Growing evidence indicates that microRNAs (miRNAs) play critical roles in the initiation and progression of breast carcinoma (BC) and are promising diagnostic biomarkers. In the present study, we aimed to identify a multi-marker miRNA pool with high diagnostic performance for BC. We collected miRNA expression profiles of BC samples and normal breast tissues from The Cancer Genome Atlas (TCGA) and screened differentially expressed miRNAs by conducting two‑sample t-tests and by calculating log2 fold-change (log2FC) ratios. Statistical significance was established at p<0.001 and |log2FC| >1. Then, we generated receiver operating characteristic (ROC) curves, calculated the area under the curve (AUC) with a 95% confidence interval (95% CI), and calculated the diagnostic sensitivity and specificity using MedCalc software. Additionally, we predicted the targets of candidate miRNAs using 10 online databases: TarBase, miRTarBase, TargetScan, TargetMiner, microRNA.org, RNA22, PicTar-vert, miRDB, PITA and PolymiRTS. Target genes that were predicted by at least four algorithms were chosen, and cooperative targets of multiple miRNAs were further selected for GO and KEGG pathway analyses through the DAVID online tool. Eventually, a total of 66 differentially expressed miRNAs were identified after miRNA expression profiles were analyzed in BC and normal breast samples. Of these, we selected nine dysregulated miRNAs as candidate diagnostic markers: seven upregulated miRNAs (hsa-miR-21, hsa-miR-96, hsa-miR-183, hsa-miR‑182, hsa-miR-141, hsa-miR-200a and hsa-miR-429) and two downregulated miRNAs (hsa-miR-139 and hsa-miR‑145). The ROC curve for the combination of these nine differently expressed miRNAs showed extremely high diagnostic accuracy, with an AUC of 0.995 (95% CI, 0.988‑0.999) and diagnostic sensitivity and specificity of 98.7 and 98.9%, respectively. In conclusion, the combination of these nine miRNAs significantly improved the accuracy of breast cancer diagnosis.

Background Hepatocellular carcinoma (HCC) causes a heavy disease burden worldwide. Cell division cycle 45 (Cdc45) and its encoding gene ( CDC45 ) have been studied for a long time, but their expression patterns and roles in liver carcinogenesis and advanced HCC deterioration are still incompletely understood. This study integrated tissue microarray and bioinformatics analyses to explore the expression and clinical value of CDC45 and Cdc45 in HCC. Material/Methods In HCC, the expression and relationships with clinic-pathological parameters of CDC45 and Cdc45 were investigated by integrating the RNA-sequencing data, downloaded from The Cancer Genome Atlas and Oncomine databases, and tissue microarray with immunohistochemistry staining. Co-expressed genes and genetic alterations of CDC45 separately obtained from Oncomine and cBioPortal databases were identified to shed light on the potential mechanisms of CDC45 in HCC. Results CDC45 and Cdc45 were both overexpressed in HCC tissues, and the CDC45 level progressively increased from stage I to III. The survival outcomes of the group with high CDC45 expression were significantly worse compared with the group with low expression. Amplification and deep deletion were 2 major significant alteration types in HCC patients, and the outcomes were worse in patients with altered versus unaltered CDC45 . NUDT1 , E2F1 , CCNE2 , MCM5 , and CENPM were identified as the most significantly co-expressed genes. Conclusions CDC45 and Cdc45 were both upregulated in HCC, and increased expression levels and genetic alternations of CDC45 were correlated with worse prognosis in HCC patients. CDC45 may promote HCC by co-expressing with NUDT1 , E2F1 , CCNE2 , MCM5 , and CENPM .

During the pandemic of the coronavirus disease 2019, there exist quite a few studies on angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 infection, while little is known about ACE2 in hepatocellular carcinoma (HCC). The detailed mechanism among ACE2 and HCC still remains unclear, which needs to be further investigated. In the current study with a total of 6,926 samples, ACE2 expression was downregulated in HCC compared with non-HCC samples (standardized mean difference = −0.41). With the area under the curve of summary receiver operating characteristic = 0.82, ACE2 expression showed a better ability to differentiate HCC from non-HCC. The mRNA expression of ACE2 was related to the age, alpha-fetoprotein levels and cirrhosis of HCC patients, and it was identified as a protected factor for HCC patients via Kaplan-Meier survival, Cox regression analyses. The potential molecular mechanism of ACE2 may be relevant to catabolic and cell division. In all, decreasing ACE2 expression can be seen in HCC, and its protective role for HCC patients and underlying mechanisms were explored in the study.

Synaptojanin 2 (SYNJ2) regulates cell proliferation and apoptosis via dephosphorylating plasma membrane phosphoinositides. Aim of this study is to first seek the full-scale expression levels and potential emerging roles of SYNJ2 in hepatocellular carcinoma (HCC). We systematically analyzed SYNJ2 mRNA expression and protein levels in HCC tissues based on large-scale data and in-house immunohistochemistry (IHC). The clinical significance and risk factors for SYNJ2-related HCC cases were identified. A nomogram of prognosis was created and its performance was validated by concordance index (C-index) and shown in calibration plots. Based on the identified differentially coexpressed genes (DCGs) of SYNJ2, enriched annotations and potential pathways were predicted, and the protein interacting networks were mapped. Upregulated SYNJ2 in 3,728 HCC and 3,203 non-HCC tissues were verified and in-house IHC showed higher protein levels of SYNJ2 in HCC tissues. Pathologic T stage was identified as a risk factor. Upregulated mRNA levels and mutated SYNJ2 might cause a poorer outcome. The C-index of the nomogram model constructed by SYNJ2 level, age, gender, TNM classification, grade, and stage was evaluated as 0.643 (95% CI = 0.619-0.668) with well-calibrated plots. A total of 2,533 DCGs were extracted and mainly functioned together with SYNJ2 in metabolic pathways. Possible transcriptional axis of CTCF/ POLR2A-SYNJ2/INPP5B (transcription factor-target) in metabolic pathways was discovered based on ChIP-seq datasets. In summary, transcriptional regulatory axis CTCF/POLR2A-SYNJ2 might influence SYNJ2 expression levels. Increased SYNJ2 expression level could be utilized for predicting HCC prognosis and potentially accelerates the occurrence and development of HCC via metabolic perturbations pathways.

The Pt subnano clusters dispersed on the (110) facet of regularly shaped hexagonal Al2O3 plates were fabricated via an atomic layer deposition approach. The resulting material contains Pt loading as low as 0.07 wt %; the interfacial structure exhibits nearly full CO conversion for water gas shift reaction at 210 °C, and the turnover frequency (TOF) of CO is as high as 2.1 s–1, outperforming most of the systems reported. The same interfacial structure was also found to be highly active for catalytic decomposition of formic acid (FA), with full FA conversion (with little CO product) and the TOF being 1.02 s–1. Further characterizations together with density functional theory simulations elucidate that the superior catalytic performances are attributed to the unique interfacial structure and the synergism between the small Pt clusters and the Al2O3 (110) substrate, leading to lower energy barriers for the *COOH intermediate formation over the ultrafine Pt ensembles and the hydroxylation over the Al2O3 (110) substrate close to the Pt entities. Both are favorable for the evolution of *COOH intermediate and the reaction between *COOH and neighbor OH species. The current study provides insights into the effectiveness in generating high-performance catalytic material for clean energy production and modulation through precise control of the metal entity dimension and the oxide substrate engineering to achieve specific facet exposure.