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Comparative bioinformatic analysis of genes expressed in common bean (Phaseolus vulgaris L.) seedlings.

To rapidly and cost-effectively generate gene expression data, we developed an annotated unigene database of common bean (Phaseolus vulgaris L.). In this study, 3 cDNA libraries were constructed from the bean breeding line SEL1308, 1 from young leaf and 2 from seedlings inoculated or not inoculated with the fungal pathogen Colletotrichum lindemuthianum (Sacc. & Magnus) Briosi & Cavara, which causes anthracnose in common bean. To this date, 5255 single-pass sequences have been included in the database after selection based on sequence quality. These ESTs were trimmed and clustered using the computer programs Phred and CAP3 to form a unigene collection of 3126 unique sequences. Within clusters, 318 single nucleotide polymorphisms (SNPs) and 68 insertions-deletions (indels) were found, indicating the presence of paralogous gene families in our database. Each unigene sequence was analyzed for possible function using their similarity to known genes represented in the GenBank database and classified into 14 categories. Only 314 unigenes showed significant similarities to Phaseolus genomic sequences and P. vulgaris ESTs, which indicates that 90% (2818 unigenes) of our database represent newly discovered common bean genes. In addition, 12% (387 unigenes) were shown to be specific to common bean. This study represents a first step towards the discovery of novel genes in beans and a valuable source of molecular markers for expressed gene tagging and mapping.

Computational Biology↗

Screening anti-inflammatory compounds in injured spinal cord with microarrays: a comparison of bioinformatics analysis approaches.

Inflammatory responses contribute to secondary tissue damage following spinal cord injury (SCI). A potent anti-inflammatory glucocorticoid, methylprednisolone (MP), is the only currently accepted therapy for acute SCI but its efficacy has been questioned. To search for additional anti-inflammatory compounds, we combined microarray analysis with an explanted spinal cord slice culture injury model. We compared gene expression profiles after treatment with MP, acetaminophen, indomethacin, NS398, and combined cytokine inhibitors (IL-1ra and soluble TNFR). Multiple gene filtering methods and statistical clustering analyses were applied to the multi-dimensional data set and results were compared. Our analysis showed a consistent and unique gene expression profile associated with NS398, the selective cyclooxygenase-2 (COX-2) inhibitor, in which the overall effect of these upregulated genes could be interpreted as neuroprotective. In vivo testing demonstrated that NS398 reduced lesion volumes, unlike MP or acetaminophen, consistent with a predicted physiological effect in spinal cord. Combining explanted spinal cultures, microarrays, and flexible clustering algorithms allows us to accelerate selection of compounds for in vivo testing.

Algorithms↗

RNA:(guanine-N2) methyltransferases RsmC/RsmD and their homologs revisited--bioinformatic analysis and prediction of the active site based on the uncharacterized Mj0882 protein structure.

BACKGROUND: Escherichia coli guanine-N2 (m2G) methyltransferases (MTases) RsmC and RsmD modify nucleosides G1207 and G966 of 16S rRNA. They possess a common MTase domain in the C-terminus and a variable region in the N-terminus. Their C-terminal domain is related to the YbiN family of hypothetical MTases, but nothing is known about the structure or function of the N-terminal domain. RESULTS: Using a combination of sequence database searches and fold recognition methods it has been demonstrated that the N-termini of RsmC and RsmD are related to each other and that they represent a "degenerated" version of the C-terminal MTase domain. Novel members of the YbiN family from Archaea and Eukaryota were also indentified. It is inferred that YbiN and both domains of RsmC and RsmD are closely related to a family of putative MTases from Gram-positive bacteria and Archaea, typified by the Mj0882 protein from M. jannaschii (1dus in PDB). Based on the results of sequence analysis and structure prediction, the residues involved in cofactor binding, target recognition and catalysis were identified, and the mechanism of the guanine-N2 methyltransfer reaction was proposed. CONCLUSIONS: Using the known Mj0882 structure, a comprehensive analysis of sequence-structure-function relationships in the family of genuine and putative m2G MTases was performed. The results provide novel insight into the mechanism of m2G methylation and will serve as a platform for experimental analysis of numerous uncharacterized N-MTases.

Archaeal Proteins↗

Bioinformatics analysis of SARS coronavirus genome polymorphism.

BACKGROUND: We have compared 38 isolates of the SARS-CoV complete genome. The main goal was twofold: first, to analyze and compare nucleotide sequences and to identify positions of single nucleotide polymorphism (SNP), insertions and deletions, and second, to group them according to sequence similarity, eventually pointing to phylogeny of SARS-CoV isolates. The comparison is based on genome polymorphism such as insertions or deletions and the number and positions of SNPs. RESULTS: The nucleotide structure of all 38 isolates is presented. Based on insertions and deletions and dissimilarity due to SNPs, the dataset of all the isolates has been qualitatively classified into three groups each having their own subgroups. These are the A-group with "regular" isolates (no insertions / deletions except for 5' and 3' ends), the B-group of isolates with "long insertions", and the C-group of isolates with "many individual" insertions and deletions. The isolate with the smallest average number of SNPs, compared to other isolates, has been identified (TWH). The density distribution of SNPs, insertions and deletions for each group or subgroup, as well as cumulatively for all the isolates is also presented, along with the gene map for TWH. Since individual SNPs may have occurred at random, positions corresponding to multiple SNPs (occurring in two or more isolates) are identified and presented. This result revises some previous results of a similar type. Amino acid changes caused by multiple SNPs are also identified (for the annotated sequences, as well as presupposed amino acid changes for non-annotated ones). Exact SNP positions for the isolates in each group or subgroup are presented. Finally, a phylogenetic tree for the SARS-CoV isolates has been produced using the CLUSTALW program, showing high compatibility with former qualitative classification. CONCLUSIONS: The comparative study of SARS-CoV isolates provides essential information for genome polymorphism, indication of strain differences and variants evolution. It may help with the development of effective treatment.

Amino Acid Sequence↗

Bioinformatics analysis of the early inflammatory response in a rat thermal injury model.

BACKGROUND: Thermal injury is among the most severe forms of trauma and its effects are both local and systemic. Response to thermal injury includes cellular protection mechanisms, inflammation, hypermetabolism, prolonged catabolism, organ dysfunction and immuno-suppression. It has been hypothesized that gene expression patterns in the liver will change with severe burns, thus reflecting the role the liver plays in the response to burn injury. Characterizing the molecular fingerprint (i.e., expression profile) of the inflammatory response resulting from burns may help elucidate the activated mechanisms and suggest new therapeutic intervention. In this paper we propose a novel integrated framework for analyzing time-series transcriptional data, with emphasis on the burn-induced response within the context of the rat animal model. Our analysis robustly identifies critical expression motifs, indicative of the dynamic evolution of the inflammatory response and we further propose a putative reconstruction of the associated transcription factor activities. RESULTS: Implementation of our algorithm on data obtained from an animal (rat) burn injury study identified 281 genes corresponding to 4 unique profiles. Enrichment evaluation upon both gene ontologies and transcription factors, verifies the inflammation-specific character of the selections and the rationalization of the burn-induced inflammatory response. Conducting the transcription network reconstruction and analysis, we have identified transcription factors, including AHR, Octamer Binding Proteins, Kruppel-like Factors, and cell cycle regulators as being highly important to an organism's response to burn response. These transcription factors are notable due to their roles in pathways that play a part in the gross physiological response to burn such as changes in the immune response and inflammation. CONCLUSION: Our results indicate that our novel selection/classification algorithm has been successful in selecting out genes with play an important role in thermal injury. Additionally, we have demonstrated the value of an integrative approach in identifying possible points of intervention, namely the activation of certain transcription factors that govern the organism's response.

Algorithms↗

Bioinformatic analysis of an unusual gene-enzyme relationship in the arginine biosynthetic pathway among marine gamma proteobacteria: implications concerning the formation of N-acetylated intermediates in prokaryotes.

BACKGROUND: The N-acetylation of L-glutamate is regarded as a universal metabolic strategy to commit glutamate towards arginine biosynthesis. Until recently, this reaction was thought to be catalyzed by either of two enzymes: (i) the classical N-acetylglutamate synthase (NAGS, gene argA) first characterized in Escherichia coli and Pseudomonas aeruginosa several decades ago and also present in vertebrates, or (ii) the bifunctional version of ornithine acetyltransferase (OAT, gene argJ) present in Bacteria, Archaea and many Eukaryotes. This paper focuses on a new and surprising aspect of glutamate acetylation. We recently showed that in Moritella abyssi and M. profunda, two marine gamma proteobacteria, the gene for the last enzyme in arginine biosynthesis (argH) is fused to a short sequence that corresponds to the C-terminal, N-acetyltransferase-encoding domain of NAGS and is able to complement an argA mutant of E. coli. Very recently, other authors identified in Mycobacterium tuberculosis an independent gene corresponding to this short C-terminal domain and coding for a new type of NAGS. We have investigated the two prokaryotic Domains for patterns of gene-enzyme relationships in the first committed step of arginine biosynthesis. RESULTS: The argH-A fusion, designated argH(A), and discovered in Moritella was found to be present in (and confined to) marine gamma proteobacteria of the Alteromonas- and Vibrio-like group. Most of them have a classical NAGS with the exception of Idiomarina loihiensis and Pseudoalteromonas haloplanktis which nevertheless can grow in the absence of arginine and therefore appear to rely on the arg(A) sequence for arginine biosynthesis. Screening prokaryotic genomes for virtual argH-X 'fusions' where X stands for a homologue of arg(A), we retrieved a large number of Bacteria and several Archaea, all of them devoid of a classical NAGS. In the case of Thermus thermophilus and Deinococcus radiodurans, the arg(A)-like sequence clusters with argH in an operon-like fashion. In this group of sequences, we find the short novel NAGS of the type identified in M. tuberculosis. Among these organisms, at least Thermus, Mycobacterium and Streptomyces species appear to rely on this short NAGS version for arginine biosynthesis. CONCLUSION: The gene-enzyme relationship for the first committed step of arginine biosynthesis should now be considered in a new perspective. In addition to bifunctional OAT, nature appears to implement at least three alternatives for the acetylation of glutamate. It is possible to propose evolutionary relationships between them starting from the same ancestral N-acetyltransferase domain. In M. tuberculosis and many other bacteria, this domain evolved as an independent enzyme, whereas it fused either with a carbamate kinase fold to give the classical NAGS (as in E. coli) or with argH as in marine gamma proteobacteria. Moreover, there is an urgent need to clarify the current nomenclature since the same gene name argA has been used to designate structurally different entities. Clarifying the confusion would help to prevent erroneous genomic annotation.

Acetylation↗

Integrated bioinformatics analysis and experimental validation reveal the relationship between ALOX5AP and the prognosis and immune microenvironment in glioma.

BACKGROUND: Treatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood. METHODS: The differential expression of ALOX5AP was evaluated based on public Databases. Kaplan-Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray. RESULT: ALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma. CONCLUSION: ALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma.

Humans↗

Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis.

BACKGROUND: Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. METHODS: The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. RESULTS: In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. CONCLUSIONS: Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.

Bipolar Disorder↗

Bioinformatic analysis of peptide precursor proteins.

Neuropeptides are among the most important signal molecules in animals. Traditional identification of peptide hormones through peptide purification is a tedious and time-consuming process. With the advent of the genome sequencing projects, putative peptide precursor can be mined from the genome. However, because bioactive peptides are usually quite short in length and because the active core of a peptide is often limited to only a few amino acids, using the BLAST search engine to identify neuropeptide precursors in the genome is difficult and sometimes impossible. To overcome these shortcomings, we subject the entire set of all known Drosophila melanogaster peptide precursor sequences to motif-finding algorithms in search of a motif that is common for all prepropeptides and that could be used in the search for new peptide precursors.

Amino Acid Sequence↗

Bioinformatic analysis of the human mu opioid receptor (OPRM1) splice and polymorphic variants.

Mu opioid receptor (OPRM1), a member of the G-protein coupled receptor superfamily, mediates the analgesic and euphoric effects of opioid drugs. The sequences of OPRM1 cDNA and reported splice variants were used to search the public and Celera genomic databases. The matched sequences were analyzed to assemble an OPRM1 genomic contig. Human OPRM1 gene was estimated to span at least 90 kb in the chromosome 6q24-25 region. Four coding exons are separated by 3 introns. While intron 2 has only 773 bp, these databases for the first time provide the precise length of and other information about long introns 1 and 3, containing 50 and 27 kb, respectively. When a consensus exon/intron splice junction at the end of the coding exon 3 was not utilized, it may have resulted in continuous translation of the exon to yield the splice variant OPRM1A. The study did not identify human orthologs of other OPRM1 variants that had been reported for mouse OPRM1, although several proposed exons were found to be included in mouse genomic clones. Single nucleotide polymorphisms in the OPRM1 gene were also analyzed and summarized, which could provide potential polymorphic markers for molecular genetic studies.

Alternative Splicing↗

Identification of cuproptosis-realated key genes and pathways in Parkinson's disease via bioinformatics analysis.

INTRODUCTION: Parkinson's disease (PD) is the second most common worldwide age-related neurodegenerative disorder without effective treatments. Cuproptosis is a newly proposed conception of cell death extensively studied in oncological diseases. Currently, whether cuproptosis contributes to PD remains largely unclear. METHODS: The dataset GSE22491 was studied as the training dataset, and GSE100054 was the validation dataset. According to the expression levels of cuproptosis-related genes (CRGs) and differentially expressed genes (DEGs) between PD patients and normal samples, we obtained the differentially expressed CRGs. The protein-protein interaction (PPI) network was achieved through the Search Tool for the Retrieval of Interacting Genes. Meanwhile, the disease-associated module genes were screened from the weighted gene co-expression network analysis (WGCNA). Afterward, the intersection genes of WGCNA and PPI were obtained and enriched using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, the key genes were identified from the datasets. The receiver operating characteristic curves were plotted and a PPI network was constructed, and the PD-related miRNAs and key genes-related miRNAs were intersected and enriched. Finally, the 2 hub genes were verified via qRT-PCR in the cell model of the PD and the control group. RESULTS: 525 DEGs in the dataset GSE22491 were identified, including 128 upregulated genes and 397 downregulated genes. Based on the PPI network, 41 genes were obtained. Additionally, the dataset was integrated into 34 modules by WGCNA. 36 intersection genes found from WGCNA and PPI were significantly abundant in 7 pathways. The expression levels of the genes were validated, and 2 key genes were obtained, namely peptidase inhibitor 3 (PI3) and neuroserpin family I member 1 (SERPINI1). PD-related miRNAs and key genes-related miRNAs were intersected into 29 miRNAs including hsa-miR-30c-2-3p. At last, the qRT-PCR results of 2 hub genes showed that the expressions of mRNA were up-regulated in PD. CONCLUSION: Taken together, this study demonstrates the coordination of cuproptosis in PD. The key genes and miRNAs offer novel perspectives in the pathogenesis and molecular targeting treatment for PD.

Humans↗

Bioinformatics analysis to identify the relationship between human papillomavirus-associated cervical cancer, toll-like receptors and exomes: A genetic epidemiology study.

INTRODUCTION: Genetic variants may influence Toll-like receptor (TLR) signaling in the immune response to human papillomavirus (HPV) infection and lead to cervical cancer. In this study, we investigated the pattern of TLR expression in the transcriptome of HPV-positive and HPV-negative cervical cancer samples and looked for variants potentially related to TLR gene alterations in exomes from different populations. MATERIALS AND METHODS: A cervical tissue sample from 28 women, which was obtained from the Gene Expression Omnibus database, was used to examine TLR gene expression. Subsequently, the transcripts related to the TLRs that showed significant gene expression were queried in the Genome Aggregation Database to search for variants in more than 5,728 exomes from different ethnicities. RESULTS: Cancer and HPV were found to be associated (p<0.0001). TLR1(p = 0.001), TLR3(p = 0.004), TLR4(221060_s_at)(p = 0.001), TLR7(p = 0.001;p = 0.047), TLR8(p = 0.002) and TLR10(p = 0.008) were negatively regulated, while TLR4(1552798_at)(p<0.0001) and TLR6(p = 0.019) were positively regulated in HPV-positive patients (p<0.05). The clinical significance of the variants was statistically significant for TLR1, TLR3, TLR6 and TLR8 in association with ethnicity. Genetic variants in different TLRs have been found in various ethnic populations. Variants of the TLR gene were of the following types: TLR1(5_prime_UTR), TLR4(start_lost), TLR8(synonymous;missense) and TLR10(3_prime_UTR). The "missense" variant was found to have a risk of its clinical significance being pathogenic in South Asian populations (OR = 56,820[95%CI:40,206,80,299]). CONCLUSION: The results of this study suggest that the variants found in the transcriptomes of different populations may lead to impairment of the functional aspect of TLRs that show significant gene expression in cervical cancer samples caused by HPV.

Humans↗

Identification of Critical Genes Related to Breast Cancer with Brain Metastasis Through Bioinformatics Analysis.

INTRODUCTION: Distant metastasis accounts for the majority of Breast Cancer (BC)-related mortality. The brain is one of the most common regions of metastasis. However, the underlying molecular mechanisms remain uncertain. METHODS: In this study, gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Datasets GSE100534 and GSE52604, containing 16 primary brain tumor samples and 38 breast cancer brain metastasis samples, were used to identify the Differentially Expressed Genes (DEGs). The Metascape database was used to analyze enriched Gene Ontology (GO) entries and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway entries in DEGs. The STRING database was then used to construct a Protein-Protein Interaction (PPI) network, and the Cytoscape platform was employed to visualize the network. Furthermore, the Kaplan-Meier curve was used to analyze the Relapse-Free Survival (RFS) among the hub genes. Finally, the iRegulon plugin was used to construct a regulatory network to find the transcription factors (TFs) that regulate the expression of the hub genes. RESULTS: A total of 344 DEGs, including 182 up-regulated and 162 down-regulated genes, were identified by using the limma package in R. A module with 18 nodes and 9 hub genes was selected from the PPI network by using the plugins MCODE and Cyto- Hubba, respectively. KEGG pathway analysis demonstrated that brain metastasis in BC was closely related to the oocyte cell cycle. The Kaplan-Meier curve showed that high expression of these 9 hub genes was associated with poor RFS in BC patients. TFs' analysis showed that E2F4, SIN3A, FOXM1, and TFDP1 interacted with these hub genes. DISCUSSION: This study revealed that Breast Cancer Brain Metastasis (BCBM) may have a promoting effect on the cell cycle of oocytes and affect the maturation and division of oocytes through the KEGG and GO analyses of 344 DEGs. The selected 9 hub genes (ASPM, BUB1, BUB1B, CCNA2, CCNB1, CDK1, NDC80, NCAPG, and TOP2A) and 4 transcription factors (E2F4, SIN3A, FOXM1, TFDP1) may play a critical role in brain metastasis of BC. CONCLUSION: The results of this study may aid in the early diagnosis and suggest potential targets for the treatment of BCBM.

Brain Neoplasms↗

Web-ware bioinformatical analysis and structure modelling of N-terminus of human multisynthetase complex auxiliary component protein p43.

Human multisynthetase complex auxiliary component, protein p43 is an endothelial monocyte-activating polypeptide II precursor. In this study, comprehensive sequence analysis of N-terminus has been performed to identify structural domains, motifs, sites of post-translation modification and other functionally important parameters. The spatial structure model of full-chain protein p43 is obtained.

Amino Acid Motifs↗

[Bioinformatics analysis to the differentially expressed genes of normal mucosa and carcinoma of colon].

OBJECTIVE: To systemically analyze the differentially expressed genes from normal mucosa and carcinoma of colon obtained by SSH method. METHODS: An automatic platform for the analysis of nucleotides based on Linux was constructed, and one of the three subtracted libraries from SSH (T -N) was systematically analyzed by this platform. Part of the results was verified by semi- quantity RT-PCR. RESULT: The automatic platform for the analysis of nucleotides based on Linux was successfully constructed. There were 15 contigs from the subtracted T-N libraries, among which 2 had no match with known genes in the GenBank. The expressions of genes Homo Sapiens thymosin beta 4 (THY) and Homo Sapiens HbxAg transactivated protein 2 (XTP) had trends of increase with the progress of normal tissue-adenoma-adenocarcinoma when verified by semi- quantity RT-PCR. CONCLUSION: Linux-based automatic platform provides an efficient way to systematically analyze the nucleotide sequences, which may be used in study on the mechanism of colorectal carcinogenesis.

Colon↗

Human Wings Apart-Like Protein as a Serum Diagnostic Biomarker in Cervical Cancer: An Integrative Bioinformatics Analysis with Serum Validation.

Cervical cancer remains a major threat to women's health worldwide, and reliable serum biomarkers for early detection and therapeutic stratification remain limited. Human wings-apart-like (hWAPL) protein has been implicated in cervical carcinogenesis, but its diagnostic and clinical value has not been fully elucidated. To address this gap, this study integrated public multi-omics datasets, including The Cancer Genome Atlas, GEPIA2, the Human Protein Atlas, and single-cell transcriptomic data, to characterize hWAPL expression, clinicopathological associations, immune infiltration, co-expression networks, post-translational modifications, and drug sensitivity predictions. These findings were evaluated in an independent single-center serum cohort comprising 89 patients with histologically confirmed cervical squamous cell carcinoma and 89 healthy female controls. Serum hWAPL and squamous cell carcinoma antigen (SCC) levels were measured, and diagnostic performance was assessed by receiver operating characteristic curve analysis. In silico, hWAPL was broadly upregulated across multiple malignancies, particularly cervical cancer, enriched in malignant epithelial cells and monocytes/macrophages, and associated with shorter progression-free interval, predicted reduced sensitivity to cisplatin, paclitaxel, and 5-fluorouracil, and predicted sensitivity to MCL-1 and Wee1 inhibitors. In the serum cohort, hWAPL levels were significantly higher in patients than controls and discriminated cervical cancer with an area under the curve of 0.961, exceeding SCC alone. Combining hWAPL with SCC further improved diagnostic performance (area under the curve, 0.974; sensitivity, 93.3%; specificity, 95.5%). These findings suggest that serum hWAPL is a potential novel diagnostic biomarker for cervical squamous cell carcinoma whose performance is enhanced by SCC, whereas the observed associations with chemoresistance and immune microenvironment remodeling are hypothesis-generating and require experimental confirmation.

Humans↗

Bioinformatics: analysis of HLA sequence data.

High resolution HLA typing is a requirement for the selection of matched donors in hematopoietic cell transplantation. The high resolution typing method that provides the most accurate and complete identification of HLA genotypes is sequencing-based typing (SBT). For each sample being tested, SBT defines the exact nucleotide sequence of the coding regions of both alleles at a given HLA locus. Identification of the underlying genotype of the sample can then be made by computerized sequence comparison with all possible HLA allele combinations at that locus. The use of SBT to identify the complete nucleotide sequence of a given HLA gene also enables the direct detection of previously undefined alleles. Since different HLA alleles may differ by a single nucleotide, the accurate assignment of an HLA genotype by SBT is absolutely dependent on the correct identification of the nucleotide at each position for a given sample. However, automated sequence analysis of heterozygous samples may result in the ambiguous assignment of nucleotides at a given position. In addition, ambiguous assignments may result from the sequencing of two different samples that express different HLA alleles but whose sequence profiles appear exactly the same. Both of these ambiguous situations can be resolved by the application of the multi-sequence analysis (MSA) method described here.

Alleles↗