Wen Gao

Background: Metabolic reprogramming within the tumor microenvironment is a pivotal barrier to effective immune checkpoint blockade (ICB). While programmed death ligand 1 (PD-L1) is well characterized as a ligand inhibiting T-cell function, its intrinsic ‘reverse signaling’ role in regulating tumor metabolism and shaping the immune landscape remains poorly understood. Here, we investigated the metabolic determinants of resistance to anti-programmed cell death protein 1 (anti-PD-1) therapy and the underlying molecular mechanisms. Methods: Integrated metabolomics and transcriptomics were performed on tumor samples from patients with non-small cell lung cancer and cell lines. Mechanisms were delineated using RNA sequencing, cleavage under targets and tagmentation assays, metabolic flux analysis, and coculture systems. The therapeutic efficacy of targeting metabolic effectors was evaluated in syngeneic mouse models and correlated with immune profiling. Results: We identified a distinct metabolic signature characterized by aberrant pyruvate accumulation in patients resistant to anti-PD-1 therapy. Mechanistically, we demonstrate that antibody-mediated ligation of PD-L1 triggers an intrinsic endoplasmic reticulum (ER) stress response via the PERK–ATF4–CHOP axis. ATF4 acts as a transcriptional activator that directly upregulates pyruvate dehydrogenase kinase 4 (PDK4) (blocking pyruvate oxidation) and glutaminase (GLS) (promoting glutaminolysis), creating a ‘dual-hit’ metabolic rewiring that drives intracellular pyruvate build-up. Subsequently, tumor-secreted pyruvate is taken up by tumor-associated macrophages (TAMs) via MCT1, inducing mitochondrial reactive oxygen species accumulation and driving them into a state of cellular senescence. These senescent TAMs upregulate PD-L1 via STAT3 signaling, thereby reinforcing an immunosuppressive feedback loop. Pharmacological inhibition of PDK4 and GLS effectively abolished pyruvate accumulation, prevented macrophage senescence, and restored CD8+ T-cell cytotoxicity. Conclusions: Our study identifies a novel ‘PD-L1–ER stress–pyruvate–macrophage senescence’ axis as a key mechanism underlying primary resistance to ICB. These findings highlight the non-canonical reverse-signaling function of PD-L1 in metabolic remodeling and propose that targeting the PDK4/GLS-dependent pyruvate surge offers a promising therapeutic strategy to sensitize tumors to anti-PD-1 immunotherapy.

Background: 10%–30% of patients with lung adenocarcinoma (LUAD) and leptomeningeal metastasis (LM) respond poorly to conventional and targeted therapy. The relationship between genetic subtypes and both MRI features and survival outcomes remains poorly understood in this patient population. Purpose: To explore the genetic phenotypes among LUAD‐LM patients who respond poorly to conventional and targeted therapy, and to compare the MRI characteristics and survival outcomes among these genetic phenotypes: Study Type: Retrospective. Population: 110 LUAD‐LM patients (LU confirmed by histology, LM by cytology) treated with intrathecal chemotherapy, comprising 43 with epidermal growth factor receptor exon 21 L858R mutations (EGFR 21), 29 with EGFR exon 19 deletions (EGFR 19), and 38 with Non‐Classic and Other Mutations (NCOM). Field Strength/Sequence: 3.0T; axial T ₁ ‐ and T ₂ ‐weighted turbo spin echo (TSE), fluid‐attenuated inversion recovery (FLAIR), diffusion‐weighted echo‐planar imaging (DWI), and post‐contrast 3D T ₁ ‐weighted gradient‐echo sequences (3D T1WI). Assessment: MRI morphologic features (including LM presence, presentation subtype, and lesion distribution) were independently reviewed by three radiologists (Y. J., W. S., and M. Y., with 5, 5, and 15 years of experience, respectively), following standardized criteria. Intracranial progression‐free survival (iPFS) and overall survival (OS) were analyzed from the date of LM diagnosis based on clinical follow‐up. Statistical Tests: Chi‐square or Fisher's exact tests for imaging features; Kaplan–Meier method with log‐rank tests for survival analysis; Cox proportional hazards regression for multivariable analysis. A two‐sided p < 0.05 was considered significant. Results: MRI ‐negative LM was significantly more frequent in EGFR 19 (65.5%). However, these patients showed no survival advantage ( iPFS : p = 0.10, OS : p = 0.64) over other groups. Among MRI ‐positive LM patients, EGFR 21 affected significantly fewer lobes (< 4 lobes: 85.7%) compared to NCOM (< 4 lobes: 45.5%). Median iPFS in EGFR 21 was significantly longer than in NCOM (12.0 vs. 6.5 months; 95% CI : 5.16–7.84), and OS was also significantly longer (18.0 vs. 10.2 months; 95% CI : 4.79–15.61) Data Conclusion: This radiogenomics study showed that EGFR mutation subtypes are associated with MRI features and survival outcomes in LUAD‐LM patients with poor response to conventional and targeted therapies. Evidence Level: 3 Technical Efficacy Stage: 4

Background: Patients with thymic epithelial tumors (TETs) frequently show coexistence of various paraneoplastic syndromes, which severely affect their survival. Moreover, there is a lack of effective clinical treatment strategies for patients with unresectable metastatic and recurrent TETs. Methods: To explore the genetic alterations that play a key role in the pathogenesis of TETs, we analyzed the whole-exome sequencing data from 24 patients diagnosed to have TETs at the First Affiliated Hospital of Nanjing Medical University. Results: Mutated genes in TETs were enriched in several hormone-associated pathways such as insulin secretion; Cushing syndrome; parathyroid hormone; and thyroid hormone, as well as multiple classical tumor-associated pathways, including cAMP, Notch, PI3K-Akt, and WNT signaling pathway. Patients with paraneoplastic syndromes (PNS) exhibited more pronounced alterations in hormone-related pathways. RHPN2 is the most frequently mutated gene in TETs. TETs with RHPN2 mutation showed greater upregulation of the hormone-related signaling pathways such as thyroid hormone and parathyroid hormone as well as a trend toward shorter survival of patients. Conclusion: We analyzed the possible role of hormones in TETs on several levels, explored potential links between hormones and other genetic mutations, and found that RHPN2 may be a potentially valuable gene.

Drug combination is a promising therapeutic strategy for complex diseases. However, only a small fraction of potential drug combinations exhibit true synergistic effects, making the prediction of drug synergy a critical yet challenging task. In this study, we propose BridgeSyn, a novel bridge fusion framework for drug synergy prediction. BridgeSyn leverages the knowledge from pretrained biological language models to enrich both drug compound and cell line representations. We introduce a bridging fusion mechanism that employs a set of shared latent tokens derived from global features, serving as a semantic interface to effectively fuse the representations of drug pairs and cell lines. By combining biological prior knowledge with this fusion strategy, BridgeSyn can capture complex biological interactions and achieve superior prediction results. Extensive experiments on two public datasets demonstrate that BridgeSyn consistently outperforms existing computation methods.

Correction on: Wang F, Li C, Li S, Zhang T, Yu T, Zhang W, He J, Yuan M and Gao W (2025) CTbased radiomics integrated model for brain metastases in stage III/IV ALK-positive lung adenocarcinoma patients. Front. Oncol. 15:1585930. doi: 10.3389/fonc.2025.1585930In the published article, there was an error in the legend for Figure 7as published. The rad_score threshold was computed using the surv_cutpoint function not Xtile, which was mistakenly attributed to wrong reference. Upon rechecking the sources, I confirmed that this should instead cite the reference(Xi J, Yin J, Liang J, Zhan C, Jiang W, Lin The rad_score threshold (0.20) was computed by surv_cutpoint function for dividing patients into high-and low-risk groups (A). The Kaplan-Meier cumulative event curve for survival status shows that the patients in the low-risk group showed a significantly better PFS compared to those in the high-risk group in the training cohort (B) and validation cohort (C), whereas the survival difference between the low-and high-risk groups was not statistically significant in the external test cohort (D). But the longer medial survival was seen in the lowrisk group than those in the high-risk group in three cohorts.The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.In the published article, the reference for [38] The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.In the published article, there was an error. The error in our manuscript originated from an oversight in referencing a key study. We deeply regret this oversight and have taken steps to ensure such errors do not occur in future work.A correction has been made to Materials and methods, PFS analysis, Paragraph 1. This sentence previously stated: "According to the cutoff of the Rad_score, participants were categorized into a high-risk group and a low risk group by Xtile (38)."The corrected sentence appears below: "According to the cutoff of the Rad_score, participants were categorized into a high-risk group and a low risk group using the surv_cutpoint function in R survminer package (38)."The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.In the published article, there was an error. The error in our manuscript originated from an oversight in referencing a key study. The statistical approach for PFS analysis in our manuscript need to be added.

Purpose: This study aims to develop and validate a computed tomography (CT)-based radiomics nomogram for predicting brain metastases in lung adenocarcinoma with anaplastic lymphoma kinase positive (ALK+).Methods: Of 117 patients were retrospectively reviewed, among them, 34 patients from another hospital. Patients were randomly allocated into training (70%) and validation (30%) cohorts. We integrated the radiomics score (Rad_score) with independent clinic-radiological variables to build the nomogram model. The DeLong test and Decision curve analysis (DCA) were utilized to evaluate performance of three models. Cox regression analysis was used to identify statistically significant factors for progression-free survival (PFS) in ALK-positive lung adenocarcinoma, with model discrimination evaluated by the concordance index (C-index). The patients were divided into low-risk and high-risk groups. Finally, the Log-rank test was used to ascertain significant differences between the two risk groups in the nomogram models.Results: From Stage III/IV lung cancer cases, we extracted 1834 radiomics features, identifying two features can serve as standalone indicators of BM. The AUC of radiomics model was 0.905 and 0.880 in the validation and external test cohort, respectively. The AUC of nomogram model was 0.940 in the validation cohort and 0.896 in the external test cohort, respectively. The statistical difference merely exists between nomogram and clinical model (P=0.009, P=0.012) in validation and external test cohorts, respectively. The multivariate Cox regression analysis showed that lymphadenopathy (Hazard ratio (HR) = 5.41, 95% confidence interval (CI): 1.38-21.16, P = 0.015) and rad_score (HR = 25.67, 95% CI: 5.41–121.94, P< 0.001) were independent predictive factors for PFS. The Concordance index (C-Index) for training cohort (C-Index(95%CI):0.887 (0.826-0.956); testing cohort:0.798 (0.676-0.938), and the external cohort with 0.927 (0.857-0.996). Patients in the low-risk group showed a significantly better PFS compared to those in the high-risk group in the training cohort and validation cohort (P all < 0.010, respectively), whereas the results were not consistent in the external test cohort (P=0.130).Conclusion: CT-derived radiomic signatures show promise as a tool for predicting BM within 2 years after detection of primary lung adenocarcinoma detection with ALK+. Combing these radiomic signatures with clinical features can enhance risk stratification for these patients.

Background: Thymic epithelial tumors (TETs), categorized predominantly as thymoma (T) or thymic carcinoma (TC), face a challenging prognosis and limited treatment options. Although chemotherapy remains the established treatment for advanced TETs, its responses tend to be short-lived. The emergence of immunotherapy, particularly programmed cell death-1 (PD-1) and programmed death ligand-1 inhibitors (PD-L1), is increasingly being regarded as a promising new treatment option for various malignancies.Methods: Herein, we present a case series of eight patients with TETs who received tislelizumab treatment at Jiangsu Provincial Hospital between 2021 and 2023. All cases were histologically confirmed as either thymoma or thymic carcinoma. Among these eight cases, six patients (5 thymic carcinomas [TC] and 1 thymoma [T]) received tislelizumab in combination with chemotherapy following multiple cycles of prior chemotherapy without achieving significant therapeutic response. Two TC patients were administered this combination regimen as first-line treatment. Following the initiation of immunotherapy, patients received tislelizumab at a dose of 200 mg every three weeks until disease progression or the occurrence of unacceptable toxicity. Treatment response was assessed by the investigators according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 guidelines.Results: The 8 patients described had a median age of 59 years (range, 47-72). During the course of immunotherapy, five patients (62.5%) achieved partial response, and notably, even after transitioning to maintenance therapy with tislelizumab, the lesions continued to shrink, with the longest sustained partial response lasting over 2 years. Three patient (37.5%) experienced stable disease as their best response to immunotherapy. Among all these patients, three patients (37.5%) demonstrated initial efficacy but subsequently exhibited progressive disease (median progression-free survival of 14 months). All patients are still being followed up, with the longest PFS extending to 31 months. Notably, five of the eight patients underwent PD-L1 testing and were all found to be negative. Despite this, no immune-related Grade 3–5 adverse events (AEs) were reported and all AEs were manageable with supportive measures. Grade 1–2 AEs were adrenal insufficiency (n=1), thyroid dysfunction (n=1), and pneumonia (n=1).Conclusions: Our study findings suggest that the combination of immunotherapy and chemotherapy yields durable clinical responses in patients with TETs, suggesting its potential as a safe and effective first-line treatment strategy for advanced TETs. Notably, the therapeutic benefits of chemo-immunotherapy appear to extend beyond patients with high PD-L1 expression (≥50%), indicating that this treatment approach may not be strictly limited to individuals with elevated PD-L1 levels.

Background: High expression levels of programmed death receptor 1 (PD-1) and its ligand 1 (PD-L1) have been observed in thymic epithelial tumors (TET), suggesting their potential as prognostic indicators for disease progression and the effectiveness of immunotherapy in TET. The conventional method obtaining PD-L1 was challenging due to invasive sampling and tumor heterogeneityMethods: A total of 124 patients with pathologically confirmed TET (57 PD-L1 positive, 67 PD-L1 negative) were retrospectively enrolled and allocated into training and validation cohorts in a ratio of 7:3. Radiomics features were extracted from T1-weighted, T2-weighted fat suppression, and apparent diffusion coefficient (ADC) map images to establish a radiomics signature in the training cohort. Multivariate logistic regression analysis was conducted to develop a combined radiomics nomogram that incorporated clinical, conventional MR features, or ADC model for evaluation purposes. The performance of each model was compared using receiver operating characteristics analysis, while discrimination, calibration, and clinical efficiency of the combined radiomics nomogram were assessed.Results: The radiomics signature, consisting of four features, demonstrated a favorable ability to predict and differentiate between PD-L1 positive and negative TET patients. The combined radiomics nomogram, which incorporates the peri-cardial invasion sign, ADC value, WHO classification, and radiomics signature, showed excellent performance (training cohort: area under the curve [AUC] = 0.903; validation cohorts: AUC = 0.894). The calibration curve and decision curve analysis further confirmed the clinical usefulness of this combined model. The decision curve analysis demonstrated the clinical utility of the integrated radiomics nomogram.Conclusions: The radiomics signature serves as a valuable tool for predicting the PD-L1 status of TET patients. Furthermore, the integration of radiomics nomogram enhances the personalized prediction capability.

Background: Due to the acceleration of the aging population and the prevalence of unhealthy lifestyles, the incidence of cardiovascular diseases (CVDs) in China continues to grow. However, due to the uneven distribution of medical resources across regions and significant disparities in diagnostic and treatment levels, the diagnosis and management of CVDs face considerable challenges. Objective: The purpose of this study is to build a cardiovascular diagnosis and treatment knowledge base by using new technology, form an auxiliary decision support system, and integrate it into the doctor’s workstation, to improve the assessment rate and treatment standardization rate. This study offers new ideas for the prevention and management of CVDs. Methods: This study designed a clinical decision support system (CDSS) with data, learning, knowledge, and application layers. It integrates multimodal data from hospital laboratory information systems, hospital information systems, electronic medical records, electrocardiography, nursing, and other systems to build a knowledge model. The unstructured data were segmented using natural language processing technology, and medical entity words and entity combination relationships were extracted using IDCNN (iterated dilated convolutional neural network) and TextCNN (text convolutional neural network). The CDSS refers to global CVD assessment indicators to design quality control strategies and an intelligent treatment plan recommendation engine map, establishing a big data analysis platform to achieve multidimensional, visualized data statistics for management decision support. Results: The CDSS system is embedded and interfaced with the physician workstation, triggering in real-time during the clinical diagnosis and treatment process. It establishes a 3-tier assessment control through pop-up windows and screen domination operations. Based on the intelligent diagnostic and treatment reminders of the CDSS, patients are given intervention treatments. The important risk assessment and diagnosis rate indicators significantly improved after the system came into use, and gradually increased within 2 years. The indicators of mandatory control, directly became 100% after the CDSS was online. The CDSS enhanced the standardization of clinical diagnosis and treatment. Conclusions: This study establishes a specialized knowledge base for CVDs, combined with clinical multimodal information, to intelligently assess and stratify cardiovascular patients. It automatically recommends intervention treatments based on assessments and clinical characterizations, proving to be an effective exploration of using a CDSS to build a disease-specific intelligent system.

Background: Circular RNAs (circRNAs), which are a new type of single-stranded circular RNA, have significant involvement in progression of many diseases, including tumors. Currently, multiple circRNAs have been identified in hepatocellular carcinoma (HCC). Our study aims to investigate the function and mechanism of circDCAF8 in HCC. Methods: The expression of circDCAF8 (hsa_circ_0014879) in HCC and para-carcinoma tissue samples was determined using quantitative real-time polymerase chain reaction (qRT-PCR). The biological function of circDCAF8 in HCC was confirmed by experiments conducted both in vitro and in vivo. And the relationship between circDCAF8, miR-217 and NAP1L1 was predicted by database and verified using qRT-PCR, RNA-binding protein immunoprecipitation (RIP) and dual-luciferase reporter assays. Exosomes isolated from HCC cells were utilized to assess the connection of exosomal circDCAF8 with HCC angiogenesis and regorafenib resistance. Results: CircDCAF8 is upregulated in HCC tissues and cell lines, and is linked to an unfavourable prognosis for HCC patients. Functionally, circDCAF8 was proved to facilitate proliferation, migration, invasion and Epithelial-Mesenchymal Transformation (EMT) in HCC cells. Animal examinations also validated the tumor-promoting characteristics of circDCAF8 on HCC. Besides, exosomal circDCAF8 promoted angiogenesis in HUVECs. Mechanistically, circDCAF8 interacted with miR-217 and NAP1L1 was a downstream protein of miR-217. CircDCAF8 promoted NAP1L1 expression by sponging miR-217. In addition, exosomes may transfer circDCAF8 from regorafenib-resistant HCC cells to sensitive cells, where it would confer a resistant phenotype. Conclusion: CircDCAF8 facilitates HCC proliferation and metastasis via the miR-217/NAP1L1 axis. Meanwhile, circDCAF8 can promote angiogenesis and drive resistance to regorafenib, making it a viable therapeutic target for HCC patients.