The claudin multigene family is associated with various aberrant physiological and cellular signaling pathways. However, the association of claudins with survival prognosis, signaling pathways, and diagnostic efficacy in colon cancer remains poorly understood. Methods: Through the effective utilization of various bioinformatics methods, including differential gene expression analysis, gene set enrichment analysis protein-protein interaction (PPI) network analysis, survival analysis, single sample gene set enrichment analysis (ssGSEA), mutational variance analysis, and identifying receiver operating characteristic curve of claudins in The Cancer Genome Atlas colon adenocarcinoma (COAD). Results: We found that: CLDN2, CLDN1, CLDN14, CLDN16, CLDN18, CLDN9, CLDN12, and CLDN6 are elevated in COAD. In contrast, the CLDN8, CLDN23, CLDN5, CLDN11, CLDN7, and CLDN15 are downregulated in COAD. By analyzing the public datasets GSE15781 and GSE50760 from NCBI-GEO (https://www.ncbi.nlm.nih.gov/geo/), we have confirmed that CLDN1, CLDN2, and CLDN14 are significantly upregulated and CLDN8 and CLDN23 are significantly downregulated in normal colon, colon adenocarcinoma tumor, and liver metastasis of colon adenocarcinoma tissues from human samples. Various claudins are mutated and found to be associated with diagnostic efficacy in COAD. Conclusion: The claudin gene family is associated with prognosis, immune regulation, signaling pathway regulations, and diagnosis of COAD. These findings may provide new molecular insight into claudins in the treatment of colon cancer.

Cerebral ischaemia‒reperfusion (I/R) frequently causes late-onset neuronal damage. Breviscapine promotes autophagy in microvascular endothelial cells in I/R and can inhibit oxidative damage and apoptosis. However, the mediation mechanism of breviscapine on neuronal cell death is unclear.
First, transcriptome sequencing was performed on three groups of mice: the neuronal normal group (Control group), the oxygen-glucose deprivation/ reoxygenation group (OGD/R group) and the breviscapine administration group (Therapy group). Differentially expressed genes (DEGs) between the OGD/R and control groups and between the Therapy and OGD/R groups were obtained by the limma package. N6-methyladenosine (m6A) methylation-related DEGs were selected by Pearson correlation analysis. Then, prediction and confirmation of drug targets were performed by Swiss Target Prediction and UniProt Knowledgebase (UniProtKB) database, and key genes were obtained by Pearson correlation analysis between m6A-related DEGs and drug target genes. Next, gene set enrichment analysis (GSEA) and Ingenuity pathway analysis (IPA) were used to obtain the pathways of key genes. Finally, a circRNA-miRNA‒mRNA network was constructed based on the mRNAs, circRNAs and miRNAs.
A total of 2250 DEGs between the OGD/R and control groups and 757 DEGs between the Therapy and OGD/R groups were selected by differential analysis. A total of 7 m6A-related DEGs, including Arl4d, Gm10653, Gm1113, Kcns3, Olfml2a, Stk26 and Tfcp2l1, were obtained by Pearson correlation analysis. Four key genes (Tfcp2l1, Kcns3, Olfml2a and Arl4d) were acquired, and GSEA showed that these key genes significantly participated in DNA repair, e2f targets and the g2m checkpoint. IPA revealed that Tfcp2l1 played a significant role in human embryonic stem cell pluripotency. The circRNA-miRNA‒mRNA network showed that mmu_circ_0001258 regulated Tfcp2l1 by mmu-miR-301b-3p.
In conclusion, four key genes, Tfcp2l1, Kcns3, Olfml2a and Arl4d, significantly associated with the treatment of OGD/R by breviscapine were identified, which provides a theoretical basis for clinical trials.

暂无摘要。

Lactiplantibacillus plantarum is one of the important species of lactic acid bacterium (LAB) found in diverse environments, with many strains exhibiting probiotic properties. In our previous study, 41.6% of protein families (PFs) encoded by 395 plasmids from several L. plantarum strains were found to be hypothetical proteins with no predicted function. This study aimed at predicting the functions of these 647 hypothetical proteins using 21 different bioinformatics methods. As a result, 160 PFs could be newly annotated. A lower proportion of plasmid-specific functions was annotated as compared to the functions shared between plasmids and chromosomes. Also, hypothetical proteins were less conserved than the annotated proteins across L.plantarum plasmids. Based on the subcellular localization, cell envelope proteins represented the biggest category in the newly annotated proteins. Transporters (112 PFs) which was a part of cell envelop proteins represented the largest functional group. Additionally, 40 and 25 other PFs were predicted to contain signal peptides and transmembrane helices, respectively. We speculate that such hypothetical proteins might be involved in the transport of various chemicals and environmental interactions in L. plantarum. In the future, functional characterization of these proteins through wet-lab experimental approach can provide novel insights into their contribution to the physiology, probiotic properties, and industrial utility of these bacteria.

UNASSIGNED: Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with high heterogeneity. The prognosis of HCC is quite poor and the prognostic prediction also has challenges. Ferroptosis is recently recognized as a kind of iron-dependent cell death, which is involved in tumor progression. However, further study is needed to validate the influence of drivers of ferroptosis (DOFs) on the prognosis of HCC.
UNASSIGNED: The FerrDb database and the Cancer Genome Atlas (TCGA) database were applied to retrieve DOFs and information of HCC patients respectively. HCC patients were randomly divided into training and testing cohorts with a 7:3 ratio. Univariate Cox regression, LASSO and multivariate Cox regression analyses were carried out to identify the optimal prognosis model and calculate the risk score. Then, univariate and multivariate Cox regression analyses were performed to assess the independence of the signature. At last, gene functional, tumor mutation and immune-related analyses were conducted to explore the underlying mechanism. Internal and external databases were used to confirm the results. Finally, the tumor tissue and normal tissue from HCC patients were applied to validate the gene expression in the model.
UNASSIGNED: Five genes were identified to develop as a prognostic signature in the training cohort relying on the comprehensive analysis. Univariate and multivariate Cox regression analyses confirmed that the risk score was able to be an independent factor for the prognosis of HCC patients. Low-risk patients showed better overall survival than high-risk patients. Receiver operating characteristic (ROC) curve analysis confirmed the signature\'s predictive capacity. Furthermore, internal and external cohorts were consistent with our results. There was a higher proportion of nTreg cell, Th1 cell, macrophage, exhausted cell and CD8+T cell in the high-risk group. The Tumor Immune Dysfunction and Exclusion (TIDE) score suggested that high-risk patients could respond better to immunotherapy. Besides, the experimental results showed that some genes were differentially expressed between tumor and normal tissues.
UNASSIGNED: In summary, the five ferroptosis gene signature showed potential in prognosis of patients with HCC and could also be regarded as a value biomarker for immunotherapy response in these patients.

UNASSIGNED: Lung Squamous Cell Carcinoma (LUSC) is a major subtype of lung malignancies and is associated with the cause of cancer-mediated mortality worldwide. However, identification of transcriptomic signatures associated with survival-prognosis and immunity of tumor remains lacking.
UNASSIGNED: The GSE2088, GSE6044, GSE19188, GSE21933, GSE33479, GSE33532, and GSE74706 were integrated for identifying differentially expressed genes (DEGs) with combined effect sizes. Also, the TCGA LUSC cohort was used for further analysis. A series of bioinformatics methods were utilized for conducting the whole study.
UNASSIGNED: The 831 genes (such as DSG3, PKP1, DSC3, TPX2, and UBE2C) were found upregulated and the 731 genes (such as ABCA8, SELENBP1, FAM107A, and CACNA2D2) were downregulated in the LUSC. The functional enrichment analysis identifies the upregulated KEGG pathways, including cell cycle, DNA replication, base excision repair, proteasome, mismatch repair, and cellular senescence. Also, the key hub genes (such as EGFR, HRAS, JUN, CDH1, BRCA1, CASP3, RHOA, HDAC1, HIF1A, and CCNA2) were identified along with the eight gene modules that were significantly related to the protein-protein interaction (PPI). The clinical analyses identified that the overexpression group of CDH3, PLAU, PKP3, STIL, CALU, LOXL2, POSTN, DPP3, GALNT2, LOX, and ITPA are substantially associated with a poor survival prognosis and the downregulated group of IL18R1 showed a similar trend. Moreover, our investigation demonstrated that the survival-associated genes were correlated with the stromal and immune scores in LUSC, indicating that the survival-associated genes regulate tumor immunity. The survival-associated genes were genetically altered in 27% of LUSC patients and showed excellent diagnostic efficiency. Finally, the consistent expression level of CDH3, PLAU, PKP3, STIL, CALU, LOXL2, POSTN, DPP3, GALNT2, and ITPA were found in the TCGA LUSC cohort.
UNASSIGNED: The identification of key transcriptomic signatures can be elucidated by the crucial mechanism of LUSC carcinogenesis.

African swine fever virus (ASFV) poses a serious threat to domestic pigs and wild boars, which is responsible for substantial production and economic losses. A dominant ASFV specific linear B cell epitope that reacted with the convalescent serum was explored and identified with the help of immune informatics techniques. It is essential in understanding the host immunity and in developing diagnostic technical guidelines and vaccine design. The confirmation of dominant epitopes with a positive serological matrix is feasible. To improve the immunogenicity of the epitope, we designed the dominant epitope of CD2v in the form of 2 branch Multiple-Antigen peptide (MAPs-2), CD2v-MAPs-2. Notably, CD2v peptide can be taken up by dendritic cells (DCs) to activate T lymphocytes and induce highly effective valence antibodies in BALB/c mice. The specific CD8+ T cell response were observed. The dominant epitope peptide identified in this study was able to effectively activate humoral and cellular immunity in mice model.

Breast cancer (BRCA) is the most commonly diagnosed cancer and among the top causes of cancer deaths globally. The abnormality of the metabolic process is an important characteristic that distinguishes cancer cells from normal cells. Currently, there are few metabolic molecular models to evaluate the prognosis and treatment response of BRCA patients. By analyzing RNA-seq data of BRCA samples from public databases via bioinformatic approaches, we developed a prognostic signature based on seven metabolic genes (PLA2G2D, GNPNAT1, QPRT, SHMT2, PAICS, NT5E and PLPP2). Low-risk patients showed better overall survival in all five cohorts (TCGA cohort, two external validation cohorts and two internal validation cohorts). There was a higher proportion of tumor-infiltrating CD8+ T cells, CD4+ memory resting T cells, gamma delta T cells and resting dendritic cells and a lower proportion of M0 and M2 macrophages in the low-risk group. Low-risk patients also showed higher ESTIMATE scores, higher immune function scores, higher Immunophenoscores (IPS) and checkpoint expression, lower stemness scores, lower TIDE (Tumor Immune Dysfunction and Exclusion) scores and IC50 values for several chemotherapeutic agents, suggesting that low-risk patients could respond more favorably to immunotherapy and chemotherapy. Two real-world patient cohorts receiving anti-PD-1 therapy were applied for validating the predictive results. Molecular subtypes identified based on these seven genes also showed different immune characteristics. Immunohistochemical data obtained from the human protein atlas database demonstrated the protein expression of signature genes. This research may contribute to the identification of metabolic targets for BRCA and the optimization of risk stratification and personalized treatment for BRCA patients.

Background: Radioresistance in head and neck squamous cell carcinoma (HNSCC) patients means response failure to current treatment. In order to screen radioresistant biomarkers and mechanisms associated with HNSCC, differentially expressed genes (DEGs) associated with radioresistance in HNSCC were investigated. Methods: The HNSCC cell line with radioresistance, Hep2-R, was established and detected the radiosensitivity using MTT, colony formation assay and flow cytometry analysis. Clariom™ D chip was applied to compare DEGs between Hep2 and Hep2-R groups and build the differential gene expression profiles associated with radioresistance in HNSCC. Bioinformatic analysis were used to find biological functions and pathways that related to radioresistance in HNSCC, including cell adhesion, cytochrome P450 and drug metabolism. Gene Expression Omnibus (GEO) datasets were selected to verify DEGs between HNSCC radioresistant cells and tissues. The representation of DEGs were validated between HNSCC patients with complete response and post-operative radiation therapy failure. In addition, we evaluated the clinical prognosis of DEGs using The Cancer Genome Atlas (TCGA) database. Results: 2,360 DEGs (|Fold Change|>1.5, p < 0.05) were identified between Hep2 and Hep2-R, including 1,144 upregulated DEGs and 1,216 downregulated DEGs. They were further verified by HNSCC radioresistant cells and tissues in GEO. 13 radioresistant DEGs showed same difference in expression level between cells and tissues. By comparing 13 DEGs with HNSCC patients, upregulations of FN1, SOX4 and ETV5 were found identical with above results. Only FN1 was a prognostic indicator of HNSCC in TCGA. Conclusion: FN1 is the potential novel biomarker for predicting poor prognosis and radioresistance in HNSCC patients. Overexpression of FN1 plays an important role in the tumorigenesis, prognosis and radioresistance of HNSCC.

Postoperative cognitive dysfunction (POCD) is a cognitive deterioration and dementia that arise after a surgical procedure, affecting up to 40% of surgery patients over the age of 60. The precise etiology and molecular mechanisms underlying POCD remain uncovered. These reasons led us to employ integrative bioinformatics and machine learning methodologies to identify several biological signaling pathways involved and molecular signatures to better understand the pathophysiology of POCD. A total of 223 differentially expressed genes (DEGs) comprising 156 upregulated and 67 downregulated genes were identified from the circRNA microarray dataset by comparing POCD and non-POCD samples. Gene ontology (GO) analyses of DEGs were significantly involved in neurogenesis, autophagy regulation, translation in the postsynapse, modulating synaptic transmission, regulation of the cellular catabolic process, macromolecule modification, and chromatin remodeling. Pathway enrichment analysis indicated some key molecular pathways, including mTOR signaling pathway, AKT phosphorylation of cytosolic targets, MAPK and NF-κB signaling pathway, PI3K/AKT signaling pathway, nitric oxide signaling pathway, chaperones that modulate interferon signaling pathway, apoptosis signaling pathway, VEGF signaling pathway, cellular senescence, RANKL/RARK signaling pathway, and AGE/RAGE pathway. Furthermore, seven hub genes were identified from the PPI network and also determined transcription factors and protein kinases. Finally, we identified a new predictive drug for the treatment of SCZ using the LINCS L1000, GCP, and P100 databases. Together, our results bring a new era of the pathogenesis of a deeper understanding of POCD, identified novel therapeutic targets, and predicted drug inhibitors in POCD.