BackgroundBiliary tract infections (BTIs) are clinically important conditions characterized by complex heterogeneous microbial profiles. However, the complete spectrum of implicated microorganisms, particularly anaerobic species and polymicrobial signatures, remains insufficiently defined due to the inherent limitations of conventional microbiological methods.MethodsIn this retrospective study, bile samples obtained from patients with BTIs were analyzed using DNA- and RNA-based metagenomic next-generation sequencing (mNGS) alongside conventional microbiological techniques, including culture and smear microscopy. The breadth of microbial detection across these methods was systematically compared. Microbial profiles were further stratified according to clinical variables, including sex, infection site, and disease severity.ResultsMetagenomic sequencing revealed a broad array of microorganisms, including bacteria, fungi, viruses, and parasites, with bacteria constituting the predominant component. A considerable proportion of identified bacterial taxa were obligate or facultative anaerobes, and polymicrobial detection patterns were frequently observed. Gram-positive genera such as Streptococcus and Enterococcus, as well as Gram-negative genera including Klebsiella and Escherichia, were commonly detected. Male patients had higher detection rates of Enterococcus and Enterobacter, whereas Staphylococcus species were more frequently identified in gallbladder infections than in bile duct infections. In this cohort, DNA-based mNGS showed broader microbial detection coverage than RNA-based mNGS and conventional culture methods.ConclusionThese results underscore the complexity of microbial detection in bile-associated infections and support the value of metagenomic sequencing for comprehensive microbial characterization in BTIs. The marked heterogeneity in microbial distribution indicates that bile samples from patients with BTIs commonly show polymicrobial profiles rather than a uniform single-organism profile.

Objective : Cholangiocarcinoma (CCA) is a highly aggressive malignancy with limited therapeutic options and poor prognosis. Erianin has demonstrated broad-spectrum antitumor activity, yet its role in CCA and tumor immunity remains unclear. Methods : The cytotoxic and growth-inhibitory effects of erianin were evaluated in CCA cell lines and xenograft models. Apoptosis induction, mitochondrial dysfunction, and suppression of focal adhesion kinase (FAK) signaling were examined. The effects of erianin on cellular senescence, senescence-associated secretory phenotype (SASP) factor secretion, and senescent cell clearance were assessed. Pharmacological FAK inhibition was applied to validate the FAK-mediated cell growth and senolytic activity of erianin. The therapeutic efficacy of erianin alone or combined with anti-PD-L1 therapy was evaluated in senescent tumor-bearing mice. Results : Erianin exhibited significant cytotoxicity and induced mitochondrial apoptosis in CCA cells. Rather than inducing senescence, erianin eliminated senescent cells by promoting apoptosis and reduced SASP factor secretion. Erianin effectively inhibited FAK phosphorylation, and FAK blockade further enhanced its antiproliferative and senolytic activity. Moreover, erianin reprogrammed senescence-induced macrophage polarization from an M2- to an M1-like phenotype and increased antitumor immune cell infiltration within the tumor microenvironment. Importantly, erianin synergized with anti-PD-L1 therapy to achieve superior tumor control and prolonged survival in vivo . Conclusions : Erianin exerts potent antitumor effects in CCA by inhibiting FAK-mediated cell growth and senolytic activity, thereby enhancing antitumor immunity and immune checkpoint inhibitor efficacy. These findings identify erianin as a promising senolytic and immunotherapy adjuvant for CCA.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death, and anti-silencing function 1B histone chaperone (ASF1B) has been implicated in several cancers. This study aimed to investigate the role and molecular mechanism of ASF1B in HCC. ASF1B expression was analyzed using the TIMER2, GEO, Oncomine, and GEPIA2 databases, as well as western blotting. Cell viability, cell cycle distribution, and apoptosis were assessed via CCK-8 assay and flow cytometry, respectively. Survival analysis and immune infiltration analysis were performed using the TIMER2 database, and enrichment analysis was conducted via Metascape. Results showed that ASF1B expression was significantly higher in HCC tissues than in normal tissues, and high ASF1B expression predicted poor prognosis and was associated with higher tumor stage. Knockdown of ASF1B by siRNA significantly reduced cell viability, promoted apoptosis, and induced G1 phase cell cycle arrest in SNU-423 cells. Moreover, ASF1B expression was positively correlated with the infiltration levels of immune cells and tumor microenvironment signature cells, particularly functional T cells. Enrichment analysis further indicated that ASF1B may contribute to HCC progression through mechanisms involving cell cycle, cell division and differentiation, and DNA replication and repair. Collectively, these findings suggest that ASF1B overexpression predicts poor prognosis and increased immune infiltration in HCC, highlighting ASF1B as a potential therapeutic target for this malignancy.

To evaluate the efficacy and safety of adding bronchial artery chemoembolization (BACE) to chemotherapy in combination with immune checkpoint inhibitors (ICIs) in patients with lung squamous cell carcinoma (LUSC). This retrospective study included 71 patients with advanced LUSC treated at Lishui Central Hospital between January 2020 and March 2025. Patients received either chemotherapy plus ICIs (Chemo + ICIs group) or chemotherapy plus ICIs combined with BACE (Chemo + ICIs + BACE group). All patients were histologically diagnosed with LUSC. Baseline clinical characteristics, including demographics, comorbidities, tumor burden, and performance status, were recorded. Tumor response was evaluated using the response evaluation criteria in solid Tumors (RECIST) version 1.1. Progression-free survival (PFS) and overall survival (OS) were calculated using the Kaplan–Meier method. Prognostic factors were further explored through univariate and multivariate Cox proportional hazards regression analyses. Adverse events (AEs) were recorded throughout the treatment period and graded according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0. Baseline characteristics were balanced between groups. The objective response rate (ORR) was 59.26

Background Cholangiocarcinoma is a highly malignant tumor of the biliary system with a poor prognosis. The epigenetic molecular mechanisms underlying its occurrence and progression remain unclear, and no effective molecular targets for clinical treatment have been identified. Methods EdU incorporation, colony formation, growth curve, TUNEL, transwell, and wound-healing assays were used to assess the role of KAT2B in cholangiocarcinoma proliferation, metastasis, and apoptosis. Immunoaffinity purification coupled with mass spectrometry was used to identify KAT2B-interacting proteins, GST pull-down assays were conducted to assess direct interactions between KAT2B and its binding partners, and RNA sequencing, ChIP, and chromatin-binding assays were performed to investigate the regulatory mechanisms of KAT2B and histone demethylases on target genes. In vivo experiments further validated KAT2B's role in cholangiocarcinoma proliferation and metastasis. Results KAT2B is significantly downregulated in cholangiocarcinoma. Both in vitro and in vivo experiments demonstrated that KAT2B significantly inhibits cholangiocarcinoma cell proliferation and metastatic potential. Mass spectrometry revealed that KAT2B interacts with histone demethylase KDM6B, forming a KAT2B/KDM6B complex that regulates the downstream target genes PTPN12 and CDKN1A. Disruption of any component of this complex leads to reduced chromatin binding and occupancy of the PTPN12 and CDKN1A promoter region by the remaining components. The increased proliferation induced by KAT2B interference can be rescued by PTPN12 overexpression, and changes in proliferation phenotype caused by KAT2B are dependent on its enzymatic activity. Conclusions KAT2B acts as a tumor suppressor by promoting PTPN12 expression through its interaction with KDM6B, thereby inhibiting cholangiocarcinoma proliferation.

e15531 Background: Hepatic arterial infusion (HAI) chemotherapy combined with systemic therapy may better control the progression of liver lesions. Up to the present, there have been no relevant reports on the application of liposomal paclitaxel formulation in combined systemic treatment of gastrointestinal cancer with liver metastasis. Here, we assessed the safety and primary efficacy of HA131 (a novel cationic liposomal paclitaxel formulation) administered via HAI plus systemic chemotherapy for gastrointestinal cancer with liver metastases. Methods: This open-label dose escalation and dose expansion phase I clinical trial was conducted at two centers in China. Based on accelerated titration followed by a 3+3 design with five planned HA131 dose levels, the initial dose of HA131 was 11 mg/m 2 followed by 22, 33, 44, and 55 mg/m 2 administered on Day 15 every 3 weeks for about 6–8 cycles. XELOX (±bevacizumab) administration was repeated every 3 weeks accordingly. The primary endpoint of the study was safety; secondary endpoints included pharmacokinetics (PK) charactertics, overall response rate (ORR), disease control rate (DCR), duration of response (DOR), progression-free survival (PFS), which were assessed using the RECIST v1.1/mRECIST criteria. Results: Twenty-three patients were enrolled between March 13, 2023, and December 12, 2025. Evaluation of five HA131 dose levels revealed no dose-limiting toxicities. All patients experienced treatment-emergent adverse events (TEAEs), with 87.0% experiencing TEAEs of grade 3 or higher. The most common HA131-related TEAEs were thrombocytopenia, elevated procalcitonin, lymphopenia, neutrophilia, and leukocytosis. No drug-related fatal TEAEs have been reported to date. Among the 20 evaluable patients, ORR was 85.0% per RECIST and 90.0% per mRECIST; in patients with colorectal liver metastases (n = 18), ORR was 88.9% and 94.4% accordingly; both with a DCR of 100.0%. All patients exhibited tumor shrinkage following treatment. After a median follow-up of 13.3 months, the median PFS has not been reached (6 patients had disease progression). The estimated 18-month PFS rate was 65.7%. In addition, nonlinear pharmacokinetic properties were observed. Conclusions: This regimen demonstrated manageable safety and notably primary efficacy, warranting further exploration in patients with gastrointestinal cancer and liver metastases. Clinical trial information: ChiCTR2300069012.

The field of nanomedicine holds great promise in healthcare, offering opportunities for precise drug delivery and accurate diagnostic techniques. However, the practical implementation of nanomedicine in clinical settings faces significant barriers. This study critically analyzes the key challenges and proposes innovative approaches to overcome them. The analysis begins by providing a comprehensive explanation of the complex obstacles in translating nanomedicine, with a particular emphasis on the critical need for coordinated regulatory guidelines, nanoformulation design criteria, and the development of standardized preclinical models that accurately simulate clinical scenarios. Additionally, this study investigated the potential toxic impacts of nanocarriers, particularly focusing on issues related to their immunogenicity, cancer biology, and biocompatibility. To enhance the translation process, various innovative solutions, including AI-based drug design, developing next-generation nanomedicines, drug design based on the biology of cancer, merging other advanced technologies, etc., have been suggested. By addressing these challenges, we can expedite the development of safe and effective nanomedicines, ushering in a new era in healthcare.

To compare drug-eluting transarterial chemoembolization (DE-TACE) followed by systemic chemotherapy versus systemic chemotherapy alone for advanced lung adenocarcinoma that has progressed after targeted therapy. All patients undergoing DE-TACE followed by systemic chemotherapy (DE-TACE group) or systemic chemotherapy alone (chemotherapy group) for stage III-IV lung adenocarcinoma from January 2018 to January 2022 were screened. On day 1 of each 21-day cycle, patients received pemetrexed (500 mg/m2) and cisplatin (75 mg/m2). Patients in the DE-TACE group received cisplatin (75 mg/m2) and gemcitabine (600 mg/m2) via the feeding arteries and then embolization using drug-eluting beads carrying gemcitabine (400 mg). DE-TACE was repeated if deemed necessary based on CT examination three weeks later. Overall survival (OS) and treatment-emergent adverse events (TEAEs) were compared in the overall cohort, as well as propensity score-matched (PSM) cohort (1:1 ratio with 0.05 caliper width). The final analysis included 62 and 69 patients in the chemotherapy and DE-TACE groups, respectively. Within the 49-month median follow-up, the median OS was 18.3 months and 33.6 months in the chemotherapy and DE-TACE groups, respectively, with a hazard ratio (HR) of 0.18 (95

Bronchial artery chemoembolization (BACE) is regarded as a safe and effective treatment method for advanced lung cancer. However, the therapeutic effects of BACE vary greatly, and there is no reliable prognostic tool in clinical practice.The aim of this study was to develop and validate a model based on computed tomography (CT) radiomics for predicting tumor response to bronchial artery chemoembolization (BACE) in advanced lung cancer (Stage III-IV) after failure of first-line therapy. A total of 227 patients from three centers enrolled this retrospective study. Radiomic features were derived from arterial phase CT images, and feature selection was performed successively using variance thresholding, univariate feature selection, and least absolute shrinkage and selection operator (LASSO) regression. Five machine learning classifiers were employed to calculate radiomics (Rad)-scores. A fusion model was developed based on the Rad-scores and independent clinical predictors. Five important radiomics features were ultimately identified and used to create the models. The LightGBM model had the highest efficiency, with an area under the curve (AUC) of 0.809 and 0.746 for the internal validation and external validation cohorts, respectively. The LightGBM-based Rad-score was combined with independent clinical predictors (ECOG Score, blood supply count, and ProGRP) to generate the fusion model, which achieved better predictive performance (AUC = 0.928, 0.875, and 0.813 in the training, internal validation, and external validation cohort, respectively) than the radiomics model (AUC = 0.872, 0.809, and 0.746, respectively) and clinical model alone (AUC = 0.750, 0.732, and 0.672, respectively). The fusion model could effectively predict the tumor response to BACE in lung cancer and help clinicians identify the appropriate surgical population.

Background:Systemic immunochemotherapy is the standard of care in patients with advanced non-small cell lung cancer (NSCLC) without druggable driving mutations, yet many older patients cannot tolerate systemic chemotherapy. Bronchial arterial chemoembolization (BACE) represents an alternative to systemic chemotherapy for this population. Methods:This retrospective single-center study included consecutive patients with stage IIIC-IV NSCLC over 65 years old who underwent BACE or systemic chemotherapy, plus a PD-1 inhibitor, in our hospital from August 2019 to October 2024. The objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were compared between the two groups. Results:The final analysis included 81 patients: 39 and 42 in the chemotherapy and BACE groups, respectively. In comparison to the chemotherapy group, the BACE group had older age (median age: 78 vs 71 years) and poorer Eastern Cooperative Oncology Group Performance Status (ECOG PS≥2: 47.6% vs 2.6%). The ORR was 73.8% in the BACE group vs 64.1% in the chemotherapy group. The median PFS was 5.4 months in the BACE group vs 5.2 months in the chemotherapy group (P=0.841). The median OS was 10.3 months in the BACE group vs 8.7 months in the chemotherapy group (P=0.449). Neither PFS nor OS differed significantly between the 2 groups in either Cox proportional hazards regression or inverse probability of treatment weighting analyses. The BACE group had lower rate of myelosuppression (28.6% vs 74.4%) but higher rate of dyspnea (16.7% vs 0%). No treatment-related serious AEs, eg, spinal artery injury due to ectopic embolism or venous thrombosis of the lower limb, were reported in the BACE group. Conclusion:In older patients with stage IIIC-IV NSCLC, BACE combined with PD-1 inhibitor showed no statistically inferior response or survival versus chemoimmunotherapy. These exploratory results require validation in large prospective cohorts.

Non-small cell lung cancer (NSCLC) is the most common pathological type of lung cancer, characterized by high morbidity and mortality. Traditional treatments, including surgery, chemotherapy, and radiotherapy, have long been the mainstay of management. However, the advent of targeted therapy and immunotherapy, particularly immune checkpoint inhibitors (ICIs) such as anti-PD-1/PD-L1 antibodies, has significantly improved patient survival outcomes. These advancements have transformed the therapeutic landscape for early-stage, locally advanced, and advanced NSCLC without actionable gene mutations. Despite multiple ICIs being approved for clinical use, critical questions regarding the optimal beneficiary population and predictive biomarkers remain under investigation. To address these challenges, the Yangtze River Delta Lung Cancer Cooperation Group (ECLUNG; Youth Committee) has formulated an expert consensus on the diagnosis and treatment of NSCLC with ICIs. This consensus aims to provide standardized and evidence-based recommendations to optimize diagnostic precision and therapeutic decision-making in NSCLC.

Pulmonary sarcomatoid carcinoma (PSC) is frequently underdiagnosed or misdiagnosed due to its rarity and complex histological features. To date, no universally recommended treatment regimens have been established for this rare subtype, and clinical management is currently extrapolated primarily from standard non-small cell lung cancer (NSCLC) protocols. Herein, we report a case of PSC initially diagnosed as multiple primary lung cancer, including adenosquamous carcinoma and adenocarcinoma (pT1N0M0, IA stage, EGFR Exon-21 L858R mutation, below the detection limit) and adenocarcinoma (pT2aN0M0, stage IB, EGFR Exon-21 L858R mutation). Despite radical surgical resection followed by targeted therapy with afatinib (30 mg orally once daily), the disease recurred. Repeat biopsy confirmed the diagnosis of PSC secondary to histological transformation. The patient achieved a durable complete response (CR) to combined immunochemotherapy. We further review the existing literature on EGFR-TKI-associated histological transformation in lung cancer, to provide guidance for the clinical management of this challenging clinical scenario.

Abstract Background Lung adenocarcinoma (LUAD) is the most prevalent and lethal subtype of non-small cell lung cancer (NSCLC), characterized by an unfavorable 5-year survival rate ranging from 10% to 20%. Neoantigen-based vaccine platforms show encouraging benefits for NSCLC patients. However, the vaccine efficacy may be limited, partially due to low immunogenicity and an immunosuppressive tumor microenvironment. This study aims to design a multiple epitopes vaccine targeting neoantigens derived from hub genes in LUAD, using immunoinformatics based strategies to explore a potential immunotherapeutic approach for LUAD. Method Multiple GEO datasets were ultilized to identify the up-regulated genes in LUAD. Protein-protein interaction networks were analyzed and hub gene were identified based on overlapping top-ranked nodes across five topological algorithms in cytoscape. Hub gene derived neoantigens were identified using TSNAdb v2.0 and futher screened for LUAD in the cBioportal database. Neoantigen-derived CTL epitopes were predicted across all 12 MHC class I supertypes and subsequently screened for antigenicity, allergenicity, and toxicity. Linear B-cell epitopes were predicted from the extracellular region of PD-L1 using established B-cell epitope prediction methods. The multi-epitope vaccine (MEV) was constructed by rationally conjugating selected CTL and B cell epitopes using appropriate peptide linker. Results 114 differential express genes were identified from GEO dataset in LUAD. Subsequently, ten hub genes were identified and validated and their expression was associated with poorer overall survival in patients with LUAD. Tumor specific neoantigens were screened from these hub genes, and eight neoantigen epitopes with antigencity, non-allergenicity and non-toxicity were selected as cytotoxic T lymphocyte (CTL) epitopes for multi-epitopes vaccine construction. The vaccine was further incorporated predicted PD-L1 derived linear B-cell epitopes, pan HLA DR-binding epitope (PADRE), a universal helper T-cell epitope and β-defensin to augment protective efficacy. The designed and optimized vaccine possessed properties of solubility, antigenicity, non-allergenicity, and non-toxicity. Molecular docking demonstrated stable and favorable binding interactions between MEV and TLR2, TLR3 and TLR4 complex, as validated by molecular dynamics simulations. Immune simulation analysis revealed that MEV had the potential to elicit a series of T cell and B cell specific immune responses. Finally, the optimized MEV was cloned in silico and successfully expressed in eukaryotic cells. Conclusions Our findings suggest that hub genes may serve as a promising source of neoantigens in lung adenocarcinoma. The multiple epitopes vaccine engineered from these hub genes shows potential for stimulating immune responses which highlights the potential of hub genes as prioritized candidates for advancing neoantigen-based vaccine development against LUAD.

Objectives:To develop and validate a preoperative multimodal model that predicts a high-risk recurrence phenotype indicative of poor disease-free survival (DFS), in order to stratify patients with stage IA non-small cell lung cancer (NSCLC). Materials and methods:This retrospective multicenter study enrolled 342 stage IA NSCLC patients from three independent centers. The high-risk recurrence phenotype (indicative of poor DFS) was defined by postoperative pathology as the presence of spread through air spaces (STAS), lymphovascular invasion (LVI), a predominant solid/micropapillary/complex glandular pattern, or a > 5% solid/micropapillary component. Deep learning features were extracted from preoperative biopsy whole-slide images (WSI) using the UNI foundation model, and CT morphological and textural features were extracted from preoperative chest CT. An early-fusion multimodal model integrating clinical, radiomics, and pathomics features was developed and evaluated with five-fold cross-validation. The Kaplan-Meier method with log-rank tests was used to assess associations between the model-predicted risk and DFS. Logistic regression identified clinical predictors of high-risk pathology. Model interpretability and clinical utility were examined with SHapley Additive exPlanations (SHAP) and calibration analysis, respectively. Results:The multimodal model achieved higher discriminative performance than each single-modality model in both the internal and external test sets. In the internal test set, it yielded an AUC of 0.76 (95% CI 0.58-0.90); in external validation, AUCs were 0.69 (95% CI 0.55-0.82) in Center 2 and 0.86 (95% CI 0.74-0.96) in Center 3. Multivariable analysis identified solid tumor density as the only independent predictor (OR = 5.13, 95% CI 1.53-17.24; P = 0.008). Model-stratified high-risk patients showed significantly inferior DFS in both the training (2-year DFS 78% vs. 99%; log-rank P < 0.0001) and external (3-year DFS 86% vs. 100%; log-rank P = 0.003) cohorts. Conclusion:The multimodal model consistently predicted the high-risk recurrence phenotype across multiple centers. This phenotype may serve as a pragmatic indicator of poor DFS to guide earlier individualized treatment decisions, including adjuvant therapy and intensified surveillance, in stage IA NSCLC.

Purpose:To compare bronchial arterial chemoembolization (BACE) plus anlotinib versus BACE alone for advanced non-small cell lung cancer (NSCLC) in the elderly. Patients and Methods:We screened all elderly patients (≥75 years of age) receiving BACE (75 mg/m2 cisplatin and 1000 mg/m2 gemcitabine via feeding arteries and then embolization using microspheres) plus anlotinib (21-day cycles, 12 mg/day on the first 14 days of each cycle) or BACE alone for advanced NSCLC (stage III and IV) with no driver gene mutations at the participating centers from January 2018 to December 2023. Overall survival (OS) was analyzed in the overall and propensity score-matched (PSM) (1:1 ratio with 0.05 caliper width) cohorts, adjusting for confounders via PSM and stabilized inverse probability of treatment weighting (sIPTW). Results:The final analysis included 95 patients: 33 and 62 in the BACE/anlotinib and BACE groups, respectively. The median lines of previous anti-tumor therapy was 1 (range, 1-3) and 1 (range, 1-3) in the BACE/anlotinib and BACE groups, respectively. The median OS was 39 months and 18.9 months in the BACE/anlotinib and BACE groups, respectively (hazard ratio 0.12, 95% confidence interval 0.06-0.24; P < 0.001). In multivariate Cox regression analysis, BACE plus anlotinib was associated with lower risk of death versus BACE alone (hazard ratio 0.15, 95% confidence interval 0.08-0.29; P < 0.001). Longer OS in the BACE/anlotinib group was also evident in the PSM and sIPTW analyses. The rate of grade ≥ 3 adverse events was 24.2% in the BACE/anlotinib group versus 12.9% in the BACE group (P = 0.16). Conclusion:In comparison to BACE, BACE plus anlotinib was associated with improved OS in elderly patients with NSCLC.

Incomplete radiofrequency ablation (iRFA) of hepatocellular carcinoma frequently results in tumor recurrence driven by residual tumor cells and an immunosuppressive microenvironment dominated by M2 macrophages. Although RFA transiently stimulates antitumor immunity through tumor antigen release, post-ablation efferocytosis of apoptotic tumor cells reinforces immune tolerance and limits durable responses. Here, we report a multifunctional liposomal nano-vaccine (R/B@Lipo-I, composed of the MerTK inhibitor BMS777607, the TLR7/8 agonist R848, and surface-anchored interferon-γ) to overcome post-RFA immunosuppression by inhibiting efferocytosis while promoting macrophage M1 polarization. Mechanistically, BMS777607 suppressed efferocytosis, converting apoptotic tumor cells into immunogenic signals, whereas R848 and interferon-γ activated NF-κB and JAK-STAT pathways to drive pro-inflammatory macrophage reprogramming. In vitro, R/B@Lipo-I induced M1 polarization, enhanced phagocytic and antigen-presenting functions, and promoted dendritic cell maturation and CD8+ T-cell activation. In vivo, it significantly potentiated RFA efficacy, suppressed tumor growth, and remodeled the tumor immune microenvironment by increasing M1 macrophages, mature dendritic cells, and cytotoxic T cells while reducing M2 macrophages and regulatory T cells. Transcriptomic analyses further confirmed activation of interferon-γ-responsive, TNF-related, and innate immune pathways. Collectively, this work establishes macrophage reprogramming via efferocytosis inhibition as an effective strategy to overcome RFA-induced immunosuppression and provides a rational nanotherapeutic approach to reduce tumor recurrence. STATEMENT OF SIGNIFICANCE: Incomplete radiofrequency ablation leaves behind an immunosuppressive tumor niche that conventional therapies fail to overcome. We demonstrate a rationally engineered liposomal nano-vaccine that hijacks apoptotic tumor signals, rewires macrophages toward a pro-inflammatory state, and orchestrates a systemic anti-tumor immune response. This strategy transforms post-ablation immune tolerance into durable immunity, offering a mechanistically guided approach to prevent tumor recurrence and advance nanomedicine-based cancer immunotherapy.

BACKGROUND:Accurate prognostic prediction is crucial for personalized treatment of patients with lung adenocarcinoma (LUAD) receiving epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). This study aims to develop and validate a pathomics-based prognostic model for EGFR-TKI-treated patients with LUAD. PATIENTS AND METHODS:Data from 122 patients with LUAD who underwent first-line EGFR-TKI therapy were retrospectively analyzed. Pretreatment whole-slide images of hematoxylin and eosin (H&E)-stained biopsy specimens were collected for annotation and feature extraction. Maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) Cox regression were applied to select features associated with disease progression. The selected features were used to construct the pathomicsScore, and its clinical relevance was assessed via Kaplan-Meier analysis. A predictive model incorporating both pathomicsScore and clinical risk factors was developed. RESULTS:Five pathomics features associated with disease progression were identified, and a pathomicsScore was developed to stratify patients into low- and high-risk groups. PFS analysis revealed longer survival in the low-risk group. Both pathomicsScore and pathological stage were independent predictors of disease progression and were integrated into a predictive model. The model achieved area under the curve (AUCs) of 0.789 and 0.728, sensitivity of 0.909 and 1, and specificity of 0.677 and 0.714 in the training and validation cohorts. Time-dependent receiver operating characteristic (ROC) curves at 6, 12, and 18 months validated the model's predictive performance. Calibration curves showed excellent agreement between predicted and observed progression probabilities. Decision curve analysis confirmed the clinical utility of the model. CONCLUSIONS:The pathomics-based model effectively predicts disease progression in patients with LUAD receiving EGFR-TKI therapy, enabling personalized treatment strategies.

e20508 Background: The clinical need for differential diagnosis of pleural effusion etiologies remains unmet. This study aimed to identify exosomal proteins from lung cancer-related pleural effusion (LCPE), tuberculous pleural effusion (TPE), and parapneumonic pleural effusion (PPE) and evaluate their diagnostic value. Methods: A total of 47 pleural effusion samples were collected. Exosomes were extracted. Bioinformatics was employed to assess differential protein expression and functional pathways, while ROC curves evaluated the diagnostic significance of these proteins. Validation of the differential proteins was conducted on an expanded sample set (46 LCPE, 23 TPE, 9 PPE) via ELISA. Results: A total of 772 proteins that are expressed in both LCPE, TPE and PPE were identified. Based on our analysis and literature research, 18 candidate biomarkers were selected. Validation using Parallel Reaction Monitoring (PRM) analysis and ELISA showed that TLN1, APOH, and PSMD8 were significantly overexpressed in LCPE compared to TPE and PPE (P < 0.05), while SYWC was overexpressed in TPE (P < 0.05). ROC analysis demonstrated excellent diagnostic accuracy of the combination of TLN1, APOH, PSMD8, and SYWC in differentiating LCPE from TPE (AUC = 0.953, 95% CI: 0.891-1.00), especially in cases with CEA < 15 ug/L in PE. The combination of HPTR, ANT3, and TLN1 effectively distinguished LCPE from PPE (AUC = 0.933, 95% CI: 0.837-1.00). ELISA further confirmed the diagnostic utility of the TLN1, SYWC, and APOH combination in distinguishing LCPE from TPE (AUC = 0.969, 95% CI: 0.935-1.00), with SYWC exhibiting remarkable accuracy in solely differentiating TPE from PPE (AUC = 100%). Conclusions: Ourstudy identified and validated pleural effusion exosomal protein biomarkers with significant diagnostic potential. The combinations of TLN1, APOH and SYWC, or ANT3, HPTR and TLN1, can serve as biomarkers for differentiating LCPE from TPE or PPE.

AIM:The aim of this study was to investigate the safety and diagnostic performance of ablation-first versus biopsy-first approach for computed tomography (CT)-guided biopsy-cryoablation of pulmonary nodules. MATERIALS AND METHODS:This retrospective analysis included 60 patients (60 pulmonary nodules) undergoing CT-guided biopsy-cryoablation between February 2023 and October 2023 at authors' centre: 28 in the ablation-first cohort and 32 in the biopsy-first cohort. The two groups were compared in technical success rate, positive biopsy rate, 1-year disease-free survival (DFS) rate, and procedure-related complications. Multivariate logistic regression was conducted to identify variables associated with haemorrhage; results are shown as odds ratio (OR) and 95% confidence interval (CI). RESULTS:The mean size of pulmonary nodules was 1.6 ± 0.5 cm. The technical success rate was 100%, the median follow-up time was 13 months, and the 1-year DFS rate was 100%. The positive biopsy rate was 78.1% (25/32) in the biopsy-first cohort and 85.7% (24/28) in the ablation-first cohort (P=0.423). The ablation-first cohort had a lower rate of total procedure-related complications (53.6% vs 78.1% in the biopsy-first cohort, P=0.04) as well as a lower rate of intraoperative bleeding (10.7% vs 40.6%, P=0.03). In the multivariable regression analysis, intraoperative haemorrhage was independently associated with perivascular nodule location (OR: 4.20, 95% CI: 1.55-11.40, P=0.005) and the biopsy-first approach (OR: 3.70, 95% CI: 1.25-11.10, P=0.018). CONCLUSION:In comparison to biopsy-first approach, ablation-first approach was associated with comparable positive biopsy rate but lower haemorrhage risk in patients undergoing CT-guided biopsy-cryoablation of pulmonary nodules.

Objective: Overexpressed CRABP2 (Cellula Retinoi Aci Bindin Protei 2D) can promote progression of various tumors. However, there are few comprehensive analysis studies on CRABP2 in lung adenocarcinoma (LUAD). Methods: Several large public databases and online analysis tools such as TCGA, GEO, GEPIA2, UALCAN, Kaplan Meier plotter, LinkedOmics, TIMER, CCLE and Metascape were used for big data mining analysis. RNA interference technology, CCK8 assay, flow cytometry and apoptosis detection, and western blot were used for in vitro experiments. Results: The study revealed that the expression level of CRABP2 in plasma were higher (mean level 31.6587 ±13.8541 ng/mL vs. 13.9328 ± 5.5805 ng/mL, p<0.0001) in patients with early stage (stage IA) LUAD compared to the control group based on analysis of 640 LUAD patients and 640 matched healthy control plasma samples from Lishui Central Hospital. Receiver Operating Characteristic curve showed that CRABP2 had certain accuracy in predicting early LUAD, with a sensitivity of 70.98%, a specificity of 94.53%, a cut-off value of 0.6551 ng/mL, and an Area Under the Curve of 0.839 (95%CI: 0.817 - 0.859, p<0.0001). Compared with normal lung tissue, CRABP2 was significantly overexpressed in LUAD (p<0.05). High CRABP2 expression in LUAD predicts poor prognosis both in Overall Survival (95%CI: 1.04-1.46, HR:1.23, p=0.018) and FP (First Progression, 95%CI: 1.10-1.65, HR = 1.35, p=0.0032) in LUAD patients. CRABP2 can promote the progression of LUAD by promoting the G2/M phase transition, inhibiting the apoptosis and participating in the regulation of immune microenvironment. The high expression of CRABP2 will inhibit the recruitment of immune effector cells and promote the proportion of immuno-suppressive cells, thus promoting the progression of LUAD. The low expression of CRABP2 may enhance the expression of CD274(PD-L1), HAVCR2 and PDCD1LG2(PD-L2) in LUAD. While, the high expression of CRABP2 may enhance the expression of CTLA4, LAG3, PDCD1(PD-1), TIGIT and IGSF8 in LUAD. Conclusions: CRABP2 may be a valuable biomarker for diagnosis, treatment and prognosis of LUAD. Patients with high expression of CRABP2 in LUAD may have suboptimal efficacy when treated with inhibitors targeting CD274, HAVCR2, and PDCD1LG2, whereas they may experience better efficacy with inhibitors targeting CTLA4, LAG3, PDCD1, TIGIT, and IGSF8. Most of cancer patients with high CRABP2 expression may benefit from immune checkpoint inhibitor therapy. Our study results have laid a positive foundation for LUAD diagnosis and therapy.