搜索结果：Translational cancer research

Post-translational modifications (PTMs) are crucial regulatory mechanisms that modulate the structure, function, and stability of proteins, playing an essential role in the regulation of cellular processes. Dysregulated PTMs are associated with various aspects of cancer development, including uncontrolled cell growth, evasion of apoptosis, metastasis, and drug resistance. This review offers a detailed examination of several major PTMs, including phosphorylation, acetylation, ubiquitination, SUMOylation, and methylation, discussing their distinct roles in cancer biology. It also provides an in-depth analysis of the latest advancements in the study of PTMs in cancer biology, focusing on the mechanisms by which these modifications contribute to tumorigenesis and their potential as therapeutic targets. It highlights the significant progress made in the identification of PTMs across different cancer types, emphasizing the role of PTMs in shaping cancer progression and immune modulation. Additionally, the paper discusses cutting-edge technologies, particularly mass spectrometry and computational proteomics, that have revolutionized the detection and characterization of PTMs. These advancements have enabled the identification of novel cancer biomarkers and therapeutic targets, offering new avenues for early detection, prognostic monitoring, and the development of targeted therapies in cancer treatment.

Cancer cells undergo intense metabolic reprogramming to provide fast proliferation, persistence, immune evasion, and resistance to therapy. Malignant cells often rely on exogenous lipids and maintaining strict metabolic regulation. Cancer cells stimulate de novo lipogenesis, lipid uptake, and storage pathways even in nutrient-limited microenvironments. This review combines current knowledge of cancer types, highlights vital enzymatic regulators and translational prospects. A comprehensive literature review was conducted, focusing on the complex relationship between lipid metabolic pathways and oncogenesis. This review focuses on de novo fatty acid synthesis, lipid uptake mechanisms, and cholesterol regulation in cancer. Important therapeutic targets, including Acetyl-CoA carboxylase (ACC), ATP citrate lyase (ACLY), fatty acid synthase (FASN), and sterol regulatory element-binding proteins (SREBPs) were evaluated. It also emphasizes the role in resistance to chemotherapy, radiotherapy, and specific targeted therapies. Several studies have revealed that dysregulated lipid metabolism contributes to tumour growth, immune evasion, and treatment resistance. Evidence from preclinical and clinical studies revealed that treatments targeting small-molecule inhibitors of FASN, ACLY, SREBPs and CD36, show promising outcomes. Alterations in lipid metabolic pathways serve as critical nodes in oncogenic networks and immune modulation. The inclusion of dietetaey modifications and nanoparticle-conjugated drug delivery provides encouraging results against tumour development. This review combines the roles of key regulators, therapeutic targets, and biomarker approaches that can update future therapies. However, challenges persist, including drug-induced toxicity, metabolic changes, and tumour heterogeneity.

Gemcitabine (Gem), a primary treatment for advanced and metastatic bladder cancer, can lead to malignant progression and drug resistance, though the underlying mechanisms are not fully understood. Post-translational modifications (PTMs) are key to understanding this resistance and identifying new chemosensitizers. To decipher the relationship between the PTM and Gem-induced chemotherapy resistance in bladder cancer, a Gem-resistant cell line was developed from Gem-sensitive cells through repeated exposure to the drug, revealing increased levels of acetylation and O-GlcNAcylation compared to the parent cells. Thereafter, considering the significant role of histone acetylation in gene regulation, the histone acetyltransferase inhibitor C646 was employed to inhibit growth of Gem-resistant bladder cancer cells. Intriguingly, C646 was found to prevent the progression of Gem-resistant bladder cancer not only by inhibiting acetylation but also O-GlcNAcylation modifications both in vitro and in vivo. Immunohistochemistry analysis of bladder cancer clinical specimens confirmed that both histone H3 lysine 27 acetylation (H3K27ac) and O-GlcNAc transferase (OGT) expression levels were elevated post-chemotherapy and positively correlated. Further, chromatin immunoprecipitation followed by quantitative reverse transcription polymerase chain reaction (ChIP-qPCR) demonstrated that H3K27ac influences OGT expression by binding to its promoter region. Additionally, C646 disrupted OGT-mediated O-GlcNAcylation by suppressing the acetylation of H3K27 and its accumulation on the OGT promoter, thereby inhibiting Gem-resistant bladder cancer growth. Consequently, targeting the H3K27ac/OGT axis with histone acetyltransferase inhibitor offers a promising strategy to overcome Gem resistance in bladder cancer.

Accurate detection of KRAS codon mutations is essential for precision oncology in colorectal cancer (CRC), yet conventional liquid biopsy methods often lack sufficient sensitivity for rare ctDNA variants, particularly in early diseases. We developed a three-dimensional (3D) plasmonic KRAS microarray integrating blocked recombinase polymerase amplification with plasmon-enhanced fluorescence. Quencher-modified blocking probes suppress wild-type DNA while selectively enabling mutant signal amplification. A single primer-probe set per codon allows comprehensive detection of all substitutions within KRAS codons 12/13, 61, and 146. The platform achieved detection down to 1 fM by direct hybridization and 100 zM after blocked amplification, exceeding conventional PCR and next-generation sequencing sensitivity. Codon-level specificity was validated in CRC cell lines, with distinct signals for each mutation. Clinical analysis of 58 patients showed 100% concordance between tissue, plasma, and urine in mutation-positive malignant cases when sufficient input was available, indicating accurate reflection of tumor profiles. In benign tumors, detection was rare despite tissue mutations, likely due to limited ctDNA release.This plasmonic microarray enables ultra-sensitive, specific, and non-invasive detection, supporting early diagnosis, minimal residual disease monitoring, and longitudinal CRC management.

Bladder cancer remains a major urologic malignancy with substantial recurrence and progression risk, underscoring the need for mechanism-informed therapeutic candidates. Ginkgetin, a biflavonoid derived from Ginkgo biloba leaves, has shown antitumor potential in several cancer settings, yet its key signaling axis and actionable molecular node in bladder cancer have not been systematically defined. We evaluated ginkgetin across multiple bladder cancer cell lines (5637, T24, HT-1376, J82) and normal urothelial cells (SV-HUC-1) using viability assays and IC₅₀ estimation. Antitumor phenotypes were assessed by colony formation, wound-healing migration assays, EMT marker profiling, and Annexin V/PI flow cytometry. Network pharmacology and RNA-seq were integrated to prioritize enriched pathways, followed by western blot validation of PI3K/AKT/mTOR phosphorylation. An insulin reactivation ("rescue") strategy was used to functionally test pathway dependence. Transcriptome-derived candidates were further examined by RT-qPCR and STEAP2 overexpression to probe node-level involvement. In addition, molecular docking and 100-ns molecular dynamics simulations were performed to characterize ligand-target binding stability. Ginkgetin suppressed bladder cancer cell viability in a time- and dose-dependent manner at low micromolar concentrations, while normal urothelial cells required markedly higher exposures. Functionally, ginkgetin reduced clonogenic survival, inhibited migration, and shifted EMT features toward an epithelial phenotype. Apoptosis increased in parallel, accompanied by a pro-apoptotic protein signature. Multi-omics and network analyses converged on PI3K-Akt signaling, and experimental validation showed that ginkgetin primarily dampened pathway output by reducing PI3K/AKT/mTOR phosphorylation rather than total protein abundance. Insulin-mediated reactivation partially reversed phosphorylation suppression and attenuated apoptosis-related shifts, supporting a functional link between axis inactivation and apoptotic tendency. STEAP2 was consistently downregulated after treatment, and STEAP2 overexpression partially counteracted apoptosis-associated changes. These findings support a coherent "phenotype-pathway-node" model in which ginkgetin inhibits malignant phenotypes and promotes apoptosis in bladder cancer cells, associated with reduced PI3K/AKT/mTOR activity and STEAP2 downregulation. The PI3K/AKT/mTOR axis and STEAP2 emerge as testable mechanistic entry points for further translational validation.

Deep learning neural network (DLNN)-based tools can automate body composition analysis for cancer cachexia research. We aimed to evaluate a DLNN tool trained on a European population of Chinese cancer patients. Computed tomography (CT) images at the 3rd lumbar vertebral (L3) level of Chinese gastric cancer patients were retrospectively collected. An externally validated DLNN tool (Mosamatic) was used to segment skeletal muscle, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT). Manual segmentation was performed using SliceOmatic software (TomoVision, version 5.0). Geometric similarity between automated and manual segmentation, and the reliability was assessed. The cohort comprised 203 patients with a median body mass index (BMI) of 22.2&#x2009;kg/m2, and 604 CT images at L3 were collected. The median Dice Similarity Coefficient (IQR) of skeletal muscle, VAT and SAT were 0.973 (0.961-0.980), 0.980 (0.964-0.989), and 0.967 (0.945-0.977), respectively. The median Lin's Concordance Correlation Coefficient for skeletal muscle area (0.983), VAT area (1.000), SAT area (0.998), skeletal muscle radiation attenuation (0.995), VAT radiation attenuation (0.994), and SAT radiation attenuation (0.997) demonstrated excellent reliability. Low BMI (<18.5&#x2009;kg/m2) and ascites impaired the agreement between the 2 methods. The automated method showed high diagnostic concordance with manual segmentation for sarcopenia (&#x3ba;&#x2009;=&#x2009;0.843, P&#x2009;<&#x2009;.001) and myosteatosis (&#x3ba;&#x2009;=&#x2009;0.946, P&#x2009;<&#x2009;.001). The Mosamatic tool displays excellent generalizability to analyse body compositions in Chinese gastric cancer patients and can facilitate cachexia research. The Mosamatic tool displayed excellent generalizability without recalibration to analyse body composition on the 3rd lumbar vertebral CT images in Chinese gastric cancer patients.

BACKGROUND The incidence of breast cancer is high among women, with a significant proportion of cases being familial. However, the driver genes for breast cancer can differ across families. CASE REPORT Our patient was a 37-year-old woman diagnosed with triple-negative breast cancer (TNBC) by pathology, revealing invasive ductal carcinoma of the outer upper quadrant of the breast, WHO grade 3. The maximum diameter of the microscopic invasive cancer was approximately 0.5 cm. No definite vascular tumor thrombus or nerve invasion was observed. Some (30-90%) of the tumor cells disappeared, and the remaining tumor cells showed degeneration, interstitial sclerosis, scattered lymphocyte infiltration, and hemosiderin deposition. No cancer was found in the nipple and base resection margins, or in the other quadrants. The chemotherapy response was classified as grade III according to the MP (Miller and Payen classification) scoring system. Blood samples were collected from affected family members. Whole-exome sequencing (WES) and bioinformatics analyses were used to identify potential driver genes, followed by Sanger sequencing for validation, which ultimately confirmed the pathogenic gene and the underlying mechanism in this family. CONCLUSIONS A series of analyses suggested that the co-occurrence of heterozygous deletions in BRCA1 and OBSCN was the main cause of breast cancer in this family. The simultaneous association of 2 genes with the occurrence of breast cancer was discovered for the first time in this family, which could help guide disease prevention for family.

This study aimed to determine the prevalence of death anxiety and examine its psychological correlates within a hypothesized psycho-social-spiritual framework among Chinese patients with metastatic breast cancer. Consecutive inpatients with metastatic breast cancer were recruited from the Breast Cancer Department at Peking University Cancer Hospital (Beijing, China) between January 2022 and March 2025. Of 412 consented patients, 400 completed all questionnaires (response rate: 97.1%). Measures included the Chinese Death and Dying Distress Scale (DADDS), Patient Health Questionnaire-9 (PHQ-9), Distress Thermometer (DT), Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-Sp), Brief Experiences in Close Relationships scale (ECR-M16), and Quality of Life at the End of Life in Cancer (QUAL-EC). Death anxiety was common: 37.5% reported mild symptoms and 19.0% reported moderate-to-severe levels. In multivariable ordinal logistic regression, higher death anxiety severity was associated with greater depressive symptoms (PHQ-9), greater general distress (DT), higher attachment insecurity (ECR-M16), and poorer end-of-life preparation (all p<0.001). In a theoretically informed path model, attachment insecurity showed a direct association with death anxiety and an indirect association through distress and depressive symptoms; spiritual well-being moderated the attachment insecurity-death anxiety association after adjusting for distress and depression (interaction p=0.017). In this cross-sectional sample of Chinese patients with metastatic breast cancer, death anxiety was prevalent and was significantly associated with attachment insecurity, distress, depressive symptoms, and poorer end-of-life preparation. Higher spiritual well-being may buffer the association between attachment insecurity and death anxiety among patients with greater attachment vulnerability, highlighting the potential value of targeted psycho-social-spiritual assessment and supportive intervention.

Beyond established risk factors such as genetics and hormones, the human microbiome has emerged as a pivotal player in breast cancer pathogenesis. This review delineates the technological evolution in breast microbiome research, spanning traditional culture methods to high-throughput sequencing and cutting-edge spatial omics. We elucidate the role of the gut-breast axis in modulating breast cancer development through its influence on estrogen metabolism, immune responses, and microbial metabolites. Furthermore, we analyze the distinctive compositional features of the intratumoral microbiota and their dual, context-dependent roles in promoting invasion, inducing immunosuppression, and driving metabolic reprogramming within the tumor microenvironment. Novel microbiome-based therapeutic strategies, including targeted microbiota depletion, engineered microbial therapeutics, and dietary interventions, are summarized. Finally, we discuss the translational potential of microbiome research in refining breast cancer risk prediction, evaluating treatment responses, and advancing personalized prevention and treatment strategies, ultimately contributing to improved patient outcomes.

Partial epithelial-mesenchymal transition (p-EMT) is a dynamic cellular state associated with metastasis and adverse outcomes in multiple cancers, but its prognostic significance in ovarian cancer remains unclear. This study aimed to develop and validate an ovarian cancer-specific transcriptomic signature based on p-EMT-related genes, and to determine whether this signature can improve prognostic stratification and overall survival prediction across independent cohorts. A pan-cancer p-EMT gene set was curated from ten published studies. Using transcriptomic and clinical data from TCGA-OV (n = 488), a six-gene p-EMT signature was developed via LASSO regression to generate a patient-specific risk score. The score was integrated with clinical variables to construct a prognostic nomogram and validated in the external GEO cohort GSE140082 (n = 380) and GSE165808 (n = 51). A six-gene p-EMT transcriptomic signature (ADAM9, ANXA8L1, FSTL3, RABAC1, TPM4, and TWIST1) was significantly associated with overall survival (OS) and stratified patients into high- and low-risk groups (adjusted HR = 1.74, p < 0.001). Incorporation with age and FIGO stage in a nomogram improved predictive performance, with AUCs of 0.727, 0.700, and 0.656 at 1-, 3-, and 5-year OS, respectively. External validation in GSE140082 and GSE165808 confirmed model robustness, yielding 3-year AUCs of 0.630 and 0.826, respectively, demonstrating preserved prognostic value across independent cohorts and disease stages. This six-gene p-EMT transcriptomic signature demonstrates prognostic value in ovarian cancer and offers potential for individualized risk stratification and clinical decisionsupport.

Conventional type-1 dendritic cells (cDC1) are the main mediators of crosspresentation of tumor antigens to CD8+ T cells and provide a context of costimulatory molecules and cytokines that lead to cytotoxic T lymphocyte (CTL) responses. We analyzed bulk RNA sequences from 7 key clinical trials testing checkpoint inhibitors across multiple cancer types. cDC1- and CD8-associated gene signatures were analyzed. Multiplex tissue immunofluorescence was used to quantify cDC1 in melanoma, urothelial cancer, and non-small-cell lung cancer (NSCLC) samples and assess cDC1 tissue neighborhoods. Melanoma samples were studied with Xenium spatial transcriptomics (ST) and one series of NSCLC was analyzed using GeoMX-DSP. Strong associations across tumor types were found between cDC1 and CD8+ T cell transcripts with clinical outcomes. As mechanistically expected, transcripts for the CCL4 and CCL5 chemokines and the growth factor FLT3-L showed associations with cDC1 abundance. Tissue immunofluorescence showed a strong correlation of cDC1 and CD8+ T cell infiltration with clinical benefit upon treatment with checkpoint inhibitors (CPIs). Moreover, short distance between cDC1 and CD8+ T cells was found to define tissue niches associated with favorable outcomes. ST revealed recent T cell activation within immune cDC1-rich niches. cDC1 abundance, which determines CD8+ T lymphocyte density and activation in tumor tissues across cancer types, is strongly associated with clinical response to CPI-based immunotherapies.

The treatment of advanced hormone receptor-positive (HR+) breast cancer has seen relevant changes in last years. However, bevacizumab remains an option when combined with paclitaxel, but no certified pharmacogenetic profiles are now usable for the prediction of its response in breast cancer patients. This study aimed to explore the pharmacogenetic interactions among single nucleotide polymorphisms (SNPs) of genes involved in the angiogenic process and their impact on progression-free survival (PFS) and overall survival (OS) in hormone receptor-positive (HR+) metastatic breast cancer subjects administered with bevacizumab plus paclitaxel, or with paclitaxel alone (clinicaltrial.gov identifier NCT01935102). Germline DNA extracted from blood samples was analyzed using real-time polymerase chain reaction to investigate SNPs. The multifactor dimensionality reduction (MDR) analysis was employed to assess interactions between these genetic variants. A total of 168 eligible patients were analyzed. Among these, 106 patients received both paclitaxel and bevacizumab, while 62 received paclitaxel alone. In the combination therapy group, MDR analysis identified two pharmacogenetic interaction profiles involving specific genotypes of vascular endothelial growth factor-A(VEGF-A) rs833061 and vascular endothelial growth factor receptor-2 (VEGFR-2) rs1870377. Patients with a favorable genetic profile had a median PFS (mPFS) of 22.9 months, compared to 8.7 months in those with an unfavorable profile (p = 0.001). Cox proportional hazards analysis displayed an adjusted hazard ratio of 0.443 (95% CI: 0.284-0.691; p < 0.0001). The median OS (mOS) was 50.2 months for the favorable profile vs. 23.5 months for the unfavorable (p = 0.003), with an adjusted hazard ratio (HR) of 0.404 (95% CI: 0.249-0.657; p < 0.0001). In the 62 subjects administered with just paclitaxel, no significant differences in PFS (p = 0.820) or OS (p = 0.143) were observed between favorable and unfavorable genetic profiles. The MDR analysis of VEGF-A rs833061 and VEGFR-2 rs1870377 genotypes can detect a subgroup of bevacizumab-administered+ metastatic breast cancer patients with improved PFS and OS.

Bladder cancer (BC) is a highly prevalent malignant tumor. The traditional Chinese medicine formula Guo Lou Qu Mai Wan (GLQMW), when used in conjunction with chemotherapy, has been shown to reduce adverse reactions and prolong survival time, although its specific mechanisms remain unclear. This study aims to investigate whether GLQMW exerts its therapeutic effects on bladder cancer by modulating the tumor immune microenvironment. To elucidate the molecular mechanisms of GLQMW, we employed bioinformatics analysis, systems pharmacology, and molecular docking to explore the prognostic value of GLQMW-related target genes for BC and to establish a prognostic prediction model. We analyzed the relationship between GLQMW-related target genes and immune cell infiltration, as well as the compositional differences of immune cell subpopulations across different risk groups. Molecular docking was used to screen for pachymic acid (PA) as the main anticancer active compound, and CCK8 and western blot were used to determine the target of PA as the active compound. In our immune infiltration analysis, the expression levels of five genes (MAPK12, MAN1B1, EGFR, FABP6, and ZAP70) were found to be associated with immune cells. Moreover, a higher presence of na&#xef;ve B cells, plasma cells, CD8+ T cells, and Tregs was observed in the low-risk group, indicating that GLQMW can significantly impact the immune microenvironment by targeting these five model genes, thereby exerting therapeutic effects. In the single-cell data analysis, our results demonstrated that the percentage of CD8 T+ cells and plasma cells in tumor tissue was significantly lower than that in adjacent non-tumor tissue. In addition, through drug similarity analysis and molecular docking, we identified PA as a potential anti-tumor compound. Furthermore, PA was validated in vitro to upregulate FABP6 and downregulate EGFR expression and suppress the bladder cancer progression in vivo. PA, the active ingredient of GLQMW, can inhibit BC by inhibiting EGFR and upregulating FABP6.

Esophageal cancer (EC) ranks among the most lethal gastrointestinal malignancies. Due to challenges in early diagnosis, molecular heterogeneity, and therapeutic resistance, patient prognosis remains extremely poor, necessitating the development of novel biomarkers and therapeutic targets. As a core effector of the Hippo signaling pathway, the potential significance of Yes-associated protein 1 (YAP1) has garnered increasing attention. This paper aims to systematically summarize the multi-omics research, molecular mechanisms, and preclinical/translational evidence for YAP1, covering its activation pathways, biological functions, clinical significance, and therapeutic strategies. We elucidated YAP1's multidimensional regulatory network in EC, including Hippo-dependent and -independent mechanisms, cross-regulation with environmental risk factors, and its role in malignant phenotypes such as cell proliferation, apoptosis, epithelial-mesenchymal transition (EMT), and metastasis. The potential of YAP1 as a diagnostic, prognostic, and predictive biomarker is evaluated, alongside summarizing its role in mediating chemotherapy, radiotherapy, and immune tolerance mechanisms, along with recent advances in targeted therapies. This provides a theoretical foundation for subsequent basic research and precision medicine translation. As a potential hub in the EC signaling network, it is considered to play a key role in driving tumor progression and treatment resistance through multiple pathways. Targeting YAP1 holds broad clinical promise but faces challenges including functional duality, subtype heterogeneity, and complex resistance mechanisms. Future efforts should focus on developing highly selective inhibitors, integrating multi-omics technologies and innovative models to advance clinical translation and provide new strategies for precision treatment of EC patients.

Nanotechnology has emerged as a promising frontier in the identification and treatment of skin cancer by offering innovative platforms for targeted drug administration, real-time imaging, and enhanced therapeutic efficacy. Though preclinical results are promising and scientific enthusiasm is rising, the shift of nanotechnological breakthroughs from research laboratories to clinical environments remains hampered. The main translational problems preventing the clinical acceptance of nanomedicine in skin cancer treatment are investigated in this chapter. It explores obstacles like manufacturing scalability, reproducibility, regulatory uncertainty, clinical trial design restrictions, financial limits, and intellectual property complexity. Moreover, the chapter describes strategic ways to get beyond these obstacles: multidisciplinary cooperation, regulatory harmonization, and the inclusion of digital technologies into development pipelines together with artificial intelligence (AI). This chapter seeks to give a complete knowledge of what it takes to propel nanotechnology beyond the bench and into pragmatic, patient-centred applications in oncology by closely analysing both the challenges and possible solutions.

Pancreatic ductal adenocarcinoma (PDAC) is frequently preceded by new-onset diabetes mellitus (NODM), yet differentiating PDAC-associated DM from type 2 diabetes (T2D) remains clinically challenging. We investigated whether plasma proteomic profiling combined with machine learning could discriminate these conditions. Plasma samples from individuals with PDAC (with and without DM), long-standing T2D, and controls were analyzed by MALDI-TOF mass spectrometry. Spectral features were processed through a nested cross-validation framework to prevent data leakage, and model interpretability was explored using SHAP values. In parallel, low-molecular-weight proteins were characterized by GeLC-MS followed by LC-MS/MS and differential abundance analysis. Machine learning models distinguished PDAC-associated DM from T2D with a balanced accuracy of 85%. Proteomic analyses identified distinct signatures in PDAC- associated DM, including downregulation of erythrocyte-related proteins and PPBP, and upregulation of acute-phase reactants such as FGA, CP, and SERPINA3. Treatment-na&#xef;ve cases displayed increased circulating epithelial and keratin-associated proteins, which were attenuated after therapy, suggesting dynamic tumor-related remodeling. These findings demonstrate that integrating MALDI-TOF profiling with machine learning can capture plasma signatures associated with PDAC-associated DM. Although exploratory, this approach supports further validation in prospective cohorts aimed at improving PDAC risk stratification among individuals with NODM. SIGNIFICANCE: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a dismal 5-year survival rate, primarily due to late-stage diagnosis. The frequent occurrence of new-onset diabetes mellitus (NODM) as a paraneoplastic syndrome offers a critical window for early detection. However, the clinical challenge of distinguishing PDAC-associated diabetes (PDAC-DM) from type 2 diabetes mellitus (T2D) has hindered the implementation of effective screening strategies. This study addresses this significant clinical problem by leveraging a multi-faceted proteomics approach. We demonstrate that the integration of MALDI-TOF mass spectrometry peptide profiling with machine learning algorithms can accurately discriminate PDAC-DM from T2D with 85% accuracy. Furthermore, we used LC-MS/MS to identify specific low molecular weight proteins that are differentially regulated between these conditions, providing a molecular basis for the observed discrimination. Our work is significant as it presents a novel, high-throughput pipeline for biomarker discovery that combines the scalability of MALDI-TOF with the analytical power of LC-MS/MS and machine learning. The identified plasma signatures hold strong translational potential to improve risk stratification in patients with new-onset diabetes, ultimately enabling earlier diagnosis of PDAC and improving patient survival prospects. This research directly contributes to the field of clinical proteomics by providing a robust methodological framework and candidate biomarkers for the early detection of one of oncology's most challenging diseases.

Oral submucous fibrosis (OSF) is a chronic, progressive, and irreversible fibrotic disorder of the oral mucosa that is strongly associated with areca nut consumption. It is classified as an oral potentially malignant disorder (OPMD) with one of the highest malignant transformation rates (4%-7%). Despite extensive research across Asia and globally, significant heterogeneity persists in diagnostic criteria, grading systems, and management strategies. This hinders effective clinical practice, surveillance, and public health policymaking. By integrating translational evidence on areca nut-associated fibrosis, oral potentially malignant disorders, and oral cancer into a consensus-driven framework, this manuscript advances biologically informed, equitable, and collaborative strategies for oral cancer prevention and early risk reclassification in resource-limited settings. This guideline was developed through a structured consensus process modelled on the ACCORD reporting framework for consensus-based biomedical research. A multi-institutional steering committee was convened, and included senior oral pathologists and clinicians: Vinay Hazarey (VH), WM Tilakaratne (WMT), Kannan Ranganathan (KR), Raghu Radhakrishnan (RR), Jayanta Chattopadhyay (JC), Punnya V Angadi (PA), Karishma Desai (KD), and Pratibha Ramani (PR) (as a moderator from Saveetha Dental College, Chennai). The panel head was Dinesh Daftary (DD). Evidence was synthesised from peer-reviewed publications indexed in PubMed, Scopus, and Web of Science. Consensus was defined as &#x2265;80% agreement following structured rounds of discussion. The recommendations were graded as Strong or Conditional according to the quality of evidence, feasibility, and global applicability. The panel achieved a consensus on key areas: (1) OSMF is caused primarily by areca nut, a Group I carcinogen with no safe level of use; (2) clinical diagnosis should combine functional limitations with mucosal changes, supported by histopathology that incorporates fibrosis severity and epithelial dysplasia; (3) management should prioritize habit cessation, supplemented by pharmacological and surgical interventions as appropriate; (4) malignant transformation warrants long-term surveillance and potential revision of staging for OSMF-related oral cancer; and (5) strong public health measures are urgently needed, including regulation of areca nut sales and the establishment of centres of Excellence for OPMDs. These WHO-style guidelines provide an evidence-based, globally relevant framework for the diagnosis, management, and prevention of OSMF. The emphasis should be on early detection, habit cessation, translational research, and policy reforms. The adoption of these recommendations will strengthen clinical practice and reduce the burden of OSMF, and associated oral cancer worldwide.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with poor prognosis and rising incidence. Late detection and limited responsiveness to standard treatment translates into a 5-year overall survival of less than 12%. The pathology contributes to a desmoplastic tumor microenvironment that creates a physical barrier, leading to a dense, hypoxic environment that promotes further tumorigenesis, limited immunogenicity, and chemoresistance, resulting in a still significant translational gap in PDAC research. Feasible techniques to further elucidate tumorigenesis are indispensable because of the frequently limited predictive value of current preclinical models. PDAC organoids offer a powerful tool that can be rapidly generated from resected tumors and biopsies. This review summarizes the current technical and scientific knowledge and highlights the importance of the tumor microenvironment, the use of realistic oxygen conditions, and the role of the hypoxia-inducible factors. Additionally, various protocols based on different media and scaffolds are displayed, and it is illustrated how PDAC organoids can help to improve both diagnosis and treatment options. Finally, critical bottlenecks in modeling PDAC tumor-stromal interactions are identified, and integrated co-culture platforms are proposed as a promising solution for translational applications.

Hepatocyte growth factor activator inhibitor type-1 (HAI-1) plays pivotal roles in epithelial integrity and tumour biology. Although implicated in various malignancies, its expression profile and prognostic value in bladder cancer (BC) remain incompletely defined. High levels of HAI-1 ectodomain in urine have previously been reported to be associated with poor prognosis in BC patients. This study aimed to determine the relationships between tissue and urine levels of HAI-1 and clinical outcomes in BC. This study used immunohistochemistry to measure HAI-1 expression across 770&#x202f;BCs of all stages and grades. HAI-1 expression was scored on the basis of the percentage of positive cancer cells, subcellular localisation, and staining intensity. Additionally, HAI-1 (SPINT1) mRNA expression was compared with protein levels in tissue and urine. HAI-1 was highly expressed in low-grade, early-stage disease with strong membranous staining. Reduced overall HAI-1 expression, loss of membranous staining and increased cytoplasmic staining correlated with higher stage and grade and shorter survival. SPINT1 mRNA levels were positively correlated with membranous HAI-1 staining intensity (p&#x202f;=&#x202f;0.005). Urinary levels of HAI-1 were negatively associated with the fraction of HAI-1 positive cancer cells and membranous staining intensity (p&#x202f;<&#x202f;0.05). A positive correlation was observed between SPINT1 expression and urinary HAI-1 levels (p&#x202f;<&#x202f;0.05). The Urobasal A subtype had lower urinary HAI-1 ectodomain levels than other subtypes. HAI-1 expression may serve as a biomarker of tumour differentiation and prognosis in BC. Increased ectodomain shedding into the urine, rather than increased expression, likely explains the higher urine HAI-1 levels seen in more aggressive tumours.