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linical decision-making for patients.

High-grade glioma (HGG) and solitary brain metastasis (sBM) patients show similar symptoms in clinical practice, and accurately differential diagnosis directly affects the management and prognosis of patients. The aim of this study was to distinguish two entities by preoperative serum β2-microglobulin (β2-m) and routine blood test-associated inflammatory indexes including, white blood cell (WBC), neutrophils, lymphocytes, monocytes, and platelets count, red cell distribution width (RDW), platelet distribution width (PDW), neutrophil/lymphocyte ratio (NLR) and monocyte/lymphocyte ratio (MLR).

A retrospective analysis was performed in the Cancer Hospital of the University of Chinese Academy of Sciences from January 2015 to December 2019, including 127 patients of newly pathologically diagnosed with HGG and 174 patients with sBM. Clinical information including age, gender, pathological diagnosis, preoperative serum β2-m and routine blood tests were collected, and NLR and MLR were calculated. The diagnostic significance of these markers for HGG and sBM was assessed by receiver operating characteristic (ROC) curves.

The patients with sBM had significantly higher values of preoperative age, β2-m, NLR and MLR as well as lower lymphocytes count than patients with HGG. Besides, the area under the curve (AUC) in differentiating HGG from sBM was 0.625 (95%CI 0.561-0.689) for age, 0.655 (0.594-0.717) for β2-m, 0.634 (0.571-0.698) for NLR and 0.622 (0.559-0.686) for MLR, and the combination of Age+β2-m+NLR+MLR showed the best diagnostic performance with AUC of 0.731 (0.675-0.788) and 0.048*Age+0.001*β2-m+0.201*NLR+0.594*MLR>5.813 could indicate sBM rather than HGG.

The Age+β2-m+NLR+MLR combination was revealed as an inexpensive and noninvasive biomarker for differentiating between HGG and sBM before surgery.

The Age+β2-m+NLR+MLR combination was revealed as an inexpensive and noninvasive biomarker for differentiating between HGG and sBM before surgery.

Metastasis is the main cause of renal cell carcinoma (RCC) tumor death, and effective inhibition of RCC metastasis is an essential means to meliorate the prognosis of RCC patients. MicroRNAs (miRs) have been proved to be stable and important biomarkers for several malignancies. This study is therefore set out to explore the metastasis-related miR and its mechanism in RCC.

The expression of

in RCC was analyzed using the expression profile in the Cancer Genome Atlas (TCGA).

and E2F transcription factor 7 (

) in RCC patients were detected by qRT-PCR. Cell Counting Kit-8 (CCK-8) was adopted to assess cell proliferation, Transwell was utilized to evaluate migration and invasion, and flow cytometry (FC) was used to determine apoptosis. Mouse cell-derived and patient-derived xenotransplantation models were established to evaluate the effect of

on tumor growth and metastasis in vivo. The molecular mechanism of

was analyzed by dual-luciferase reporter (DLR) gene analysis, qRT-PCR, and Western blot (WB) both in vivo and in vitro.

was reduced in renal carcinoma cells and may serve as a biomarker for renal cancer metastasis and prognosis.

up-regulation inhibited migration and invasion in renal cell lines and tumor metastasis in vivo. Bioinformatics target prediction and RNA-seq results showed that

was among the targets of

and was significantly inhibited by

in vivo and in vitro.

presents low expression in RCC and promotes RCC cell apoptosis and prevents cells from proliferating and invading by targeting

, which is a promising therapeutic target for RCC.

MiR-26a-5p presents low expression in RCC and promotes RCC cell apoptosis and prevents cells from proliferating and invading by targeting E2F7, which is a promising therapeutic target for RCC.

Prostate cancer (PCa) is a major contributor to reduce the life quality of males. Circular RNAs were frequently reported to be associated with cancers. In the case of radiotherapy to PCa, the role of circ_0062020 was still inconclusive, which was further explored in this study.

Quantitative real-time polymerase chain reaction (qRT-PCR) was used to determine the expression of circ_0062020, miR-615-5p and thyroid hormone receptor interactor 13 (TRIP13) in PCa tissues and cells, as well as in normal tissues and cell. Meanwhile, the proliferation of PCa cells was evaluated by clone formation assay and cell counting kit 8 (CCK8) assay. Moreover, the metastasis of PCa cells was assessed by transwell and wound healing assays. Furthermore, the apoptosis of PCa cells was determined by flow cytometry assay. Besides, dual-luciferase reporter system was applied to verify the correlation between miR-615-5p and circ_0062020 or TRIP13, which was predicted by online tool CircRNA interactome or TargetScan. In addition, the protein expression of TRIP13 was measured by Western blot in PCa tissues and cells and normal tissues and cells. Finally, xenograft tumor assay was performed to further confirming the function of circ_0062020 in PCa in vivo.

Circ_0062020 and TRIP13 were upregulated, while miR-615-5p was downregulated in PCa tissues and cells. Circ_0062020 knockdown or miR-615-5p overexpression inhibited the proliferation and metastasis, and promoted apoptosis, which could be reversed by miR-615-5p inhibitor or pc-TRIP13 in ionizing radiation (IR)-treated PCa cells. As expected, circ_0062020 sponged miR-615-5p to regulate TRIP13 expression in PCa cells. Circ_0062020 knockdown also suppressed PCa tumor growth in vivo.

Circ_0062020 suppressed the radiosensitivity by miR-615-5p/TRIP13 axis in PCa cells, which might provide insights into the radiotherapy for PCa.

Circ_0062020 suppressed the radiosensitivity by miR-615-5p/TRIP13 axis in PCa cells, which might provide insights into the radiotherapy for PCa.

Colorectal cancer (CRC) is one of the most lethal malignancies and the incidence of CRC has been on the rise. find more Herein, we aimed to identify effective biomarkers for early diagnosis and treatment of colorectal cancer via bioinformatic tools.

To identify differentially expressed genes (DEGs) in CRC, we downloaded CRC gene expression data from GSE24514 and GSE110223 datasets in Gene Expression Omnibus (GEO) and employed R to analyze the data. We further performed functional enrichment analysis of the DEGs on the DAVID gene ontology analysis tool. STRING database and Cytoscape visualization tool were employed to construct a PPI (protein-protein interaction) network and establish intensive intervals in the network. Immunohistochemistry, qRT-PCR and Western blotting were performed to identify the expression level of

in CRC. In vitro and in vivo experiments were performed to assess the impact of

in the pathogenesis of CRC in terms of proliferation, migration and metastasis.

Among the two datasets, 389 DEGs were identified and used to construct a PPI network.