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PubMed2026

CDC20B Dysregulation: Links to Tumor Prognosis and Immunity.

OBJECTIVE: This study aimed to clarify the pan-cancer expression pattern, upstream regulatory mechanisms, prognostic relevance, and immune associations of CDC20B. METHOD: Using public databases (GTEx, GEO, and TCGA), we examined CDC20B expression and its associations with prognosis and tumor immunity across multiple cancers. Immunohistochemistry (IHC) on an independent clinical cohort was performed to validate CDC20B upregulation in tumor tissues. Promoter methylation, genetic alterations, and immune infiltration were analyzed using bioinformatics tools (cBioPortal, UALCAN, TIMER2.0, ESTIMATE). Functional enrichment was assessed by GSEA and single-cell state analysis (CancerSEA). RESULTS: CDC20B was markedly upregulated in most tumor types (p < 0.001), with strong diagnostic efficiency (AUC > 0.7 in 15 cancers) and potential regulation by promoter hypomethylation. IHC confirmed its overexpression in clinical tumor tissues. However, the prognostic impact of CDC20B was cancer-type-specific: high expression correlated with poor overall survival in UCS, LGG, KIRC, and OV, but with favorable survival in BRCA, LUAD, and PAAD. CDC20B expression was associated with immune infiltration patterns, showing negative correlations with ImmuneScore in most cancers but positive correlations with CD8+ T cells in PAAD. Functional analyses indicated involvement in EMT, KRAS/NF-κB signaling, and DNA damage response pathways. DISCUSSION: The dual prognostic role of CDC20B suggests context-dependent functions, likely influenced by tumor microenvironment composition and underlying oncogenic programs. Promoter hypomethylation emerges as a potential epigenetic driver of overexpression. The associations with immune modulation and genomic instability suggest that CDC20B is a candidate biomarker, though causal relationships require experimental validation. CONCLUSION: CDC20B may contribute to tumor progression in a context-dependent manner, with its prognostic impact varying across cancer types. Its role in tumor immunity and oncogenic pathways warrants further investigation, particularly in stratified patient populations.

CDC20B↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

PubMed2005

Bioinformatic methods to exploit mass spectrometric data for proteomic applications.

The new technologies in mass spectrometric analysis of peptides and proteins necessary to accommodate proteomics-scale analyses require, in turn, concomitant development of informatics technologies suitable for very large-scale data handling and analysis. This chapter focuses on the data analysis tools available to the community for analysis of mass spectrometric proteomics data. Different database searching strategies are discussed for peptide and protein identification, and approaches and tools available for comparative quantitative analysis of samples are outlined.

Animals↗

PubMed2006

Bioinformatics and cancer: an essential alliance.

Modern research in cancer has been revolutionized by the introduction of new high-throughput methodologies such as DNA microarrays. Keeping the pace with these technologies, the bioinformatics offer new solutions for data analysis and, what is more important, it permits to formulate a new class of hypothesis inspired in systems biology, more oriented to blocks of functionally-related genes. Although software implementations for this new methodologies is new there are some options already available. Bioinformatic solutions for other high-throughput techniques such as array-CGH of large-scale genotyping is also revised.

Chromosome Aberrations↗

PubMed2006

Understanding the cell in terms of structure and function: insights from structural genomics.

Structural genomics programs are only now moving into the large-scale production phase, yet have already produced around 2000 protein structures. Through a widespread if not exclusive emphasis on structural novelty, our knowledge of the protein fold universe is improving rapidly. With this information comes the challenge of structure-based function annotation for the many target proteins about which little or nothing is known. Recent years have therefore seen the emergence of impressively diverse bioinformatics approaches to predict the function of a protein structure. Attention is now turning to means of combining these predictions with information from various other sources.

Computational Biology↗

PubMed2001

Structural and functional features of eukaryotic mRNA untranslated regions.

The crucial role of the non-coding portion of genomes is now widely acknowledged. In particular, mRNA untranslated regions are involved in many post-transcriptional regulatory pathways that control mRNA localization, stability and translation efficiency. We review in this paper the major structural and compositional features of eukaryotic mRNA untranslated regions and provide some examples of bioinformatic analyses for their functional characterization.

3' Untranslated Regions↗

PubMed2001

MutaProt: a web interface for structural analysis of point mutations.

A web-based tool, termed 'MutaProt', is described which analyses pairs of PDB files whose members differ in one, or two, amino acids. MutaProt examines the micro environment surrounding the exchanged residue(s) and can be searched by specifying a PDB ID, keywords, or any pair of amino acids. Detailed information about accessibility of the exchanged residue(s) and its atomic contacts are provided based on CSU software (Sobolev et al., Bioinformatics, 15, 327-332, 1999). An interactive 3D presentation of the superimposed regions around the mutation(s) is included. MutaProt is updated weekly.

Databases, Factual↗

PubMed2001

A genomic perspective on human proteases.

Over 400 human proteases documented in secondary databases can already be delineated in genomic sequence. A Genome Ontology annotation of 30585 sequences in the provisional human proteome set recognises 498 proteases, i.e. 1.6%. Homology searches against finished sequence and comparisons between mouse and zebrafish are likely to increase this total. However, the data already indicate that the mechanistic class, sequence family and domain distribution of the genomic complement of proteases is unlikely to shift significantly from that already observed in the transcript data. Genomically derived novel sequences will require bioinformatic analysis and biochemical verification. The increasing availability of annotated genomic data will enable studies of splice variants, transcriptional control, polymorphisms, pseudogenes, inactive homologues and evolution. Comparative work on complete human protease families should produce a more integrated picture of their biochemistry and physiology. Genomic data will also lead to the identification of new protease involvement in disease processes and their evaluation as drug targets.

Alternative Splicing↗

PubMed2024

Interactions between microbiota and uterine corpus endometrial cancer: A bioinformatic investigation of potential immunotherapy.

Microorganisms in the gut and other niches may contribute to carcinogenesis while also altering cancer immune surveillance and therapeutic response. However, determining the impact of genetic variations and interplay with intestinal microbes' environment is difficult and unanswered. Here, we examined the frequency of thirteen mutant genes that caused aberrant gut in thirty different types of cancer using The Cancer Genomic Atlas (TCGA) database. Substantially, our findings show that all these mutated genes are quite frequent in uterine corpus endometrial cancer (UCEC). Further, these mutant genes are implicated in the infiltration of different subset of immune cells within the Tumor Microenvironment (TME) of UCEC patients. The top-ranking mutant genes that promote immune cell invasion into the TME of UCEC patients were PGLYRP2, OLFM4, and TLR5. In this regard, we used the same deconvolution of the TCGA database to analyze the microbiome that have a strong association with immune cells invasion with TME of UCEC patients. Several bacteria and viruses have been linked to the invasion of immune cells, such as B cell memory and T cell regulatory (Tregs), into the TME of UCEC patients. As a result, our findings pave the way for future research into generating novel immunizations against bacteria or viruses as immunotherapy for UCEC patients.

Humans↗

PubMed2004

In-silico identification of chicken immune-related genes.

In order to increase the resources available in chicken, a large-scale expressed sequence tag (EST) project was recently undertaken, resulting in the addition of more than 330,000 sequences to the databases. With the sequencing of further EST collections, there are now more than 460,000 chicken EST sequences publicly available (http://www.ncbi.nlm.nih.gov/). Previous analyses of the EST data estimate that the chicken genome may contain up to 35,000 genes. However, human data indicate that there may only be around 25,000, although there may be many more transcripts than actual genes. Here we describe how we used a bioinformatics approach with this large EST collection in order to identify immune-related genes, many of which were previously unreported in the chicken. The ESTs include cytokines, chemokines, antigens, cell surface proteins, receptors and MHC-associated genes. The identification of these kinds of genes will allow further study of avian immunology and will pave the way for large-scale immune-related microarray experiments, giving new insight into functional and evolutionary studies.

Animals↗

PubMed2006

Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application.

MOTIVATION: The CEBS data repository is being developed to promote a systems biology approach to understand the biological effects of environmental stressors. CEBS will house data from multiple gene expression platforms (transcriptomics), protein expression and protein-protein interaction (proteomics), and changes in low molecular weight metabolite levels (metabolomics) aligned by their detailed toxicological context. The system will accommodate extensive complex querying in a user-friendly manner. CEBS will store toxicological contexts including the study design details, treatment protocols, animal characteristics and conventional toxicological endpoints such as histopathology findings and clinical chemistry measures. All of these data types can be integrated in a seamless fashion to enable data query and analysis in a biologically meaningful manner. RESULTS: An object model, the SysBio-OM (Xirasagar et al., 2004) has been designed to facilitate the integration of microarray gene expression, proteomics and metabolomics data in the CEBS database system. We now report SysTox-OM as an open source systems toxicology model designed to integrate toxicological context into gene expression experiments. The SysTox-OM model is comprehensive and leverages other open source efforts, namely, the Standard for Exchange of Nonclinical Data (http://www.cdisc.org/models/send/v2/index.html) which is a data standard for capturing toxicological information for animal studies and Clinical Data Interchange Standards Consortium (http://www.cdisc.org/models/sdtm/index.html) that serves as a standard for the exchange of clinical data. Such standardization increases the accuracy of data mining, interpretation and exchange. The open source SysTox-OM model, which can be implemented on various software platforms, is presented here. AVAILABILITY: A universal modeling language (UML) depiction of the entire SysTox-OM is available at http://cebs.niehs.nih.gov and the Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov CONTACT: xirasagars@saic.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational Biology↗

PubMed2003

TIP, a T-cell factor identified using high-throughput screening increases survival in a graft-versus-host disease model.

A coordinated effort combining bioinformatic tools with high-throughput cell-based screening assays was implemented to identify novel factors involved in T-cell biology. We generated a unique library of cDNAs encoding predicted secreted and transmembrane domain-containing proteins generated by analyzing the Human Genome Sciences cDNA database with a combination of two algorithms that predict signal peptides. Supernatants from mammalian cells transiently transfected with this library were incubated with primary T cells and T-cell lines in several high-throughput assays. Here we describe the discovery of a T cell factor, TIP (T cell immunomodulatory protein), which does not show any homology to proteins with known function. Treatment of primary human and murine T cells with TIP in vitro resulted in the secretion of IFN-gamma, TNF-alpha, and IL-10, whereas in vivo TIP had a protective effect in a mouse acute graft-versus-host disease (GVHD) model. Therefore, combining functional genomics with high-throughput cell-based screening is a valuable and efficient approach to identifying immunomodulatory activities for novel proteins.

Adjuvants, Immunologic↗

PubMed2024

The prognostic significance of ubiquitination-related genes in multiple myeloma by bioinformatics analysis.

BACKGROUND: Immunoregulatory drugs regulate the ubiquitin-proteasome system, which is the main treatment for multiple myeloma (MM) at present. In this study, bioinformatics analysis was used to construct the risk model and evaluate the prognostic value of ubiquitination-related genes in MM. METHODS AND RESULTS: The data on ubiquitination-related genes and MM samples were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The consistent cluster analysis and ESTIMATE algorithm were used to create distinct clusters. The MM prognostic risk model was constructed through single-factor and multiple-factor analysis. The ROC curve was plotted to compare the survival difference between high- and low-risk groups. The nomogram was used to validate the predictive capability of the risk model. A total of 87 ubiquitination-related genes were obtained, with 47 genes showing high expression in the MM group. According to the consistent cluster analysis, 4 clusters were determined. The immune infiltration, survival, and prognosis differed significantly among the 4 clusters. The tumor purity was higher in clusters 1 and 3 than in clusters 2 and 4, while the immune score and stromal score were lower in clusters 1 and 3. The proportion of B cells memory, plasma cells, and T cells CD4 naïve was the lowest in cluster 4. The model genes KLHL24, HERC6, USP3, TNIP1, and CISH were highly expressed in the high-risk group. AICAr and BMS.754,807 exhibited higher drug sensitivity in the low-risk group, whereas Bleomycin showed higher drug sensitivity in the high-risk group. The nomogram of the risk model demonstrated good efficacy in predicting the survival of MM patients using TCGA and GEO datasets. CONCLUSIONS: The risk model constructed by ubiquitination-related genes can be effectively used to predict the prognosis of MM patients. KLHL24, HERC6, USP3, TNIP1, and CISH genes in MM warrant further investigation as therapeutic targets and to combat drug resistance.

Humans↗

PubMed2005

The SOL Genomics Network: a comparative resource for Solanaceae biology and beyond.

The SOL Genomics Network (SGN; http://sgn.cornell.edu) is a rapidly evolving comparative resource for the plants of the Solanaceae family, which includes important crop and model plants such as potato (Solanum tuberosum), eggplant (Solanum melongena), pepper (Capsicum annuum), and tomato (Solanum lycopersicum). The aim of SGN is to relate these species to one another using a comparative genomics approach and to tie them to the other dicots through the fully sequenced genome of Arabidopsis (Arabidopsis thaliana). SGN currently houses map and marker data for Solanaceae species, a large expressed sequence tag collection with computationally derived unigene sets, an extensive database of phenotypic information for a mutagenized tomato population, and associated tools such as real-time quantitative trait loci. Recently, the International Solanaceae Project (SOL) was formed as an umbrella organization for Solanaceae research in over 30 countries to address important questions in plant biology. The first cornerstone of the SOL project is the sequencing of the entire euchromatic portion of the tomato genome. SGN is collaborating with other bioinformatics centers in building the bioinformatics infrastructure for the tomato sequencing project and implementing the bioinformatics strategy of the larger SOL project. The overarching goal of SGN is to make information available in an intuitive comparative format, thereby facilitating a systems approach to investigations into the basis of adaptation and phenotypic diversity in the Solanaceae family, other species in the Asterid clade such as coffee (Coffea arabica), Rubiaciae, and beyond.

Arabidopsis↗

PubMed2026

pSTRminer: integrated bioinformatic software for genome-wide identification and population-scale evaluation of polymorphic short tandem repeats.

Animal forensic genetics plays a critical role in criminal investigations by providing crucial evidence through domestic animal individualization and wildlife species identification. While human forensic genetics benefits from standardized short tandem repeats (STR) genotyping systems, animal forensic applications encounter significant challenges, including the limited availability of validated STR markers, the prevalence of error-prone dinucleotide STRs (di-STRs), and insufficient integration of population data. To address these challenges, we developed pSTRminer, an integrated bioinformatic tool that automates genome-wide STR mining and polymorphism evaluation. By applying pSTRminer to domestic cattle (Bos taurus), we identified 775,444 STRs de novo from the reference genome and genotyped them using whole-genome sequencing data from 60 Chinese and 111 African cattle to evaluate polymorphism across diverse genetic backgrounds. This led to the development of the cattle STR database (CSDB), comprising loci with a genotyping success rate ≥ 40% and polymorphism information content (PIC) ≥ 0.5. Experimental validation of 30 randomly selected tetranucleotide STRs (tetra-STRs) and 33 di-STRs via next-generation sequencing in a local Chinese cattle population (n = 145) confirmed marker reliability. Although tetra-STRs had lower average polymorphism levels, they exhibited significantly lower stutter ratios (p < 0.05), providing a viable path for identifying discriminative markers with fewer artifacts. Systematic screening revealed that certain tetra-STRs could surpass di-STRs in polymorphism. In conclusion, pSTRminer provides a scalable framework for developing standardized STR panels, facilitating the identification of robust and informative markers in forensic applications.

Bioinformatic software↗

PubMed2006

NovelFam3000--uncharacterized human protein domains conserved across model organisms.

BACKGROUND: Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins. DESCRIPTION: From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system. CONCLUSION: Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families.

Animals↗

PubMed2007

In silico whole-genome screening for cancer-related single-nucleotide polymorphisms located in human mRNA untranslated regions.

BACKGROUND: A promising application of the huge amounts of genetic data currently available lies in developing a better understanding of complex diseases, such as cancer. Analysis of publicly available databases can help identify potential candidates for genes or mutations specifically related to the cancer phenotype. In spite of their huge potential to affect gene function, no systematic attention has been paid so far to the changes that occur in untranslated regions of mRNA. RESULTS: In this study, we used Expressed Sequence Tag (EST) databases as a source for cancer-related sequence polymorphism discovery at the whole-genome level. Using a novel computational procedure, we focused on the identification of untranslated region (UTR)-localized non-coding Single Nucleotide Polymorphisms (UTR-SNPs) significantly associated with the tumoral state. To explore possible relationships between genetic mutation and phenotypic variation, bioinformatic tools were used to predict the potential impact of cancer-associated UTR-SNPs on mRNA secondary structure and UTR regulatory elements. We provide a comprehensive and unbiased description of cancer-associated UTR-SNPs that may be useful to define genotypic markers or to propose polymorphisms that can act to alter gene expression levels. Our results suggest that a fraction of cancer-associated UTR-SNPs may have functional consequences on mRNA stability and/or expression. CONCLUSION: We have undertaken a comprehensive effort to identify cancer-associated polymorphisms in untranslated regions of mRNA and to characterize putative functional UTR-SNPs. Alteration of translational control can change the expression of genes in tumor cells, causing an increase or decrease in the concentration of specific proteins. Through the description of testable candidates and the experimental validation of a number of UTR-SNPs discovered on the secreted protein acidic and rich in cysteine (SPARC) gene, this report illustrates the utility of a cross-talk between in silico transcriptomics and cancer genetics.

Computational Biology↗

PubMed2005

Gene expression profile studies of human keratoconus cornea for NEIBank: a novel cornea-expressed gene and the absence of transcripts for aquaporin 5.

PURPOSE: To increase the database of genes expressed in human cornea and to gain insights into the molecular basis of keratoconus (KC). METHODS: A cDNA library was constructed from KC corneas harvested at keratoplasty and used for expressed sequence tag (EST) analysis. Data were analyzed using grouping and identification of sequence tags (GRIST). Expression of selected clones was examined by RT-PCR. RESULTS: A total of 7680 clones was sequenced from the 5' end. After bioinformatics analysis, 4090 clusters of clones, each potentially representing individual genes, were identified. Of these, 887 genes were represented by more than one clone. The five most abundant transcripts, represented by >60 clones each, were for keratin-12, TGFBI (BIGH3), decorin, ALDH3, and enolase 1, all known markers for cornea. Many other markers for epithelial, stromal, and endothelial genes were also present. One cluster of six clones came from an apparently novel gene (designated KC6) located on chromosome 18 at p12.3. RT-PCR of RNA from several human tissues detected KC6 transcripts only in cornea. In addition, no clones were observed for the usually prominent corneal epithelial cell marker aquaporin 5 (AQP5), a water channel protein. Semiquantitative RT-PCR confirmed that expression of AQP5 is much lower in KC cornea than in non-KC cornea. CONCLUSIONS: This analysis increases the database of genes expressed in the human cornea and provides insights into KC. KC6 is a novel gene of unknown function that shows cornea-preferred expression, whereas the suppression of transcripts for AQP5 provides the first clear evidence of a molecular defect identified in KC.

Amino Acid Sequence↗