PURPOSE: To investigate the antitumor efficacy of a novel antimicrobial peptide WK-13-3D, against triple-negative breast cancer (TNBC) and elucidate its mechanism of action via targeting binding immunoglobulin protein BiP and modulating the AKT/mTOR pathway to disrupt autophagy-lysosome homeostasis. METHODS: TNBC cell lines MDA-MB-231 and MDA-MB-468 were employed as in vitro models. Cell viability and clonogenic potential were assessed using CCK-8 and colony formation assays. Autophagy-related proteins (LC3-II/I, p62) and phosphorylation levels of key AKT/mTOR pathway components were analyzed by Western blotting. Autophagosome formation was visualized via transmission electron microscopy and immunofluorescence. Autophagic flux was monitored using mCherry-GFP-LC3 tandem fluorescent adenovirus. Lysosomal acidification was evaluated by LysoTracker Red and acridine orange (AO) staining. Functional rescue experiments were conducted using the AKT activator SC79. The in vivo antitumor activity of WK-13-3D was validated in a nude mouse xenograft model. RESULTS: WK-13-3D significantly suppressed TNBC cell viability and clonogenicity. Mechanistically, WK-13-3D concurrently inhibited AKT/mTOR signaling and directly bound to BiP, triggering endoplasmic reticulum (ER) stress. Notably, WK-13-3D treatment led to autophagic flux blockade, evidenced by autophagosome accumulation (increased LC3-II/I ratio) and impaired degradation of the autophagic substrate p62, without compromising lysosomal acidification or hydrolytic function. Activation of the AKT/mTOR pathway partially reversed WK-13-3D-induced autophagy dysregulation, whereas BiP overexpression restored autophagic flux and enhanced lysosomal activity. These dual-targeting effects converged to exert a potent and enhanced antitumor response. CONCLUSIONS: WK-13-3D disrupts autophagy-lysosome crosstalk in TNBC via coordinated inhibition of AKT/mTOR signaling and BiP-mediated ER stress, representing a promising lead candidate that provides mechanistic insights for TNBC treatment and warrants further preclinical investigation.

PURPOSE: This retrospective study investigated the impact of Allergic Rhinitis (AR) patients receiving Allergen-specific Immunotherapy (AIT) on Coronavirus Disease 2019 (COVID-19) infection, clinical characteristics, and prognosis. METHODS: This was a single-center, retrospective cohort study that included patients with AR who received subcutaneous desensitization with Aloege or sublingual desensitization from 10 December to 31 March 2023 at Changsha The Second Xiangya Hospital, China. RESULTS: The investigation comprised 761 outpatients, including 336 individuals with allergic rhinitis who underwent AIT and 425 healthy subjects. Patients with AR who received AIT treatment showed a significantly lower risk of COVID-19 infection in the multivariate analysis (OR=0.48, p = 0.005). The probability of developing hyposmia after contracting COVID-19 was reduced in the experimental cohort compared to the control cohort (OR = 0.39, 95 % CI 0.27‒0.57, p < 0.001). Additionally, the test group experienced a reduction in sore throat (OR = 0.32, 95 % CI 0.22‒0.47, p < 0.001) and a shorter duration of systemic symptoms (OR = 0.49, 95 % CI 0.34‒0.7, p < 0.001) following COVID-19 infection. Furthermore, it was discovered that the impact on quality of life after COVID-19 infection was significantly different between the two groups, with the test group exhibiting a higher quality of life compared to the control group (p < 0.001). CONCLUSION: During a concentrated or sudden outbreak of COVID-19, patients with AR who received AIT had a lower proportion of hyposmia than the healthy population, and the severity of sore throat and its impact on quality of life were relatively mild.

BACKGROUND AND OBJECTIVES: In this study, we aim to evaluate trends in smoking cessation among breast cancer patients, with a particular focus on the impact of breast reconstruction surgery, and to assess if breast reconstruction surgery represents a unique opportunity for intervention. METHODS: We performed a retrospective analysis of active smokers with a new diagnosis of breast cancer who were treated with any surgical or non-surgical intervention at our institution between 2015 and 2024. Quitting was defined as continuous cessation for at least 30 days. Patients who quit were followed for at least 6 months after cessation. RESULTS: One hundred twenty-seven patients were identified. Mean age was 56 years (range 35-87). Eighty patients (63%) underwent surgery without reconstruction, 26 patients (20%) underwent surgery with reconstruction, and 21 patients (17%) received non-surgical treatment only. Overall, 26% (34/127) of patients quit smoking. Among patients undergoing surgical treatment, patients undergoing reconstruction were significantly more likely to quit smoking than those without reconstruction (50% [13/26] vs. 23% [18/80]; p = 0.007). Patients receiving reconstruction were also significantly more likely to quit preoperatively (77% [10/13] vs. 33% [12/18]; p = 0.048). Median time from initial visit with surgical oncology to surgery was longer among reconstructive patients who quit pre-operatively (90.5 days [IQR: 44-164]) than those who quit post-operatively or did not quit (45 days [IQR: 26-68]; p = 0.13). CONCLUSIONS: Patients receiving breast reconstruction are significantly more likely to quit smoking than those who do not. Longer median time to surgery among patients who quit pre-operatively emphasizes the need for targeted cessation interventions that allow for timely oncologic care.

Previous studies have shown that DARS is highly expressed in patients with myeloproliferative neoplasms (MPN), and these patients have higher disease burdens. However, the mechanism by which DARS promotes the proliferation of MPN cells remains unclear. Here, we explored the tumor-intrinsic role of DARS in human MPN cell models and the associated molecular mechanisms using an integrated multi-omics approach. DARS depletion suppressed the proliferation of MPN cells in vitro and xenograft tumor growth in vivo, induced cell-cycle arrest, and promoted apoptosis. Metabolomic analysis identified 190 differential metabolites associated with DARS depletion in MPN cells, many of which were enriched in cancer-related pathways. Transcriptomic analysis showed that DARS depletion was associated with altered expression of more than 2,000 genes; integrated analysis of transcriptomic and metabolomic data indicated potential involvement of calcium signaling, pyrimidine metabolism, and nucleotide metabolism. Re-analysis of independent public MPN datasets further supported the association of DARS with disease context and immune-infiltration features. Overall, our results support a pro-proliferative role of DARS in human MPN cell models. DARS depletion was associated with PI3K/AKT-related transcriptional and metabolic alterations, and reactivation of PI3K/AKT partially rescued the phenotypic changes induced by DARS depletion.

BACKGROUND AND OBJECTIVES: Neuroendocrine tumors are a rare and heterogeneous group of neoplasms that frequently cause carcinoid syndrome, characterized by diarrhea, flushing, and carcinoid heart disease. A recent therapy for carcinoid syndrome involves inhibition of tryptophan hydroxylase, the rate-limiting enzyme in serotonin synthesis, using telotristat ethyl. Telotristat has demonstrated clinical control of carcinoid syndrome; however, its potential antitumoral effects remain unclear. This study aimed to evaluate the antitumor activity of telotristat ethyl alone and in combination with everolimus in neuroendocrine tumor models. METHODS: Cell viability was assessed in three neuroendocrine tumor cell lines of pancreatic (BON-1, QGP-1) and intestinal (HROC57) origin following treatment with telotristat ethyl. Combination treatments with telotristat ethyl and everolimus or other antitumoral agents were evaluated for effects on cell viability, apoptosis, and cell cycle distribution. In vivo efficacy was examined in nude mice bearing BON-1-derived xenografts treated with telotristat ethyl, everolimus, or the combination. Tumor growth, toxicity, proliferation (Ki67), and apoptosis (active caspase-3) were analyzed. RESULTS: Telotristat ethyl reduced cell viability in all three neuroendocrine tumor cell lines. Combination with everolimus, but not with other antitumoral treatments, synergistically decreased cell viability, induced apoptosis, and reduced the proportion of cells in the G2/M phase. In nude mice bearing BON-1 xenografts, combined treatment with telotristat ethyl and everolimus arrested tumor growth without signs of toxicity compared with single treatments. At the end of treatment, tumors from combination-treated mice showed a reduction in proliferation (Ki67) comparable to single-treated groups and an increase in apoptosis as indicated by active caspase-3. CONCLUSIONS: Telotristat ethyl exhibits antitumoral activity in neuroendocrine tumor models in vivo. Moreover, the combination of telotristat ethyl and everolimus, two therapies already used in clinical practice, may represent a safe and effective therapeutic strategy for neuroendocrine tumors.

BACKGROUND: Advancements in PET technologies and reconstruction methods have improved spatial resolution and noise in PET/CT, making respiratory motion artefacts more impactful on image quality. The motion-match CT (MMCT) algorithm estimates the phase of a helical CT and warps it towards the end expiration of a patient's respiratory cycle. This MMCT-attenuation correction (MMCTAC) can then be used to reconstruct whole body FDG PET/CT data. The performance of these images were compared to those reconstructed using the uncorrected clinical standard attenuation correction from helical CT (normAC), indicating the proportion of cases where MMCTAC images could reduce motion artefact and improve lesion detectability. METHODS: A sequential cohort of 145 whole-body FDG PET/CT scans was previously evaluated for a data-driven gating study, which identified the gated region of interest (ROI) in 98 high-motion patients. 23 of these high-motion patients had small lesions (n=36) identified in the ROI by a clinician to undergo qualitative analysis comparing the two attenuation correction maps used. PET data were reconstructed using BSREM iterative reconstruction with 3 different portions of the collected data: 1. Ungated 6 min, 2. Ungated 3 min, 3. Quiescent period gated. These reconstructions were generated using normAC or MMCTAC, totaling six reconstructions for semi-quantitative analysis and clinician evaluation. An experienced radiologist ranked the 6 images and scored them on a 5-point Likert Scale for lesion detectability, diagnostic confidence, and image quality. RESULTS: In 52% (n=12) of patients with lesions, the clinician ranked all three MMCTAC images higher than the three normAC equivalent reconstructions. Lesion detectability and diagnostic confidence scores retained positive mean differences across the three MMCTAC reconstructions compared to normAC. Similarly, the SUVmax values for 36 lesions demonstrated a significant increase (p < 0.05) for MMCTAC versus normAC images across all three reconstructions. CONCLUSIONS: The MMCT algorithm successfully enables the phase-matching of a helical CT to the PET data to reduce the presence of respiratory motion artefact for FDG PET/CT images. Overall, the motion-matched CTAC image scores demonstrated the algorithm's efficacy at reducing the motion artefacts present in FDG PET/CT images, improving diagnostic capability for assessment of lesions in the thorax and upper abdomen.

BACKGROUND: The efficacy of deep learning-based artificial intelligence segmentation (AI-seg) in Lu-DOTATATE dosimetry remains underexplored. This study evaluates AI-seg's contouring accuracy, dosimetric reliability, and time efficiency. METHODS: We analyzed 23 patients treated with Lu-DOTATATE. Four medical physicists (MPs) and four radiological technologists (RTs) manually delineated liver (including lesions), spleen, and kidneys on CT images. The most experienced MP modified AI-seg outputs to establish a reference contour, confirmed by a board-certified physician. Both the manual and AI-seg contours were checked against this reference using the Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean distance to agreement (MDA). Maximum, mean, and minimum absorbed doses were calculated from a single time-point image using SurePlan™ MRT (MIM Software Inc.) to assess dosimetric implications. The total time required for dosimetry-including image reconstruction, segmentation, and absorbed dose calculation-was compared between the manual and reference methods. RESULTS: Only one liver delineation by an MP required correction. Median (IQR) DSCs for liver, spleen, and kidneys were 0.955 (0.950-0.961), 0.929 (0.898-0.944), and 0.929 (0.918-0.942) for manual, 0.988 (0.946-0.998), 0.965 (0.858-0.995), and 0.994 (0.985-0.999) for AI-seg, respectively. All organs met the acceptable DSC threshold ([Formula: see text]0.8). Median HD in liver exceeded 10.0 mm for both methods, with AI-seg exceeding 30.0 mm in a few cases (liver: 3/23; spleen: 2/23) due to hepatomegaly. The median MDA in manual and AI-seg was below 2.0 mm. Median mean absorbed doses in the reference was 4.03 (1.69-5.81) Gy for liver, 1.55 (1.30-2.50) Gy for spleen, and 2.03 (1.45-2.44) Gy for kidneys. Only the kidneys absorbed dose from AI-seg differed significantly, showing a 1.4% increase. Dosimetry using the reference method took significantly less time than the manual approach (47.0 [30.0-58.0] min vs. 54.3 [49.5-67.0] min, p = 0.014). CONCLUSIONS: AI-seg with minor adjustment enables faster yet accurate absorbed dose estimation in Lu-DOTATATE. Despite segmentation challenges in hepatomegaly cases, MPs and RTs demonstrated competent contouring performance, supporting collaborative dosimetry workflows with physician oversight.

Circulating tumor DNA (ctDNA) has emerged as a promising biomarker of minimal or molecular residual disease and real-time tumor burden in gastrointestinal cancers, but its clinical integration remains uneven across disease settings. This narrative review summarizes current evidence in colorectal, gastroesophageal, pancreatic, and biliary cancers, with emphasis on practical testing windows, assay selection, and evidence-aligned interpretation. The strongest data support ctDNA use in resected colon cancer, particularly stage II disease, where postoperative ctDNA refines recurrence risk assessment and has enabled treatment de-escalation in selected prospective settings. In rectal, upper gastrointestinal, pancreatic, and biliary cancers, current evidence is mainly prognostic and less practice-defining. Serial ctDNA may support postoperative risk stratification, surveillance prioritization, and trial selection, but treatment escalation or de-escalation should preferably remain within prospectively studied contexts. Key barriers include assay standardization, false-positive calls, turnaround time, reimbursement, and the need to distinguish prognostic validity from proven clinical utility.

INTRODUCTION: Whether programmed cell death ligand 1 (PD-L1) expression differs between different specimen types remains unclear. This meta-analysis aimed to compare PD-L1 expression between biopsy and surgical specimens in non-small cell lung cancer (NSCLC). METHODS: We searched the PubMed and Web of Science databases from January 2015 to December 2025 to evaluate PD-L1 expression detection across different types of specimens. The QUADAS-2 tool was used to evaluate the quality of the included studies. Review Manager 5.4 and Stata 17.0 were used to calculate the relative risk (RR) and the corresponding 95% confidence interval (95% CI). RESULTS: This meta-analysis of 13 studies involving 966 patients demonstrated that no significant difference in PD-L1 positivity rates between biopsy and surgical specimens was observed at the 1% cutoff (RR = 0.85, 95% CI [0.71 - 1.01], P = 0.07), but a significant difference was detected at the 50% cutoff (RR = 0.76, 95% CI [0.65 - 0.90], P < 0.01). Similar findings were observed in patients without neoadjuvant therapy. Additionally, PD-L1 expression in tumor cells was significantly lower with the SP142 assay than with other antibodies at both the 1 and 50% cutoffs. CONCLUSIONS: PD-L1 expression may differ between biopsy specimens and surgically resected specimens in patients with advanced NSCLC, even in patients who have not received neoadjuvant therapy. Consequently, PD‑L1 status evaluated from biopsy specimens should be interpreted with caution in clinical practice. In addition, the selection of PD-L1 immunohistochemistry (IHC) detection methods may also affect the evaluation results.

BACKGROUND: Breast cancer (BC) represents one of the most prevalent malignancies among women worldwide. Despite substantial advances in diagnostic and therapeutic modalities and pharmacological interventions in recent years, the accurate assessment of prognosis continues to pose formidable challenges. Exosomes exert pivotal roles in tumorigenesis, tumor progression, and immune modulation, with exosome-related mRNAs emerging as promising novel prognostic biomarkers. Nevertheless, the role of exosome-related mRNA in BC oncogenesis, progression, and prognostic prediction warrants further extensive investigation. METHODS: The study constructed the exosome-related signature and validated the results in the Gene Expression Omnibus database (GSE9893). Candidate genes were selected based on differential expression, univariate Cox, and LASSO regression to build a prognostic risk model. Its predictive accuracy was evaluated using Kaplan-Meier (K-M) survival curves and time-dependent ROC analysis. Furthermore, the ESTIMATE and CIBERSORT algorithms were employed to elucidate the association between the prognostic risk signature and tumor immune microenvironment (TIME), alongside comparative analyses of HLA gene and immune checkpoint expression differences. GSEA was subsequently conducted to explore the potential biological pathways associated with the prognostic risk signature and individual signature genes. In addition, qRT-PCR was performed in breast cancer cell lines to experimentally validate the expression of signature genes. Finally, a nomogram was developed by combining risk scores with clinical features. RESULTS: Ultimately, four exosome-related mRNAs were identified to construct a prognostic risk signature. In the TCGA cohort, this signature effectively stratified patients into high- and low-risk groups with respect to overall survival (OS), as evidenced by robust predictive performance in ROC analysis. In the GEO validation cohort (GSE9893), results aligned with the training cohor. Immunological analyses showed the risk score's association with the tumor microenvironment (TME), encompassing stromal scores, immune cell abundance, and HLA gene and immune checkpoint levels. In vitro qRT-PCR validation demonstrated expression trends consistent with the computational predictions. The nomogram integrating clinical characteristics demonstrated calibration and substantial clinical utility. CONCLUSION: This study innovatively developed a BC prognostic risk signature based on exosome-related mRNAs, which not only effectively predicts patient survival but also elucidates its intimate association with the TIME. This signature offers novel insights and substantial clinical utility for personalized prognostic evaluation and treatment decision-making in BC patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterized by high heterogeneity and poor prognosis. Despite the importance of natural killer (NK) cells in innate immunity, their role in the HCC microenvironment remains unclear. This study aims to develop an NK-cell-related signature to optimize prognostic prediction and personalized therapy. METHODS: Single-cell RNA sequencing (scRNA-seq) identified candidate genes. Differential expression and univariate Cox analyses were performed on an integrated cohort comprising The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) and the Gene Expression Omnibus (GEO) dataset GSE76427. To ensure data consistency, technical batch effects were eliminated using the ComBat algorithm. The integrated cohort was randomly assigned to training and testing sets (1:1). A prognostic model was constructed via Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression (seed = 2) and validated in an independent ICGC-LIRI-JP cohort. Survival differences and model accuracy were evaluated using Kaplan-Meier and Receiver Operating Characteristic (ROC) curves. Finally, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm and the Tumor Immune Dysfunction and Exclusion (TIDE) database were applied to characterize immune cell infiltration and predict immunotherapy response, respectively. RESULTS: From 790 initial candidates, 18 prognosis-related DEGs associated with NK-cell-related cellular programs were identified, which classified HCC into two distinct subtypes. A three-gene prognostic model (AP1S3, RPL23, and HM13) was established, showing high predictive accuracy in both the internal testing set and an independent external ICGC-LIRI-JP cohort. High-risk patients exhibited significantly poorer survival and specific clinical profiles. Notably, the risk score served as an independent prognostic factor, and a combined nomogram offered superior predictive power. Further characterization of the tumor microenvironment revealed that a high-risk score correlated with a remodeled stroma and a distinct potential for immunotherapy response. Additionally, high-risk patients showed increased sensitivity to targeted agents, such as sorafenib. Finally, the expression patterns of these signature genes were validated via RT-qPCR and immunohistochemistry (IHC), further supporting their role as key components of the identified prognostic landscape. CONCLUSION: The established risk score model, reflecting an NK-cell-related immune landscape, effectively predicts HCC prognosis and provides an integrated molecular landscape for optimizing personalized interventions.

Disulfidptosis, a newly identified form of programmed cell death (PCD) that was discovered in 2023, occurs specifically in cells with high SLC7A11 expression when glucose is scarce. The underlying mechanism involves NADPH depletion, which triggers severe disulfide stress and ultimately causes the actin cytoskeleton to collapse. In recent years, researchers have increasingly focused on the potential role of disulfidptosis in liver diseases. Current evidence mainly supports its involvement in hepatocellular carcinoma (HCC), with some preliminary data also suggesting connections to liver cirrhosis and metabolic liver disorders. This review critically synthesizes the molecular mechanisms underlying disulfidptosis, explores its possible links to various liver conditions based on the available evidence, and assesses the potential of disulfidptosis-related genes (DRGs) as exploratory tools for diagnosis, prognostic stratification, and exploratory therapeutic prediction. Together, these insights provide a foundation for understanding liver disease pathogenesis and may guide future research efforts, pending rigorous experimental and clinical validation.

INTRODUCTION: In vivo data on volumetric laser efficiency and clinical outcomes of the p-Tm: YAG laser from large multicenter cohorts remain limited. The present study aimed to evaluate the real-world in vivo volumetric ablation efficiency of the p-Tm: YAG laser during flexible ureterorenoscopy (FURS), with secondary assessment of clinical outcomes and safety in a multicenter cohort. METHODS: We conducted a retrospective multicenter cohort study including adult patients (≥ 18 years) who underwent p-Tm: YAG-based FURS for ureteral and/or renal calculi at three tertiary referral centers between 2023 and 2025. Preoperative stone volume was quantified using manual three-dimensional CT segmentation. Laser-on time (LOT), total delivered energy, and laser settings were prospectively recorded. Volumetric ablation speed (mm³/s) and energy consumption (J/mm³) were calculated using standardized definitions based on segmented pre- and postoperative stone volumes in patients with postoperative non-contrast CT (NCCT). Stone-free rate (SFR) was assessed 1-3 months postoperatively using NCCT and classified as Grade A (no residual fragments), Grade B (residual fragments ≤ 2 mm), and Grade C (residual fragments ≤ 4 mm). In patients without postoperative NCCT, SFR was assessed by intraoperative endoscopic evaluation and analyzed separately. RESULTS: Of 222 screened patients, 167 met the inclusion criteria. Median preoperative stone volume was 987 mm³ (IQR 329-3,124), and 47% of patients presented with multiple/complex stones. Median LOT was 21.4 min, and median total delivered energy was 12 kJ. In the 108 patients with paired volumetric data and postoperative NCCT, median ablation speed was 0.55 mm³/s (IQR 0.30-0.95), and median energy consumption was 13 J/mm³ (IQR 8-23). In this NCCT subgroup, SFR were 47%, 59%, and 66% for Grade A, B, and C, respectively. Among the 59 patients assessed endoscopically only, complete stone clearance was visually assessed in 20 patients (34%). Overall, 45 patients (27%) required additional stone-related treatment. Complications were uncommon, with 4.8% Clavien-Dindo grade I-II events and 0.6% grade III events; no grade IV-V complications were observed. CONCLUSION: In this multicenter real-world cohort, p-Tm: YAG laser lithotripsy showed measurable volumetric efficiency and was associated with acceptable stone clearance and a favorable safety profile during FURS. These findings support the clinical feasibility of this technology in routine endourological practice; however, prospective comparative studies are warranted to further define its relative performance compared with established laser platforms.

Hepatocellular carcinoma (HCC) represents a major contributor to cancer-associated mortality globally. Due to the frequently asymptomatic early course and high proportion of late-stage detection, patient outcomes remain unsatisfactory, underscoring the demand for innovative diagnostic markers and treatment approaches. This study was dedicated to characterizing expression profiles and evaluating the prognostic value of myristoylated alanine-rich C kinase substrate-like 1 (MARCKSL1) in HCC. Through integrated analysis of data from the TCGA-LIHC and GSE14520 cohorts alongside in vitro validation, we comprehensively assessed MARCKSL1 expression patterns and their links with clinicopathological parameters. Public cohort analyses showed that MARCKSL1 was significantly upregulated in HCC tissues, and qRT-PCR analysis further supported elevated MARCKSL1 expression in selected HCC cell lines. This upregulated MARCKSL1 expression showed a positive correlation with various poor prognostic clinical factors, namely advanced tumor stage, higher histological grade, and elevated alpha-fetoprotein (AFP) concentration. Moreover, elevated MARCKSL1 expression was linked to reduced overall survival (OS) and disease-specific survival (DSS). A prognostic model built on these observations demonstrated reliable performance in predicting patient survival. Functional annotation analyses implicated MARCKSL1 in essential processes including cell cycle control, and its expression showed a significant association with immune cell infiltration, indicating a potential connection to the tumor immune landscape. Additionally, MARCKSL1 expression correlated with m⁶A methylation markers, suggesting its potential implication in the correlative networks of these epigenetic pathways during HCC development. We also established a predictive competing endogenous RNA (ceRNA) network, identifying key long non-coding RNAs (lncRNAs) that may co-regulate MARCKSL1 via specific microRNAs. Preliminary in vitro assessment supported increased MARCKSL1 transcript expression in selected HCC cell lines. In summary, MARCKSL1 is overexpressed in HCC and closely tied to aggressive clinicopathological traits and inferior prognosis, offering new insights into the evaluation of candidate prognostic biomarkers for HCC.

PURPOSE: To evaluate the intrarenal temperature (IRT) variations using the 9.2Fr and 7.5Fr flexible ureteroscopes featuring direct-in-scope suction (DISS-FURS) in an in-vitro set up in different inflow and outflow irrigation conditions. MATERIALS AND METHODS: The experimental setting consisted of two DISS-FURS: a 7.5Fr ureteroscope with a 3.6Fr working channel (WC), and a 9.2Fr scope with a 5.1Fr WC. An Aldaver upper urinary tract model was used, and IRT was continuously monitored using a calibrated digital thermometer. Temperature dynamics were assessed by measuring the time required for IRT to increase from physiological baseline (37 °C) to 43 °C, from 43 to 50 °C, and the time required for IRT to decrease from 50 °C to 43 °C and to 37 °C following laser deactivation. Measurements were performed using a 272-µm laser fiber. A Holmium: YAG laser was activated continuously at power settings of 10 and 20 W. Experiments were conducted under the following conditions: with/without ureteral access sheath (UAS), with gravity-driven irrigation alone, with manual pump-assisted irrigation, and with/without activation of the DISS system. Thermal dose was calculated using the cumulative equivalent minutes at 43 °C (CEM43). A total of 32 experimental cohorts (96 experiments) were analyzed. RESULTS: For the 7.5Fr DISS FURS, the safest combinations, defined by slower IRT rise and more controlled thermal profiles, were those with manual pump-assisted irrigation, use of UAS and no DISS activation. IRT increased more rapidly at 20 W in cohorts combining DISS activation without manual pump assistance and without UAS. In experiments performed with the 9.2Fr DISS FURS, manual pump-assisted irrigation and the use of UAS represented the safest maneuver for maintaining controlled IRT levels. The larger 5.1Fr WC allowed increased inflow, prolonging the time to critical temperature thresholds even when DISS was activated. CONCLUSIONS: The combination of manual pump-assisted irrigation, UAS use, and the 9.2 Fr DISS flexible ureteroscope with a 5.1 Fr working channel provided the most favorable intrarenal temperature profile. In contrast, simultaneous activation of suction and laser with the smaller 7.5Fr scope, particularly without adequate irrigation, may increase thermal risk and should be used with caution. These findings suggest that optimizing irrigation dynamics and coordinating suction use are key to minimizing thermal risks during DISS-assisted FURS. Further clinical studies are warranted.

BACKGROUND: Histologic variants (HV) of urothelial carcinoma (UC-V) and non-urothelial carcinomas (NUC) of the bladder and urinary tract are aggressive malignancies with poor prognosis and limited response to platinum-based chemotherapy. Despite their biological particularities and distinct immune microenvironments, these HV subtypes are under-represented in immune checkpoint blockade (ICB) trials. METHODS: PEMBROBLAD is a French national multicenter retrospective study conducted across 24 centers. We included patients with advanced UC-V or NUC who received second-line anti-PD-(L)1 monotherapy after progression on platinum-based chemotherapy between 2016 and 2022. Primary endpoint was overall survival (OS); secondary endpoints included progression-free survival (PFS), objective response rate (ORR) and safety. RESULTS: We included 129 UC-V and 34 NUC. With a median follow-up was 21.9 months, the median OS was 8.6 [95% confidence interval (CI), 5.3-11.2] months, with 8.5 [95% CI 5.3-10.9] months for UC-V and 10.5[95% CI 3.5-22.8] months for NUC. The median PFS was 2.6 [95% CI 2.1-3.4] months with 2.5 [95% CI 2.0-3.4] months for the UC-V group and 2.6 [2.0-3.4] months for the NUC group. ORR was 31.4% overall (complete response 15.3%, partial response 16.1%). In multivariable analysis, ECOG performance status ≥ 2 was independently associated with both poorer OS (HR 3.30, 95% CI 1.22-8.92; p = 0.018) and PFS (HR 2.32, 95% CI 1.52-3.54; p < 0.001). Pembrolizumab treatment was associated with improved PFS (HR 0.53, 95% CI 0.31-0.81; p = 0.017). Grade ≥ 3 immune-related adverse events occurred in 10.8% of patients, with no treatment-related deaths. CONCLUSIONS: Anti-PD-(L)1 monotherapy shows clinical benefit in advanced UC-V and NUC after platinum failure.

To overcome resistance to MEK inhibitors such as selumetinib in neurofibroma, we developed a metabolism-targeted nanotherapeutic based on a pH-responsive silver nanoparticle platform (AgNP-PEG-TC) for delivering Triacsin C (TC), an inhibitor of long-chain acyl-CoA synthetases, to disrupt tumor-associated lipid metabolism. AgNP-PEG-TC was synthesized and characterized for its physicochemical properties, drug-loading efficiency, and pH-responsive release behavior. Its antitumor effects were assessed in human neurofibroma cells, including selumetinib-resistant cells, and in normal Schwann cells by examining proliferation, apoptosis, migration, and invasion. In vivo therapeutic efficacy and biosafety were evaluated in neurofibroma xenograft models. Bulk RNA sequencing, lipidomics, and protein analyses were performed to investigate the underlying mechanisms. AgNP-PEG-TC demonstrated stable colloidal properties and successful pH-sensitive release. It selectively reduced neurofibroma cell growth, migration, and invasion while promoting apoptosis, with minimal effects on normal cells. In xenograft models, AgNP-PEG-TC significantly inhibited tumor growth and showed good biocompatibility. Multi-omics analyses indicated that its antitumor activity was associated with ACSL4 downregulation, remodeling of arachidonic-acid-enriched phospholipids, enhanced lipid peroxidation, and increased lipid-droplet accumulation, suggesting heightened ferroptosis susceptibility. Notably, AgNP-PEG-TC synergized with MEK inhibitors and restored antitumor responses in resistant neurofibroma cells. These findings establish a metabolism-nanotechnology synergy in which AgNP-PEG-TC-mediated ACSL4 inhibition and lipid metabolic reprogramming resensitize MEK inhibitor-resistant neurofibromas to therapy. The platform functions as both a targeted drug carrier and a modulator of tumor lipid homeostasis, offering a promising combinatorial strategy.

OBJECTIVE: This review systematically evaluates why CA derivatives have failed to transition from bench to bedside despite superior preclinical performance. SIGNIFICANCE: Cinnamaldehyde (CA) clinical translation is stymied by a biopharmaceutical paradox: promising efficacy is negated by poor aqueous solubility (≈1 mg/mL), rapid first-pass metabolism, and a short plasma half-life (≈1.7 h). Also, the reactive α,β-unsaturated aldehyde moiety often triggers Pan-Assay Interference (PAINS) behavior. KEY FINDINGS: We identify three primary chemical strategies that circumvent native CA's limitations: (1) Aldehyde masking (e.g., N-oxide conversion in PX5-9), which improves aqueous solubility by >2000-fold; (2) α-substitution (e.g., α-bromo-4-chloro CA), which modulates Michael acceptor reactivity to achieve an 87-fold higher selectivity index than the parent compound; and (3) Stimuli-responsive polymer conjugation (e.g., ROS-labile thioacetals), which enables tumor-microenvironment-triggered CA release and reduces cytotoxicity to IC ≫ 1600 µM in normal cells. While these derivatives show compelling efficacy in oncological, antiviral, and anti-inflammatory models, progress is halted by a lack of human pharmacokinetic profiling and "safety bridging" toxicology. CONCLUSION: The science of CA derivatives is more mature and future development must shift from broad scaffold exploration to targeted translational consortia focused on four priority leads (Compound 5, HCAG, PX5-9, and Compound 6f). Addressing the "- disconnection" through chemoproteomic target validation and IND-enabling PK studies is the essential next step for advancing this reactive scaffold into clinical trials.

Phosphoinositide 3-kinase δ (PI3Kδ) has emerged as a promising therapeutic target for inflammatory respiratory diseases. Herein, we report the design and synthesis of a novel series of 4-methylquinazoline derivatives as potent and highly selective PI3Kδ inhibitors for the treatment of acute lung injury (ALI). Guided by structure-based drug design optimization of a -PI3K inhibitor scaffold, the lead compound was identified, exhibiting single-digit nanomolar potency against PI3Kδ and exceptional selectivity over other class I PI3K isoforms. Mechanistically, compound effectively modulated immune responses by suppressing pro-inflammatory M1 macrophage polarization while promoting the anti-inflammatory M2 phenotype. Possessing favorable pharmacokinetic properties, compound was evaluated in murine models of LPS-induced ALI and septic lung injury, where it significantly attenuated pulmonary edema and inflammatory infiltration. Collectively, compound represents a promising preclinical candidate for the therapeutic intervention of ALI.

While traditionally used in early-phase oncology trials, we explore the benefits of Bayesian methods in clinical trial design, emphasizing their application in rare neurological disease trials. Focusing in this report on a potential redesign of the Phase II trial of SAR445088 in chronic inflammatory demyelinating polyneuropathy (CIDP), we compare the performance of the original design to two potential optimization alternatives. First, we retained continuous outcomes to preserve information. In the second modification, we propose the use of information borrowing through Bayesian hierarchical models (BHM). BHM for subgroup analysis increase precision in individual subpopulations by borrowing information from the whole study population and pooling individual estimates towards the overall estimate. Such models are used in basket trials which aim to evaluate a single targeted therapy across multiple settings that share a common characteristic. We found that the proposed optimizations demonstrate notable power gains. We advocate enhancing the efficiency of neurological disorders research through the implementation of this optimized Bayesian approach.

Liquid biopsy is a promising biomarker for cancer detection and prediction of therapy responses. In this study, we developed new antibody-based sandwich assays to measure three extracellular vesicle (EV) subsets that express cell surface vimentin (CSV) and co-express epithelial cell adhesion molecule (EpCAM) or PD-L1 in plasma. Fifty-seven non-small cell lung cancer (NSCLC) patients who underwent complete resection and 89 stage IV NSCLC patients who received anti-PD-1 antibody were enrolled. Correlations between the plasma EV subsets at baseline and various clinicopathological factors were evaluated. Plasma EpCAM/CSV-EV levels were significantly higher in stage I NSCLC patients compared to healthy donors, suggesting this may be a valuable biomarker for detecting early-stage NSCLC. High plasma CSV/CSV-EV levels at baseline were significantly correlated with a poor prognosis after treatment, both in the surgery cohort and the anti-PD-1 antibody cohort, which suggests that this may be useful for predicting the post-treatment prognosis in NSCLC patients. High plasma CSV/PD-L1-EV levels at baseline were significantly correlated with poor postoperative prognosis. However, high plasma CSV/PD-L1-EV levels at baseline were significantly correlated with a favorable clinical response and prognosis following anti-PD-1 antibody treatment in stage IV NSCLC. Therefore, plasma CSV-related EV subsets at baseline may be attractive biomarkers for early cancer detection (EpCAM/CSV), prediction of postoperative prognosis (CSV/CSV), and prediction of clinical responses and prognosis after anti-PD-1 antibody therapy (CSV/PD-L1). These EV subsets can be easily measured repetitively at appropriate timing. These novel liquid biopsies may be additional and complementary diagnostic biomarkers for NSCLC patients.

Over the past two decades, omics and big data have shifted plant molecular biology from single-gene, hypothesis driven studies to systems level, data driven discovery. As datasets expand in scale and diversity, bioinformatics software has become essential for routine analysis and interpretation. However, the efficiency of data exploration and evidence integration has not kept pace with data growth, leaving many datasets underutilized and only slowly translated into biological insight. A central bottleneck is the widening gap between the limited data analysis skills of many experimental biologists and the increasing complexity of biological data. TBtools was developed to narrow this gap by providing low-barrier, interactive functions for common plant omics tasks, and it has been broadly adopted. Here, we use it as a decade-long case study to determine why certain local tools achieve broad adoption in plant omics, distill eight actionable design recommendations, and propose four capacity pillars for next-generation local workbenches: project-level data management, reproducible workflow construction, elastic remote computing, and AI-assisted navigation and automation. Together, these lessons provide a practical roadmap for accelerating the translation of omics data into biological insight.

OBJECTIVE: To construct a machine learning model using contrast-enhanced CT radiomics and clinical indicators, aiming to improve the diagnostic accuracy for lymph node metastasis in children with peripheral neuroblastoma and provide practical evidence for clinical diagnosis and treatment. METHODS: A total of children with pathologically confirmed neuroblastoma were retrospectively enrolled between February 2014 and December 2024, and then randomly divided into a training set and a test set via random sampling. Radiomics features were extracted separately from CT images of the arterial phase and venous phase. In the training set, four radiomics models, one clinical model, and one combined model incorporating radiomics and clinical features were constructed respectively using the filtered radiomics features and clinical features. All models were validated against the pathological reference standard in the test set, and the area under the receiver operating characteristic curve of each model was calculated. The clinical utility of each model was evaluated using the decision curve analysis curve. The optimal model was visualized with a nomogram, and the diagnostic gain of the nomogram for evaluating lymph node metastasis in neuroblastoma children was quantified via human-machine comparison. RESULTS: A total of 225 children with neuroblastoma were enrolled in this study, (with a mean age of 2.23 ± 2.34 years and an age range of 0-13 years). All subjects were randomly divided into a training set (n = 157) and a test set (n = 68) at a ratio of 7:3. Compared with four radiomics models (Arterial phase, Venous phase, Delta-Absolute, Delta-Relative) and one clinical model (Ki-67), the nomogram integrating radiomics and clinical features (Arterial phase + Delta-Relative + Ki-67) exhibited superior diagnostic performance in evaluating lymph node metastasis in pediatric peripheral neuroblastoma. The AUC values of the nomogram reached 0.937 and 0.829 in the training set and validation set, respectively. In the human-machine comparison experiment, the diagnostic accuracy of radiologists for lymph node metastasis in neuroblastoma children was improved by 21% when assisted by the nomogram. CONCLUSION: The nomogram combining contrast-enhanced CT radiomics and clinical indicators has significant diagnostic value in evaluating lymph node metastasis in pediatric patients with peripheral neuroblastoma. Moreover, it can substantially improve the diagnostic accuracy of radiologists with different levels of clinical experience.