Cancer is associated with a high degree of heterogeneity, encompassing both inter- and intra-tumor heterogeneity, along with considerable variability in clinical response to common treatments across patients. Conventional models for tumor research, such as in vitro cell cultures and in vivo animal models, demonstrate significant limitations that fall short of satisfying the research requisites. Patient-derived tumor organoids, which recapitulate the structures, specific functions, molecular characteristics, genomics alterations and expression profiles of primary tumors. They have been efficaciously implemented in illness portrayal, mechanism exploration, high-throughput drug screening and assessment, discovery of innovative therapeutic targets and potential compounds, and customized treatment regimen for cancer patients. In contrast to conventional models, tumor organoids offer an intuitive, dependable, and efficient in vitro research model by conserving the phenotypic, genetic diversity, and mutational attributes of the originating tumor. Nevertheless, the organoid technology also confronts the bottlenecks and challenges, such as how to comprehensively reflect intra-tumor heterogeneity, tumor microenvironment, tumor angiogenesis, reduce research costs, and establish standardized construction processes while retaining reliability. This review extensively examines the use of tumor organoid techniques in fundamental research and precision medicine. It emphasizes the importance of patient-derived tumor organoid biobanks for drug development, screening, safety evaluation, and personalized medicine. Additionally, it evaluates the application of organoid technology as an experimental tumor model to better understand the molecular mechanisms of tumor. The intent of this review is to explicate the significance of tumor organoids in cancer research and to present new avenues for the future of tumor research.

BACKGROUND AND PURPOSE: Previous studies have suggested that increased mortality and disability in patients with brain tumor are associated with peritumoral brain edema. However, the mechanism of peritumoral brain edema in brain tumors is unknown. This study aimed to investigate the effect of Piezo1 overexpression on peritumoral brain edema in glioblastomas. MATERIALS AND METHODS: The Piezo1 expression in cell lines and paired samples was detected by quantitative reverse transcription polymerase chain reaction, Western blot, and immunohistochemistry. Sixty-four patients with glioblastomas were analyzed retrospectively. The Piezo1 expression of tumor tissue was detected by immunohistochemistry. The diameters of tumor and edema were measured by preoperative MR imaging, and the edema index value was calculated. RESULTS: Western blot and quantitative reverse transcription polymerase chain reaction showed that Piezo1 expression was higher in 6 glioma cell lines than in the normal astrocyte cell line. Compared with peritumoral tissues, Piezo1 was up-regulated in tumor tissues. Sixty-four patients with glioblastomas were enrolled in further study. Piezo1 was higher in the moderate edema group than in the mild edema group (P < .001), higher in the severe edema group than in the moderate edema group (P < .001), and correlated with the edema index (r = 0.73; P < .001). Receiver operating characteristic curve analysis showed that the edema index yielded an area under the curve of 0.867 (95% CI, 0.76–0.97; P < .001), with a sensitivity of 100% and a specificity of 70%. CONCLUSIONS: Piezo1 overexpression is positively correlated with the degree of peritumoral brain edema in glioblastomas. Predicting high Piezo1 expression in tumor tissues based on the edema extent shows good sensitivity and specificity.

Purpose: Previous study reported that Piezo1 was highly expressed in glioma and promoted the proliferation of glioma cells, suggesting that Piezo1 overexpression might contribute to the poor prognosis of patients. Thus, this study aimed to identify whether Piezo1 may become a new prognostic biomarker for glioma patients. Patients and Methods: Firstly, Piezo1 expression of gliomas was analyzed through GEO and Oncomine dataset, and verified by qRT-PCR and immunohistochemistry (IHC) methods. A total of 183 glioma patients were included in this study between January 2010 and December 2014. Kaplan-Meier survival analyses, Cox regression analyses and ROC curve analyses were performed to assess the diagnostic and prognostic values of Piezo1 in glioma patients. Results: In this study, Piezo1 was identified to be highly expressed in gliomas, and increased with WHO grade. Chi-square test results showed that Piezo1 expression was significantly related to age (P=0.00), WHO grade (P=0.00), Histopathology (P=0.00), IDH1 mutation (P=0.00) and chemotherapy (P=0.00). Kaplan-Meier analysis showed that the overall survival (OS) of patients with high Piezo1 expression was significantly worse than that of patients with low Piezo1 expression (HR=3.39, 95% CI=2.40– 4.81, P< 0.0001). A multivariate Cox regression analysis revealed that Piezo1 might be an independent prognostic factor for glioma patients (HR=1.34, 95% CI=1.23– 1.47, P=0.000). The area under the ROC curve (AUC) of 1-, 3-, and 5-year overall survival for Piezo1 overexpression was 0.820 (P=0.000), 0.849 (P=0.000), and 0.861 (P=0.000), respectively. Conclusion: Piezo1 was overexpressed in glioma samples. Piezo1 overexpression as an independent prognostic factor adversely affects the prognosis of patients, which could be a new novel prognostic indicator in glioma patients.

Depression is a major contributor to poor global health and disability, with a recently increasing incidence. Although drug therapy is commonly used to treat depression, conventional antidepressant drugs have several disadvantages, including slow onset, low response rates and severe adverse effects. Therefore, developing effective therapies for depression remains challenging. Although various aetiological theories of depression exist, the underlying mechanisms of depression are complex, and further research is crucial. Moreover, oxidative stress (OS)‐induced lipid peroxidation has been demonstrated to trigger ferroptosis. Both OS and ferroptosis are pivotal mechanisms implicated in the pathogenesis of neurological disorders, and investigation of the mediators involved in these processes has emerged as a prominent and active research direction. One previous study revealed that regulatory proteins involved in ferroptosis are implicated in the pathogenesis of depression, and antidepressant drugs could reverse depressive symptoms by inhibiting ferroptosis in vivo , suggesting an important role of ferroptosis in the pathogenesis of depression. Hence, our current comprehensive review offers an up‐to‐date perspective on the intricate mechanisms involved, specifically concerning ferroptosis and OS in the context of depression, along with promising prospects for using molecular mediators to target ferroptosis. We delineate the key targets of molecular mediators involved in OS and ferroptosis implicated in depression, most notably reactive oxygen species and iron overload. Considering the pivotal role of OS‐induced ferroptosis in the pathogenesis of neurological disorders, delving deeper into the underlying subsequent mechanisms will contribute significantly to the identification of novel therapeutic targets for depression.

Background: Previous research indicated that the tumor cells and microenvironment interactions are critical for the immunotherapeutic response. However, predicting the clinical response to immunotherapy remains a dilemma for clinicians. Hence, this study aimed to investigate the associations between EVA1B expression and prognosis and tumor-infiltrating immune cells in glioma.Methods: Firstly, we detected the EVA1B expression in glioma tissues through biological databases. The chi-squared test, Kaplan-Meier, and univariate and multivariate Cox regression analyses were used to analyze the clinical significance of EVA1B expression. The correlation between EVA1B expression and levels of tumor-infiltrating immune cells in glioma tissues was investigated. Receiver operating characteristic (ROC) analysis was performed to compare the predictive power between EVA1B and other commonly immune-related markers.Results: In the CGGA cohort of 325 glioma patients, we found that EVA1B was upregulated in glioma, and increased with tumor grade. High EVA1B expression was prominently associated with unfavorable clinicopathological features, and poorer survival of patients, which were further confirmed by TCGA (n=609) and GEO (n=74) cohorts. Furthermore, multivariate analysis indicated that EVA1B is an independent prognostic biomarker for glioma. Importantly, EVA1B overexpression was associated with a higher infiltration level of CD4⁺ T cells, CD8⁺ T cells, B cells, macrophages, and neutrophils in glioma. ROC curves showed that, compared with PD-L1, CTLA-4, and Siglec15, EVA1B presented a higher area under the curve (AUC) value (AUC=0.824) for predicting high immune infiltration levels in glioma.Conclusions: We found that EVA1B was upregulated and could act as a poor prognostic biomarker in glioma. Importantly, EVA1B overexpression was associated with the immune infiltration levels of immune cells including B cells, CD4⁺ T cells, CD8⁺ T cells, macrophages, and neutrophils, and strongly with the overall immune infiltration levels of glioma. These findings suggested that EVA1B might be a potential biomarker for evaluating prognosis and immune infiltration in glioma.

Background: Although aberrant expression of N6‐methyladenine (m⁶A) methylation‐related genes contribute to tumorigenesis in many solid tumors, the prognostic value of the m⁶A‐related genes and their correlation with clinicopathological features in gliomas need advanced study.Methods: The clinical and sequencing data of 288 patients with glioma were extracted from Chinese Glioma Genome Atlas database. By univariate and multivariable Cox regression analysis, the m⁶A‐related prognostic genes were identified, and their correlation with clinicopathological features was further analysis. A nomogram was constructed by R software and the performance of it was assessed by calibration and time‐dependent receiver operating characteristic curve.Results: Nine m⁶A‐related genes were identified as independent prognostic factors, which were mostly enriched in RNA splicing, regulation of immune response and vesicle‐mediated transport. By expression value and regression coefficient of these genes, we constructed risk score of each patient, which was highly associated with clinicopathological features. Kaplan–Meier curve showed that the prognosis of patients with high‐risk scores was significantly worse than that with low‐risk scores (HR = 4.30, 95% CI = 3.16–5.85, p < 0.0001). A nomogram was constructed based on the nine m⁶A‐related genes signature and clinicopathological features with well‐fitted calibration curves (c‐index = 0.82), showing high specificity and sensitivity (area under the curve for 1‐, 3‐, and 5‐years survival probability = 0.874, 0.918, and 0.934).Conclusions: A nine m⁶A‐related genes signature was identified in gliomas. The m⁶A‐related risk score is a novel prognostic factor for patients with glioma, and is associated with clinicopathological features. Moreover, the nomogram based on the nine m⁶A‐related genes signature and clinicopathological features had good efficacy in predicting the survival probability.