BackgroundBladder cancer was a malignant disease in patients, our research aimed at discovering the possible biomarkers for the diseases.ResultsThe gene chip GSE31684, including 93samples, was downloaded from the GEO datasets and co-expression network was constructed by the data. Molecular complex detection(MCODE) was used to identify hub genes. The most significant cluster including 16 genes: CDH11, COL3A1, COL6A3, COL5A1, AEBP1, COL1A2, NTM, COL11A1, THBS2, COL8A1, COL1A1, BGN, MMP2, PXDN, THY1, and TGFB1I1 was identified. After annotated by BiNGO, they were suggested associated with collagen fibril organization and blood vessel development. In addition, the Kaplan Meier curves were obtained by UALCAN. The high expression of THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1, and TGFB1I1 indicated poor prognosis of the patients(P < 0.05). Finally, we examined genes’ expression between low and high tumor stage by the Wilcoxon test(P < 0.05), TGFB1I1 was excluded.ConclusionTHY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1 associated with the tumor stage as well as tumor patients’ prognosis. COL5A1, COL8A1(P < 0.01) may serve as therapeutic targets for the disease.

Objective: To evaluate the value of serum sialic acid (SA) in diagnosis of benign prostatic hyperplasia (BPH), prostate cancer (PCa), and bone metastases in PCa patients.Materials and Methods: Data from 540 patients who were newly diagnosed with PCa or BPH between November 2014 and March 2018 were retrospectively collected and analyzed. Pretreatment SA levels were compared across various groups, then, associations between SA levels and clinic parameters of patients were analyzed as well. Univariate and multivariate logistic regression analyses were further used to identify independent associations.Results: The mean SA levels in patients with PCa were significantly higher than with BPH (p = 0.013). Furthermore, PCa patients with bone metastases showed elevated SA levels compared with PCa without bone metastases (p < 0.001). A multivariate logistic regression model showed that: SA level > 52.35 mg/dL was identified to be independently associated with the diagnosis of PCa (HR = 1.645, p = 0.036), and SA level > 59 mg/dL was identified to be independent association with the presence of bone metastases in PCa patients (HR = 6.421, p = 0.012).Conclusions: Elevated SA level is an independent predictor of prostate cancer as well as its bone metastases. Therefore, SA level may be a promising diagnostic and prognostic biomarker for prostate cancer and bone metastases.

BackgroundHepatoma-derived growth factor (HDGF) is a heparin-binding protein that has been observed to be abnormally expressed in numerous malignancies, but the definite role of HDGF in bladder cancer (BCa) has not been clarified. Here, we conduct the present study to evaluate correlations between HDGF and BCa.MethodsBioinformatics analysis was used to evaluate HDGF expression levels in BCa tissues. The effect of HDGF on cell proliferation, migration, invasion, cell cycle and apoptosis was analyzed utilizing CCK-8, clone formation, Transwell assays and flow cytometry, respectively. In addition, the xenograft tumor model was established.ResultsBased on bioinformatics analysis, we noticed that HDGF was highly expressed in BCa tissues and was positively correlated with poor prognosis in patients. Knockdown of HDGF markedly reduced tumorigenesis in BCa cells. Furthermore, the results of flow cytometry showed that HDGF deletion enhanced apoptosis in T24 and 253J cells and led to cell cycle arrest in G1 phase. In further studies, we found that tumor growth was inhibited in xenograft nude mouse models with HDGF deletion. The results of RNA-seq analysis revealed that the PI3K-AKT signaling pathway-related genes were obviously changed in HDGF-deficient 253J cells, and this result was further confirmed by Western blot analysis.ConclusionIn summary, we suggest that HDGF plays a substantial role in BCa and promotes tumor development and progression by regulating the PI3K-AKT signaling pathway, which provides a promising target for BCa treatment.

Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality.e Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important role in judging the prognosis of tumor and influencing the progression of malignant, inflammatory, and metabolic disorders. In our study, we conducted a quantitative analysis of immune and stromal elements based on the ESTIMATE algorithm and thus divided BLCA cases into high and low groups. en the differentially expressed genes closely related to tumor prognosis between groups were identified and had been shown to correlate with immune response and stromal alterations, which was further confirmed by functional enrichment analysis and protein-protein interaction networks. We validated those genes through BLCA dates downloaded from ArrayExpress and thus got the marker genes to predict prognosis of BLCA. Additionally, immune cell infiltration analysis explored the correlation between the verified genes and immune cells. In conclusion, we identified a series of TME-related genes that assess the prognosis and explored the interaction between TME and tumor prognosis to guide clinical individualized treatment.

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