, remains unknown. Methods. The Gene Expression Omnibus and Cancer Genome Atlas Program databases provided the open-access information needed for the research. The CCK8 and colony formation assays were used to measure cell proliferation. The capacity of breast cancer cells to invade and migrate was assessed using the transwell assay. Results. In our study, CDCA5 was identified as the interested gene through a series of bioinformatics analysis. We found a higher CDCA5 expression level in tissue and cells of breast cancer. Meanwhile, CDCA5 has been linked to increased proliferation, invasion, and migration of breast cancer cells, which was also associated with worse clinical features. The biochemical pathways, in which CDCA5 was engaged, were identified using biological enrichment analysis. Immune infiltration research revealed that CDCA5 was linked to enhanced activity of several immune function terms. Meanwhile, DNA methylation might be responsible for the aberrant level of CDCA5 in tumor tissue. In addition, CDCA5 could significantly increase the paclitaxel and docetaxel sensitivity, indicating that it has the potential for clinical application. Also, we found that CDCA5 is mainly localized in cell nucleoplasm. Moreover, in the breast cancer microenvironment, we found that CDCA5 is mainly expressed in malignant cells, proliferation T cells, and neutrophils. Conclusion. Overall, our findings suggest that CDCA5 is a potential prognostic indicator and target for breast cancer, which can indicate the direction of the relevant research. [ABSTRACT FROM AUTHOR]

Background. Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC. Materials and Methods. ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed. Results. Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress. Conclusion. In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer (LC) and one of the leading causes of cancer-related death worldwide. LUAD has a low survival rate owing to tumour invasion and metastasis. Circulating tumour cells (CTCs) are precursors of distant metastasis, which are considered to adopt the characteristics of cancer stem cells (CSCs). Therefore, analysing the risk factors of LUAD from the perspective of CTCs may provide novel insights into the metastatic mechanisms and may help to develop diagnostic and therapeutic strategies.Methods: A total of 447 patients from TCGA dataset were included in the training cohort, and 460 patients from the GEO dataset were included in the validation cohort. A CTC-related-gene risk model was constructed using LASSO penalty-Cox analysis, and its predictive value was further verified. Functional enrichment analysis was performed on differentially expressed genes (DEGs), followed by immune correlation analysis based on the results. In addition, western blot, CCK-8 and colony formation assays were used to validate the biological function of RAB26 in LUAD.Results: A novel in-silico CTC-related-gene risk model, named the CTCR model, was constructed, which successfully divided patients into the high- and low-risk groups. The prognosis of the high-risk group was worse than that of the low-risk group. ROC analysis revealed that the risk model outperformed traditional clinical markers in predicting the prognosis of patients with LUAD. Further study demonstrated that the identified DEGs were significantly enriched in immune-related pathways. The immune score of the low-risk group was higher than that of the high-risk group. In addition, RAB26 was found to promote the proliferation of LUAD.Conclusion: A prognostic risk model based on CTC-related genes was successfully constructed, and the relationship between DEGs and tumour immunity was analysed. In addition, RAB26 was found to promote the proliferation of LUAD cells. [ABSTRACT FROM AUTHOR]