BackgroundTumor metabolism is important for cancer progression. Nevertheless, the role of the metabolism pathway and related molecules in nasopharyngeal carcinoma (NPC) is limited.MethodsOpen-accessed data was downloaded from The Cancer Genome Atlas database. All the analysis was performed using the R software and the package in R environments.ResultsIn our study, we firstly explored the role of 21 metabolism-related pathways in NPC patients. We found that the steroid biosynthesis and biosynthesis of unsaturated fatty acids were risk factors, while the alpha linolenic acid metabolism was a protective factor. Then, the alpha linolenic acid metabolism aroused our interest. A total of 128 differentially expressed genes (DEGs) were identified, including 71 downregulated and 57 upregulated genes identified between high and low alpha linolenic acid metabolism level. Based on these DEGs, we constructed a prognosis model including DEFB4B, FOXL2NB, MDGA2, RTL1, SLURP2, TMEM151B and TSPAN19, which showed great prediction efficiency in both training and validation cohorts. Clinical correlation analysis showed that high-risk patients might have worse clinical pathology parameters. Pathway enrichment analysis showed that riskscore was positively correlated with angiogenesis, DNA repair, G2/M checkpoints, IL6/JAK/STAT3 signaling, KRAS signaling up, WNT beta-catenin signaling, PI3K/AKT/mTOR signaling, yet positively correlated with inflammatory response, xenobiotic metabolism, TNF-α signaling via NFKB and interferon-gamma response. Immune infiltration analysis showed that the riskscore was positively correlated with the M2 and M0 macrophages, but negatively correlated with neutrophils, plasma cells, follicular helper T cells and resting dendritic cells Moreover, we found that the low-risk patients might be more sensitive to immunotherapy and lapatinib.ConclusionsIn all, our study identified the genes associated with alpha linolenic acid metabolism and constructed an effective prognosis model which could robustly predict NPC patients prognosis.

Oral squamous cell carcinoma (OSCC) is a common head-and-neck cancer with a deficiency of early diagnosis and poor prognosis. To identify potential diagnostic and prognostic markers of OSCC, we firstly used weighted gene co-expression network analysis (WGCNA) to build a co-expression module from GSE42743. Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses on specified units from selected modules utilizing Database for Annotation, Visualization, and Integrated Discovery (DAVID). Additionally, we identified and validate hub genes of these specified modules from multiple datasets like GEPIA and TCGA. In total 16 co-expression modules were built by 17,238 genes of 74 tumor samples utilizing WGCNA. Through pathway and functional enrichment analysis, the turquoise module was most firmly relevant to the cell cycle, oocyte meiosis, and p53 signaling pathway. Hub genes VRK1, NUP37, HMMR, SPC25, and RUVBL1 were identified to be related to oral cancer at both molecular level and clinical levels. The expressions of these genes differed in tumor tissues and normal tissues. Meanwhile, patients with high hub gene expression had a poor prognosis clinically. To conclude, five hub genes were identified to be relevant to oral cancer from the molecular level and the clinical level. Therefore, the detection of these genes was of great significance. They can be regarded as diagnostic and prognostic biomarkers for oral cancer. Also, they could shed light on the improvement of patients’ overall survival and prognosis, which needs further analysis in the future.

LncRNA EIF3J-AS1 has shown to play an important regulatory role in a variety of tumor tissues, IGFB3 Gene is the target gene of LncRNA EIF3J-AS1, experimental studies shows that IGFB3 gene risk typing is associated with an increased risk of gastric cancer susceptibility of gastric cancer(GC),the relationship between LncRNA EIF3J-AS1 target IGFB3 Gene polymorphisms expression in GC patients is related. Methods: A case-controlled study was conducted, including 490 primary gastric cancers and 1476 normal controls. Targetscan, miRanda and other software are used to target and predict the genes and mirnas that lncRNA can bind to, and the expression correlation analysis is conducted, so as to construct the ceRNA network and speculate its regulation of gastric cancer expression. The target gene IGFB3 fragment was amplified in blood samples using PCR. Genotyping was performed using the snapshot method. Results: This rearch shows a signal pathway LncRNA EIF3J-AS1-IGFBP3, in IGFBP3 gene variants GA and GA + AA models, castric cancer can be decreased when in male subgroup and ≥ 61 years old subgroup, but during smoking and alcohol groups, gastic cancer risk is encreased. IGFBP3 gene is regulated by LncRNA EIF3J-AS1-miRNAs-IGFBP3 network, which could provide a potential drug target biomarker.