Front Oncol. 2026 Aug 28;16:1907210. doi: 10.3389/fonc.2026.1907210. eCollection 2026.

ABSTRACT

Clonal evolution in hepatocellular carcinoma (HCC), esophageal squamous cell carcinoma (ESCC), and gastric cancer (GC) reflects the interaction of genetic diversification, cell-state plasticity, and tissue-specific selection. Multi-region and single-cell DNA sequencing resolve truncal and subclonal lineages, whereas single-cell and spatial transcriptomics, proteomics, and serial liquid biopsy characterize cellular states, ecological niches, and temporal dynamics. The three cancers differ in dissemination timing, dominant selective pressures, and biomarker maturity: early seeding is best supported in selected HCC cohorts, ESCC is strongly influenced by field cancerization and epithelial-stromal crosstalk, and GC follows subtype- and ecotype-dependent trajectories. We discuss the assumptions and sampling biases that constrain phylogenetic inference, the causal limits of cross-sectional tumor atlases, clonal hematopoiesis, and the incremental value of broad multi-omics over focused assays. Liquid-biopsy detection of minimal residual disease is prognostic, but treatment benefit from marker-guided intervention remains context dependent. Near-term translation requires standardized, decision-linked assays; adaptive therapy and evolutionary steering remain investigational.

PMID:42729528 | PMC:PMC13563159 | DOI:10.3389/fonc.2026.1907210

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

Front Med (Lausanne). 2026 Aug 27;13:1875846. doi: 10.3389/fmed.2026.1875846. eCollection 2026.

ABSTRACT

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is the most common chronic liver disease around the world, affecting 33.6% of the adult population (95% CI: 28.1%-39.5%; I ² = 99.9%), or roughly one in three. The extent of the liver damage is variable, from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH, formerly NASH), cirrhosis and hepatocellular carcinoma (HCC). Early diagnosis is essential to prevent serious liver damage. Traditional diagnostic techniques such as liver biopsy, imaging, and biomarker testing are all invasive, costly, reduced sensitive to early-stage disease, and they also have variability among observers. Modern diagnostic and prognostic approaches based on the principles of Artificial Intelligence (AI) and specifically on machine learning (ML) and deep learning (DL) have enabled multimodal approaches integrating clinical, imaging and molecular data. This scoping review conducted per PRISMA-ScR guidelines, synthesizes findings from 73 studies (search window 2020-2026) across three dimensions: clinical data driven models, imaging-based classifiers (ultrasound, CT and MRI), and multi-omics (genomics, transcriptomics and proteomics) techniques. Moreover, emergence of models such as U-Net and LiverNet 2.x, classification models like DeepLiverNet and BiLSTM models, as well as transformer frameworks and the identification of biomarkers models are also described. This study also investigates challenges such as data heterogeneity, data interpretability, fairness and real-world clinical application. Finally, important areas of research opportunities and future directions are highlighted to present a developing clinically applicable, explainable and ethical AI solutions to manage MASLD.

PMID:42724126 | PMC:PMC13558856 | DOI:10.3389/fmed.2026.1875846

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

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