J Liq Biopsy. 2025 Jul 8;9:100310. doi: 10.1016/j.jlb.2025.100310. eCollection 2025 Sep.

ABSTRACT

Bladder cancer is the ninth most common malignancy worldwide, with two clinically distinct forms: non-muscle-invasive disease, characterized by high recurrence and excellent long-term survival, and muscle-invasive disease, associated with poorer outcomes. Current surveillance-cystoscopy and urine cytology-offers high specificity but is invasive, costly, and insensitive to low-grade tumors, underscoring the need for reliable, non-invasive biomarkers. Liquid biopsy approaches in urine and blood have demonstrated promise for real-time assessment of tumor burden, molecular heterogeneity, and early recurrence. Circulating tumor DNA (ctDNA) assays detect tumor-derived genetic and epigenetic alterations, enabling dynamic monitoring of minimal residual disease and treatment response. Methylation-based tests and CpG-targeted sequencing in urine achieve high diagnostic accuracy, potentially reducing dependence on cystoscopy. Molecular classification of bladder tumors into luminal and basal subtypes has refined therapeutic strategies: FGFR inhibitors for luminal-papillary tumors, EGFR-targeted and chemotherapy approaches for basal/squamous cases, and immune-checkpoint inhibitors guided by immune-infiltration profiles. Integration of artificial intelligence with multi-omic liquid biopsy data further enhances predictive modeling for recurrence, treatment response, and minimal residual disease detection. Despite these advances, clinical implementation faces challenges including pre-analytical variability, lack of standardized assays, limited prospective validation, and unclear cost-effectiveness. Harmonized protocols, large multicenter trials, and health-economic evaluations are essential to translate liquid biopsy technologies into routine practice. Future integration with advanced imaging, tissue biopsy, and digital pathology-supported by multidisciplinary collaboration and formal guideline endorsement-holds the potential to personalize bladder cancer management, reduce invasive procedures, and improve patient outcomes.

PMID:40698358 | PMC:PMC12281373 | DOI:10.1016/j.jlb.2025.100310

J Hepatocell Carcinoma. 2025 Jul 17;12:1453-1469. doi: 10.2147/JHC.S493907. eCollection 2025.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) necessitates novel immunotherapeutic targets. PBK, a cancer/testis antigen (CTA), was identified as a pivotal hub gene influencing prognosis, tumor mutation burden (TMB), and immune microenvironment remodeling.

METHODS: PBK was prioritized using weighted gene co-expression network analysis (WGCNA) and differential expression screening in the TCGA-LIHC cohort, intersected with curated CTAs. Analyses assessed correlations with clinicopathological features (TNM stage, survival), genomic characterization (mutation frequencies), and functional validation via siRNA-mediated PBK knockdown in Huh7 cells (migration assay). Single-cell RNA sequencing (scRNA-seq) profiled of the tumor immune microenvironment.

RESULTS: PBK overexpression was significantly correlated with advanced TNM stage (P < 0.05) and poor survival (log-rank P = 0.003). Genomic analysis revealed distinct mutation profiles: high-PBK tumors exhibited increased TP53 mutation frequency (39% vs 17%) but decreased CTNNB1 mutations (20% vs 31%). Patients exhibiting with combined PBK overexpression and high TMB demonstrated the poorest prognosis. Functional validation confirmed that PBK knockdown significantly inhibited Huh7 cell migration capacity (P < 0.05). scRNA-seq analysis showed PBK-enriched tumors contained elevated proportions of immunosuppressive SPP1(+) macrophages (22.33% vs 6.6%, FDR corrected P < 0.001) and CD8(+) SLC4A10(+) MAIT cells (9.82% vs 4.7%, FDR corrected P < 0.001).

CONCLUSION: PBK synergistically drives HCC progression through three synergistic mechanisms: (1) promoting oncogenic mutation accumulation (eg, TP53), (2) increasing metastatic potential, and (3) reprogramming an immune-suppressive microenvironment enriched for SPP1(+) macrophages and CD8(+)SLC4A10(+) MAIT cells. This establishes PBK as a dual-purpose biomarker for prognostic stratification and immunotherapy resistance prediction, providing a mechanistic rationale for developing PBK-targeted therapies in HCC.

PMID:40697330 | PMC:PMC12279550 | DOI:10.2147/JHC.S493907

ACS Omega. 2025 Jun 30;10(27):28782-28796. doi: 10.1021/acsomega.4c10637. eCollection 2025 Jul 15.

ABSTRACT

Despite the high prevalence of type 2 diabetes (T2D), the mechanisms driving pathology in pancreatic islet β cells remain poorly understood. We utilized a multiomics approach to evaluate the transcriptional and biochemical makeup of islets from human organ donors with T2D and nondiabetic controls. Transcriptomic (N = 10), proteomic (N = 6), and untargeted high-resolution metabolomic (N = 10) data were analyzed individually and then integrated using sparse partial least-squares regression, and differential network analysis was performed. In individual data sets, 25 transcripts, 30 proteins, and 30 metabolites were differentially abundant between T2D and nondiabetic islets, representing some pathways not previously characterized in T2D islets including purine and pyrimidine, branched-chain amino acid, and histidine metabolism. Network analysis of integrated data sets highlighted disrupted relationships among features in T2D islets compared to those from nondiabetic individuals. Fatty and amino acid metabolism and immune activity were identified as prominent drivers of the distinctions in biochemical interactions in T2D networks. Our findings also suggested greater abundance and influence of industrial chemicals, including polychlorinated and polybrominated biphenyls, in T2D islets. This pilot study demonstrates that multiomics profiling can identify candidate molecules and mechanisms impacting islet cell activity in T2D, which could represent targets for therapeutic intervention.

PMID:40687044 | PMC:PMC12268419 | DOI:10.1021/acsomega.4c10637

Curr Opin Oncol. 2025 Sep 1;37(5):408-413. doi: 10.1097/CCO.0000000000001178. Epub 2025 Jul 2.

ABSTRACT

PURPOSE OF REVIEW: This review evaluates the importance of circulating tumor DNA (ctDNA) as a minimally invasive tool in lymphoma management.

RECENT FINDINGS: Current literature demonstrates ctDNA's ability to alleviate the shortcomings of standard biopsy and imaging, providing real-time insights into tumor burden, clonal evolution, and treatment resistance. In Hodgkin lymphoma, ctDNA allows for comprehensive genomic profiling and treatment monitoring. In diffuse large B-cell lymphoma (DLBCL), ctDNA correlates with disease burden and is valuable for tracking resistance, especially in CAR T-cell therapy. In rare subtypes like primary central nervous system lymphoma (PCNSL) and intravascular large B-cell lymphoma (IVLBCL), ctDNA enhances diagnostic precision and enables early relapse detection. Even in indolent lymphomas, ctDNA could prove useful in relapse monitoring and risk assessment.

SUMMARY: CtDNA analysis could become a key element in personalized lymphoma management, enabling earlier interventions and tailored treatment strategies. However, future efforts should focus on harmonizing methodologies and validating findings in large-scale trials to allow these techniques to be adopted in routine practice.

PMID:40658005 | DOI:10.1097/CCO.0000000000001178

Sci Rep. 2025 Jul 1;15(1):21173. doi: 10.1038/s41598-025-08986-0.

ABSTRACT

Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring of disease burden. Caris Assure is a multifunctional blood-based assay that couples whole exome and whole transcriptome sequencing on plasma and leukocytes with advanced machine learning techniques to satisfy all three clinical testing needs on one platform. Caris Assure for therapy selection was CLIA validated using 1,910 samples. 376,197 tissue profiles along with 7,061 paired blood and tissue profiles were used to engineer features for three machine learning models. The MCED model was trained on 1,013 patients and validated on an independent set of 2,675 patients. The tissue of origin for MCED model was trained on 1,166 samples and validated using 5-fold cross validation. The MRD & Monitoring model was trained on 3,439 patients and validated on two independent sets of 86 patients for MRD and 101 patients for monitoring. For early detection, sensitivities for stages I-IV cancers (n = 284, 129, 90, 23 respectively) were 83.1%, 86.0%, 84.4%, and 95.7%, all at 99.6% specificity (n = 2149). The diagnostic first-line procedure for tissue of origin was determined for 8 categories with a top-3 accuracy of 85% for stage I and II cancers. Detection of driver mutations for therapy selection from blood collected within 30 days of matched tumor tissue, demonstrated high concordance (PPA of 93.8%, PPV of 96.8%) using CHIP subtraction. For MRD and recurrence monitoring, the disease-free survival of patients whose cancers were predicted to have an event was significantly shorter than those predicted not to have an event using a tumor naïve approach (HR = 33.4, p < 0.005, HR = 4.39, p = 0.008, respectively). The data presented here demonstrate a unified liquid biopsy platform that uses blood-based whole-exome and transcriptome sequencing coupled with artificial intelligence to address the important clinical needs in multi-cancer early detection, monitoring of MRD and recurrent cancers, and precision selection of molecularly targeted therapies.

PMID:40596693 | PMC:PMC12214926 | DOI:10.1038/s41598-025-08986-0

Eur J Trauma Emerg Surg. 2025 Jun 27;51(1):238. doi: 10.1007/s00068-025-02922-7.

ABSTRACT

PURPOSE: Obesity is a prevalent disease, but its influence on post-injury biology remains unclear. In this study, we aimed to characterize the independent effect of obesity on the proteomic and metabolomic signatures of trauma.

METHODS: Plasma was obtained on arrival from injured patients at a Level 1 Trauma Center and analyzed with modern mass spectrometry-based proteomics and metabolomics. Samples obtained after start of transfusion were excluded. Patients were stratified by "obesity" (body mass index [BMI]≥30 kg/m²) vs. "no obesity" (BMI < 30 kg/m²). In sub-group analyses, patients were sub-stratified by Low Injury/Low Shock (ISS < 15, base excess [BE]≥-6mEq/L) and High Injury/High Shock (ISS≥15, BE<-6). Multiple regression was used to adjust the omics data for significant covariates prior to performing ome-wide analyses.

RESULTS: There were 183 patients included (48 [26%] with obesity and 135 [74%] without). After covariate-adjustment, multiple proteins and metabolites were correlated with ISS and/or BE and were significantly different from Low Injury/Low Shock to High Injury/High Shock only in patients with obesity. This obesity-specific omics response to injury was characterized by increased inflammation, hypercoagulability, altered nitrogen metabolism, and mitochondrial dysfunction. Patients with obesity also exhibited excessive injury-provoked tissue destruction and organ damage compared to patients without obesity. In injury severity-adjusted analyses, the obesity signature consistently displayed markers of hemolysis, likely reflecting a pre-injury hemolytic propensity.

CONCLUSION: Obesity is independently associated with altered post-injury biology, which likely underlies unique pathology in trauma patients with obesity. Identifying this aberrant response to injury is the first step in developing personalized therapies for this patient population.

PMID:40576654 | DOI:10.1007/s00068-025-02922-7

JCI Insight. 2025 Jun 26:e191595. doi: 10.1172/jci.insight.191595. Online ahead of print.

ABSTRACT

Pancreatic ductal adenocarcinoma (PDAC) has a poor survival rate due to late detection. PDAC arises from precursor microscopic lesions, termed pancreatic intraepithelial neoplasia (PanIN), that develop at least a decade before overt disease--this provides an opportunity to intercept PanIN-to-PDAC progression. However, immune interception strategies require full understanding of PanIN and PDAC cellular architecture. Surgical specimens containing PanIN and PDAC lesions from a unique cohort of five treatment-naïve patients with PDAC were surveyed using spatial-omics (proteomic and transcriptomic). Findings were corroborated by spatial proteomics of PanIN and PDAC from tamoxifen-inducible KPC (tiKPC) mice. We uncovered the organization of lymphoid cells into tertiary lymphoid structures (TLSs) adjacent to PanIN lesions. These TLSs lacked CD21+CD23+ B cells compared to more mature TLSs near the PDAC border. PanINs harbored mostly CD4+ T cells with fewer Tregs and exhausted T cells than PDAC. Peri-tumoral space was enriched with naïve CD4+ and central memory T cells. These observations highlight the opportunity to modulate the immune microenvironment in PanINs before immune exclusion and immunosuppression emerge during progression into PDAC.

PMID:40569674 | DOI:10.1172/jci.insight.191595

Adv Respir Med. 2025 Jun 12;93(3):17. doi: 10.3390/arm93030017.

ABSTRACT

Circulating free DNA (cfDNA) is genetic material released from various cells into bodily fluids. Among its fractions, circulating tumor DNA (ctDNA) originates from tumor cells and reflects their genetic material, including mutations and epigenetic changes. Methods commonly employed for detecting ctDNA in blood include next-generation sequencing (NGS) and various types of PCR. The presence of ctDNA can be utilized in liquid biopsies for many diagnostic purposes related to various cancers. It is a minimally invasive method of sampling molecular compounds from tumor cells. In this paper, we focus on current knowledge regarding the liquid biopsy of blood ctDNA in the context of lung cancer, one of the leading causes of cancer-related mortality. Currently, as a clinically approved method, liquid biopsy serves as a complementary technique in NSCLC diagnostic and genetic profiling. Other applications of liquid biopsy that are still being investigated include the detection of minimal residual disease (MRD) after curative treatment and response monitoring to systemic treatment. This review discusses current and future potential directions for the development and implementation of ctDNA for patients with NSCLC.

PMID:40558116 | PMC:PMC12189613 | DOI:10.3390/arm93030017

Trends Mol Med. 2025 Jun 23:S1471-4914(25)00118-2. doi: 10.1016/j.molmed.2025.05.007. Online ahead of print.

ABSTRACT

Gastric cancer (GC) remains a deadly disease because of late detection and limited treatment options at advanced stages. Treatment of patients with metastatic disease is based on chemotherapy, complemented by antibodies targeting HER2, VEGFR2, and more recently PD-1 or claudin 18.2. Further targets, such as FGFR2b, as well as novel drug classes including antibody-drug conjugates (ADCs) and bispecific antibodies, are promising developments in GC treatment. Despite the failure of several targeted agents, the landscape of GC therapy is evolving rapidly, facilitated by umbrella or platform precision medicine trials. The integration of next-generation sequencing and other omics techniques into molecular tumor boards, as well as functional drug testing on patient-derived models, might bring us closer to personalized oncology and ultimately improve patient survival.

PMID:40555635 | DOI:10.1016/j.molmed.2025.05.007

Cytokine Growth Factor Rev. 2025 Jun 6:S1359-6101(25)00071-1. doi: 10.1016/j.cytogfr.2025.06.001. Online ahead of print.

ABSTRACT

Lung cancer is a leading cause of cancer-related mortality worldwide, characterized by the uncontrolled growth and spread of abnormal cells. Despite constant progress in diagnosis and treatment of lung cancer remains highly challenging. Present review explores the molecular underpinnings of lung cancer, emphasizing genetic mutations, altered metabolism, and the role of biomarkers in diagnosis and treatment. Advances in diagnostic methods, particularly liquid biopsies, have enabled non-invasive detection and monitoring of lung cancer. Therapeutic approaches have evolved significantly, with molecular-targeted therapies focusing on pathways like EGFR, ALK, KRAS, and MET. Caner Immunotherapy, including immune checkpoint inhibitors, artificial intelligence, and multi-omics analysis, including genomics and image data to predict treatment response, has further enhanced precision medicine by enabling earlier detection, better prognostic models, and efficient drug discovery. AI has a significant impact on various aspects of oncology, including improving the earlier diagnosis of lung cancer. Despite these advancements, challenges such as drug resistance, tumor heterogeneity, and limited efficacy of certain therapies persist, necessitating continued research and innovation.

PMID:40544104 | DOI:10.1016/j.cytogfr.2025.06.001