Nucleotide‐binding domain, leucine‐rich repeat family with a caspase activation and recruitment domain 3 (NLRC3) participates in both immunity and cancer. The aim of this study was to determine the role of NLRC3 in human hepatocellular carcinoma (HCC) and the underlying mechanisms. We collected human liver tissues from nonalcoholic steatohepatitis (NASH), HCC, and adjacent normal tissues to characterize the pattern of NLRC3 expression by real‐time quantitative polymerase chain reaction and immunohistochemistry. Then, we used the HCC cell line, HuH‐7, transfected with small interfering RNA to silence the NLRC3 expression. 5‐Ethynyl‐2'‐deoxyuridine assay, scratch assay, and transwell invasion assay were used for assessing proliferation, migration, and invasion, respectively. Flow cytometry and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay were conducted to assess cell apoptosis. The expression of NLRC3 was reduced in human HCC tissues, compared with normal liver and nonalcoholic steatohepatitis tissues. After knocking down of NLRC3, the proliferation, migration, and invasion were increased in HuH‐7 cells. And flow cytometry and TUNEL assay showed that HuH‐7 cell apoptosis was suppressed after NLRC3 knockdown. As for the underlying mechanisms, knockdown of NLRC3 in HuH‐7 cells was associated with the activation of Janus kinase 2/signal transducers and activators of transcription 3 (JAK2/STAT3) pathway under interleukin‐6 (IL‐6) stimulation. NLRC3 expression was downregulated in human HCC tissues. NLRC3 silencing in HuH‐7 cells can promote the proliferation, migration, and invasion of hepatocellular carcinoma cells. JAK2/STAT3 pathway activation induced by IL‐6 may be the underlying mechanism for HCC when NLRC3 expression is silenced. And the invasion of HuH‐7 cells was partially suppressed by the STAT3 specific inhibitor (cryptotanshinone). Therefore, NLRC3 may play a significant role in HCC and might be a therapeutic target for the treatment of HCC.

Background. Low-grade chronic inflammation in dysfunctional adipose tissue links obesity with insulin resistance through the activation of tissue-infiltrating immune cells. Numerous studies have reported on the pathogenesis of insulin-resistance. However, few studies focused on genes from genomic database. In this study, we would like to explore the correlation of genes and immune cells infiltration in adipose tissue via comprehensive bioinformatics analyses and experimental validation in mice and human adipose tissue. Methods. Gene Expression Omnibus (GEO) datasets (GSE27951, GSE55200, and GSE26637) of insulin-resistant individuals or type 2 diabetes patients and normal controls were downloaded to get differently expressed genes (DEGs), and GO and KEGG pathway analyses were performed. Subsequently, we integrated DEGs from three datasets and constructed commonly expressed DEGs’ PPI net-works across datasets. Center regulating module of DEGs and hub genes were screened through MCODE and cytoHubba in Cytoscape. Three most significant hub genes were further analyzed by GSEA analysis. Moreover, we verified the predicted hub genes by performing RT qPCR analysis in animals and human samples. Besides, the relative fraction of 22 immune cell types in adipose tissue was detected by using the deconvolution algorithm of CIBERSORT (Cell Type Identification by Estimating Relative Subsets of RNA Transcripts). Furthermore, based on the significantly changed types of immune cells, we performed correlation analysis between hub genes and immune cells. And, we performed immunohistochemistry and immunofluorescence analysis to verify that the hub genes were associated with adipose tissue macrophages (ATM). Results. Thirty DEGs were commonly expressed across three datasets, most of which were upregulated. DEGs mainly participated in the process of multiple immune cells’ infiltration. In protein-protein interaction network, we identified CSF1R, C1QC, and TYROBP as hub genes. GSEA analysis suggested high expression of the three hub genes was correlated with immune cells functional pathway’s activation. Immune cell infiltration and correlation analysis revealed that there were significant positive correlations between TYROBP and M0 macrophages, CSF1R and M0 macrophages, Plasma cells, and CD8 T cells. Finally, hub genes were associated with ATMs infiltration by experimental verification. Conclusions. This article revealed that CSF1R, C1QC, and TYROBP were potential hub genes associated with immune cells’ infiltration and the function of proinflammation, especially adipose tissue macrophages, in the progression of obesity-induced diabetes or insulin-resistance.

Introduction: The aim of the study was to reveal the mechanisms for the pathogenesis and progression of type 1 diabetes mellitus (T1DM). Material and methods: Two mRNA expression profiles and two miRNA expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs), differentially expressed miRNAs (DEMs), functional enrichment analyses, pathways, putative targets for DEMs and the miRNA-gene pairs, protein-protein pairs of DEGs, and PPI network were constructed. Results: Based on mRNA expression profiles, 37 and 110 DEGs were identified, and named as DEGs-short and DEGs-long, respectively. Based on miRNA expression profiles, 15 and six DEMs were identified, and named as DEMs-short and DEMs-long, respectively. DEGs-short were enriched in six GO terms and four pathways, and DEGs-long enriched in 40 GO terms and 10 pathways. Seventeen miRNA-gene pairs for DEMs-short were screened out; hisa-miR-181a and hisa-miR-181c were involved in the most pairs. Twenty pairs for DEMs-long were obtained; hsa-miR-338-3p was involved in all the pairs. KLRD1 was involved in more pairs in the network of DEGs-short. ACTA2 and USP9Y were involved in more pairs in the network of DEGs-long. Conclusions: KLRD1, hisa-miR-181a, and hisa-miR-181c might be pathogenic biomarkers for T1DM, ACTA2, USP9Y, and hsa-miR-338-3p progressive biomarkers of T1DM.

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