Liang Xia

Glioblastoma (GBM), the most aggressive primary brain tumor, develops within a tumor microenvironment (TME) dominated by tumor-associated macrophages (TAMs) that critically influence disease progression. Through single-cell RNA sequencing (scRNA-seq) and bioinformatic analysis, we delineated macrophage heterogeneity within the GBM TME and identified a distinct VCAN⁺ macrophage subpopulation. Pseudotime trajectory analysis revealed these cells at the terminal stage of macrophage differentiation, where they exhibit enhanced granulocyte migration and chemotaxis pathways and exhibit a pro-tumorigenic phenotype that diverges from classical M1/M2 polarization. These VCAN⁺ macrophages displayed a distinct polarization state driven by tumor necrosis factor-α (TNF-α), contributing to both a pro-inflammatory and an immunosuppressive TME. CellChat analysis demonstrated their pivotal role in intercellular communication—predominantly mediating crosstalk with GBM tumor cells, endothelial cells, and CD8⁺ T cells via SPP1 signaling: SPP1 binding to CD44 on tumor cells enhances their invasiveness, while its interaction with CD47 on CD8⁺ T cells inhibits anti-tumor immunity. Transcriptional regulatory network analysis identified that CDX2 and MXI1 serve as key transcription factors modulating VCAN⁺ macrophage function and maintaining their specific polarization and homeostasis. Through machine learning, we identified seven hub genes— C1QA , C1QC , C3 , CCL4 , CD44 , SERPINE1 , and TREM2 (all highly expressed in VCAN⁺ macrophages and involved in their polarization or intercellular communication)—and constructed an effective GBM prognostic model (AUC = 0.83 in validation cohort), underscoring their roles in immune regulation, extracellular matrix remodeling, and VCAN⁺ macrophage-mediated tumor progression. Further studies with larger cohorts and functional validation will clarify this subpopulation’s therapeutic potential and spatial distribution patterns.

Leptomeningeal metastasis (LM) arising from solid tumors signifies a late-stage complication in the cancer trajectory, often portending a poor prognosis. The prognostic factors remain elusive. Prior research has established the Neutrophil-to-Lymphocyte Ratio (NLR) as an independent prognostic marker in various malignancies; however, its prognostic utility in LM patients remains underexplored. This study aims to investigate the prognostic significance of NLR at the time of LM diagnosis. We conducted a retrospective analysis involving 490 diagnosed LM patients with solid tumor origins at Zhejiang Cancer Hospital. NLR was computed at the time of LM diagnosis. Kaplan-Meier curves and Cox proportional models were employed to examine the association between NLR and overall survival (OS). Following exclusions, the cohort comprised 384 patients. The median age was 55 years (interquartile range, IQR: 51-61.25), with a median OS was 6.45 months (IQR: 2.1–15.6) and a median NLR was 4.09 (IQR: 2.81–7.57). The median interval between LM diagnosis and NLR assessment was 1 day (IQR: 0–3). NLR proved effective in stratifying the prognosis of LM patients (HR = 1.02, 95% CI 1.01–1.04, p = 0.009). Stratifying patients based on the median NLR into low- and high-risk groups revealed that the high-risk group exhibited a 1.324-fold increased risk of death compared to the low-risk group (HR = 1.324, 95% CI 1.069–1.640, p = 0.010). Subgroup analysis indicated that NLR independently predicted prognosis specifically in the invasive breast cancer subgroup (p = 0.002). NLR emerges as a simple and accessible prognostic indicator in newly diagnosed patients with leptomeningeal metastasis stemming from solid tumors. The online version contains supplementary material available at 10.1186/s12885-026-16043-w. The online version contains supplementary material available at 10.1186/s12885-026-16043-w.

Lung cancer brain metastases refer to intracranial space-occupying lesions formed by the metastasis of tumor cells from the lung to the brain parenchyma or dissemination in the meninges. The datasets GSE200563 and GSE126548 for lung cancer brain metastasis were obtained from gene expression omnibus database with the platform files GPL21697 and GPL16791. Differentially expressed genes analysis was conducted, followed by weighted gene co-expression network analysis, construction and analysis of protein–protein interaction networks, functional enrichment analysis, gene set enrichment analysis, comparative toxicogenomics database analysis. Five hundred differentially expressed genes were identified. According to gene ontology, they were mainly enriched in terms of fucosyltransferase activity, protein–DNA complex, cAMP signaling pathway, and transcriptional misregulation in cancer. Ten core genes (JUN, IL1A, VEGFA, MMP1, EDN1, SOCS3, NOD2, NCOR2, VDR, and HDAC2) were obtained. Comparative toxicogenomics database analysis revealed associations between core genes (JUN, IL1A, VEGFA, MMP1, EDN1, SOCS3, NOD2, NCOR2, VDR, and HDAC2) and tumor cell transformation, non-small cell carcinoma, lung neoplasms, tumor invasiveness, tumor metastasis, and inflammation. JUN and MMP1 are abnormally highly expressed in lung cancer brain metastasis tissues, which may be their molecular targets.

Advances in molecular biology have extended survival for lung cancer patients with brain metastases. However, radiotherapy and surgery remain standard for non-small cell lung cancer (NSCLC) brain metastases. Existing studies assess surgical and radiotherapeutic outcomes using outdated data and lack relevant subgroup analyses. We retrospectively analyzed 298 NSCLC patients with 1–3 brain metastases. Overall survival (OS) and median OS were compared across five treatments: surgery + postoperative radiotherapy, surgery + postoperative non-radiotherapy, whole brain radiotherapy, stereotactic radiosurgery (SRS), and whole brain radiotherapy + SRS. Univariate and multivariate Cox regression analyses were conducted. Significant survival differences were noted among treatments (p = 0.0041) for patients with 1–3 brain metastases, single metastasis (p = 0.0034), age > 57 (p = 0.0001), wild-type EGFR/ALK (p = 0.0017), KPS ≥ 90 (p = 0.0379), tumor diameter ≤ 2.7 cm (p = 0.0147), and no extracranial metastasis (p = 0.0014). Surgery + postoperative radiotherapy and SRS significantly improved OS and median OS. For KPS ≥ 90, surgery + postoperative radiotherapy improved OS. Multivariate analysis identified age ≤ 57 (HR: 1.89; p < 0.001), surgery + postoperative radiotherapy (HR: 0.60; p = 0.017), and SRS (HR: 0.57; p = 0.01) as independent protective factors for OS. Surgery + postoperative radiotherapy and SRS enhance survival in NSCLC patients with 1–3 brain metastases, particularly those with wild-type EGFR/ALK, small metastases, and no extracranial metastases. For KPS ≥ 90, surgery followed by radiotherapy is recommended. SRS improves median OS in patients with KPS ≤ 80.

Glioma is the most common primary malignant brain tumor globally, with a poor prognosis due to its complex interaction with the tumor microenvironment (TME). Despite advancements in glioma treatments, patient survival remains low, highlighting the need for additional molecular investigations. Long non-coding RNA Colorectal Neoplasia Differentially Expressed (lncRNA-CRNDE) has been linked to tumorigenesis in various cancers, influencing tumor progression via the tumor microenvironment (TME). Its role in tumor-associated macrophages in gliomas is unclear. This study investigates whether lncRNA-CRNDE promotes glioma progression by modulating these macrophages. Using the TCGA database, we assessed lncRNA-CRNDE expression and its prognostic significance in glioma, and its association with the immune microenvironment. We collected 42 glioma samples of different grades from our institution. Using RT-qPCR, Western blotting, ELISA, and other cell biology techniques, we analyzed lncRNA-CRNDE’s effects on glioma proliferation and invasion and validated its role in glioma progression through animal model experiments. TCGA bioinformatic analysis showed higher lncRNA-CRNDE expression in glioma than in normal tissues, which correlated with poorer prognosis. Clinical glioma samples via RT-qPCR also showed elevated lncRNA-CRNDE in tumors, which was associated with reduced survival. Cellular experiments confirmed lncRNA-CRNDE’s promotion of glioma proliferation and invasion, which was associated with the tumor microenvironment (TME). Further studies revealed lncRNA-CRNDE’s role in macrophage polarization in the TME, enhancing glioma progression. Animal experiments confirmed lncRNA-CRNDE’s role in glioma progression. LncRNA-CRNDE is highly expressed in M2 macrophages and strongly associated with glioma progression. It is a potential prognostic marker and therapeutic target for glioma.

Background: Gliomas are recognized as the most frequent type of malignancies in the central nervous system, and efficacious prognostic indicators are essential to treat patients with gliomas and improve their clinical outcomes. The chemokine (C‐C motif) ligand 2 (CCL2) is a promising predictor for glioma malignancy and progression. However, at present, the methods to evaluate CCL2 expression level are invasive and operator‐dependent.Objective: It was expected to noninvasively predict CCL2 expression levels in malignant glioma tissues by magnetic resonance imaging (MRI)‐based radiomics and assess the association between the developed radiomics model and prognostic indicators and related genes.Methods: MRI‐based radiomics was used to predict CCL2 expression level using data obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) databases. A support vector machine (SVM)‐based radiomics model and a logistic regression (LR)‐based radiomics model were used to predict the radiomics score, and its correlation with CCL2 expression level was analyzed.Results: The results revealed that there was an association between CCL2 expression level and the overall survival of cases with gliomas, and bioinformatics correlation analysis showed that CCL2 expression level was highly correlated with disease‐related pathways, such as mTOR signaling pathway, cGMP‐PKG signaling pathway, and MAPK signaling pathway. Both SVM‐ and LR‐based radiomics data robustly predicted CCL2 expression level, and radiomics scores could also be used to predict the overall survival of patients. Moreover, the high/low radiomics scores were highly correlated with the known glioma‐related genes, including CD70, CD27, and PDCD1.Conclusion: An MRI‐based radiomics model was successfully developed, and its clinical benefits were confirmed, including the prediction of CCL2 expression level and patients' prognosis.

Background: Brain metastases are crucial in cancer progression, requiring focused efforts on the screening, early detection, and treatment. However, accurate forecasting the postoperative prognosis of patients with non-small cell lung cancer brain metastasis remains a challenge. This retrospective study aims to discern the factors that influence the prognosis of such patients. Methods: A total of 151 cases from Zhejiang Cancer Hospital were collected. Univariate analysis was conducted using Kaplan-Meier and Log-rank test, while multivariate analysis was performed using Cox proportional hazards regression model. Student’s t-test and chi-square test were employed to examine the differences between the long-term survival and the short-term survival groups. Ultimately, a predictive model was constructed using R 4.2.1. Results: Univariate analysis identified 12 factors as prognostic factors, showing statistical significance. In multivariate analysis, the primary contributing factors to survival were identified as age, chemotherapy of brain metastases, pathology, surgery of nonsmall cell lung cancer, targeted drugs, and GPA score. Comparing long-term and short-term groups, age, pathology, surgery of lung, targeted therapy, and radiotherapy of brain metastases were statistically differentiating factors. Based on multivariate analysis, we established a clinical predictive model predicting 2-year, 3-year, and 5-year survival rates. Conclusion: Younger age, receiving chemotherapy for brain metastases, adenocarcinoma pathology, lung cancer surgery, targeted therapy, and a high GPA score are associated with longer survival. This model predicts the survival period for patients with non-small cell lung cancer brain metastasis after surgery and helps in selecting more effective treatment plans.

Background: Reliable predictive data are crucial for making accurate treatment decisions in glioma patients, but it can be challenging to obtain due to limited information in many cases. Numerous research studies have indicated the involvement of cyclic adenosine monophosphate (cAMP)-response element binding protein (CREBBP) and E1A binding protein p300 (EP300) in tumorigenesis and tumor progression across various types. Methods: The messenger RNA (mRNA) expression levels of CREBBP and EP300 were retrospectively analyzed in 17 grade-3 glioma patients. The SYBR Green real-time polymerase chain reaction (RT-PCR) technique was employed for mRNA expression analysis, with the glyceraldehyde-3-phosphate dehydrogenase gene ( GAPDH) used as a reference gene for data normalization. In addition, the relationship between CREBBP, EP300 expression and patients’ clinical information, imaging features, histologic features, immune factors, and overall survival was assessed through univariate analyses. Results: The analysis of the data unveiled a statistically significant upregulation of CREBBP and EP300 mRNA expression levels in large gliomas as compared with their smaller counterparts ( P < .05). Histological examination using hematoxylin and eosin (H&E) staining exhibited marked cellular heterogeneity, with heightened cell density observed specifically within tumors displaying elevated CREBBP expression levels. In contrast, there was a substantial downregulation of complement 3 and complement 4 within larger tumor volumes when compared with smaller ones ( P < .05). However, these findings do not serve as clinically relevant prognostic indicators for glioma. Conclusions: It is suggested that higher expression levels of CREBBP and EP300 are positively associated with increased tumor volume. Inhibition of CREBBP and EP300 enhances local immunogenicity, leading to the recruitment of immune cells and release of cytokines for effective tumor eradication, ultimately resulting in the inhibition of tumor growth.