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PubMed2006

The identification of human tumour antigens: Current status and future developments.

The biggest challenge facing us today in cancer control and prevention is the identification of novel biomarkers for detection and improved therapeutic interventions to reduce mortality and morbidity rates. Biomarkers are important indicators to inform us of the physiological state of the cell at a specific time. It is now clear that malignant transformation occurs by changes in cellular DNA and protein expression with subsequent clonal proliferation of the altered cells. The affected genes and their expressed protein products or biomarkers are those involved in the normal growth and maintenance of the cancerous cells. These biomarkers could prove pivotal for the identification of early cancer and people at risk of developing cancer. Altered proteins or changes in gene expression in malignant cells may lead to the expression of tumour antigens recognised by host immune system. In this review we discuss current research into the molecular technologies making possible the global genomic-wide analysis of changes in DNA (genotyping), RNA expression (transcriptomics) and protein expression (proteomics) that have accelerated the rate of new biomarker/tumour antigen discovery. To gain a comprehensive understanding of the physiology and pathophysiology of cancer an approach that harmoniously integrates the various 'omic' platforms are key to unraveling the complexity 'needle-in-a-haystack' quality of biomarker/tumour antigen discovery.

Antigens, Neoplasm↗
PubMed2026

Integrated transcriptomic and metabolomic analysis reveals candidate regulatory networks associated with starch accumulation in tetraploid potato.

Potato (Solanum tuberosum L.) tuber starch is a major determinant of crop quality and industrial value, yet the regulatory mechanisms underlying starch accumulation in autotetraploid cultivars remain poorly resolved. Here, we performed integrated transcriptomic and metabolomic analyses using a segregating tetraploid population derived from parents with contrasting starch content. Extreme phenotypes were selected to systematically dissect the molecular basis of starch accumulation. Transcriptome profiling revealed extensive transcriptional reprogramming between high- and low-starch genotypes, with differentially expressed genes significantly enriched in carbohydrate metabolism, particularly the starch and sucrose metabolism pathway. Notably, multiple transcription factor families, including AP2/ERF, MYB, and bHLH, were prominently represented, suggesting coordinated regulatory control. Metabolomic analysis identified substantial metabolic divergence, with differentially accumulated metabolites predominantly enriched in starch and sucrose metabolism as well as secondary metabolic pathways. Most metabolites exhibited negative associations with starch content, indicating competitive carbon allocation between primary and secondary metabolism. Integrative multi-omics analysis further resolved a core regulatory module comprising key structural genes and transcription factors tightly associated with starch-related metabolites. In particular, genes involved in sucrose cleavage and ADP-glucose metabolism, together with trehalose-6-phosphate synthase (TPS) and UDP-glucose-associated pathways, emerged as critical nodes linking carbon flux to starch biosynthesis. Correlation network analysis suggested that AP2/ERF-, MYB-, and bHLH-type transcription factors modulate these pathways by coordinating structural gene expression and metabolic flux distribution. Collectively, our study establishes a transcriptional-metabolic framework for starch accumulation in tetraploid potato, highlighting the central role of carbon allocation and signaling intermediates in shaping starch content, and providing candidate targets for molecular breeding and genome editing.

Solanum tuberosum↗
PubMed2026

Circulating Biomarkers Related to Mitral Valve Prolapse: Current Evidence and Mechanistic Perspective.

PURPOSE OF REVIEW: Although imaging remains central to diagnosis and risk stratification, circulating biomarkers provide complementary information reflecting myocardial stress, fibrosis, extracellular matrix remodeling, inflammation, and metabolic dysregulation. The purpose of this review is to critically evaluate current and emerging circulating biomarkers in MVP and to assess whether these biomarkers may improve individualized management of this disease. RECENT FINDINGS: Natriuretic peptides are the most validated biomarkers in MVP, consistently predicting adverse outcomes and providing complementary prognostic information that may help inform the timing of surgical intervention, particularly in asymptomatic patients with significant mitral regurgitation. In contrast, evidence supporting fibrosis and inflammation mediators, proteomics, metabolomics, and circulating microRNAs remains emerging. In arrhythmic MVP, no circulating biomarker is currently recommended for routine risk stratification. Future research should prioritize phenotype-specific MVP registries, biomarker-CMR integration, multi-omics profiling, and biomarker-guided interventional trials.

Humans↗
PubMed2026

Integrative Genomic and Transcriptomic Insights into High-Altitude Adaptation in Changthangi Goats.

The Changthangi goat, native to the high-altitude Ladakh Plateau in northern India, thrives in oxygen-deficient environments above 4,000 m. This study investigated the genetic basis of high-altitude adaptation in Changthangi goats by integrating comparative genomics and transcriptomics, using the tropical lowland Jamunapari goat as a comparative model. Whole-genome sequence data from 15 individuals per breed were analyzed using complementary selection sweep metrics, including nucleotide diversity, Tajima's D, iHS, CLR, XP-EHH, and FST. These analyses identified candidate genomic regions under strong selective pressure, encompassing genes involved in hypoxia sensing (HIF-1α, HIF-2α/EPAS1, EGLN1), angiogenesis (VEGFA, AGGF1, ZEB1), cardiovascular regulation (PRKCB, ESR1, RYR2), mitochondrial and energy metabolism (ACADSB, ACSS3, ACSL1), cellular stress tolerance (BCL2, ATM), and thermogenesis (UCP1, FGF21). Unlike previous caprine studies that primarily infer hypoxia adaptation from genomic signals alone, our study integrates cardiac transcriptomics to demonstrate that genomic selection in Changthangi goats is accompanied by coordinated transcriptional remodeling across interconnected physiological systems in a physiologically relevant tissue. Comparative cardiac transcriptomic profiling revealed concordant expression divergence in genes associated with oxygen transport, vascular remodeling, mitochondrial function, substrate utilization, redox balance, and genome maintenance. This integrative multi-omics framework provides a mechanistic view of caprine high-altitude adaptation and highlights the value of combining genomic selection analyses with tissue-specific transcriptional profiling to resolve complex adaptive traits.

Animals↗
PubMed2025

Oncogenic EME1 promotes tumor progression and immune modulation in human cancers with therapeutic targeting potential.

BACKGROUND: EME1, a critical DNA repair endonuclease, has emerged as a potential oncogene implicated in genome instability and cancer progression. However, its pan-cancer roles, prognostic significance, immune interactions, and therapeutic targeting remain underexplored. METHODS: We conducted a comprehensive pan-cancer analysis integrating multi-omics data from public databases, including TIMER2.0, GEPIA2, TISIDB, and cBioPortal, to evaluate EME1 expression, genetic alterations, and their association with clinical outcomes, immune infiltration, and molecular pathways. Virtual screening of 3180 FDA-approved drugs and molecular dynamics (MD) simulations were employed to identify and validate potential EME1 inhibitors. RESULTS: EME1 was significantly overexpressed in various human cancers and positively associated with advanced tumor grade and stage. High EME1 expression and mutations were linked to poor overall and disease-free survival. Immunogenomic profiling revealed strong positive correlations between EME1 and myeloid-derived suppressor cells (MDSCs), alongside a negative association with endothelial cell function, suggesting immunosuppressive roles. Machine learning models based on EME1-associated genes demonstrated high predictive accuracy for liver hepatocellular carcinoma (AUC > 0.90). Virtual screening identified eight promising drug candidates, including Everolimus and Dioscin, with strong binding affinities. MD simulations confirmed the stability of these interactions, particularly for Dioscin. CONCLUSION: This study reveals the multifaceted oncogenic roles of EME1 in tumor progression, immune evasion, and prognosis. It proposes EME1 as a promising biomarker and therapeutic target across multiple cancer types. The identified drug candidates warrant further in vitro and in vivo validation for potential repurposing in EME1-targeted cancer therapy.

EME1↗
PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗
PubMed2026

Molecular mechanisms of plant thermal response: from signal transduction and epigenetic regulation to signaling integration.

Global warming intensification elevates heat stress to one of the major threats to crop productivity. This review synthesizes recent advances in understanding the mechanisms governing plant responses to both moderate and acute heat stress, with a focus on the integration of epigenetic regulation and signaling networks that underpin thermal adaptation. This review highlights how transcription factors PHYTOCHROME-INTERACTING FACTOR 4 (PIF4, during thermomorphogenesis) and HEAT SHOCK FACTOR A1s (HSFA1s, in heat shock responses) orchestrate plant adaptive growth through crosstalk among light, circadian, and hormone signaling pathways. Importantly, epigenetic mechanisms, including histone variant H2A.Z dynamics and histone modification reprogramming, function as central regulators of thermal plasticity. Key among these processes are HSFA2-mediated chromatin remodeling and small interfering RNA (siRNA)-dependent control of transgenerational thermomemory. Despite this progress, fundamental questions persist regarding temperature sensing, HSFA1s activation dynamics, and stress signal integration. Multi-omics and synthetic biology approaches are proposed to be pivotal in deciphering conserved principles of plant thermal resilience, ultimately providing a theoretical foundation and molecular breeding strategies for climate-smart crops.

Epigenesis, Genetic↗
PubMed2026

Prdm15 deficiency perturbs hematopoietic stem and progenitor cell homeostasis.

The maintenance of homeostasis in hematopoietic stem and progenitor cells (HSPCs) is essential for the proper development of the entire hematopoietic system. However, the mechanisms underlying this regulatory equilibrium remain elusive. Here, we report that Prdm15 deficiency in HSPCs induces the accumulation of immature hematopoietic stem cells in mice. A series of transplantation assays shows that these cells display impaired reconstitution capacity and competitive fitness, which are associated with abnormal differentiation trajectories and transcriptional alterations identified by single-cell RNA sequencing. Mechanistically, integrated multi-omics analyses including ATAC-seq and CUT&Tag sequencing of HSPCs indicate that Prdm15 deficiency induces significant transcriptional and epigenetic alterations, particularly affecting the methyltransferase KMT2C and altering H3K4me1 and H3K27ac modifications at the promoters of hematopoietic developmental genes. Collectively, our findings establish PRDM15 as a critical epigenetic regulator of HSPCs, offering valuable insights into the molecular mechanisms underlying hematopoietic homeostasis.

Cell differentiation↗
PubMed2026

Sec and Tat Mediated Secretion Safeguards Mycobacterium tuberculosis Membrane Homeostasis.

Protein secretion is essential for the growth and virulence of Mycobacterium tuberculosis, yet the organization and function of its secretion pathways remain poorly understood. We reviewed the existing literature, combined it with systematic queries, and finalized annotations based on experimental data and computational predictions to compile a curated list of 92 secretory components and 198 reactions involved in Sec, twin-arginine translocation (Tat), and ESX pathways. Using CRISPRi, targeted depletion of SecA1 or TatAC impaired both in vitro growth and ex vivo survival. Label-free quantitative secretome analysis revealed decreased export of substrates dependent on SecA1 and TatAC, with enrichment of cytosolic proteins in culture filtrates, indicating increased membrane dysbiosis. Membrane proteomics showed elevated levels of proteins engaged in intermediary and lipid metabolism, while proteins associated with the cell wall and cell processes decreased, suggesting weakened membrane integrity. Loss of SecA1 or TatAC increased membrane permeability, with the effect being more pronounced in the case of TatAC, and caused structural abnormalities seen under electron microscopy. Overall, our integrated multi-omics and functional genetics studies demonstrate that the SecA1 and Tat pathways are essential for maintaining membrane homeostasis in Mycobacterium tuberculosis. These results suggest that essential secretory proteins may be promising targets for therapeutic intervention.

Mycobacterium tuberculosis↗
PubMed2025

Using Large Genomic Biobanks to Generate Insights into Genetic Kidney Disease.

Chronic kidney disease (CKD) affects approximately 9% of the global population, leading to increased risks of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and mortality. Patients with CKD are a huge burden on health care resources globally. CKD is a complex condition influenced by a combination of genetic, environmental, and traditional risk factors. Family studies have suggested heritability rates for CKD ranging from 30% to 75%, and large genomic biobank studies have proven essential in identifying genes with substantial effects on CKD risk and in capturing cumulative genetic risk through polygenic risk scores. These biobanks are crucial for discovering new genes associated with kidney health and disease, and their growing size enhances the power to detect novel genetic associations. Integrating multi-omics technologies such as transcriptomics, metabolomics, and proteomics further enriches our understanding of CKD, while advanced computational tools continue to expand our insights into genetic data. Polygenic risk scores, derived from hundreds of genetic variants with small effect sizes, can help identify individuals at high risk of CKD. Genomic biobanks offer valuable opportunities for early identification and personalized treatment of monogenic kidney disorders, such as autosomal dominant polycystic kidney disease and Alport syndrome. These biobanks help fill knowledge gaps, particularly in individuals with milder or asymptomatic presentations who are often underrepresented in traditional studies. Expanding genomic biobank efforts globally, especially in diverse populations, is vital to enhancing our understanding of the genetic underpinnings of kidney disease. This review highlights the significant contributions of genomic biobanks to advancing our comprehension of the genetics of CKD.

Humans↗
PubMed2026

Phytolacca acinosa Roxb. induces intestinal toxicity through the histamine-MLCK-tight junction axis: Integrated evidence from proteomics, metabolomics, intestinal organoids and epithelial barrier validation.

Phytolacca acinosa Roxb. (PR) is a saponin-rich medicinal plant associated with gastrointestinal toxicity, but the mechanisms underlying PR-induced intestinal barrier injury remain unclear. In this study, raw PR extract was analytically characterized by UPLC-ZenoTOF-MS/MS, confirming triterpenoid saponins as the predominant constituents. C57BL/6 J mice were orally exposed to characterized PR extract (1.20 or 12.0 g/kg for 5 h), and Caco-2 cells and mouse intestinal organoids were used to assess epithelial toxicity and barrier disruption. Histopathology, ELISA, FITC-dextran permeability assays, immunofluorescence, CCK-8, LDH release, western blotting, DIA-based proteomics and untargeted metabolomics were integrated to define toxicological mechanisms. PR induced dose-dependent intestinal inflammation and barrier dysfunction, with the ileum as the most sensitive target. PR increased serum DAO and D-lactate and intestinal TNF-α and IL-1β, disrupted organoid morphology, enhanced epithelial permeability, and reduced ZO-1 expression. Proteomics revealed changes in inflammatory, lipid-metabolic, cytoskeletal and tight-junction pathways, including upregulation of MLCK3 and phospholipase-related proteins and downregulation of ZO-1 and ZO-2. Metabolomics identified histidine metabolism disturbance and histamine accumulation. Integrated multi-omics and pharmacological validation indicated that histamine activated the PLC/IP₃/Ca²⁺/CaM/MLCK cascade, promoting MLC phosphorylation, tight-junction disassembly and epithelial leakiness. MLCK inhibition partially restored ZO-1/ZO-2 expression and attenuated PR-induced epithelial injury. These findings identify the histamine-MLCK-tight junction axis as a key mechanism of PR-induced intestinal toxicity and support hazard identification of saponin-rich PR exposure.

Animals↗
PubMed2026

Elucidating shared genetic signals between type 2 diabetes and three neurodegenerative dementia phenotypes.

Type 2 diabetes (T2D) and dementia frequently co-occur, yet the biological mechanisms underlying this comorbidity remain incompletely understood. Here, we systematically investigate shared genetic signals between T2D and three forms of neurodegenerative dementia (Alzheimer disease, Lewy body dementia, and sporadic frontotemporal dementia) using large-scale genome-wide association studies of clinically diagnosed individuals. We identify five genomic regions harboring shared association signals between T2D and at least one dementia subtype. Among these, the APOE locus was common to all dementia subtypes, whereas the remaining four loci (GBA, CRY2/PEX16/MAPK8IP1, INO80E, and NSF) were each shared exclusively between T2D and one dementia subtype. Integrating multi-omics data across several disease-relevant tissues and orthogonal lines of functional evidence, we prioritize 26 candidate genes through which these shared genetic loci potentially mediate their effect. Pathway enrichment highlights lipid and lipoprotein regulatory biology as a central shared axis. Mendelian randomization analyses using genetically regulated gene expression in relevant tissues indicate pleiotropic mechanisms with divergent phenotypic consequences. Our findings identify shared genetic loci between T2D and neurodegenerative dementia, revealing systemic metabolic-neurodegenerative trade-offs and highlighting key genes that underpin the comorbidity, providing a framework for improved understanding of age-related multi-morbidity.

Alzheimer disease↗
PubMed2005

Assessment and integration of publicly available SAGE, cDNA microarray, and oligonucleotide microarray expression data for global coexpression analyses.

Large amounts of gene expression data from several different technologies are becoming available to the scientific community. A common practice is to use these data to calculate global gene coexpression for validation or integration of other "omic" data. To assess the utility of publicly available datasets for this purpose we have analyzed Homo sapiens data from 1202 cDNA microarray experiments, 242 SAGE libraries, and 667 Affymetrix oligonucleotide microarray experiments. The three datasets compared demonstrate significant but low levels of global concordance (rc<0.11). Assessment against Gene Ontology (GO) revealed that all three platforms identify more coexpressed gene pairs with common biological processes than expected by chance. As the Pearson correlation for a gene pair increased it was more likely to be confirmed by GO. The Affymetrix dataset performed best individually with gene pairs of correlation 0.9-1.0 confirmed by GO in 74% of cases. However, in all cases, gene pairs confirmed by multiple platforms were more likely to be confirmed by GO. We show that combining results from different expression platforms increases reliability of coexpression. A comparison with other recently published coexpression studies found similar results in terms of performance against GO but with each method producing distinctly different gene pair lists.

Gene Expression Profiling↗
PubMed2026

Unlocking the Circulating Proteome: Toward Clinical Translation.

Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Humans↗
PubMed2026

Intratumoral Mycobacterium abscessus promotes cytidine deaminase mutagenesis in non-small cell lung cancer.

The intratumoral microbiota is increasingly recognized as an active component of the tumor microenvironment, yet whether it directly drives tumor mutagenesis remains unclear. Here, integrated multi-omics analysis of human non-small cell lung cancer (NSCLC) identifies Mycobacterium abscessus as a microbial determinant of APOBEC3A-associated mutagenesis. Mechanistically, the bacterial effector nucleoside diphosphate kinase (NDK) directly targets the host transcription factor IRF3 and installs a non-canonical 1-phosphohistidine modification at H263, thereby amplifying type I interferon signaling and sustaining APOBEC3A expression. This inter-kingdom phosphotransfer event links intratumoral microbial colonization to an endogenous mutational process that promotes genomic diversification. Genetic inactivation of NDK, or pharmacologic elimination using an engineered NDK-PROTAC, suppresses APOBEC3A activation and attenuates microbe driven mutagenesis. Together, these findings establish a direct microbial effector mechanism that promotes APOBEC3A-associated mutagenesis and provide a therapeutic framework to intercept microbiome driven mutagenesis in NSCLC.

Humans↗
PubMed2026

Methyltransferase METTL1 regulates MSC mRNA stability via m7G modification in acute pancreatitis.

Acute pancreatitis (AP) is a serious inflammatory disease with significant morbidity, yet its underlying molecular mechanisms remain incompletely understood. This study reveals a novel epitranscriptomic pathway in AP pathogenesis centered on METTL1-mediated N7-methylguanosine (m7G) RNA modification. We found that METTL1 expression and global m7G levels were significantly elevated in serum from AP patients, pancreatic tissues of sodium taurocholate-induced AP mice, and in vitro models of LPS-polarized macrophages and STC-injured pancreatic acinar cells. Through integrated multi-omics analysis combining m7G methylome mapping and transcriptome profiling, we identified Musculin (MSC) as a key target whose mRNA stability is enhanced by METTL1-mediated m7G modification. Functional experiments demonstrated that MSC upregulation activates TNF signaling through phosphorylation of NF-&#x3ba;B, JNK, and MAPK proteins, thereby promoting macrophage M1 polarization and pancreatic acinar cell injury. The pathological significance of this pathway was confirmed in vivo, where pancreas-targeted knockdown of Mettl1 significantly attenuated AP severity. Furthermore, mechanistic studies using a catalytic-dead METTL1 mutant established that both the methyltransferase activity of METTL1 and subsequent TNF signaling activation are essential for driving inflammatory responses. Our findings delineate a previously unrecognized METTL1-m7G-MSC-TNF signaling axis that promotes AP progression, highlighting the therapeutic potential of targeting METTL1-mediated epitranscriptomic modification in inflammatory diseases.

Animals↗
PubMed2026

CpG hypermethylation and WNT/AP-1 cooperativity define the epigenetic landscape and a clinical subgroup of high-risk pediatric adrenocortical carcinoma.

Pediatric adrenocortical tumors are rare, clinically heterogeneous neoplasms with unpredictable outcomes and limited treatment options. Through integrated multi-omic analysis of 214 pediatric adrenocortical tumors combining DNA methylation profiling, transcriptomics, chromatin accessibility, and spatial deconvolution, we identify four distinct risk groups. A high-risk subgroup is characterized by CpG island hypermethylation, chromosomal instability, and dismal survival. These tumors exhibit transcriptional co-activation of WNT signalling and activator protein-1 transcriptional programs and display balanced admixture of zona glomerulosa and zona fasciculata/reticularis-like cells. Spatial analysis reveals zona glomerulosa cells as WNT signaling hubs driving intercellular crosstalk. Mechanistically, the histone deacetylase inhibitor entinostat reverses promoter methylation, silences activator protein-1 activity, and induces apoptotic reprogramming in tumor models. These findings establish a molecular framework for risk stratification and identify actionable therapeutic vulnerabilities, providing an essential resource for studying this molecularly uncharted pediatric malignancy.

Humans↗
PubMed2026

AI proteomics: from protein identification to virtual cells.

Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and protein complexes; advancing spatial and perturbation proteomics; integrating multi-omics data; and, ultimately, enabling AI virtual cells. Finally, we call for global collaboration among data producers, data consumers and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics, laying the foundation for transformative advancements in proteomics driven by AI.

Proteomics↗