Biliary duct invasion (BDI) is an underrecognized growth pattern of colorectal cancer (CRC) liver metastases that can mimic intrahepatic cholangiocarcinoma or intraductal papillary neoplasm of the bile duct. Its prevalence and clinicopathologic associations remain unclear. This study aimed to determine the prevalence of BDI and its clinicopathologic associations in surgically resected CRC liver metastases.

We retrospectively analyzed 133 consecutive patients who underwent hepatic resection for CRC liver metastases. Clinicopathologic variables, including age, sex, resection type, tumor differentiation, lymphovascular invasion (LVI), tumor budding, surgical margin status, and primary tumor characteristics, were compared between BDI-positive and BDI-negative cases. Categorical variables were analyzed using the chi-square, Fisher exact, or Fisher-Freeman-Halton exact test, as appropriate; continuous variables were analyzed using the Mann-Whitney U test.

BDI was identified in 19 of 133 cases (14.3%). Male sex showed the strongest numerical trend toward BDI (84.2% vs. 61.4%, P = 0.096), and LVI showed a nonsignificant numerical trend toward higher BDI rates (26.3% vs. 12.3%, P = 0.149). No clinicopathologic variable in the primary cohort analysis reached statistical significance after Bonferroni correction (α = 0.0050).

BDI occurs in approximately 14% of surgically resected CRC liver metastases in this cohort. Male sex and LVI show nonsignificant numerical trends toward higher BDI rates, but these findings should be interpreted cautiously given the limited sample size. Accurate histopathologic recognition of BDI and its distinction from intrahepatic cholangiocarcinoma remain important for correct pathologic diagnosis. Further prospective studies are warranted to clarify the clinicopathologic and prognostic significance of BDI.

Estrogen receptor alpha, encoded by the ESR1 gene, is a major oncogenic driver in hormone receptor-positive/HER2-negative breast cancers. While endocrine therapies are effective in treating this subgroup, patients with advanced or metastatic disease may develop resistance associated with acquired somatic ESR1 mutations. This mini review summarizes recent clinical and technological advances in understanding ESR1 mutations, newly approved targeted therapies, and the use of liquid biopsy companion diagnostics, with a focus on their implications for pathologists.

We conducted a narrative review of PubMed-indexed literature and relevant regulatory and guideline sources related to ESR1 in breast cancer, with an emphasis on recent peer-reviewed studies of ESR1 mutations and clinical trials of emerging therapies.

This review describes the molecular features of ESR1 alterations and estrogen receptor pathway biology, the mechanisms and key trial data for recently approved ER-targeted therapies for ESR1-mutated breast cancer. Additionally, it evaluates liquid biopsy testing platforms for detecting ESR1 mutations, discusses the advantages and limitations of liquid biopsy in detection of treatment resistance, and considers the evolving role of pathologists in breast cancer care.

Acquired ESR1 mutations are major drivers of endocrine therapy resistance. Next-generation sequencing and liquid biopsy have increasingly informed the clinical management of breast cancer in the past decade. Pathologists can play an important role in implementing molecular testing, interpreting complex biomolecular data, and helping to guide timely treatment decisions in the era of precision oncology.

EWSR1 fusions are recurrent genetic alterations in a wide spectrum of mesenchymal tumors and are often associated with specific clinicopathologic entities. However, the presence of an EWSR1 rearrangement does not always indicate a functional or disease-defining fusion.

We report a case of undifferentiated pleomorphic sarcoma with high-grade morphologic features harboring an EWSR1 rearrangement detected by fluorescence in situ hybridization. It was subsequently characterized by RNA sequencing as a likely nonfunctional fusion of EWSR1 exon 1 and NF2 intron 1. Histologically, the tumor was composed of pleomorphic spindle cells with brisk mitotic activity and lacked a specific line of differentiation. Immunohistochemically, the tumor showed diffuse cytoplasmic S100 positivity, with nuclear staining in a subset of tumor cells, while the overall immunophenotype did not support a specific line of differentiation. The EWSR1::NF2 fusion was inferred to have a tail-to-tail configuration, and additional KRAS and TP53 alterations were detected.

This case highlights that an EWSR1 rearrangement detected by fluorescence in situ hybridization should be interpreted cautiously and does not necessarily represent a functional or disease-defining fusion. Comprehensive molecular evaluation is important for the accurate interpretation and classification of sarcomas with atypical EWSR1 rearrangements.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a multifactorial disorder driven by complex interactions among genetic, epigenetic, transcriptional, proteomic, metabolic, and microbiome factors. Single-omics technologies have provided valuable insights into disease mechanisms, yet each layer captures only a partial view of MAFLD pathogenesis. Recent advances in multi-omics integration allow systematic dissection of molecular networks, cell differentiation trajectories, intercellular communication, and spatial organization, revealing causal links between molecular alterations and tissue phenotypes. Horizontal integration connects different omic layers within the same biological state, while longitudinal integration captures dynamic changes across disease stages. Emerging spatial transcriptomics, proteomics, and metabolomics techniques further enable in situ mapping of cellular and molecular heterogeneity, uncovering spatially defined pathogenic niches and regulatory hubs. Collectively, these integrated approaches offer a multidimensional framework for understanding MAFLD progression, identifying potential biomarkers, and guiding precision therapeutic strategies. Future efforts should focus on standardized multi-omics pipelines, interdisciplinary collaboration, and functional validation to translate these insights into clinical applications.

Upper gastrointestinal precancerous lesions are important targets for cancer screening and prevention. This study evaluated the diagnostic accuracy of artificial intelligence (AI)-assisted endoscopy for upper gastrointestinal precancerous lesions.

PubMed, Embase, MEDLINE, Cochrane Library, and IEEE Xplore were searched from inception to March 31, 2026. Studies reporting sensitivity and specificity, or sufficient data for their calculation, were included. Two reviewers independently extracted data. Pooled sensitivity, specificity, and the area under the receiver operating characteristic curve were estimated using a bivariate random-effects model.

Fifteen studies comprising 24 datasets and 19,578 records were included. Pooled sensitivity and specificity were 0.930 (95% confidence interval (CI): 0.886–0.958) and 0.944 (95% CI: 0.906–0.967), respectively; the diagnostic odds ratio was 223.79 (95% CI: 92.24–542.94), and the area under the receiver operating characteristic curve was 0.9661. Substantial heterogeneity was observed (bivariate I² = 73%). Among the variables formally evaluated by meta-regression, imaging modality was associated with heterogeneity (global test P = 0.005); image-enhanced endoscopy had higher sensitivity than white-light endoscopy (0.960 vs. 0.875). No significant publication bias was detected by Egger’s test (P = 0.833), Begg’s test (P = 0.641), or Deeks’ funnel plot asymmetry test (P = 0.053).

AI-assisted endoscopy shows high diagnostic accuracy for upper gastrointestinal precancerous lesions. Multicenter prospective studies are needed for validation.

Balloon-occluded transarterial chemoembolization (B-TACE) has emerged as a significant advancement in the locoregional treatment of hepatocellular carcinoma. This technique utilizes a balloon microcatheter selectively placed in target hepatic arteries to occlude blood flow and enhance drug accumulation within tumors while minimizing systemic exposure. The feasibility, safety, and effectiveness of the balloon occlusion technique have been verified. Recent studies have demonstrated that B-TACE achieves superior tumor response rates and potentially improves survival outcomes compared with conventional transarterial chemoembolization (C-TACE) techniques, particularly in cases with complex tumor vasculature or C-TACE-refractory disease. However, determining which patients would benefit from B-TACE requires comprehensive assessment. It remains to be determined in clinical practice whether this technique increases the risk of liver function impairment or is associated with specific complications. Further research is needed to better understand the technical conditions required for its clinical application, prognostic factors, and how it can be combined with other interventional techniques. This review summarizes the current literature on B-TACE, focusing on its technical principles, clinical efficacy, safety profile, and evolving role within the contemporary treatment landscape for advanced hepatocellular carcinoma, including its integration with systemic therapies.

Biliary atresia (BA) is a severe pediatric cholangiopathy characterized by rapidly progressive liver fibrosis. This study aimed to characterize scar-associated macrophages and investigate the role of PLG–PLGRKT signaling in BA-associated fibrogenesis.

Single-cell RNA sequencing and spatial transcriptomics were applied to liver tissues from patients with BA and non-BA controls. Key findings were validated in an independent cohort using quantitative polymerase chain reaction and multiplex immunohistochemistry. The functional role of the PLGRKT pathway was further examined using primary human peripheral blood mononuclear cell-derived macrophages with small interfering RNA (siRNA)-mediated PLGRKT knockdown, together with co-culture systems involving LX-2 hepatic stellate cells and human liver organoids. In vivo therapeutic potential was evaluated in a murine bile duct ligation model of cholestatic liver fibrosis using macrophage-targeted Plgrkt–Trem2 antibody–siRNA conjugates.

In BA, scar-associated macrophages (SAMs) increased with fibrosis progression and co-localized with hepatic stellate cells in fibrotic areas. PLGRKT was upregulated in BA liver tissue and increased during monocyte-to-macrophage differentiation. In primary human macrophages, plasminogen induced a PLGRKT-dependent pro-fibrotic phenotype, and conditioned medium from these cells increased COL1A1 deposition in hepatic stellate cells and human liver organoids. In vivo, macrophage-targeted Plgrkt–Trem2 antibody–siRNA conjugates reduced SAM accumulation and attenuated bile duct ligation-induced liver fibrosis.

These findings support a role for SAMs and the PLGRKT–SAM axis in BA-associated liver fibrosis and suggest that PLGRKT warrants further investigation as a potential macrophage-directed anti-fibrotic target.

Metabolic dysfunction-associated steatotic liver disease affects roughly 38% of adults, yet approved agents do not correct the upstream redox-metabolic perturbations—a depressed nicotinamide adenine dinucleotide (NAD+/NADH) ratio, saturated lipid excess, and endoplasmic reticulum (ER) stress—that drive hepatocyte injury. Cytochrome b5 reductase 3 (CYB5R3) couples NADH oxidation to fatty acid desaturation, nuclear factor erythroid 2-related factor 2 (NRF2)-linked antioxidant and cholesterol-handling pathways, NAD+/sirtuin signaling, and ER-phagy, and is the sole electron input to mitochondrial amidoxime-reducing component 1 (mARC1). This review grades every link in the axis across the steatosis–cirrhosis–hepatocellular carcinoma spectrum, reporting effect estimates with sample sizes and test statistics alongside a study-level appraisal of clinical relevance. The common MTARC1 p.A165T variant protects against all-cause cirrhosis (odds ratio, 0.91; 95% CI, 0.89–0.94; P = 2.3 × 10−11; 12,361 cases, 790,095 controls), with lower hepatic fat, liver enzyme levels, and low-density lipoprotein cholesterol levels. Germline mARC1 deletion reduces picrosirius red fibrosis area by 24–50% depending on diet, without altering histological disease activity, whereas partial protein reduction confers no protection. Critically, therapeutic hepatocyte-directed knockdown loses its anti-fibrotic effect when started at higher disease burden and in the choline-deficient model: efficacy depends on the depth, compartment, and timing of inhibition. Deep, hepatocyte-restricted mARC1 inhibition by GalNAc-conjugated oligonucleotides—which also avoids a male-predominant cardiac liability—is therefore the most credible near-term strategy, only in pre-cirrhotic F2–F3 disease. CYB5R3 activation, and its combination with mARC1 inhibition, remain unproven, and no clinical trial of this axis has been reported. Falsifiable in vivo and pharmacodynamic biomarker roadmaps are proposed, together with the efficacy, delivery, and safety uncertainties specific to advanced cirrhosis and a non-invasive pharmacodynamic framework.

Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate and a substantial long-term surveillance burden. However, current detection and surveillance strategies rely largely on invasive cystoscopy and urine cytology, which are limited by patient discomfort, suboptimal adherence, and insufficient sensitivity, particularly for low-grade disease. This mini review examines the role of liquid biopsy in the detection, risk stratification, and surveillance of NMIBC. It summarizes current evidence on circulating tumor DNA, circulating tumor cells, exosomes and extracellular vesicles, urinary tumor DNA, and DNA methylation and protein biomarkers in blood or urine. For detection, urine-based molecular assays complement cystoscopy and cytology in the noninvasive assessment of patients with suspected bladder cancer. For risk stratification, molecular detection of residual disease and longitudinal biomarker changes help identify patients at increased risk of recurrence or progression. During surveillance, urine-based assays support earlier recurrence detection and, in selected settings, help reduce the frequency of cystoscopy. Overall, liquid biopsy is a promising minimally invasive complement to conventional NMIBC management although technical standardization and prospective clinical validation are required before routine implementation.

Machine-learning approaches that combine predictive performance with model interpretability may improve lung cancer status classification. This study aimed to develop and internally evaluate an Explainable Precision Screening Framework for lung cancer risk classification using demographic, behavioral, and symptom-based variables from a publicly available dataset.

This retrospective cross-sectional study analyzed a publicly available Kaggle dataset containing 309 records, including 270 labeled as lung cancer and 39 as non-cancer. Six models—logistic regression, support vector machine (SVM), random forest, LightGBM, XGBoost, and a stacking ensemble—were compared using a stratified hold-out test set and repeated stratified five-fold cross-validation. Performance was assessed using classification metrics with bootstrap 95% confidence intervals (CIs). A separate Shapley additive explanations (SHAP) analysis was applied to the standalone SVM model for exploratory feature attribution.

Across all models, accuracy ranged from 85% to 92% (ROC-AUC: 0.93–0.95). The stacking ensemble achieved 0.92 accuracy (95% CI: 0.85–0.98), 0.94 sensitivity (95% CI: 0.88–1.00), 0.75 specificity (95% CI: 0.40–1.00), 0.96 precision (95% CI: 0.89–1.00), 0.95 F1 score (95% CI: 0.91–0.99), and 0.95 ROC-AUC (95% CI: 0.89–0.99). Its PR-AUC was 0.993 (95% CI: 0.981–0.999), and its Brier score was 0.074 (95% CI: 0.037–0.121). SHAP analysis identified smoking, yellow fingers, coughing, chest pain, wheezing, shortness of breath, and age as the features contributing most strongly to its predictions.

Within this public retrospective dataset, the stacking ensemble was among the highest-performing models, whereas separate SHAP analysis of the standalone SVM model identified the features contributing most strongly to its predictions. Given the marked class imbalance, the absence of a reported clinical reference standard for the source labels, the framework requires independent validation in clinically verified multicenter cohorts before clinical use.