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Head and neck cancer (HNC) tumorigenesis involves a combination of multiple genetic alteration processes. Tumour necrosis factor-alpha-induced proteins (TNFAIPs) are involved in tumour development and progression, but few studies have been conducted on these factors in HNC. We aimed to analyse TNFAIPs and assess their potential as prognostic biomarkers and therapeutic targets using the Oncomine, UALCAN, Human Protein Atlas, LinkedOmics, cBioPortal, GeneMANIA, Enrichr, and Tumor IMmune Estimation Resource databases. We found that the transcript levels of TNFAIP1, TNFAIP3, EFNA1, TNFAIP6 and TNFAIP8 were increased, while those of TNFAIP8L3 and STEAP4 were reduced in HNC tissues versus normal tissues. The EFNA1, TNFAIP8 and TNFAIP8L3 expression levels were significantly correlated with the pathological stage. In HNC patients, high PTX3 and TNFAIP6 transcript levels were significantly associated with shorter overall survival (OS). Moreover, genetic alterations in TNFAIP1, TNFAIP6, and STEAP4 resulted in poorer disease-free survival, progression-free survival, and OS, respectively. TNFAIPs may mediate HNC tumorigenesis by regulating PI3K-Akt, Ras and other signalling pathways. TNFAIPs are also closely correlated with the infiltration of immune cells, including B cells, CD8+ T cells, CD4+ T cells, etc. The data above indicate that TNFAIPs may be potential biomarkers and therapeutic targets for HNC.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) tumorigenesis involves a combination of multiple genetic alteration processes. Constructing a survival-associated competing endogenous RNA (ceRNA) network and a multi-mRNA-based prognostic signature model can help us better understand the complexity and genetic characteristics of CESC. In this study, the RNA-seq data and clinical information of CESC patients were downloaded from The Cancer Genome Atlas. Differentially expressed mRNAs, lncRNAs and miRNAs were identified with the edgeR R package. A four-mRNA prognostic signature was developed by multivariate Cox regression analysis. Kaplan–Meier survival with the log-rank tests was performed to assess survival rates. The relationships between overall survival (OS) and clinical parameters were evaluated by Cox regression analysis. A survival-associated ceRNA network was constructed with the multiMiR package and miRcode database. Kyoto encyclopedia of genes and genomes (KEGG) analysis and gene ontology analyses were used to identify the functional role of the ceRNA network in the prognosis of CESC. A total of 298 differentially expressed mRNAs, 8 miRNAs, and 29 lncRNAs were significantly associated with the prognosis of CESC. A prognostic signature model based on 4 mRNAs (OPN3, DAAM2, HENMT1, and CAVIN3) was developed, and the prognostic ability of this signature was indicated by the AUC of 0.726. Patients in the high-risk group exhibited significantly worse OS. The KEGG pathways, TGF-β and Cell adhesion molecules, were significantly enriched. In this study, a CESC-associated ceRNA network was constructed, and a multi-mRNA-based prognostic model for CESC was developed based on the ceRNA network, providing a new perspective for cancer pathogenesis research.

Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

BackgroundIn the present study, we aimed to retrospectively analyze the correlation between toxicity of pemetrexed (PEM) chemotherapy and methylenetetrahydrofolate reductase (MTHFR) C677T polymorphisms in patients with advanced non-squamous non-small cell lung cancer (non-sq NSCLC).Material/MethodsWe used polymerase chain reaction, gene scanning, and restriction fragment length polymorphism to analyze MTHFR C677T in 51 patients with advanced non-sq NSCLC. The patients received chemotherapies with single-agent PEM (monotherapy group) or with PEM combined with cisplatin (joint group). The correlation between MTHFR C677T polymorphisms and chemotherapy efficacy/toxicity was also assessed.ResultsThere were 40 patients in the monotherapy group and 11 patients in the joint group. Among the 40 patients received single-agent PEM chemotherapy, those with the CT/TT genotype had higher incidence of leukopenia, neutropenia, nausea, and fatigue compared to patients with the with wild-type genotype CC (all P<0.05). However, polymorphisms of MTHFR C677T were not significantly associated with other adverse events and clinical outcomes.ConclusionsCompared with genotype CC (the wild type), patients with the CT/TT genotype had higher incidence of leukopenia, neutropenia, nausea, and fatigue. Therefore, the MTHFR C677T polymorphism could be a predictive factor for leukopenia, neutropenia, nausea, and fatigue toxicities in non-sq NSCLC patients treated with single-agent PEM.