Leucine-rich glioma inactivated 3: Integrative analyses reveal its potential prognostic role in cancer

Identification of coagulation-associated subtypes of lung adenocarcinoma and establishment of prognostic models

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer, is a global health challenge with high recurrence and mortality rates. The coagulation cascade plays an essential role in tumor disease progression and leads to death in LUAD. We differentiated two coagulation-related subtypes in LUAD patients in this study based on coagulation pathways collected from the KEGG database. We then demonstrated significant differences between the two coagulation-associated subtypes regarding immune characteristics and prognostic stratification. For risk stratification and prognostic prediction, we developed a coagulation-related risk score prognostic model in the Cancer Genome Atlas (TCGA) cohort. The GEO cohort also validated the predictive value of the coagulation-related risk score in terms of prognosis and immunotherapy. Based on these results, we identified coagulation-related prognostic factors in LUAD, which may serve as a robust prognostic biomarker for therapeutic and immunotherapeutic efficacy. It may contribute to clinical decision-making in patients with LUAD.

Integrative proteomic network analyses support depot-specific roles for leucine rich repeat LGI family member 3 in adipose tissues

LGI family member 3 (LGI3) is a member of the LGI protein family. In our previous studies, LGI3 was determined to be expressed in adipose tissues, skin and the brain, where it served as a pleiotropic cytokine. The results indicated that LGI3 levels are increased in adipose tissues of obese individuals in comparison with control individuals and that LGI3 suppressed adipogenesis via its receptor, disintegrin and metalloproteinase domain-containing protein 23. Additionally, it was reported that LGI3 upregulates tumor necrosis factor-α and downregulated adiponectin and hypothesized that LGI3 may act as a proinflammatory adipokine involved in adipose tissue inflammation. In the present study, cytokine arrays were used to analyze cytokine levels in adipose tissues and plasma of LGI3-knockout mice and signaling protein arrays used to analyze the expression and phosphorylation of these proteins in LGI3-treated preadipocytes. The results suggested that expression levels of 129 gene products (24 cytokines and 105 signaling proteins) were altered in response to LGI3 deficiency or LGI3 treatment, respectively. Protein-protein interaction network analysis of LGI3-regulated gene products revealed that 94% of the gene products (21 cytokines and 100 signaling proteins) formed an interaction network cluster. Functional enrichment analysis for the LGI3-regulated gene products, including those from our previous studies, revealed an association with numerous biological processes, including inflammatory responses, cellular differentiation and development and metabolic regulation. Gene co-expression network analysis revealed that these LGI3-regulated gene products were involved in various biological processes in an overlapping and differential manner between subcutaneous and visceral adipose tissues. Notably, inflammatory responses were more strongly associated with the LGI3-regulated gene co-expression network in visceral adipose tissues than in subcutaneous adipose tissues. Analysis of expression quantitative trait loci identified four single nucleotide variants that affect expression of LGI3 in an adipose depot-specific manner. Taken together, the results suggested that LGI3 may serve depot-specific roles as an adipokine in adipose tissues.

Leucine rich repeat LGI family member 3: Integrative analyses reveal its prognostic association with non-small cell lung cancer

Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Our previous studies reported that LGI3 was expressed in adipose tissues, brain and skin, where it served roles as a multifunctional cytokine and pro-inflammatory adipokine. It was hypothesized that LGI3 may be involved in cytokine networks in cancer. The present study aimed to analyze differentially expressed genes in non-small cell lung cancer (NSCLC) tissues and NSCLC cohort data, to evaluate the prognostic role of LGI3. Expression microarray and NSCLC cohort data were statistically analyzed by bioinformatic methods, and protein-protein interactions, functional enrichment and pathway, gene coexpression network (GCN) and prognostic association analyses were performed. The results demonstrated that the expression levels of LGI3 and its receptor a disintegrin and metalloproteinase domain-containing protein 22 were significantly decreased in NSCLC tissues. A total of two upregulated genes and 11 downregulated genes in NSCLC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that all LGI3-regulated genes that were altered in NSCLC were involved in a protein-protein interaction network cluster. Functional enrichment, Kyoto Encyclopedia of Genes and Genomes pathway and GCN analyses demonstrated the association of these genes with the immune and inflammatory responses, angiogenesis, the tumor necrosis factor pathway, and chemokine and peroxisome proliferator-activated receptor signaling pathways. Analysis of NSCLC cohorts revealed that low expression levels of LGI3 was significantly associated with poor prognosis of NSCLC. Analysis of the somatic mutations of the LGI3 gene in NSCLC revealed that the amino acid residues altered in NSCLC included two single nucleotide polymorphism sites and three phylogenetically coevolved amino acid residues. Taken together, these results suggest that LGI3 may be a potential prognostic marker of NSCLC.

Identification of long noncoding RNAs biomarkers in patients with hepatitis B virus-associated hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancer worldwide and chronic infection of hepatitis B virus (HBV) serve as one of leading causes of HCC.

OBJECTIVE

This study aimed to identify the novel long noncoding RNAs (lncRNAs) biomarkers for HBV-associated HCC.

METHODS

The lncRNA and mRNA expression profiles of HCC patients with HBV infection were downloaded from The Cancer Genome Atlas. The differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between HCC and adjacent tissues were identified. The optimal diagnostic and prognostic lncRNA biomarkers for HCC were identified by using feature selection procedure and classification model. Functional annotation of DEmRNAs co-expressed with these lncRNAs biomarkers were performed. Receiver operating characteristic (ROC) curve and survival analysis of these lncRNAs biomarkers were performed. qRT-PCR validation was performed.

RESULTS

A total of 82 DElncRNAs and 805 DEmRNAs between HBV-associated HCC and normal tissues were identified. CAPN10-AS1, LINC01093, RP5-890E16.2, FENDRR and C17orf82 were selected as optimal diagnostic and prognostic lncRNA biomarkers for HBV-associated HCC that were co-expressed with 105, 86, 70, 30 and 1 DEmRNAs, respectively. Based on the DEmRNAs co-expressed with these five lncRNAs biomarkers, Jak-STAT signaling pathway and retinol metabolism were two significantly enriched pathways. The result in qRT-PCR validation were consistent with our analysis based on TCGA, generally.

CONCLUSIONS

This study identified five potential lncRNAs biomarkers for HBV-associated HCC with great diagnostic and prognostic value and provided clues for their functions in HBV-associated HCC.