The Screening and Identification of Key Biomarkers in Adrenocortical Carcinoma: Evidence from a Bioinformatics Analysis

<sec> <title>Objective:</title> This study aimed to identify the potential key genes associated with the progression and prognosis of adrenocortical carcinoma (ACC). </sec> <sec> <title>Methods:</title> Differentially expressed genes (DEGs) in ACC cells and normal adrenocortical cells were assessed by microarray from the Gene Expression Omnibus database. The biological functions of the classified DEGs were examined by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses and a protein–protein interaction (PPI) network was mapped using Cytoscape software. MCODE software was also used for the module analysis and then 4 algorithms of cytohubba software were used to screen hub genes. The overall survival (OS) examination of the hub genes was then performed by the ualcan online tool. </sec> <sec> <title>Results:</title> Two GSEs (GSE12368, GSE33371) were downloaded from GEO including 18 and 43 cases, respectively. One hundred and sixty-nine DEGs were identified, including 57 upregulated genes and 112 downregulated genes. The Gene Ontology (GO) analyses showed that the upregulated genes were significantly enriched in the mitotic cytokines is, nucleus and ATP binding, while the downregulated genes were involved in the positive regulation of cardiac muscle contraction, extracellular space, and heparin-binding (P < 0.05). The Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) pathway examination showed significant pathways including the cell cycle and the complement and coagulation cascades. The protein– protein interaction (PPI) network consisted of 162 nodes and 847 edges, including mitotic nuclear division, cytoplasmic, protein kinase binding, and cell cycle. All 4 identified hub genes (FOXM1, UBE2C, KIF11, and NDC80) were associated with the prognosis of adrenocortical carcinoma (ACC) by survival analysis. </sec> <sec> <title>Conclusions:</title> The present study offered insights into the molecular mechanism of adrenocortical carcinoma (ACC) that may be beneficial in further analyses. </sec>

Comprehensive bioinformatic analysis of the expression and prognostic significance of TSC22D domain family genes in acute myeloid leukemia

Background: TSC22D domain family genes, including Tsc22d1-4, have been extensively reported to be involved in tumors. However, their expression profiles and prognostic significance in acute myeloid leukemia (AML) remain unknown. Methods: The present study investigated the expression profiles and prognostic significance of TSC22D domain family genes in AML through the use of multiple online databases, including the CCLE, EMBL-EBI, HPA, Oncomine,GEPIA2, UALCAN, BloodSpot, and GSCALite databases. The cBioPortal and GSCALite databases were used to explore the genetic alteration and copy number variation (CNV) of the Tsc22d3 gene. The TRRUST (Version 2) database was used to explore the gene ontology biological process, disease ontology, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with the Tsc22d3 gene. The AnimalTFDB3.0, STRING, and Harmonizome databases were used to investigate the protein–protein interaction (PPI) network of the Tsc22d3 gene. The Harmonizome database was used for Tsc22d3 gene regulatory kinase analysis. The TargetScanHuman 7.2, MiRDB, and ENCORI databases were used to execute the analysis of the Tsc22d3 gene regulatory miRNAs. Then, the GSCALite and GEPIA2021 databases were used to investigate the correlation between Tsc22d3 expression and immune infiltration. Results: The expression of the Tsc22d3 gene was upregulated markedly in AML cells relative to normal hematopoietic stem cells. The expression of the Tsc22d3 gene was increased in AML tumor samples compared with healthy bone marrow samples. And overexpression of the Tsc22d3 gene was associated with poor OS in AML patients.This study implied that the Tsc22d3 gene is a new biomarker for predicting the prognosis of AML. Furthermore, gene ontology analysis showed that Tsc22d3 was involved in leukemia. Functional enrichment analysis showed that the Tsc22d3 gene has many biological functions, including the regulation of many genes, kinases, miRNAs, signaling pathways, and immune infiltration.Therefore, this study suggests that the Tsc22d3 gene may be a potential therapeutic target for AML. Conclusions: Tsc22d3 gene expression was upregulated in AML, and overexpression was associated with poor OS in AML patients. Therefore, the Tsc22d3 gene may serve as a novel prognostic biomarker and therapeutic target for AML.

Identification and validation of the high expression of pseudogene TCAM1P in cervical cancer via integrated bioinformatics analysis

Background HPV as the main cause of cervical cancer has long been revealed, but the detailed mechanism has not yet been elucidated. The role of testis/cancer antigen in cervical cancer has been revealed. However, there are no reports about the statement of testis/cancer-specific non-coding RNA. In this study, we first proposed TCAM1P as a testis/cancer-specific pseudogene, and used a series of experimental data to verify its relationship with HPV, and analyzed its diagnosis value of high-grade cervical lesions and the mechanism of their high expression in cervical cancer. This provides a new direction for the prevention and treatment of cervical cancer. Methods The specific expression of pseudogenes in each tissue was calculated by “TAU” formula. ROC curve was used to judge the diagnosed value of TCAM1P for high-grade lesions. The proliferation ability of cells was measured by CCK8. The expression of TCAM1P, HPV E6/E7 were detected by qRT-PCR. The binding for RBPs on TCAM1P was predicted by starbase v2.0 database, then RIP assay was used to verify. Besides, Gene Ontology (GO) and KEGG enrichment analysis were performed with “clusterprofiler” R package. Results TCAM1P was specifically high-expressed in normal testicular tissue and cervical cancer. Interesting, with the severity of cervical lesions increased, the expression of TCAM1P increased, and TCAM1P could effectively diagnose high-grade cervical lesions. Besides, the expression of TCAM1P was HPV dependent, with highest expression in HPV-positive cervical cancer tissues. Furthermore, RIP assay showed that EIF4A3 regulated the expression of TCAM1P through binding with it. CCK8 assay showed that TCAM1P promoted the proliferation and the Gene ontology (GO) and KEGG Pathway enrichment analysis same suggested that TCAM1P is involved in multiple ways in cell proliferation including Cell cycle, DNA replication and etc. Conclusions In this study, we firstly proposed that TCAM1P is cancer/testis pseudogene and is regulated by HPV E6/E7 and EIF4A3. TCAM1P promotes the proliferation of cervical cancer cells and acts as promoter in cervical cancer. Otherwise, TCAM1P promote proliferation through regulating cell cycle and DNA replication, but more evidence needs to be provided to reveal the mechanism by which TCAM1P plays a role in cervical cancer.

Expression of lncRNAs in children with pancreaticobiliary maljunction: functional analysis and potential biomarkers

IntroductionPancreaticobiliary maljunction (PBM) leads to higher rates of complications, including cholangitis,pancreatitis, and malignancies. The present study was to investigat the expression profile of long non-coding RNAs (lncRNAs) and their potential role as biomarkers in children with pancreaticobiliary maljunction.Material and methodsThe differential expression of lncRNAs and mRNAs from 15 pediatric patients with pancreaticobiliary maljunction and 15 control subjects were analyzed using a commercial microarray and validated with qRT-PCR. The potential biological functions of differentially expressed genes were explored based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment. The ability of potential lncRNA biomarkers to predict pancreaticobiliary maljunction was assessed based on the area under the receiver operating characteristic curve (AUC).ResultsThere were 2915 mRNAs and 173 lncRNAs upregulated, and 2121 mRNAs and 316 lncRNAs downregulated in pancreaticobiliary maljunction cases compared to controls. The enriched Gene Ontology categories associated with differentially expressed mRNAs were extracellular matrix, extracellular region, and kinetochore. The most enriched Kyoto Encyclopedia pathway was protein digestion and absorption, which has been associated with cancer and PI3K-Akt signaling. Analysis of cis- and trans-target genes predicted that a single lncRNA was able to regulate several mRNAs. The qRT-PCR results for NR_110876, NR_132344, XR_946886, and XR_002956345 were consistent with the microarray results, and the difference was statistically significant for NR_132344, XR_946886, and XR_002956345 (p < 0.05). AUC was significant only for XR_946886 (0.837, p < 0.001).ConclusionsOur results implicate lncRNAs in common bile duct pathogenesis in pancreaticobiliary maljunction, and they identify XR_946886 as a potential biomarker for the disease.

Deletion of the N-Terminal Domain of Yeast Eukaryotic Initiation Factor 4B Reprograms Translation and Reduces Growth in Urea

The yeast eukaryotic initiation factor 4B binds the 40S subunit in translation preinitiation complexes (PICs), promoting mRNA recruitment. Recent evidence indicates yeast mRNAs have variable dependence on eIF4B under optimal growth conditions. Given the ability of eIF4B to promote translation as a function of nutrient conditions in mammalian cells, we wondered if eIF4B activities in translation could alter phenotypes in yeast through differential mRNA selection for translation. Here we compared the effects of disrupting yeast eIF4B RNA- and 40S-binding motifs under ∼1400 growth conditions. The RNA-Recognition Motif (RRM) was dispensable for stress responses, but the 40S-binding N-terminal Domain (NTD) promoted growth in response to stressors requiring robust cellular integrity. In particular, the NTD conferred a strong growth advantage in the presence of urea, which may be important for pathogenesis of related fungal species. Ribosome profiling indicated that similar to complete eIF4B deletion, deletion of the NTD dramatically reduced translation, particularly of those mRNAs with long and highly structured 5-prime untranslated regions. This behavior was observed both with and without urea exposure, but the specific mRNA pool associated with ribosomes in response to urea differed. Deletion of the NTD led to relative increases in ribosome association of shorter transcripts with higher dependence on eIF4G, as was noted previously for eIF4B deletion. Gene ontology analysis indicated that proteins encoded by eIF4B NTD-dependent transcripts were associated with the cellular membrane system and the cell wall, while NTD-independent transcripts encoded proteins associated with cytoplasmic proteins and protein synthesis. This analysis highlighted the difference in structure content of mRNAs encoding membrane versus cytoplasmic housekeeping proteins and the variable reliance of specific gene ontology classes on various initiation factors promoting otherwise similar functions. Together our analyses suggest that deletion of the eIF4B NTD prevents cellular stress responses by affecting the capacity to translate a diverse mRNA pool.

The biomarkers of key miRNAs and gene targets associated with extranodal NK/T-cell lymphoma

Gene expression profiling studies have shown the pathogenetic role of oncogenic pathways in extranodal natural killer/T-cell lymphoma (ENKL). In this study, we aimed to identify the microRNAs (miRNAs) playing potential roles in ENKL, and to evaluate the genes and biological pathways associated to them. Gene expression profiles of ENKL patients were acquired from the gene expression omnibus (GEO) database. Most differentially expressed (DE)-miRNAs were identified in ENKL patients using limma package. Gene targets of the DE-miRNAs were collected from online databases (miRDB, miRWalk, miRDIP, and TargetScan), and used in Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses on Database for annotation, visualization, and integrated discovery database, and then used in protein–protein interaction (PPI) analysis on STRING database. Hub genes of the PPI network were identified in cytoHubba, and were evaluated in Biological networks gene ontology. According to the series GSE31377 and GSE43958 from GEO database, four DE-miRNAs were screened out: hsa-miR-363-3p, hsa-miR-296-5p, hsa-miR-155-5p, and hsa-miR-221-3p. Totally 164 gene targets were collected from the online databases, and used in the GO and KEGG pathway analyses and PPI network analysis. Ten hub genes of the PPI network were identified: AURKA, TP53, CDK1, CDK2, CCNB1, PLK1, CUL1, ESR1, CDC20, and PIK3CA. Those hub genes, as well as their correlative pathways, may be of diagnostic or therapeutic potential for ENKL, but further clinical evidence is still expected.

PyLiger: Scalable single-cell multi-omic data integration in Python

Motivation: LIGER is a widely-used R package for single-cell multi-omic data integration. However, many users prefer to analyze their single-cell datasets in Python, which offers an attractive syntax and highly-optimized scientific computing libraries for increased efficiency. Results: We developed PyLiger, a Python package for integrating single-cell multi-omic datasets. PyLiger offers faster performance than the previous R implementation (2-5× speedup), interoperability with AnnData format, flexible on-disk or in-memory analysis capability, and new functionality for gene ontology enrichment analysis. The on-disk capability enables analysis of arbitrarily large single-cell datasets using fixed memory.

Target Deconvolution of Fenofibrate in Nonalcoholic Fatty Liver Disease Using Bioinformatics Analysis

Background. Nonalcoholic fatty liver disease (NAFLD) is a prevalent form of liver damage, affecting ~25% of the global population. NAFLD comprises a spectrum of liver pathologies, from hepatic steatosis to nonalcoholic steatohepatitis (NASH), and may progress to liver fibrosis and cirrhosis. The presence of NAFLD correlates with metabolic disorders such as hyperlipidemia, obesity, blood hypertension, cardiovascular, and insulin resistance. Fenofibrate is an agonist drug for peroxisome proliferator-activated receptor alpha (PPARα), used principally for treatment of hyperlipidemia. However, fenofibrate has recently been investigated in clinical trials for treatment of other metabolic disorders such as diabetes, cardiovascular disease, and NAFLD. The evidence to date indicates that fenofibrate could improve NAFLD. While PPARα is considered to be the main target of fenofibrate, fenofibrate may exert its effect through impact on other genes and pathways thereby alleviating, and possibly reversing, NAFLD. In this study, using bioinformatics tools and gene-drug, gene-diseases databases, we sought to explore possible targets, interactions, and pathways involved in fenofibrate and NAFLD. Methods. We first determined significant protein interactions with fenofibrate in the STITCH database with high confidence (0.7). Next, we investigated the identified proteins on curated targets in two databases, including the DisGeNET and DISEASES databases, to determine their association with NAFLD. We finally constructed a Venn diagram for these two collections (curated genes-NAFLD and fenofibrate-STITCH) to uncover possible primary targets of fenofibrate. Then, Gene Ontology (GO) and KEGG were analyzed to detect the significantly involved targets in molecular function, biological process, cellular component, and biological pathways. A P value < 0.01 was considered the cut-off criterion. We also estimated the specificity of targets with NAFLD by investigating them in disease-gene associations (STRING) and EnrichR (DisGeNET). Finally, we verified our findings in the scientific literature. Results. We constructed two collections, one with 80 protein-drug interactions and the other with 95 genes associated with NAFLD. Using the Venn diagram, we identified 11 significant targets including LEP, SIRT1, ADIPOQ, PPARA, SREBF1, LDLR, GSTP1, VLDLR, SCARB1, MMP1, and APOC3 and then evaluated their biological pathways. Based on Gene Ontology, most of the targets are involved in lipid metabolism, and KEGG enrichment pathways showed the PPAR signaling pathway, AMPK signaling pathway, and NAFLD as the most significant pathways. The interrogation of those targets on authentic disease databases showed they were more specific to both steatosis and steatohepatitis liver injury than to any other diseases in these databases. Finally, we identified three significant genes, APOC3, PPARA, and SREBF1, that showed robust drug interaction with fenofibrate. Conclusion. Fenofibrate may exert its effect directly or indirectly, via modulation of several key targets and pathways, in the treatment of NAFLD.

Differential Transcriptomic Response of Rainbow Trout to Infection with Two Strains of IPNV

The IPN virus (IPNV) causes a highly contagious disease that affects farmed salmonids. IPNV isolates have been phylogenetically classified into seven genogroups, of which two are present in Chile, genogroups 1 and 5. This study aimed to compare the transcriptomic response of rainbow trout fry challenged with two Chilean isolates of IPNV, RTTX (genogroup 1), and ALKA (genogroup 5). Tissue samples from challenged individuals and controls were taken at 1, 7, and 20 days post-challenge and analyzed by RNA-Seq. The results revealed that infection with RTTX elicited a greater modulation of the trout transcriptome compared to ALKA infection, generating a greater number of highly differentially expressed genes in relation to the control fish. Gene Ontology enrichment indicated that functions related to the inflammatory and immune responses were modulated in fish challenged with both isolates throughout the trial, but with different regulation patterns. On day 1 post challenge, these functions were activated in those challenged with ALKA, but suppressed in RTTX-challenged fish. These results suggest that rainbow trout exhibit a differential transcriptomic response to infection with the two genetically distinct IPNV isolates, especially at early times post-infection.