In the tumor microenvironment, both tumor cells and tumor-associated macrophages (TAMs) frequently impede the effective treatment of glioblastoma (GBM). Herein, a co-extracellular vesicles (EVs) delivery system composed of M0 RAW264.7 macrophage-derived extracellular vesicles (MEVs) and doxorubicin (DOX)-loaded lemon-derived EVs (LEVDs) is demonstrated, enabling a significant enhancement of immunochemotherapy for GBM. This system facilitates the penetration of both EV types across the blood-brain barrier and blood-brain tumor barrier, enabling precise modulation of TAMs and tumor cells within the GBM microenvironment. During this process, MEVs exhibit a remarkable homing capacity toward TAMs, and meanwhile, they are enriched in microRNA let-7f-5p, which targets the 3' untranslated region of A20 mRNA in M2 macrophages, leading to the activation of nuclear factor κB signaling pathway. This cascade drives the repolarization of M2 macrophages toward an M1 phenotype, effectively reversing the immunosuppressive tumor microenvironment. Concurrently, LEVDs exhibit exceptional targeting of GBM cells through receptor-ligand interactions, facilitating efficient chemotherapy. As expected, the co-EVs delivery system significantly enhances immunochemotherapy for GBM through MEVs-mediated TAM repolarization and LEVDs-driven chemotherapy.

Gastric cancer (GC) poses a significant health challenge worldwide, necessitating the identification of predictive biomarkers to improve prognosis. Dysregulated lipid metabolism is a well-recognized hallmark of tumorigenesis, prompting investigation into apolipoproteins (APOs). In this study, we focused on apolipoprotein D (APOD) following comprehensive analyses of APOs in pan-cancer. Utilizing data from the TCGA-STAD and GSE62254 cohorts, we elucidated associations between APOD expression and multiple facets of GC, including prognosis, tumor microenvironment (TME), cancer biomarkers, mutations, and immunotherapy response, and identified potential anti-GC drugs. Single-cell analyses and immunohistochemical staining confirmed APOD expression in fibroblasts within the GC microenvironment. Additionally, we independently validated the prognostic significance of APOD in the ZN-GC cohort. Our comprehensive analyses revealed that high APOD expression in GC patients was notably associated with unfavorable clinical outcomes, reduced microsatellite instability and tumor mutation burden, alterations in the TME, and diminished response to immunotherapy. These findings provide valuable insights into the potential prognostic and therapeutic implications of APOD in GC.

The non-receptor protein tyrosine phosphatases gene family (PTPNs) is involved in the tumorigenesis and development of many cancers, but the role of PTPNs in acute myeloid leukemia (AML) remains unclear. After a comprehensive evaluation on the expression patterns and immunological effects of PTPNs using a pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas, the most valuable gene PTPN2 was discovered. Further investigation of the expression patterns of PTPN2 in different tissues and cells showed a robust correlation with AML. PTPN2 was then systematically correlated with immunological signatures in the AML tumor microenvironment and its differential expression was verified using clinical samples. In addition, a prediction model, being validated and compared with other models, was developed in our research. The systematic analysis of PTPN family reveals that the effect of PTPNs on cancer may be correlated to mediating cell cycle-related pathways. It was then found that PTPN2 was highly expressed in hematologic diseases and bone marrow tissues, and its differential expression in AML patients and normal humans was verified by clinical samples. Based on its correlation with immune infiltrates, immunomodulators, and immune checkpoint, PTPN2 was found to be a reliable biomarker in the immunotherapy cohort and a prognostic predictor of AML. And PTPN2'riskscore can accurately predict the prognosis and response of cancer immunotherapy. These findings revealed the correlation between PTPNs and immunophenotype, which may be related to cell cycle. PTPN2 was differentially expressed between clinical AML patients and normal people. It is a diagnostic biomarker and potentially therapeutic target, providing targeted guidance for clinical treatment.

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) has revolutionized bladder cancer (BCa) treatment. Patients likely to benefit from these therapies need to be accurately stratified; however, this remains a major clinical challenge. In the present study, single-cell RNA sequencing was used to evaluate the predictive ability of an epithelial cell population highly expressing keratin 13 (KRT13) to assess therapeutic response in BCa. The presence of KRT13-enriched tumors indicated favorable outcomes after NAC and superior response to ICT in patients with BCa. Furthermore, KRT13 population characteristics appeared to be closely related to changes in the immune microenvironment in the vicinity of this cell population. We constructed a prognostic model using an artificial neural network based on the gene signatures in the KRT13 population; the model demonstrated strong robustness and superiority. Additionally, a user-friendly and open-access web application named BCa database was developed for researchers to study BCa by mining the connective map database.

Immune checkpoint inhibitors (ICIs) have made important breakthrough in anti-tumor therapy, however, no single biomarker can accurately predict their efficacy. Studies have found that tumor microenvironment is a key factor for determining the response to ICI therapy. Cytokine receptor 3 (C-X-C Motif Chemokine Receptor 3, CXCR3) pathway has been reported to play an important role in the migration, activation, and response of immune cells. We analyzed survival data, genomics, and clinical data from patients with metastatic urothelial carcinoma (mUC) who received ICI treatment to explore the relationship between CXCR3 pathway activation and the effectiveness of ICIs. The Cancer Genome Atlas Bladder Urothelial Carcinoma cohort and six other cohorts receiving ICI treatment were used for mechanism exploration and validation. In the ICI cohort, we performed univariate and multivariate COX analyses and discovered that patients in the CXCR3-high group were more sensitive to ICI treatment. A Kaplan–Meier analysis demonstrated that patients in the high CXCR3-high group had a better prognosis than those in the CXCR3-low group (P = 0.0001, Hazard Ratio = 0.56; 95% CI 0.42−0.75). CIBERSORT analysis found that mUC patients in the CXCR3-high group had higher levels of activated CD8+ T cells, M1 macrophages, and activated NK cells and less regulatory T cell (Treg) infiltration. Immunogenicity analysis showed the CXCR3-high group had higher tumor neoantigen burden (TNB). Our study suggests that CXCR3 pathway activation may be a novel predictive biomarker for the effectiveness of immunotherapy in mUC patients.

Background Mounting evidence has demonstrated that an imbalance in liquid–liquid phase separation (LLPS) can induce alteration in the spatiotemporal coordination of biomolecular condensates, which plays a role in carcinogenesis and cachexia. However, the role of LLPS in the occurrence and progression of bladder cancer (BLCA) remains to be elucidated. Identifying the role of LLPS in carcinogenesis may aid in cancer therapeutics. Methods A total of 1,351 BLCA samples from six cohorts were retrieved from publicly available databases like The Cancer Genome Atlas, Gene Expression Omnibus, and ArrayExpress. The samples were divided into three distinct clusters, and their multi-dimensional heterogeneities were explored. The LLPS patterns of all patients were determined based on the LLPS-related risk score (LLPSRS), and its multifaceted landscape was depicted and experimentally validated at the multi-omics level. Finally, a cytotoxicity-related and LLPSRS-based classifier was established to predict the patient’s response to immune checkpoint blockade (ICB) treatment. Results Three LLPS-related subtypes were identified and validated. The differences in prognosis, tumor microenvironment (TME) features, cancer hallmarks, and certain signatures of the three LLPS-related subtypes were validated. LLPSRS was calculated, which could be used as a prognostic biomarker. A close correlation was observed between clinicopathological features, genomic variations, biological mechanisms, immune infiltration in TME, chemosensitivity, and LLPSRS. Furthermore, our classifier could effectively predict immunotherapy response in patients with BLCA. Conclusions Our study identified a novel categorization of BLCA patients based on LLPS. The LLPSRS could predict the prognosis of patients and aid in designing personalized medicine. Further, our binary classifier could effectively predict patients’ sensitivity to immunotherapy.

Treacle ribosome biogenesis factor 1 (TCOF1) plays a crucial role in multiple processes, including ribosome biogenesis, DNA damage response (DDR), mitotic regulation, and telomere integrity. However, its role in cancers remains unclear. We aimed to visualize the expression, prognostic, and mutational landscapes of TCOF1 across cancers and to explore its association with immune infiltration. In this work, we integrated information from TCGA and GEO to explore the differential expression and prognostic value of TCOF1. Then, the mutational profiles of TCOF1 in cancers were investigated. We further determined the correlation between TCOF1 and immune cell infiltration levels. Additionally, we determined correlations among certain immune checkpoints, microsatellite instability, tumor mutational burden (TMB), and TCOF1. Potential pathways of TCOF1 in tumorigenesis were analyzed as well. In general, tumor tissue had a higher expression level of TCOF1 than normal tissue. The prognostic value of TCOF1 was multifaceted, depending on type of cancer. TCOF1 was correlated with tumor purity, CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells (DCs) in 6, 14, 16, 12, 20, 13, and 17 cancer types, respectively. TCOF1 might act on ATPase activity, microtubule binding, tubulin binding, and catalytic activity (on DNA), and participate in tumorigenesis through "cell cycle" and "cellular-senescence" pathways. TCOF1 could affect pan-cancer prognosis and was correlated with immune cell infiltration. "Cell cycle" and "cellular-senescence" pathways were involved in the functional mechanisms of TCOF1, a finding that awaits further experimental validation.