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PubMed2005

The NEIBank project for ocular genomics: data-mining gene expression in human and rodent eye tissues.

NEIBank is a project to gather and organize genomic resources for eye research. The first phase of this project covers the construction and sequence analysis of cDNA libraries from human and animal model eye tissues to develop an overview of the repertoire of genes expressed in the eye and a resource of cDNA clones for further studies. The sequence data are grouped and identified using the tools of bioinformatics and the results are displayed through a web site where they can be interrogated by keyword search, chromosome location, by Blast (sequence comparison) or by alignment on completed genomes. Many novel proteins and novel splice forms of known genes have already emerged from analysis of the accumulating data. This review provides an overview of the current state of the database for human eye tissues, with specific comparisons to some parallel data from mouse and rat, and with illustrative examples of the kinds of insights and discoveries these data can produce. One of the major themes that emerges is that at the molecular level human eye tissues have significant differences from those of rodents, encompassing species specific genes, alternative splice forms and great variation in levels of gene expression. These point to specific adaptations and mechanisms in the human eye and emphasize that care needs to be taken in the application of appropriate animal model systems.

Amino Acid Sequence↗

PubMed2005

caBIONet--A .NET wrapper to access and process genomic data stored at the National Cancer Institute's Center for Bioinformatics databases.

MOTIVATION: The National Cancer Institute's Center for Bioinformatics (NCICB) has developed a Java based data management and information system called caCORE. One component of this software suite is the object oriented API (caBIO) used to access the rich biological datasets collected at the NCI. This API can access the data using native Java classes, SOAP requests or HTTP calls. Non-Java based clients wanting to use this API have to use the SOAP or HTTP interfaces with the data being returned from the NCI servers as an XML data stream. Although the XML can be read and manipulated using DOM or SAX parsers, one loses the convenience and usability of an object oriented programming paradigm. caBIONet is a set of .NET wrapper classes (managers, genes, chromosomes, sequences, etc.) capable of serializing the XML data stream into local .NET objects. The software is able to search NCICB databases and provide local objects representing the data that can be manipulated and used by other .NET programs. The software was written in C# and compiled as a .NET DLL.

Chromosome Mapping↗

PubMed2005

Expressed sequence tag analysis of zebrafish eye tissues for NEIBank.

PURPOSE: To characterize gene expression patterns in various tissues of the zebrafish (Danio rerio) eye and identify zebrafish orthologs of human genes by expressed sequence tag (EST) analysis for NEIBank. METHODS: mRNA was extracted from adult zebrafish eye tissues, including lenses, anterior segments (minus lens), retinas, posterior segments lacking retinas, and whole eyes. Five different cDNA libraries were constructed in the pCMVSport6 vector. Approximately 4,000 clones from each library were sequenced and analyzed using various bioinformatics programs. RESULTS: The analysis yielded approximately 2,500 different gene clusters for each library. Combining data from the five libraries produced 10,392 unique gene clusters. GenBank accession numbers were identified for 37.6% (3,906) of the total gene clusters in the combined libraries and approximately 50% were linked to Unigene clusters in the current database. Several new crystallin genes, including two gammaN-crystallins, and a second major intrinsic protein (MIP) were identified in the lens library. In addition, a zebrafish homolog of cochlin (COCH), a gene that may play a role in the pathogenesis of human glaucoma, was identified in the anterior segment library. Surprisingly, no clear ortholog of the major retinal transcription factor Nrl was identified. CONCLUSIONS: The zebrafish eye tissue cDNA libraries are a useful resource for comparative gene expression analysis. These libraries will complement the cDNA libraries made for the Zebrafish Gene Collection (ZGC) and provide an additional source for gene identification and characterization in the vertebrate eye.

Animals↗

PubMed2006

Personalized medicine and development of targeted therapies: The upcoming challenge for diagnostic molecular pathology. A review.

Due to continuous technical developments and new insights into the high complexity of many diseases, molecular pathology is a rapidly growing field gaining center stage in the clinical management of tumors as well as in the pharmaceutical development of new anti-cancer drugs. The application of novel compounds in clinical trials has revealed promising results; however, the current diagnostic procedures available for determining which patients will primarily benefit from rational tumor therapy are insufficient. To read a patient's tissue as "deeply" as possible, in the future, gaining information on the morphology and on genetic, proteomic, and epigenetic alterations will be the upcoming task of surgical pathologists experienced in molecular diagnostics to provide the clinicians with information relevant for an individualized medicine. Among the different high-throughput technologies, DNA microarrays are now the first array approach close to enter routine diagnostics. Technically advanced and well-established microarray platforms can nowadays be evaluated by distinct bioinformatic tools capable of identifying both novel genes associated with disease development and clusters of genes predicting clinical outcome of an individual tumor. The automatic, highly parallel analysis of proteins and complex proteins lysates for early detection of cancers such as breast, prostate and ovary as proteomic patterns in the serum also appears at the horizon. In addition, an improved analysis of tumor samples via antibody or reverse-phase protein arrays is likely to provide the pathologist in the future with information about activated oncogenic signaling pathways and other cell functions, such as drug response or the potential to metastasize. While expression microarrays and proteomic analysis rely on relatively unstable material incompatible with paraffin-embedded tissue samples, an investigation of DNA methylation using specialized high-throughput platforms has revealed the potential of being used in future diagnostics. Each of these approaches on its own might not suffice to extract all information required for an efficient individualized diagnostics. Therefore, a "multiplex approach" combining the different biological levels DNA, RNA, and protein, may be necessary to functionally classify malignant tumors. This appears to become a major challenge for diagnostic pathologists.

Drug Design↗

PubMed2002

Grouping and identification of sequence tags (GRIST): bioinformatics tools for the NEIBank database.

NEIBank is a project to develop and organize genomics and bioinformatics resources for the eye. As part of this effort, tools have been developed for bioinformatics analysis and web based display of data from expressed sequence tag (EST) analyses. EST sequences are identified and formed into groups or clusters representing related transcripts from the same gene. This is carried out by a rules-based procedure called GRIST (GRouping and Identification of Sequence Tags) that uses sequence match parameters derived from BLAST programs. Linked procedures are used to eliminate non-mRNA contaminants. All data are assembled in a relational database and assembled for display as web pages with annotations and links to other informatics resources. Genome projects generate huge amounts of data that need to be classified and organized to become easily accessible to the research community. GRIST provides a useful tool for assembling and displaying the results of EST analyses. The NEIBank web site contains a growing set of pages cataloging the known transcriptional repertoire of eye tissues, derived from new NEIBank cDNA libraries and from eye-related data deposited in the dbEST section of GenBank.

Animals↗

PubMedDate not supplied

Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools.

A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools.

Animals↗

PubMed2001

US-Japan workshops in medical mycology: past, present and future.

The Extramural Mycology Program of the National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID) has organized and implemented a five workshop series in medical mycology during a critical period in the evolution of contemporary medical mycology (1992 to 2000; http://www.niaid.nih.gov/research/dmid.htm). The goals of the workshop series were to: initiate interactions; build collaborations; identify research needs; turn needs into opportunities; stimulate molecular research in medical mycology; and summarize recommendations emerging from the workshop proceedings. A recurring recommendation in the series was to foster communications within and beyond the field of medical mycology. US-Japan interactions were noted as one specific example of potential information exchange for mutual benefit. The first formal action directed at this recommendation was the workshop Emergence and Recognition of Fungal Diseases convened under the auspices of the US-Japan Cooperative Medical Science Program (USJCMSP; http://www.niaid. nih.gov/dmid/us%5Fjapan/default.htm) in Bethesda, Maryland USA on 30 June 1999 (D.M. Dixon & T. Matsumoto, co-chairs). A major goal of the workshop was to present contemporary medical mycology to the Joint Committee of the USJCMSP through representative research presentations in order to make the Committee aware of current status in the field, and the potential for scientific interactions. The second formal action is the workshop, under the auspices of the Japanese Society for Medical Mycology Medical Perspectives of Fungal Genome Studies scheduled for 28 November 2000 in Tokyo, Japan (T. Matsumoto & D.M. Dixon, co-chairs). The NIAID Mycology Workshop series recommended interactions between the following groups: academic and pharmaceutical; medical and molecular (model systems); medical and plant pathogens; basic and clinical; mycologists and immunologists. The first two US-Japan workshops can be viewed as consistent with these recommendations, and serve as a Western/Eastern gateway for exchange. The focus of the second US-Japan workshop on genome projects for the medically important fungi provides an excellent model for international communications. Given the tsunami of information that is flowing from genomics and bioinformatics, it is clear that global interactions will be essential in managing and interpreting the data.

Consensus Development Conferences, NIH as Topic↗

PubMed2004

Missense mutations in the BRCT domain of BRCA-1 from high-risk women frequently perturb strongly hydrophobic amino acids conserved among mammals.

Inherited missense mutations in the tumor suppressor gene, BRCA-1, may predispose to breast or ovarian cancer, but the exact effects on the protein are generally unknown. The COOH-terminal region of BRCA-1 encodes two BRCT repeats, which are partially conserved in mammalian species (human, dog, rat, and mouse; 60% amino acid identity). A bioinformatic analysis was conducted to evaluate 246 BRCT missense mutations from high-risk breast and/or ovarian cancer patients (reported in the NIH Breast Cancer Information Core database). It was hypothesized that amino acids conserved in evolution would be disproportionately targeted by the mutations and that conserved amino acids with strongly hydrophobic side chains would be disproportionately perturbed. A statistical model was developed, and chi(2) tests were used to determine whether missense mutations are randomly distributed throughout the BRCT repeats or whether they disproportionately target certain amino acids. The results showed that missense mutations disproportionately target amino acids that are identical in all four mammals (chi(2) = 46.01, P < 0.001). In addition, missense mutations disproportionately perturb conserved amino acids with strongly hydrophobic side chains (chi(2) = 68.57, P < 0.001) and alter the strongly hydrophobic property. The two most frequently observed known cancer-predisposing missense mutations in the BRCT repeats, M1775R and A1708E, conform to this pattern. These results suggest that missense mutations affecting highly conserved amino acids with strongly hydrophobic side chains can disturb important features of the BRCA-1 protein and may play a role in breast and ovarian cancer formation.

Amino Acid Sequence↗

PubMed2002

Association of familial and sporadic rheumatoid arthritis with a single corticotropin-releasing hormone genomic region (8q12.3) haplotype.

OBJECTIVE: Rheumatoid arthritis (RA) is a common disabling autoimmune disease with a complex genetic component. We have previously described linkage of a region of chromosome 8q12.3 with RA and association of the microsatellite marker CRHRA1 with RA in 295 affected sibling-pair families. In the current study we aimed to physically link the RA-associated marker with the corticotropin-releasing hormone (CRH) candidate gene, and to examine the genomic region for additional short tandem repeat (STR) genetic markers in order to clarify the association with RA. METHODS: We examined the association of 2 STR markers with disease in the original 295 multicase families and in a cohort of 131 simplex families to refine our understanding of this genetic region in disease susceptibility in sporadic and familial RA. Genomic library screening and sequencing were used to generate physical sequences in the CRH genomic region. Bioinformatic analysis of the sequence flanking the CRH structural gene was used to screen for additional STRs and other genetic features. Genotyping was carried out using a standard fluorescence approach. Estimations of haplotype frequencies were performed to assess linkage disequilibrium. The transmission disequilibrium test was performed using TRANSMIT. RESULTS: Physical cloning and sequencing analyses identified the genomic region linking the CRHRA1 marker and the CRH structural locus. Moreover, we identified a further STR, CRHRA2, which was in strong linkage disequilibrium with CRHRA1 (P = 4.0 x 10(-14)). A haplotype, CRHRA1*10;CRHRA2*14, was preferentially carried by unaffected parents at a frequency of 8.6% compared with the expected frequency of 3.1%. This haplotype was overtransmitted in the multiply affected families (P = 0.0077) and, similarly, in the simplex families (P = 0.024). Combined analysis of both family cohorts confirmed significant evidence for linkage (P = 4.9 x 10(-4)) and association (P = 5.5 x 10(-3)) for this haplotype with RA. CONCLUSION: In demonstrating significant linkage disequilibrium between these 2 markers, we have refined the disease-associated region to a single haplotype and confirmed the significance of this region in our understanding of the genetics of RA.

Arthritis, Rheumatoid↗

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↗

PubMed2005

Use of extreme patient samples for outcome prediction from gene expression data.

MOTIVATION: Patient outcome prediction using microarray technologies is an important application in bioinformatics. Based on patients' genotypic microarray data, predictions are made to estimate patients' survival time and their risk of tumor metastasis or recurrence. So, accurate prediction can potentially help to provide better treatment for patients. RESULTS: We present a new computational method for patient outcome prediction. In the training phase of this method, we make use of two types of extreme patient samples: short-term survivors who got an unfavorable outcome within a short period and long-term survivors who were maintaining a favorable outcome after a long follow-up time. These extreme training samples yield a clear platform for us to identify relevant genes whose expression is closely related to the outcome. The selected extreme samples and the relevant genes are then integrated by a support vector machine to build a prediction model, by which each validation sample is assigned a risk score that falls into one of the special pre-defined risk groups. We apply this method to several public datasets. In most cases, patients in high and low risk groups stratified by our method have clearly distinguishable outcome status as seen in their Kaplan-Meier curves. We also show that the idea of selecting only extreme patient samples for training is effective for improving the prediction accuracy when different gene selection methods are used.

Biomarkers, Tumor↗

PubMed2002

Expressed sequence tag analysis of human retina for the NEIBank Project: retbindin, an abundant, novel retinal cDNA and alternative splicing of other retina-preferred gene transcripts.

PURPOSE: Expressed sequence tag (EST) analysis was performed on un-normalized, unamplified cDNA libraries constructed from adult human retina to examine the expression profile of the tissue and to contribute resources for functional genomics studies. METHODS: Two size fractionated cDNA libraries (designated hd and he) were constructed from human retina RNA. Clones were randomly selected for sequencing and analyzed using the bioinformatics program GRIST (GRouping and Identification of Sequence Tags). PCR, Northern blotting and other techniques have been used to examine selected novel transcripts. RESULTS: After informatics analysis, 2200 retina cDNAs yield 1254 unique clusters, potentially representing individual genes. Opsin is the most abundant transcript and other retina transcripts are prominently represented. One abundant cluster of cDNAs encodes retbindin, a novel, retina preferred transcript which has sequence similarity to riboflavin binding proteins and whose gene is on chromosome 19. Variant transcripts of known retina genes are also observed, including an alternative exon in the coding sequence of the transcription factor NRL and a skipped coding sequence exon in the phosphodiesterase gammasubunit (PDE6G). CONCLUSIONS: The new retina cDNA libraries compare favorably in quality with those already represented in public databases. They are rich in retina specific sequences and include abundant cDNAs for a novel protein, retbindin. The function of retbindin remains to be determined, but it is a candidate for flavinoid or carotenoid binding. Analysis of multiple clones for highly expressed retina genes reveals several alternative splice variants in both coding and noncoding sequences which may have functional significance. The validated set of retina cDNAs will contribute to a nonredundant set for microarray construction.

Aged↗

PubMed2025

Evaluating 12 automated, whole-genome sequencing analysis pipelines for Mycobacterium tuberculosis complex: a comparative study.

BACKGROUND: Reliance on complex, custom-built bioinformatics pipelines is a barrier to the implementation of whole-genome sequencing (WGS) of Mycobacterium tuberculosis in high-burden settings in some low-income and middle-income countries (LMICs). Automated analysis pipelines could address this inequity in access to WGS-based diagnostics and surveillance. This study aimed to systematically evaluate the performance and usability of publicly available WGS pipelines for M tuberculosis. METHODS: We identified automated M tuberculosis WGS analysis pipelines through searches of PubMed and GitHub from database inception up to Aug 31, 2024. Accuracy, cost, accessibility, and scalability were assessed for each pipeline. We evaluated the accuracy of genotypic drug susceptibility testing (gDST) using publicly available sequences with phenotypic susceptibility data for 12 antituberculosis drugs. We estimated pooled sensitivity and specificity for each pipeline, across all drugs, by conducting a bivariate meta-analysis, with random effects representing between-drug variability. Lineage classifications were compared, and a previously epidemiologically well-characterised dataset was used to compare measures of genomic relatedness. FINDINGS: Among 28 candidate pipelines, 16 were excluded as they were unmaintained and inexecutable. 12 pipelines (11 compatible with Illumina and four compatible with Nanopore), all free to use, were included for evaluation. Six pipelines processed and stored data remotely, but for five of these six, scalability was limited by the need to upload sequences through web portals. For local processing pipelines, scalability was dependent on substantial local computational resources, data storage capacity, and command-line interfaces that limited user-friendliness. Only one of six remote-processing pipelines removed human DNA sequences before server upload. gDST was similarly accurate across ten of 11 Illumina-compatible pipelines and three of four Nanopore-compatible pipelines. All pipelines classified the main lineages consistently, although there were differences at sublineage resolution. Outputs from three of four pipelines reporting genomic relatedness were compatible with commonly cited single nucleotide polymorphism difference thresholds. INTERPRETATION: Numerous automated analysis pipelines capable of enhancing equity in M tuberculosis WGS are available. Given the overall similarities between the pipelines evaluated in this study in terms of gDST performance, lineage classification, and genomic relatedness inference, non-functional attributes such as availability, accessibility, scalability, and privacy could represent the point of difference for prospective users in LMICs with a high burden of tuberculosis. FUNDING: The Rhodes Trust, Wellcome, Ellison Institute of Technology, and the UK National Institute for Health and Care Research Oxford Biomedical Research Centre.

Mycobacterium tuberculosis↗

PubMed2026

Key hub genes and pathways associated with HCV-related hepatocellular carcinoma as potential diagnostic biomarkers.

BACKGROUND: Hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) remains a major global health challenge, with high morbidity and mortality despite recent therapeutic advances. Early detection and identification of reliable molecular biomarkers are essential to improve patient outcomes. Therefore, the present study aimed to investigate key hub genes and pathways associated with HCV-related HCC as potential diagnostic biomarkers. METHODS: The datasets GSE69715 and GSE62232 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were recognized according to an adjusted p-value and a log fold change (logFC). The GEO2R tool facilitated the identification of common DEGs across the two datasets. Pathways were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Furthermore, protein-protein interactions (PPIs) were assessed through Cytoscape. The target genes were confirmed through a GEPIA analysis. RESULTS: A total of 421 common DEGs were identified, and 80 hub genes were subsequently determined through GEO and PPI network analyses, respectively. The GO and KEGG pathways analysis presented DEGs were enhanced in metabolic pathways, cellular components, extracellular exosome, detoxification of copper ion and monooxygenase activity. The GEPIA analysis indicated a notable variation in the expression levels of four specific genes -CDKN2A, CDK1, CCNB1, and TOP2A-when comparing normal samples to tumor samples. CONCLUSION: The present study discovered novel genes by expression variation in HCV-related hepatocellular carcinoma development. These findings suggest that CDKN2A, CDK1, CCNB1, and TOP2A are promising candidates for diagnostic biomarkers and present a valuable opportunity for the early identification of HCV-HCC, which could lead to improved treatment outcomes.

Bioinformatics↗

PubMed2026

The Gabriella Miller Kids First Data Resource for genomic research in pediatric cancer and congenital anomalies.

Nine-year-old brain tumor patient Gabriella Miller challenged members of Congress to "stop talking and start doing" when providing federal funding for research into cures for pediatric cancer and congenital anomalies. Though she ultimately lost her life to that cancer, her advocacy efforts resulted in the 2014 Gabriella Miller Kids First Research Act, launching the Gabriella Miller Kids First Pediatric Research Program at the National Institutes of Health (NIH). The overarching goal of the Gabriella Miller Kids First Pediatric Research Program is to help researchers uncover new insights into the biology of childhood cancer and congenital anomalies. Following the signing of the Gabriella Miller Kids First Research Act 2.0 in January 2025, the program has been extended at NIH through 2028 to advance the groundwork laid in the program's first ten years. The Gabriella Miller Kids First Data Resource Center has since honored her legacy by building a comprehensive data resource for genomic research into pediatric conditions. Data from more than 30,000 participants annotated with demographic and clinical information related to their diagnoses have been released for secondary research and analysis using the center's web-based platforms. This paper analyzes the outcomes of the initiative and highlights breakthroughs made by the larger research community resulting from the availability of this data resource. We explore the future expansion of the data resource to include new modalities and tools for supporting life-saving research for children like Gabriella Miller.

Humans↗

PubMed2026

Decoding protein signatures and protein interactions in oral potentially malignant disorders: a systematic review and network analysis.

BACKGROUND: Proteomic profiling offers thorough insights into protein structure and function, as well as it acts as an essential approach for analyzing molecular changes at the tissue level. However, because of the proteome's diversity and dynamic nature, biomarker discovery remains challenging. By combining proteomics with bioinformatics, the level of understanding in relation to molecular interactions and disease processes can be improved. Through an integrative approach, few limitations can be addressed, thereby promoting proteomic profiling for the discovery of new therapeutic targets and novel biomarkers for a variety of disorders. AIM: To identify differentially expressed protein markers and their key molecular pathways associated with Oral Potentially Malignant Disorders. METHODS: Systematic Review was conducted following the PRISMA guidelines and the protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the registration ID number CRD42024557545. A comprehensive literature review was performed using electronic databases, yielding 12,797, studies from which 15 eligible articles were selected. The Newcastle-Ottawa Scale was used to assess the risk of bias. Vote counting was performed to identify proteins reported in more than one study. A bipartite network was constructed using Cytoscape to identify shared and disease-specific protein markers. Lesion-wise protein-protein interaction networks were generated using STRING and analysed in Cytoscape to identify highly interconnected hub proteins, and pathway enrichment analysis for these hubs was performed using Reactome. RESULTS: A total of fifteen studies (Leukoplakia (LK) - n = 1, Proliferative Verrucous Leukoplakia (PVL) - n = 2, Oral Submucous Fibrosis (OSMF) - n = 7, and Oral Lichen Planus (OLP) - n = 5) were included. The Newcastle-Ottawa Scale was used to evaluate methodological quality and the quality of studies included in this systematic review was high for 4 articles and moderate in the remaining 11. The most commonly employed technique was mass spectrometry. A total of 318 candidate proteins (LK - 14, PVL - 82, OSMF - 172, and OLP - 50) were identified across the oral potentially malignant disorders. Key markers identified through vote counting included ERO1A, NUCB1, RHOA, and IL36A for PVL; LUM, KRT1, KRT9, ALB, and VIM for OSMF; and ALB, LYZ, HP, HBB, and AMY1A for OLP. The bipartite network showed that OSMF and OLP shared the highest number of proteins, indicating the strongest overlap among lesions. Network analysis further highlighted distinct hub proteins for each lesion: for LK- AMY1A, AMY1B and APOA1; for PVL- CFL1, RHOA and CDC42; for OSMF- HSP90AA1, ENO1 and SERPINA1; and for OLP- HP, B2M, and ORM1. Lesion-specific pathway enrichment revealed that LK was associated with epithelial differentiation, PVL with oncogenic signaling, OSMF with stress-driven fibrosis, and OLP with immune-mediated inflammation. CONCLUSIONS: Proteomic expression offers insights into disease pathogenesis by identifying important molecular changes across OPMDs. However, the majority of biomarkers are still in the exploratory stage due to the considerable variation in lesion types, sample sources, proteomic techniques, and reporting systems. In order to create reliable and clinically applicable biomarkers, future studies should concentrate on combining multi-omics techniques with large-scale, standardized cohorts.

Humans↗