A 3-MicroRNA Signature Identified From Serum Predicts Clinical Outcome of the Locally Advanced Gastric Cancer

Increased expression of LINC00323 correlates with tumor progression and poor prognosis of gastric cancer

BACKGROUD/AIMS

LINC00323 is a novel lncRNA which has reported to play an important role in the development and recurrence in several cancers. However, the expression and predictive value of LINC00323 in gastric cancer (GC) remain mysterious.

METHODS

LINC00323 expression in GC tissues and adjacent normal tissues was evaluated by quantitative reverse-transcription PCR (qRT-PCR). The relationship between LINC00323 expression and clinicopathological features and patients' survival were analyzed. Univariate and multivariate survival analyses were performed.

RESULTS

LINC00323 expression were found to be significantly increased in GC tissues. High expression of LINC00323 exerted a pro-tumor effect in the late stage of GC development. Kaplan-Meier analysis showed that patients with high LINC00323 were associated with poor overall survival (OS) and progression-free survival (PFS). Moreover, the combination of TNM stage and drinking status better identified GC patient outcome than those of TNM stage alone.

CONCLUSIONS

Our data showed that LINC00323 overexpression might serve as a novel independent prognostic factor for survival of GC patients, suggesting LINC00323 was a potential biomarker and therapeutic target for GC.

Prognostic Value of miR-1826 in Prostate Cancer and Its Regulatory Effect on Tumor Progression

Purpose

miRNAs can act as oncogenes or tumor suppressors and participate in the development and progression of tumors, thus affecting the prognosis and survival of cancer patients. In this paper, we mainly studied the role of miR-1826 in prostate cancer.

Patients and Methods

The expression of miR-1826 was studied by quantitative real-time PCR (qRT-PCR). Kaplan–Meier curves were used to analyze the relationship between the expression of miR-1826 and the survival rate of PC patients. Cox regression analysis was used to study the risk factors affecting the prognosis of PC patients. PC cells were transfected with miR-1826 mimic, mimic negative control (mimic NC), miR-1826 inhibitor, or inhibitor NC. The effect of miR-1826 on the proliferation of PC cells was studied by the CCK-8 method and colony formation assay. Transwell assays were used to detect the effect of miR-1826 on the migratory and invasive abilities of tumor cells.

Results

The expression of miR-1826 in PC tissues was lower than that in adjacent normal tissues, and that the expression levels of miR-1826 in four PC cell lines were all lower than normal human prostate epithelial cell lines. Patients with low expression of miR-1826 had shorter overall survival compared with those with high expression. The downregulation of miR-1826 promoted PC cell proliferation, migration, and invasion.

Conclusion

In summary, the low expression of miR-1826 may promote the progression of PC, and the low expression of miR-1826 is also associated with a poor prognosis in PC patients.

Identification of a Novel Prognostic Signature for Gastric Cancer Based on Multiple Level Integration and Global Network Optimization

Gastric Cancer (GC) is a common cancer worldwide with a high morbidity and mortality rate in Asia. Many prognostic signatures from genes and non-coding RNA (ncRNA) levels have been identified by high-throughput expression profiling for GC. To date, there have been no reports on integrated optimization analysis based on the GC global lncRNA-miRNA-mRNA network and the prognostic mechanism has not been studied. In the present work, a Gastric Cancer specific lncRNA-miRNA-mRNA regulatory network (GCsLMM) was constructed based on the ceRNA hypothesis by combining miRNA-target interactions and data on the expression of GC. To mine for novel prognostic signatures associated with GC, we performed topological analysis, a random walk with restart algorithm, in the GCsLMM from three levels, miRNA-, mRNA-, and lncRNA-levels. We further obtained candidate prognostic signatures by calculating the integrated score and analyzed the robustness of these signatures by combination strategy. The biological roles of key candidate signatures were also explored. Finally, we targeted the PHF10 gene and analyzed the expression patterns of PHF10 in independent datasets. The findings of this study will improve our understanding of the competing endogenous RNA (ceRNA) regulatory mechanisms and further facilitate the discovery of novel prognostic biomarkers for GC clinical guidelines.