CDK6 is a novel predictive and prognosis biomarker correlated with immune infiltrates in multiple human neoplasms, including small cell lung carcinoma.

The roles of cyclin-dependent kinase 6 (CDK6) in various cancers, including small cell lung carcinoma (SCLC), remain unclear. Here, 111,54 multi-center samples were investigated to determine the expression, clinical significance, and underlying mechanisms of CDK6 in 34 cancers. The area under the curve (AUC), Cox regression analysis, and the Kaplan-Meier curves were used to explore the clinical value of CDK6 in cancers. Gene set enrichment analysis and correlation analysis were performed to detect potential CDK6 mechanisms. CDK6 expression was essential in 24 cancer cell types. Abnormal CDK6 expression was observed in 14 cancer types (e.g., downregulated in breast invasive carcinoma; p < 0.05). CDK6 allowed six cancers to be distinguished from their controls (AUC > 0.750). CDK6 expression was a prognosis marker for 13 cancers (e.g., adrenocortical carcinoma; p < 0.05). CDK6 was correlated with several immune-related signaling pathways and the infiltration levels of certain immune cells (e.g., CD8+ T cells; p < 0.05). Downregulated CDK6 mRNA and protein levels were observed in SCLC (p < 0.05, SMD = - 0.90). CDK6 allowed the identification of SCLC status (AUC = 0.91) and predicted a favorable prognosis for SCLC patients (p < 0.05). CDK6 may be a novel biomarker for the prediction and prognosis of several cancers, including SCLC.

The clinical significance and mechanism of microRNA-22-3p targeting TP53 in lung adenocarcinoma.

BACKGROUND: At present, studies on MircoRNA-22-3p (miR-22-3p) in lung adenocarcinoma use a single method, lack multi-center validation and multi-method validation, and there is no big data concept to predict and validate target genes. OBJECTIVE: To investigate the expression, potential targets and clinicopathological significance of miR-22-3p in lung adenocarcinoma (LUAD) tissues. METHODS: LUAD formalin-fixed paraffin-embedded (FFPE) tumors and adjacent normal lung tissues were collected for real-time quantitative polymerase chain reaction (RT-qPCR). Collect miR-22-3p in LUAD and non-cancer lung tissue from high-throughput datasets, standardized mean difference (SMD) and area under the curve (AUC) of the comprehensive receiver operating curve (summary receiver operating characteristic cure, sROC curve) were calculated. Cell function experiments on A549 cells transfected with LV-hsa-miR-22-3p. Target genes were predicted by the miRwalk2.0 website and the resulting target genes were subjected to Gene Ontology (GO) pathway enrichment analysis and constructed to protein-protein interaction network. Finally, the protein expression level of the key gene TP53 was validated by searching The Human Protein Atlas (THPA) database to incorporate TP53 immunohistochemical results in LUAD. RESULTS: RT-qPCR result from 41 pairs of LUAD and adjacent lung tissues showed that miR-22-3p was downregulated in LUAD (AUC = 0.6597, p= 0.0128). Globally, a total of 838 LUADs and 494 non-cancerous lung tissues were included, and were finally combined into 14 platforms. Compared with noncancerous tissue, miR-22-3p expression level was significantly reduced in LUAD tissue (SMD =-0.32, AUC = 0.72l); cell function experiments showed that miR-22-3p has inhibitory effects on cell proliferation, migration and invasion, and has promotion effect on apoptosis. Moreover, target genes prediction, GO pathway enrichment analysis and PPI network exhibited TP53 as a key gene of target gene of miR-22-3p; at last, a total of 114 high-throughput datasets were included, including 3897 LUADs and 2993 non-cancerous lung tissues, and were finally combined into 37 platforms. Compared with noncancerous tissue, TP53 expression level was significantly increased in LUAD (SMD = 0.39, p< 0.01) and it was verified by the protein expression data from THPA. CONCLUSION: Overexpression of miR-22-3p may inhibit LUAD cell proliferation, migration and invasion through TP53, and promote cell apoptosis.

[Modeling of carbon dioxide measurement and optimization on building ceramic industry].

Input-output model and low carbon programming model on building ceramic industry were established. Carbon dioxide emissions of key steps and carbon footprint of products were calculated and predicted using the input-output model. While products planning was optimized using the low carbon programming model. The results showed that CO2 emission in the enterprise reached 182 543.9 t a year and CO2 emission per unit product was 10% more than advanced level in the world. 80% of the total CO2 was emitted during the processes of firing and drying. As a result, we should focus on these two steps in order to reduce carbon dioxide emission of building ceramic industry. Carbon footprint of blank tile, polished tile, and glazed tile were 150.2 t, 168.0 t, 159.6 t respectively. Optimized by the low carbon model, The ceramic enterprise could reduce carbon dioxide emission by 5.4% while not sacrificing any profit, and also could obtain profit 5.6% higher than before while unrise the carbon dioxide emission.