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BACKGROUND: Numerous studies reveal the clinical significance of tumor microenvironment (TME) in multiple cancers. The association between TME in oral squamous cell carcinoma (OSCC) and clinical outcomes remains unsolved. OBJECTIVE: This study aims to exhibit the TME of OSCC and identified the prognostic marker. METHODS: Gene expression profile and clinical data OSCC patients were from the TCGA database. The validated stage data was from the Gene Expression Omnibus (GSE65858). Immune/stromal scores of each patient were calculated by ESTIMATE algorithm. Biological functional prediction was conducted. Prognostic genes identified by survival analysis. Nomogram and Receiver operating characteristic curves were employed to test the predicting power. TIMER database was applied to evaluated the immune infiltrates. RESULTS: Lower immune scores were observed in male patients (P = 0.0107) and different primary tumor sites of oral cavity with different stromal scores (P = 0.0328). The Differentially expressed genes (DEGs) were involved in immune related pathways. HGF gene (hepatocyte growth factor) was prognostic related and with a better prognostic performance when combined with clinical features (AUC = TCGA 0.638, AUC = GEO 0.714). HGF was significantly related with B cell, CD4 ï ⁢ ¼ ⁢ ‹ T cell, CD8 + T cell, macrophage, neutrophils, and dendritic cell infiltration. CONCLUSION: : The current study analyzed the TME and presented immune related prognostic biomarkers for OSCC. [ABSTRACT FROM AUTHOR]

BACKGROUND: Hepatocellular carcinoma (HCC) has a high degree of malignancy and poor prognosis. N6-methyladenosine (m6A) modifications and microRNAs (miRNAs) play pivotal roles in tumorigenesis and development. However, the role of m6A-related miRNAs in HCC has not been clarified yet. This study aimed to identify the role of m6A-miRNAs in HCC prognosis through bioinformatics analysis. METHODS: The clinicopathological information and RNA sequencing data of 369 HCC tumor tissues and 49 tumor-adjacent tissues were downloaded from the TCGA database. A total of 23 m6A regulators were extracted to evaluated the m6A-related miRNAs using Pearson's correlation analysis. Then, we selected prognosis-related m6A-miRNAs using a univariate Cox regression model and used the consensus cluster analysis to explore the characteristics of the m6A-miRNAs. The coefficient of the least absolute shrinkage and selection operator (LASSO) Cox regression was applied to construct a prognostic risk score model. The receiver operated characteristic (ROC) analysis was applied to evaluate the prognostic value of the signature. The biological functions of targeted genes were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Then, to validate the potential predictive value for prognosis, the miRNA expression profiles from the GSE76903 and GSE6857 were used. Single sample Gene Set Enrichment Analysis (ssGSEA) and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) were applied to assess the immune microenvironment of HCC. Additionally, a meta-analysis was used to verify the prognostic value of the m6A-microRNAs. RT-PCR was applied to validated the expression of miRNAs in HCC tissues. Cell viability, transwell assay and RNA m6A dot blot assays of HCC cells was applied to access the function of miR-17-5p. RESULTS: The expression of 48 m6A-related miRNAs was identified and 17 prognostic m6A-miRNAs was discovered. The expression profile of those 17 miRNAs was divided into three clusters, and these clusters were associated with the tumor microenvironment (TME) and prognosis. The nine m6A-related miRNA signature was associated with the prognosis of HCC, the AUC of the ROC was 0.771(TCGA dataset), 0.788(GSE76903) and 0.646(GSE6857). The TME and the expression of immune checkpoint molecules were associated with the risk score. The meta-analysis also validated the prognostic value of the m6A-related miRNAs (miR182-5p (HR:1.58, 95%CI:1.04-2.40) and miR-17-5p (HR:1.58, 95%CI: 1.04–2.40)). The expression of miR-17-5p was upregulated in HCC tissues and miR-17-5p showed an oncogenic role in HCC cells. CONCLUSION: The clinical innovation is the use of m6A-miRNAs as biomarkers for predicting prognosis regarding immunotherapy response in HCC patients. [ABSTRACT FROM AUTHOR]

Breast cancer (BC) is the most common cancer among women and a leading cause of cancer-related deaths worldwide. The diagnosis of early patients and the prognosis of advanced patients have not improved over the past several decades. The purpose of the present study was to identify the lncRNA-related genes based on ceRNA network and construct a credible model for prognosis in BC. Based on The Cancer Genome Atlas (TCGA) database, prognosis-related differently expressed genes (DEGs) and a lncRNA-associated ceRNA regulatory network were obtained in BC. The patients were randomly divided into a training group and a testing group. A ceRNA-related prognostic model as well as a nomogram was constructed for further study. A total of 844 DElncRNAs, 206 DEmiRNAs and 3295 DEmRNAs were extracted in BC, and 12 RNAs (HOTAIR, AC055854.1, ST8SIA6-AS1, AC105999.2, hsa-miR-1258, hsa-miR-7705, hsa-miR-3662, hsa-miR-4501, CCNB1, UHRF1, SPC24 and SHCBP1) among them were recognized for the construction of a prognostic risk model. Patients were then assigned to high-risk and low-risk groups according to the risk score. The Kaplan-Meier (K-M) analysis demonstrated that the high-risk group was closely associated with poor prognosis. The predictive nomogram combined with clinical features showed performance in clinical practice. In a nutshell, our ceRNA-related gene model and the nomogram graph are accurate and reliable tools for predicting prognostic outcomes of BC patients, and may make great contributions to modern precise medicine. [ABSTRACT FROM AUTHOR]

BACKGROUND: The new systemic inflammation response index (SIRI) constructed based on neutrophil, monocyte and lymphocyte counts in peripheral blood is considered to be related to the prognosis of a variety of tumours. OBJECTIVE: To evaluate the prognostic value of the SIRI in operable breast cancer patients and establish a nomogram to predict the survival of breast cancer patients. METHODS: A total of 949 patients with operable breast cancer were enrolled in the present study. RESULTS: The overall survival (OS) of breast cancer patients with SIRI ⩽ 0.65 was significantly higher than that of breast cancer patients with SIRI > 0.65 (P < 0.001). A nomogram generated based on SIRI, grade and TNM stage and SIRI predicted the 5- and 10-year survival rates of breast cancer patients more accurately than TNM stage alone. In addition, the change in SIRI relative to baseline at 4 weeks after surgery was closely related to the survival of breast cancer patients. Compared with those with no SIRI changes (absolute value of variation < 25%), breast cancer patients with an increase in SIRI > 75% or 25–75% had worse OS (P < 0.001). CONCLUSIONS: The SIRI before and after surgery is closely related to the prognosis of breast cancer patients. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVE: N-myc downstream-regulated gene 3 (NDRG3) is one of the important members of the NDRG family which crucially take part in cell proliferation, differentiation and other biological processes. METHODS: In this present study, western-blotting analysis was performed to evaluate NDRG3 expression in NSCLC cell lines. One-step quantitative reverse transcription-polymerase chain reaction (qPCR) with 16 fresh-frozen NSCLC samples and immunohistochemistry (IHC) analysis in 100 NSCLC cases were conducted to explore the relationship between NDRG3 expression and the clinicopathological characteristics of NSCLC. RESULTS: NDRG3 expression levels were statistically higher in NSCLC cell lines and tissue samples, compared with that of in non-cancerous cell line and tissue samples (p < 0.05). The IHC data demonstrated that the NDRG3 expression was significantly correlated with pathological grade (p = 0.038), N (p = 0.020) and TNM stage (p = 0.002). Survival analysis and Kaplan-Meier curve indicated that NDRG3 expression (p = 0.002) and T (p = 0.047) were independently associated with the unfavorable overall survival of patients with NSCLC. CONCLUSIONS: The data implied that NDRG3 expression may be identified as a new predictor in NSCLC prognosis. [ABSTRACT FROM AUTHOR]