Cell Commun Signal. 2026 Sep 11;24(1):488. doi: 10.1186/s12964-026-03206-2.

ABSTRACT

BACKGROUND: While over 170 RNA modifications have been identified and implicated in various cancers, their role in hepatocellular carcinoma (HCC) progression is increasingly recognized. Despite this established relevance in tumor biology, the landscape of RNA modifications in the peripheral blood of HCC patients-and their potential diagnostic utility-remains largely unexplored.

METHODS: Peripheral blood samples from patients with HCC, liver cirrhosis (LC), and normal healthy (NH) controls were collected. The abundances of 55 RNA modifications were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess their diagnostic potential for HCC, particularly at early stages. Correlations among these modifications and their associations with clinical parameters were analyzed. Simultaneously, differentially expressed genes, including those encoding RNA-modifying enzymes, were screened in peripheral blood. The biological relevance of the identified signatures was subsequently validated using in vitro co-culture and in vivo syngeneic HCC mouse models.

RESULTS: Compared to the combined non-HCC group (NH and LC), the abundances of 11 RNA modifications were significantly altered in both overall and stage I HCC groups, with N²,N²-dimethylguanosine (m^2,2G) emerging as a key component exhibiting the most pronounced dysregulation. A diagnostic model centered on an m^2,2G-based modification panel achieved area under the curves (AUCs) of 0.901 and 0.891 for detecting HCC and stage I HCC, respectively, demonstrating promising diagnostic potential. Notably, the incorporation of two upregulated genes in peripheral blood-IFI27 and CCR2-significantly enhanced the model's performance, yielding improved AUCs of 0.972 and 0.968, respectively. Further analysis revealed distinct correlation patterns among RNA modifications, as well as between RNA modifications and clinical laboratory parameters, exhibiting both shared and HCC-specific features that suggest systemic reprogramming of RNA modification network in HCC. This biological relevance was confirmed by elevated m^2,2G abundances in human lymphocytes co-cultured with HCC cells and blood from a syngeneic HCC mouse model.

CONCLUSIONS: This study systematically profiled peripheral blood RNA modifications and provided preliminary evidence supporting their potential as diagnostic biomarkers for HCC. By integrating key modifications (m^2,2G, m^2,2,7G, m^6,6A) with two mRNA markers (IFI27 and CCR2), we developed a multi-omics signature that demonstrated promising diagnostic performance, particularly for early-stage HCC.

PMID:42732057 | PMC:PMC13570552 | DOI:10.1186/s12964-026-03206-2

World J Oncol. 2026 Sep 4;17(5):683-704. doi: 10.14740/wjon2815. eCollection 2026 Oct.

ABSTRACT

BACKGROUND: Lung cancer (LC) and venous thromboembolism (VTE) are closely associated, with VTE contributing to morbidity and mortality among patients with LC. We aimed to identify and characterize a mitochondrial-related transcriptomic signature shared between LC and VTE and to explore its association with immune microenvironment features.

METHODS: We applied a multiomics approach focused on mitochondrial-related signaling pathways. Publicly available transcriptomic datasets were analyzed using differential expression profiling and weighted gene co-expression network analysis to identify key regulatory genes. These genes were intersected with a mitochondrial gene set and subjected to functional enrichment analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to identify candidate diagnostic genes validation. Immune cell infiltration was quantified, and associated regulatory mechanisms were explored.

RESULTS: Thirty-nine shared crosstalk genes were identified and were primarily enriched in mitochondrial metabolic processes. LASSO regression identified a five-gene candidate signature (ACAA1, HSD17B10, MTIF2, THOP1, and PDE2A). The model exhibited promising discriminatory performance (area under the curve > 0.9 in LC dataset and 0.7-0.9 in VTE dataset). These genes were significantly dysregulated and were associated with altered immune cell infiltration, particularly in dendritic cell and T cell subsets.

CONCLUSION: We identified a mitochondrial-related gene signature reflecting shared transcriptomic correlates between LC and VTE. The signature showed variable performance across disease contexts and correlative associations with immune features, supporting its role as a candidate biomarker for further investigation. Prospective validation in independent clinical cohorts is required before any translational application.

PMID:42730163 | PMC:PMC13568737 | DOI:10.14740/wjon2815

Cell Commun Signal. 2026 Sep 11;24(1):488. doi: 10.1186/s12964-026-03206-2.

ABSTRACT

BACKGROUND: While over 170 RNA modifications have been identified and implicated in various cancers, their role in hepatocellular carcinoma (HCC) progression is increasingly recognized. Despite this established relevance in tumor biology, the landscape of RNA modifications in the peripheral blood of HCC patients-and their potential diagnostic utility-remains largely unexplored.

METHODS: Peripheral blood samples from patients with HCC, liver cirrhosis (LC), and normal healthy (NH) controls were collected. The abundances of 55 RNA modifications were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess their diagnostic potential for HCC, particularly at early stages. Correlations among these modifications and their associations with clinical parameters were analyzed. Simultaneously, differentially expressed genes, including those encoding RNA-modifying enzymes, were screened in peripheral blood. The biological relevance of the identified signatures was subsequently validated using in vitro co-culture and in vivo syngeneic HCC mouse models.

RESULTS: Compared to the combined non-HCC group (NH and LC), the abundances of 11 RNA modifications were significantly altered in both overall and stage I HCC groups, with N²,N²-dimethylguanosine (m^2,2G) emerging as a key component exhibiting the most pronounced dysregulation. A diagnostic model centered on an m^2,2G-based modification panel achieved area under the curves (AUCs) of 0.901 and 0.891 for detecting HCC and stage I HCC, respectively, demonstrating promising diagnostic potential. Notably, the incorporation of two upregulated genes in peripheral blood-IFI27 and CCR2-significantly enhanced the model's performance, yielding improved AUCs of 0.972 and 0.968, respectively. Further analysis revealed distinct correlation patterns among RNA modifications, as well as between RNA modifications and clinical laboratory parameters, exhibiting both shared and HCC-specific features that suggest systemic reprogramming of RNA modification network in HCC. This biological relevance was confirmed by elevated m^2,2G abundances in human lymphocytes co-cultured with HCC cells and blood from a syngeneic HCC mouse model.

CONCLUSIONS: This study systematically profiled peripheral blood RNA modifications and provided preliminary evidence supporting their potential as diagnostic biomarkers for HCC. By integrating key modifications (m^2,2G, m^2,2,7G, m^6,6A) with two mRNA markers (IFI27 and CCR2), we developed a multi-omics signature that demonstrated promising diagnostic performance, particularly for early-stage HCC.

PMID:42732057 | PMC:PMC13570552 | DOI:10.1186/s12964-026-03206-2

Clin Exp Med. 2026 Jul 26;26(1):329. doi: 10.1007/s10238-026-02264-7.

ABSTRACT

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

PMID:42726304 | PMC:PMC13569553 | DOI:10.1007/s10238-026-02264-7

J Clin Transl Hepatol. 2026 Aug 28;14(8):824-841. doi: 10.14218/JCTH.2026.00106. Epub 2026 Aug 7.

ABSTRACT

BACKGROUND AND AIMS: Despite the surging global prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and related liver fibrosis, effective treatments remain limited. While the traditional Chinese medicine Juanyu-Xiaozhi Formula (JYXZF) is used against MASLD, its bioactive components and mechanisms are poorly understood. This study aimed to investigate the therapeutic effects of JYXZF and elucidate its underlying mechanisms of action.

METHODS: The constituents of JYXZF were characterized using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Its efficacy was evaluated in a rat model of metabolic dysfunction-associated steatohepatitis (MASH) induced by a high-fat/calorie diet with high-fructose/high-glucose water, utilizing serum biochemistry, histology, and glucose/insulin tolerance tests. Mechanistic validation was performed in free fatty acid-treated human hepatocellular carcinoma cell line HepG2 (HepG2) cells and HepG2/human hepatic stellate cell line LX-2 (LX-2) co-culture models using luciferase assays, chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-qPCR), and activator protein 1 (AP-1) overexpression rescue experiments. The functional relevance of stearoyl-CoA desaturase 1 (SCD1) was further assessed in vivo through liver-targeted adeno-associated virus (AAV)-mediated Scd1 overexpression.

RESULTS: Flavonoids were identified as the main bioactive constituents. JYXZF administration alleviated metabolic dysfunction, reduced hepatic lipid accumulation, and attenuated inflammation and fibrosis in MASH rats. Multi-omics integration and machine learning-assisted target prioritization identified lipid metabolic and inflammatory pathways. Among these pathways, we selected the AP-1/peroxisome proliferator-activated receptor gamma (PPARγ)/SCD1-related lipogenic pathway for functional validation. Target perturbation experiments supported the functional involvement of AP-1 in the regulation of the PPARγ/SCD1 pathway and its contribution to the anti-steatotic effects of JYXZF.

CONCLUSIONS: JYXZF alleviates MASLD-associated steatosis and fibrosis via the AP-1/PPARγ/SCD1-related lipogenic axis, demonstrating its therapeutic potential for MASLD/MASH and providing a mechanistic basis for future clinical applications.

PMID:42723998 | PMC:PMC13558244 | DOI:10.14218/JCTH.2026.00106

Clin Exp Med. 2026 Jul 26;26(1):329. doi: 10.1007/s10238-026-02264-7.

ABSTRACT

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

PMID:42726304 | PMC:PMC13569553 | DOI:10.1007/s10238-026-02264-7

Front Genet. 2026 Aug 28;17:1900277. doi: 10.3389/fgene.2026.1900277. eCollection 2026.

ABSTRACT

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and lung cancer are major risk factors for invasive pulmonary fungal infection (IPFI), carrying an attributable mortality of 30%-80%. Their coexistence further amplifies immunosuppression, while current diagnostic criteria remain inadequate for early risk identification.

METHODS: Transcriptomic data from the GEO dataset GSE296912 (scRNA-seq; 12,078 cells from normal and COPD lung tissue) and The Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) bulk RNA-seq cohort (539 tumor and 59 normal samples) underwent differential expression and cross-omics integration analysis. Five machine learning models were constructed: logistic regression, SVM, random forest, XGBoost, and LASSO. Candidate genes were validated by qRT-PCR in A549 cells and THP-1-derived macrophages stimulated with heat-inactivated Aspergillus fumigatus conidia, a protocol selected to ensure BSL-2 biosafety compliance and isolate PAMP-mediated innate immune signaling. Model performance was evaluated using 5-fold stratified cross-validation with AUC, calibration curves, and decision curve analysis.

RESULTS: Single-cell transcriptomic analysis of 12,078 cells identified 14 distinct cell populations, with marked myeloid expansion and immune dysregulation in COPD lung tissue. Cross-omics integration with TCGA-LUAD data identified 1,145 shared genes (79 immune-related), converging on NF-κB, TLR4, and cytokine receptor signaling. The random forest model achieved excellent discriminative performance (5-fold CV AUC = 0.988), with Treg infiltration, TLR4, and MMP9 as the top predictors. qRT-PCR confirmed significant upregulation of all five candidate genes (DEFB4A, S100A8, IL-8, MMP9, and TLR4) in both A549 and THP-1 cells following fungal stimulation.

CONCLUSION: This multi-omics machine learning model integrating scRNA-seq and TCGA transcriptomic data demonstrates excellent discriminative performance (AUC = 0.988), with mechanistic convergence of NF-κB, TLR4, and oncogenic signaling pathways identified across shared immune gene signatures. In vitro qRT-PCR validation confirms the biological relevance of five key antifungal immune genes, providing a transcriptomic foundation for future prospective IPFI risk stratification in patients with COPD and lung cancer.

PMID:42725278 | PMC:PMC13561498 | DOI:10.3389/fgene.2026.1900277

Front Med (Lausanne). 2026 Aug 27;13:1865050. doi: 10.3389/fmed.2026.1865050. eCollection 2026.

ABSTRACT

Transformed small-cell lung cancer (T-SCLC) is a clinically important form of histologic transformation and a mechanism of acquired resistance in non-small-cell lung cancer (NSCLC). It is associated with poor prognosis, with a median overall survival of only about 9-13 months. This review summarizes recent advances in the mechanisms, diagnosis, monitoring, and treatment of T-SCLC. Repeat biopsy remains the gold standard for confirming histologic transformation, whereas molecular profiling and liquid biopsy may facilitate early detection and longitudinal disease monitoring. Platinum-etoposide remains the most commonly used clinical standard after transformation, but its benefit is typically transient and durable disease control remains uncommon. Continuation of EGFR tyrosine kinase inhibitors combined with chemotherapy may prolong progression-free survival in selected patients but has not consistently improved overall survival. Anti-angiogenic therapy, particularly anlotinib, and chemo-immunotherapy have shown encouraging activity in selected patients, while emerging strategies targeting DLL3, MYC, SOX2, and epigenetic regulators may broaden the therapeutic landscape. Prospective studies integrating repeat tissue sampling, comprehensive genomic profiling, biomarker-guided patient stratification, pharmacogenomics, functional drug-sensitivity testing where feasible, and integrated multi-omics approaches are needed to advance molecularly guided and individualized treatment for T-SCLC.

PMID:42724635 | PMC:PMC13560167 | DOI:10.3389/fmed.2026.1865050

J Thorac Dis. 2026 Aug 31;18(8):883. doi: 10.21037/jtd-2026-0807. Epub 2026 Jul 21.

ABSTRACT

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous lung condition not fully captured by spirometry. Quantitative computed tomography (QCT) enables objective characterization of emphysema, airway remodeling, and other structural abnormalities, playing key roles in early recognition, phenotyping, and prognosis. Despite growing literature in this field, no comprehensive bibliometric synthesis has mapped the intellectual structure, collaborative networks, or thematic evolution of QCT research in COPD. This study aims to fill this gap by providing a structured overview of the field over the past two decades.

METHODS: A systematic search was performed in the Web of Science Core Collection (WoSCC) using the topic formula: TS=(("quantitative computed tomography" OR "quantitative CT" OR "QCT" OR "CT quantification" OR "quantitative CT assessment") AND ("chronic obstructive pulmonary disease" OR "COPD" OR "chronic obstructive pulmonary disease*")). Publications from 2005 to 2025 were included, limited to English original articles and reviews. Titles and abstracts were independently screened by two reviewers; studies not primarily focusing on QCT-based quantitative analysis in COPD were excluded. Disagreements were resolved through discussion. Bibliometric and visual analyses were conducted using CiteSpace 6.4.R1, VOSviewer 1.6.19, and the R package bibliometrix.

RESULTS: A total of 300 publications (279 original articles, 21 reviews) were included. The United States was the leading contributor in overall output and international collaboration. The University of Iowa was the most productive institution, Hoffman EA was the most prolific author, and the International Journal of Chronic Obstructive Pulmonary Disease was the most productive journal. Keyword and thematic analyses revealed a clear evolutionary trajectory: early research (2005-2012) focused on technical quantification of emphysema and airway abnormalities; a transitional phase (2013-2018) emphasized "phenotypes" and disease heterogeneity; and the recent period (2019-2025) has seen rising attention to prognostic evaluation, mortality prediction, and artificial intelligence-assisted analysis.

CONCLUSIONS: This study confirms a shift from morphologic quantification toward clinically actionable imaging biomarkers. However, the existing literature suffers from several critical gaps: lack of standardized acquisition and analysis protocols, predominance of cross-sectional designs, and insufficient external validation of artificial intelligence models. Future research should prioritize multicenter prospective validation, integration with multi-omics data for endotyping, and development of open-source automated pipelines to facilitate clinical translation.

PMID:42724634 | PMC:PMC13559334 | DOI:10.21037/jtd-2026-0807

Front Immunol. 2026 Aug 27;17:1812306. doi: 10.3389/fimmu.2026.1812306. eCollection 2026.

ABSTRACT

Stroke-associated pneumonia (SAP) is the most common infectious complication following acute stroke. The limited efficacy of conventional antimicrobial therapy suggests that SAP may be fundamentally a syndrome driven by dysregulated cross-system interactions. This review proposes the "gut microbiota-immune axis" (GMIA) as a comprehensive framework for the development of SAP and systematically discusses the potential mechanisms by which post-stroke microbial-derived metabolic signals-including short-chain fatty acids (SCFAs), bile acids, tryptophan metabolites, and endotoxins-drive systemic immune reprogramming, predisposing patients to SAP. Based on the GMIA, we highlight several promising intervention strategies, including dietary modulation, precision antibiotic use, probiotics, fecal microbiota transplantation (FMT), supplementation with microbial metabolites, and receptor-targeted therapies, and summarize the current clinical translation related to the GMIA. Future research directions require high-quality clinical trials that integrate multi-omics data from the microbiome with immune biomarkers and clinical parameters. Such an approach is essential for constructing validated risk stratification models and advancing the management of SAP from empirical anti-infective treatment toward a precision medicine model centered on GMIA-based immune modulation.

PMID:42724580 | PMC:PMC13560329 | DOI:10.3389/fimmu.2026.1812306

J Thorac Dis. 2026 Aug 31;18(8):950. doi: 10.21037/jtd-2026-1704. Epub 2026 Aug 28.

ABSTRACT

BACKGROUND AND OBJECTIVE: Traditionally, two primary systems have been employed for staging small cell lung cancer (SCLC): the Veterans Administration Lung Study Group (VALG) system and the International Association for the Study of Lung Cancer (IASLC) tumor, node, metastasis (TNM) system. The term "limited disease" is defined differently: VALG characterizes it as disease encompassed within a single tolerable radiation field, while IASLC defines it as the lack of distant metastases (M0). Patients with N3 disease frequently satisfy VALG extensive-stage (ES) criteria while meeting IASLC limited-stage (LS) criteria, resulting in a notable staging discrepancy. Therefore, this review aims to clarify the clinical challenges posed by this staging overlap and provide insights for standardizing staging terminology and optimizing therapeutic decision-making in N3 SCLC.

METHODS: A narrative review utilizing a systematized search strategy was conducted. While strict adherence to PRISMA guidelines was not pursued because the extensive heterogeneity of the literature precluded a formal meta-analysis, rigorous search criteria were applied to minimize selection bias. Databases including PubMed, Web of Science, Embase, the Cochrane Library, and China National Knowledge Infrastructure (CNKI) were searched for literature from January 2000 to March 2026. Studies examining stage N3 SCLC, spatial metastatic burden, and definitional inconsistencies between the VALG and IASLC staging systems were analyzed to assess their effects on treatment dosimetry, systemic therapy, and survival outcomes.

KEY CONTENT AND FINDINGS: The staging overlap in N3 SCLC leads to heterogeneous clinical management depending on its spatial metastatic burden, and this highly variable cohort can be stratified into distinct prognostic subgroups based on the anatomical distribution (single-region vs. multi-region) of the involved lymph nodes.

CONCLUSIONS: These findings should guide clinical trial design and terminology. Clinical decision-making must transcend historical paradigms and technical constraints. Future strategies must incorporate spatial evaluations of metastatic burden alongside innovative multimodal tools, such as artificial intelligence (AI) and multi-omics, to facilitate tailored therapy for SCLC.

PMID:42724560 | PMC:PMC13559235 | DOI:10.21037/jtd-2026-1704

J Clin Transl Hepatol. 2026 Aug 28;14(8):824-841. doi: 10.14218/JCTH.2026.00106. Epub 2026 Aug 7.

ABSTRACT

BACKGROUND AND AIMS: Despite the surging global prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) and related liver fibrosis, effective treatments remain limited. While the traditional Chinese medicine Juanyu-Xiaozhi Formula (JYXZF) is used against MASLD, its bioactive components and mechanisms are poorly understood. This study aimed to investigate the therapeutic effects of JYXZF and elucidate its underlying mechanisms of action.

METHODS: The constituents of JYXZF were characterized using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Its efficacy was evaluated in a rat model of metabolic dysfunction-associated steatohepatitis (MASH) induced by a high-fat/calorie diet with high-fructose/high-glucose water, utilizing serum biochemistry, histology, and glucose/insulin tolerance tests. Mechanistic validation was performed in free fatty acid-treated human hepatocellular carcinoma cell line HepG2 (HepG2) cells and HepG2/human hepatic stellate cell line LX-2 (LX-2) co-culture models using luciferase assays, chromatin immunoprecipitation-quantitative polymerase chain reaction (ChIP-qPCR), and activator protein 1 (AP-1) overexpression rescue experiments. The functional relevance of stearoyl-CoA desaturase 1 (SCD1) was further assessed in vivo through liver-targeted adeno-associated virus (AAV)-mediated Scd1 overexpression.

RESULTS: Flavonoids were identified as the main bioactive constituents. JYXZF administration alleviated metabolic dysfunction, reduced hepatic lipid accumulation, and attenuated inflammation and fibrosis in MASH rats. Multi-omics integration and machine learning-assisted target prioritization identified lipid metabolic and inflammatory pathways. Among these pathways, we selected the AP-1/peroxisome proliferator-activated receptor gamma (PPARγ)/SCD1-related lipogenic pathway for functional validation. Target perturbation experiments supported the functional involvement of AP-1 in the regulation of the PPARγ/SCD1 pathway and its contribution to the anti-steatotic effects of JYXZF.

CONCLUSIONS: JYXZF alleviates MASLD-associated steatosis and fibrosis via the AP-1/PPARγ/SCD1-related lipogenic axis, demonstrating its therapeutic potential for MASLD/MASH and providing a mechanistic basis for future clinical applications.

PMID:42723998 | PMC:PMC13558244 | DOI:10.14218/JCTH.2026.00106

Gan To Kagaku Ryoho. 2026 Aug;53(8):483-488.

ABSTRACT

Spatial transcriptomics technologies enable omics analysis while preserving the spatial and histopathological context of cells within tissue sections, and have rapidly become widespread across various research fields, including cancer research. In cancer studies, these technologies are widely employed to elucidate changes in cancer cells and the surrounding tumor microenvironment associated with tumor progression and the emergence of therapeutic resistance. Through the application of spatial transcriptomics, numerous novel insights have been obtained regarding the identification of therapeutic targets and strategies to overcome treatment resistance. Sequencing-based platforms such as Visium capture transcriptome-wide information with spatial coordinates and have been applied to characterize the microenvironmental dynamics during lung adenocarcinoma progression and to identify microenvironmental states contributing to chemotherapy resistance in ovarian clear cell carcinoma. Imaging-based platforms such as Xenium and CosMx enable single-cell-resolution profiling of gene expression across hundreds of thousands of cells within tissue sections without requiring cell dissociation, and can be combined with multiplexed immunofluorescence staining to simultaneously obtain gene expression and protein expression data from the same section. These approaches have facilitated the discovery of novel cell subsets associated with patient prognosis and the detection of micrometastatic cancer cells in lymph nodes. In addition to the expanding range of applications, the technologies themselves have undergone remarkable development. Emerging techniques include spatial full-length transcriptome sequencing for splice isoform and immune receptor repertoire analysis, RNA-based mutation detection, spatial epigenomic profiling of chromatin accessibility and DNA methylation, and 3-dimensional spatial transcriptomics for volumetric tissue analysis. This review provides an overview of the fundamental technologies underlying spatial transcriptomics, presents representative examples of their application in cancer research, and introduces next-generation measurement techniques that are expected to further advance the field.

PMID:42723233

Ultrasound Med Biol. 2026 Sep 10:S0301-5629(26)00316-9. doi: 10.1016/j.ultrasmedbio.2026.08.004. Online ahead of print.

ABSTRACT

Cancer immunotherapy has revolutionized the treatment landscape, yet its clinical efficacy is limited by modest objective response rates and the emergence of atypical response patterns such as pseudoprogression and hyperprogression. Conventional RECIST criteria relying on anatomical size changes and invasive tissue biopsies suffer from prominent sampling bias and cannot dynamically reflect the heterogeneous tumor immune microenvironment (TIME), creating an urgent demand for non-invasive, real-time functional imaging tools to longitudinally profile intra-tumoral immune landscapes. Ultrasound molecular imaging (USMI) stands out as a distinctive imaging modality complementary to PET-CT and MRI, featuring radiation-free operation, low cost, superior spatiotemporal resolution and repeatable whole-tumor visualization-advantages that overcome the limitations of ionizing radiation, high expense and static single-spot sampling inherent to mainstream molecular imaging modalities. This review systematically elaborates state-of-the-art advances in USMI for visualizing tumor immune biomarkers, with in-depth dissection of core acoustic imaging mechanisms, rational design and multi-functional optimization strategies of immune-targeted microbubble/nanobubble probes and comprehensive collation of landmark pre-clinical investigations across melanoma, hepatocellular carcinoma, non-small cell lung cancer, colorectal and breast cancers. We thoroughly correlate USMI signal readouts with pathological immunohistochemistry, transcriptomic profiles and longitudinal immunotherapy outcomes, and elaborate on its core translational applications: dynamic tracking of immune cell infiltration and spatial distribution, quantitative mapping of global immune checkpoint expression, early prediction of therapeutic efficacy and differential diagnosis of pseudoprogression, hyperprogression and true tumor progression. We further highlight the inherent uniqueness of USMI for TIME surveillance and its complementary value relative to PET/MRI and objectively dissect critical translational bottlenecks, including probe off-target binding, insufficient standardized quantitative pipelines and deep-tissue ultrasound attenuation. Rather than overstating preliminary exploratory work, we rationally discuss the synergistic integration of USMI with multi-omics and artificial intelligence radiomics as a forward-looking developmental direction and propose theranostic probe engineering and standardized multi-center validation frameworks to accelerate clinical translation. This review constructs a complete theoretical and technical framework positioning USMI as a novel functional assessment paradigm for tumor immunotherapy, clarifies its irreplaceable strengths in immune molecular imaging and provides targeted insights to advance precision tumor immunotherapy evaluation.

PMID:42722534 | DOI:10.1016/j.ultrasmedbio.2026.08.004

Drug Des Devel Ther. 2026 Sep 5;20:543657. doi: 10.2147/DDDT.S543657. eCollection 2026.

ABSTRACT

Metabolic dysfunction-associated steatohepatitis (MASH) is not solely a disorder of hepatocellular lipid accumulation, but a multicellular disease driven by coordinated metabolic stress, sterile inflammation, fibrogenesis, and niche remodeling. Recent therapeutic progress with the provisional approval of resmetirom and semaglutide has validated MASH as a tractable clinical target. However, many experimental agents have shown limited or inconsistent efficacy, particularly for regression of hepatic fibrosis or cirrhosis, reflecting the biological heterogeneity and dynamic cellular architecture of the disease. Distinct from conventional pathway- or drug class-based reviews, we summarize emerging therapeutics through a liver cell-centered framework, integrating hepatocyte-directed metabolic therapies, immune-cell modulation, hepatic stellate cell-targeted antifibrotic strategies, niche-directed approaches involving liver sinusoidal endothelial cells and cholangiocytes, systemic multi-cell modulators, and precision-delivery technologies. We further compare how these interventions reshape pathogenic communication among hepatic and extrahepatic compartments, while emphasizing unresolved challenges in drug target selection, cellular specificity, disease-stage dependency, safety, and patient stratification. This perspective emphasizes the need to move from isolated pathway targeting toward cell- and network-informed therapeutic strategies supported by spatial multi-omics, human-relevant models, and precision delivery.

PMID:42719321 | PMC:PMC13557022 | DOI:10.2147/DDDT.S543657

Biofactors. 2026 Sep-Oct;52(5):e70150. doi: 10.1002/biof.70150.

ABSTRACT

Gastrointestinal malignancies, including gastric cancer, colorectal cancer, hepatocellular carcinoma, and pancreatic ductal adenocarcinoma, remain major causes of cancer-related morbidity and mortality worldwide. Although chimeric antigen receptor T-cell (CAR-T) therapy has revolutionized the treatment of hematologic malignancies, its efficacy in gastrointestinal solid tumors remains limited by antigen heterogeneity, insufficient trafficking and infiltration, immunosuppressive tumor microenvironments, on-target off-tumor toxicity, and adaptive resistance. In this review, we summarize the current landscape of CAR-T therapy in gastric cancer, colorectal cancer, hepatocellular carcinoma, and pancreatic cancer, with a focus on representative target antigens and emerging biomarker strategies. We further discuss two major categories of biomarkers: target antigen-related biomarkers and conventional dynamic biomarkers, including serum tumor markers, cytokine changes, CAR-T expansion kinetics, and antigen-loss monitoring. In addition, we highlight how single-cell ribonucleic acid sequencing and spatial transcriptomics provide complementary insights into cellular states, immune exhaustion, stromal barriers, and spatially restricted immune exclusion. By integrating these multi-omics approaches with biomarker-guided patient stratification and next-generation CAR-T engineering, gastrointestinal solid tumor CAR-T therapy may evolve from empirical optimization toward mechanism-driven and precision-guided clinical translation.

PMID:42717494 | PMC:PMC13558850 | DOI:10.1002/biof.70150

Ann Surg Oncol. 2026 Sep 12. doi: 10.1245/s10434-026-20366-0. Online ahead of print.

ABSTRACT

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal malignancy with limited long-term survival despite advances in surgery and systemic therapy.

PATIENTS: The population of interest comprises patients with PDAC characterized by targetable molecular alterations and biologically distinct transcriptomic subtypes.

METHODS: We performed a narrative review of landmark and contemporary clinical trials, translational studies, and emerging molecular-classification platforms relevant to precision oncology in PDAC.

RESULTS: Growing understanding of PDAC molecular biology has identified putative genetic mutations, including homologous recombination repair deficiency, mismatch repair deficiency, and mutated KRAS, enabling the development of targeted therapies and precision treatment strategies. Concurrently, transcriptomic profiling has revealed biologically distinct molecular subtypes associated with differences in prognosis and therapeutic response. Emerging tools such as molecular classifiers, deep learning models, and multiomic platforms may further refine patient selection and treatment personalization.

CONCLUSIONS: This review highlights contemporary efforts of novel targeted therapies, ongoing advances in molecular subtyping, and the evolving role of precision oncology in improving outcomes for patients with PDAC.

PMID:42732021 | DOI:10.1245/s10434-026-20366-0