Mol Divers. 2026 Apr 12. doi: 10.1007/s11030-026-11545-y. Online ahead of print.

NO ABSTRACT

PMID:41966666 | DOI:10.1007/s11030-026-11545-y

Metabolism. 2026 Apr 8:156607. doi: 10.1016/j.metabol.2026.156607. Online ahead of print.

ABSTRACT

Endoplasmic reticulum (ER) stress is a critical driver of pancreatic β-cell dysfunction and apoptosis. Although metformin, a drug used to treat type 2 diabetes, primarily decreases blood glucose levels by improving insulin sensitivity, its direct effects on β-cell survival remain unclear. Here, we investigated the effect of metformin on β-cell stress responses under ER stress conditions. Thapsigargin (Tg)-induced ER stress increased β-cell apoptosis in mouse islets, which was prevented by metformin in a dose-dependent manner. Treatment with metformin for 24 h suppressed the Tg-induced upregulation of unfolded protein response (UPR)-related genes, as confirmed by transcriptomic and pathway analyses. Quantitative proteomics revealed that Tg inhibited eIF2 signaling and protein translation, both of which were partially restored by metformin. Enrichment analysis further indicated the attenuation of apoptotic pathways in metformin-treated islets. Polysome profiling and puromycin incorporation assays demonstrated that metformin reduced protein translation independently of ER stress. Metformin promoted the dephosphorylation of 4E-BP1, a key initiator of cap-dependent protein translation that is activated by phosphorylation, and the antiapoptotic effect of metformin was abolished by 4E-BP1 knockdown in MIN6 cells. Phosphoproteomic analysis indicated that the activation of mTOR signaling, a kinase of 4E-BP1, in Tg-treated islets was mitigated by metformin. Taken together, these findings reveal a cytoprotective mechanism of metformin in β-cells, in which metformin suppresses ER stress-induced apoptosis through 4E-BP1-mediated inhibition of mRNA translation and modulation of mTOR signaling. This study highlights a β-cell-intrinsic action of metformin that may contribute to its long-term therapeutic benefits in diabetes management.

PMID:41962652 | DOI:10.1016/j.metabol.2026.156607

bioRxiv [Preprint]. 2026 Mar 11:2026.03.09.710586. doi: 10.64898/2026.03.09.710586.

ABSTRACT

The lack of accurate, human-based models recapitulating early-stage pancreatic ductal adenocarcinoma (PDAC) has hindered therapeutic development. Using pluripotent stem cell-derived pancreatic progenitor organoids, we established a human PDAC model that faithfully reproduces the genetic, epigenetic, and transcriptomic trajectory of tumor initiation and progression in vitro , validated against clinical datasets and histopathology. We demonstrate that CDKN2A loss, nearly universal in patients but dispensable in mouse models, is essential for neoplastic transformation when combined with KRAS and TP53 mutations, while SMAD4 loss promotes tumor progression. Multi-omics profiling reveals epigenetic repression of pancreatic lineage program during PDAC initiation, alongside oncogenic AP-1-driven chromatin remodeling. Notably, we identify TET1 suppression as a mechanistic link between oncogenic ERK signaling and the hypermethylation and silencing of essential pancreatic transcription factors. This model captures the genetic and epigenetic determinants of human PDAC, reveals antagonism between oncogenic and lineage restriction programs, and supports TET-based lineage restoration as a promising early intervention strategy for high-risk individuals.

PMID:41959451 | PMC:PMC13060829 | DOI:10.64898/2026.03.09.710586

bioRxiv [Preprint]. 2026 Mar 12:2026.03.10.710185. doi: 10.64898/2026.03.10.710185.

ABSTRACT

KRAS is mutated in over 90% of pancreatic ductal adenocarcinomas (PDAC), where hotspot alterations in codons 12, 13, and 61 drive tumor initiation and progression. Although distinct biochemical properties have been described for individual KRAS mutants, whether they generate unique allele-specific signaling programs in PDAC cells remains unresolved. Here, we systematically interrogated the molecular consequences of seven common KRAS mutant variants in reconstituted isogenic, KRAS-deficient PDAC cell lines by integrated transcriptomic, proteomic, and phosphoproteomic profiling. We found that baseline cellular state, rather than allele identity, was the predominant driver of molecular variation. Comparisons with established KRAS reference signatures revealed significant but moderate overlap at the mRNA level and less so at the proteome level. Pathway analyses highlighted interferon response and mitochondrial translation as recurrently altered across alleles, while phosphoproteomic data confirmed robust ERK1/2 activity and suppression of DYRK kinase substrates by mutant KRAS expression. Importantly, no robust allele-specific molecular programs were identified. Together, our study establishes a comprehensive multi-omics resource for KRAS signaling in PDAC and demonstrates that cellular context exerts a stronger influence than allele identity in shaping molecular profiles, with implications for interpreting putative allele-specific signaling dependencies and therapeutic vulnerabilities.

PMID:41959224 | PMC:PMC13060958 | DOI:10.64898/2026.03.10.710185

BioData Min. 2026 Apr 9. doi: 10.1186/s13040-026-00546-0. Online ahead of print.

NO ABSTRACT

PMID:41957754 | DOI:10.1186/s13040-026-00546-0

Hum Mutat. 2026 Apr 6;2026:8027584. doi: 10.1155/humu/8027584. eCollection 2026.

ABSTRACT

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is characterized by a complex tumor microenvironment and poor prognosis, yet the roles of specific tumor-associated macrophages (TAMs) subpopulations in driving disease progression remain elusive.

METHODS: This study evaluated the prognostic relevance of FCGR2B in HGSOC. Single-cell RNA sequencing identified FCGR2B ⁺ TAMs as a distinct macrophage subpopulation with unique transcriptional features. Integrative analyses combining single-cell and bulk differentially expressed genes, macrophage-associated modules, and ferroptosis-related gene sets identified 26 candidate prognostic genes, from which a four-gene signature (CRYAB, PLAUR, EREG, and C5AR1) was derived to construct the prognostic risk model. The model was validated in an independent cohort. Immune infiltration, single-cell trajectory, copy number variation, and drug-gene associations were analyzed to explore the molecular and therapeutic implications of risk stratification.

RESULTS: HGSOC patients classified as high risk exhibited poorer survival outcomes, increased infiltration of M2-like macrophages, elevated expression of immune checkpoints, and enrichment of immune- and ferroptosis-related pathways. Trajectory and copy number variation analyses revealed stage-specific gene expression patterns and amplification-associated regulation. Drug-gene association analyses further suggested that high-risk patients may be more responsive to targeted therapies and proteasome inhibitors, whereas low-risk patients may benefit from conventional chemotherapy.

CONCLUSION: FCGR2B ⁺ TAMs are closely linked to HGSOC progression, and the proposed prognostic model based on FCGR2B ⁺ TAMs provides predictive value and potential therapeutic insights for patient stratification.

PMID:41953398 | PMC:PMC13054137 | DOI:10.1155/humu/8027584

JHEP Rep. 2026 Feb 18;8(5):101790. doi: 10.1016/j.jhepr.2026.101790. Online ahead of print.

ABSTRACT

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) exhibits diverse aetiologies and molecular heterogeneity, with a median 5-year overall survival of <70% due to high recurrence rates following curative-intent surgery. This study investigated the complex tumour microenvironment (TME) in HCC and explored interactions between various cell types and their roles in disease recurrence.

METHODS: Using a multi-omics approach on multi-region samples of surgically resected HCC from the PLANet 1.0 cohort (NCT03267641), we performed spatial transcriptomics on 17 tissue samples from four patients and bulk RNA sequencing on 329 sectors from 90 patients. Findings were validated using immunofluorescence and multiplex immunohistochemistry.

RESULTS: Our analysis revealed extensive intra- and intertumour gene expression heterogeneity and identified a specific subset of endothelial cells (ECs), INTS6⁺ ECs, enriched and spatially colocalised with tumour cells in primary tumours from patients with recurrence (p = 0.021, n = 49). A significant ANGPTL4-SDC1 ligand-receptor interaction was identified between INTS6⁺ ECs and tumour cells. Notably, INTS6⁺ ECs were enriched in microvascular invasion regions and spatially colocalised with tumour cells in patients with recurrence (p = 0.036, n = 53). These findings highlight endothelial-tumour cell interactions within the TME as potential therapeutic targets.

CONCLUSIONS: INTS6⁺ ECs are enriched in microvascular invasion regions and spatially colocalised with tumour cells in recurrent HCC, suggesting a potential role in disease recurrence and representing a promising therapeutic target within the TME.

IMPACT AND IMPLICATIONS: The spatial co-localisation of cell types plays a significant role in the recurrence of hepatocellular carcinoma. In this study, we have pinpointed a particular group of endothelial cells, known as INTS6+ endothelial cells, which are spatially colocalised with tumour cells and enriched in microvascular invasion regions in patients experiencing recurrence. These discoveries highlight novel therapeutic targets that focus on endothelial cell interactions within the tumour microenvironment to prevent recurrence and enhance overall patient survival.

PMID:41950768 | DOI:10.1016/j.jhepr.2026.101790

Ann Afr Med. 2026 Apr 8. doi: 10.4103/aam.aam_24_26. Online ahead of print.

ABSTRACT

Acute pancreatitis (AP) is an inflammatory disorder of the pancreas with clinical manifestations that range from mild, self-limited disease to severe necrotizing inflammation complicated by organ failure and significant mortality. Accurate early assessment of disease severity remains challenging, as clinical presentation at admission often does not reflect the underlying inflammatory burden or risk of progression. Biomarkers have therefore gained increasing importance as objective tools that support diagnosis, severity stratification, and prediction of complications in AP. Traditional enzymatic markers, including serum amylase and lipase, are widely used for diagnostic confirmation but show limited value in predicting outcomes. In contrast, biomarkers reflecting systemic inflammation, immune activation, and infection provide more meaningful prognostic information. These include acute-phase reactants, cytokines, and infection-associated markers such as procalcitonin. In recent years, advances in molecular and omics-based technologies have led to the identification of novel biomarkers, including pentraxin-3, microRNAs, and proteomic and metabolomic signatures, which offer earlier insight into disease progression and pathophysiological mechanisms. This review synthesizes current evidence on established and emerging biomarkers of AP, evaluates their clinical relevance and limitations, and discusses future perspectives for integrated biomarker-based approaches aimed at improving early risk assessment and individualized patient management.

PMID:41947359 | DOI:10.4103/aam.aam_24_26

Front Immunol. 2026 Mar 19;17:1686658. doi: 10.3389/fimmu.2026.1686658. eCollection 2026.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) remains an intractable cancer marked by delayed diagnosis, rapid progression, and significant resistance to current treatments. Conventional biomarkers, such as CA19-9, have insufficient sensitivity and specificity. Meanwhile, the practical use of newer markers such as the tumor mutational burden and microsatellite instability is limited by the absence of standardized testing protocols and definitive threshold values. Circulating tumor DNA and exosomal miRNA hold promise for continuously tracking tumor dynamics and effectiveness of immunotherapy, but additional validation is necessary before their routine clinical application. Recent advancements in multiomics, nanotechnology, and artificial intelligence have opened new possibilities for more accurate and comprehensive biomarkers. For instance, Shah et al. developed shortwave-infrared-emitting nanoprobes to specifically target CD8⁺ cytotoxic T cells, permitting high-sensitivity in vivo imaging in breast cancer models. Batool et al. utilized nanoplasmonic sensors to detect changes in serum programmed death-ligand 1 and cytokine levels within 1-2 weeks post-treatment, achieving picomolar sensitivity. Chang et al. combined fluorescence and photoacoustic imaging in the NanoTrackThera platform, facilitating the real-time monitoring of immunotherapy efficacy. This review highlights the evolution of PDAC biomarkers from traditional markers to multimodal integration and dynamic monitoring. The limitations of current markers and potential of emerging technologies, including metabolic reprogramming markers, epigenetic regulators, and AI-driven predictive models, are discussed. Future directions include multicenter prospective trials to validate multimodal models, standardize detection methods, and increase interdisciplinary collaboration. By integrating genomic, epigenetic, metabolic, and microbiome data, these models can better capture the complexity of PDAC, thereby improving patient outcomes through precision immunotherapy.

PMID:41939911 | PMC:PMC13044031 | DOI:10.3389/fimmu.2026.1686658

Transl Oncol. 2026 Apr 3;67:102748. doi: 10.1016/j.tranon.2026.102748. Online ahead of print.

ABSTRACT

BACKGROUND: Epithelial ovarian cancer (EOC) encompasses five major histological subtypes with marked genetic, immunological, and clinical heterogeneity. While genome-wide association studies (GWAS) have identified subtype-specific risk loci, a critical gap remains in understanding how plasma proteins influence immune-cell traits and contribute to EOC pathogenesis.

METHODS: We integrated subtype-stratified GWAS data from two EOC cohorts with plasma proteomics and immune-cell traits to construct protein-immune-EOC regulatory landscapes using a three-stage Mendelian randomization framework. Single-cell RNA-seq and multiplex immunofluorescence were employed to delineate the cellular distribution and spatial context of causal proteins. Subsequent analyses characterized immune infiltration, macrophage polarization, and clinicopathological associations. Drug-gene correlations were used to identify potential therapeutic targets, and transcriptomic analyses were applied to delineate the underlying transcriptional landscape.

RESULTS: We identified 20 subtype-specific protein-immune-EOC regulatory axes, with FCGR2B emerging as a causal plasma protein in immune regulation and high-grade serous ovarian cancer (HGSOC) progression. FCGR2B was highly expressed in tumor-associated macrophages and was associated with an M2-like polarization phenotype. Functional characterization revealed that FCGR2B was associated with shorter progression-free survival and an immunosuppressive tumor microenvironment. Transcriptomic analyses revealed altered NF-κB signaling upon FCGR2B knockdown, and drug-response data suggested a potential association between high FCGR2B expression and sensitivity to NF-κB inhibitors.

CONCLUSIONS: These findings delineate subtype-specific genetically informed protein-immune regulatory landscapes in EOC and identify FCGR2B as a key immunoregulatory and prognostic biomarker in HGSOC, suggesting FCGR2B as a potential therapeutic vulnerability that warrants further investigation.

PMID:41934917 | DOI:10.1016/j.tranon.2026.102748

Adv Sci (Weinh). 2026 Apr 3:e17640. doi: 10.1002/advs.202517640. Online ahead of print.

ABSTRACT

The embryonic coelomic mesothelium acts as a critical progenitor hub during mammalian organogenesis, undergoing epithelial-to-mesenchymal transition (EMT) to drive vascular growth and parenchymal development in visceral organs. A prominent example is the epicardium, which plays an essential role during heart development. The principles of gene regulation in the coelomic mesothelium remain poorly defined. Specifically, it is unclear how cis-regulatory elements, including enhancers, orchestrate the spatiotemporal patterns of gene expression required for mesothelial identity and function. Here, a multi-omic approach was used to identify trans- and cis-regulatory elements that regulate mesothelial gene expression in three organs: heart, lung, and pancreas. This analysis uncovers a cardiac-specific regulatory circuit in which the transcription factor (TF) TBX20 selectively activates epicardial enhancers to orchestrate essential developmental programs. In contrast, TF MAF orchestrates pan-mesothelial gene expression via conserved CREs, which are absent in non-mesothelial lineages. Our integrated genomic analysis reveals MAF as a central custodian of mesothelial identity, a role underscored by its negative correlation with EMT, evolutionary conservation, and dynamic regulatory activity throughout development. Our work establishes a foundational blueprint of the gene regulatory landscape governing the coelomic mesothelium, defining both conserved principles and organ-specific mechanisms of spatiotemporal gene expression during early mammalian development.

PMID:41933934 | DOI:10.1002/advs.202517640

Eur J Cancer. 2026 Mar 24;239:116699. doi: 10.1016/j.ejca.2026.116699. Online ahead of print.

ABSTRACT

INTRODUCTION: The latest generation of liquid biopsies incorporates multi-omic features, including genomics, methylomics, and fragmentomics. Machine learning (ML) approaches have been proposed to synthesize these complex biological data for the development of diagnostic classifiers. This study aims to evaluate the integration of ML with circulating cell-free DNA (cfDNA) analysis for early cancer detection.

METHODS: Medline, Embase, Cochrane, and Web of Science were searched in July 2025. Eligible studies combined ML and cfDNA features to distinguish cancer patients (stages I-III) from non-cancer controls. Summary diagnostic performance metrics and their 95% confidence intervals (CI) were calculated.

RESULTS: The study included 109 articles permitting analyses for lung (n = 34), liver (n = 29), colorectal (n = 28), pancreatic (n = 16), breast (n = 17), esophageal (n = 12), ovarian (n = 13), gastric (n = 9), head and neck (n = 4), and mixed (n = 27) cancer types. Specificity was consistently high across all tumor types and stages (94%-99%). Sensitivity ranged from 72% to 92% for stage I-III, 44-91% for stage I, 71-98% for stage II and 83-99% for stage III. In the pooled study population, neural networks (90%, 95% CI: 81%-95%), random forest (86%, 95% CI: 77%-92%) and heterogeneous ensemble learning (85%, 95% CI: 79%-89%) demonstrated the highest sensitivity. The stratified analysis by classifier feature revealed 86% (95% CI: 80%-90%) sensitivity for fragmentation and 81% (95% CI: 76%-85%) for methylation, with 92%-96% specificity.

CONCLUSION: ML and cfDNA profiling show potential for early cancer detection, with ensemble methods, neural networks and random forests achieving the best overall performance. Fragmentomic features provide the highest sensitivity.

PMID:41930854 | DOI:10.1016/j.ejca.2026.116699

Front Immunol. 2026 Mar 18;17:1791707. doi: 10.3389/fimmu.2026.1791707. eCollection 2026.

ABSTRACT

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a complex tumor ecosystem that contributes to its progression. Deubiquitinases (DUBs) are vital regulators in cancer. However, the overall activity of DUBs and their role in driving PDAC progression within immune microenvironment remain largely unknown.

METHODS: We employed an integrative multi-omics strategy combining machine learning (ML) on bulk transcriptomic data, single-cell RNA sequencing and spatial transcriptomic profiling. We applied Coxnet and Fuzzy SVM for prognostic modeling, inferCNV for malignant cell identification, SCENIC for transcription factor regulon analysis, LIANA⁺ for inferring inter-cellular communication networks and cell2location for spatial deconvolution. USP54 expression was detected by real-time quantitative PCR, western blotting and immunohistochemistry. USP54 function was validated through in vitro and in vivo assays.

RESULTS: ML-based pathway analysis revealed post-translational modification as a major prognostic category, within which elevated DUBs activity emerged as an independent adverse prognostic factor. At the single-cell level, USP54 was upregulated along the trajectory of malignant ductal cells and correlated with an inflamed tumor microenvironment. Cell-cell communication analysis predicted signaling from monocytes/macrophages to tumor cells via the THBS1-integrin ligand-receptor pair. This immune-derived signaling potentially converged on KLF5-positive tumor cells, with KLF5 identified as a putative transcriptional activator of USP54. Spatial transcriptomics validated the co-localization of USP54 expression, elevated DUB activity, and KRAS signaling within specific tumor niches adjacent to THBS1-enriched immune regions. High USP54 expression was frequently observed in PDAC tissues and associated with poor patient survival. More importantly, in both BxPC-3 and PANC-1 cell lines, USP54 knockdown suppressed cell proliferation and metastasis, whereas its overexpression enhanced these malignant phenotypes. Subcutaneous xenograft growth and tail vein injection experiments validated these findings in vivo.

CONCLUSIONS: Our comprehensive multi-omics analysis and experimental validation identify the deubiquitinase USP54 as a novel promoter of PDAC progression within a spatially organized tumor-immune microenvironment. These findings suggest USP54 as both a candidate prognostic biomarker and a potential therapeutic target for this lethal malignancy.

PMID:41929495 | PMC:PMC13038871 | DOI:10.3389/fimmu.2026.1791707

Cell Rep Med. 2026 Mar 30:102708. doi: 10.1016/j.xcrm.2026.102708. Online ahead of print.

ABSTRACT

Intratumor heterogeneity (ITH) undermines transcriptome-based stratification in intrahepatic cholangiocarcinoma (iCCA). Here, we integrate multi-omics data from multi-region, single-region, and single-cell RNA sequencing cohorts to systematically characterize gene expression ITH. We uncover that immune and stromal heterogeneity are primary drivers of ITH, leading to misclassification of a median 27.8% of tumors by existing subtyping systems. To overcome this, we identify a low-intratumor-heterogeneity/high-intertumor-variability (LIHV) gene set and develop an ITH-insensitive classification system defining five subgroups: inflammatory (SI), metabolic (SII), atypical (SIII-1), immune-silent (SIII-2), and neurodegenerative (SIII-3). These subgroups exhibit distinct clinical outcomes, molecular features, immune landscapes, and therapeutic vulnerabilities. GPRC5A and VTCN1 serve as robust immunohistochemical biomarkers for SI and SIII tumors, while serum CEA and CA19-9 identify inflammatory iCCA. Therapeutically, HSP90 inhibition synergizes with anti-PD1 in inflammatory iCCA, whereas combined anti-PD1 and anti-TIM3 suppresses neurodegenerative iCCA. Collectively, our study provides a robust molecular framework and actionable therapeutic strategies for iCCA.

PMID:41916296 | DOI:10.1016/j.xcrm.2026.102708

Int J Gen Med. 2026 Mar 24;19:590621. doi: 10.2147/IJGM.S590621. eCollection 2026.

ABSTRACT

Inflammatory bowel disease (IBD) involves chronic intestinal inflammation driven by gut-brain axis imbalance, fostering complications through an "inflammation-neuro-coagulation" triad. Current staging systems inadequately capture the dynamics of this multidimensional network. Therefore, integrated multi-omics analyses-including metagenomics, metabolomics, and single-cell transcriptomics-are essential to construct dynamic models that monitor coagulation, microbiome, and metabolism for precise assessment of disease activity and thrombotic or bleeding risks. Interventions targeting gut-brain axis nodes, such as eliminating tissue factor-positive (TF⁺) T cells or modulating vagal activity, show potential to disrupt the inflammation-coagulation cycle, although rigorous randomized trials are still needed. Artificial intelligence (AI)-assisted systems that integrate real-time biomarker monitoring with multi-omics predictions represent a novel paradigm for managing IBD-related coagulation dysfunction. Key challenges include elucidating gut-brain-liver axis regulation of coagulation and characterizing platelet functional heterogeneity. Future efforts must prioritize ethically compliant multi-omics platforms and racially stratified risk models to advance personalized coagulation management in IBD.

PMID:41913906 | PMC:PMC13033200 | DOI:10.2147/IJGM.S590621