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Background. Pyroptosis is a form of programmed cell death, playing a significant role in cancer. Glioblastoma multiforme (GBM) is the most common malignant brain tumor. The poor prognosis in GBM due to temozolomide (TMZ) resistance has been widely discussed. Such being the case, the correlation between TMZ resistance and pyroptosis is seldom investigated. On this basis, this paper aims to explore the potential prognostic value of genes related to TMZ resistance and pyroptosis as well as their relationship to the immune microenvironment in GBM. Methods. A total of 103 patients from TCGA were assigned to a training cohort; 190 from CGGA were assigned to a validation cohort. The prognostic risk model reflecting pyroptosis and TMZ resistance was built from the training cohort using multivariate Cox regression and performed validation. RT-qPCR was used to examine the expression of 4 genes from the risk signature. FOXP3 was selected for overexpression and verified using the western blot. The TMZ IC50 of FOXP3-overexpressed cell lines was determined by CCK8. Results. A four genes-based risk signature was established and validated, separating GBM patients into high- and low-risk groups. Compared with the low-risk group, the high-risk group presented worse clinical survival outcomes. Its differential expressed genes were enriched in immune-related pathways and closely related to the immune microenvironment. Moreover, RT-qPCR results suggested that FOXP3, IRF3, and CD274 were significantly upregulated in TMZ-resistant strains, while TP63 was downregulated. FOXP3-overexpressed GBM cell lines had higher TMZ IC50, implying an increased resistance of TMZ. Conclusion. A novel gene signature relevant to pyroptosis and TMZ resistance was constructed and could be used for the prognosis of GBM. The four genes from the risk model might play a potential role in antitumor immunity and serve as therapeutic targets for GBM. [ABSTRACT FROM AUTHOR]

Objective. Due to the molecular heterogeneity of gastric cancer, only minor patients respond to immunotherapeutic schemes. This study is aimed at developing an immune-based gene signature for risk stratification and immunotherapeutic efficacy assessment in gastric cancer. Methods. An immune-based gene signature was developed in gastric cancer by LASSO method in the training set. The predictive performance was validated in the external datasets. KEGG pathways related to risk scores were assessed by GSEA. Based on multivariate Cox regression analysis, a nomogram was established. Sensitivity to chemotherapy drugs was evaluated between high- and low-risk samples. The relationships of risk scores with infiltration levels of immune cells, stromal scores, immune scores, immune cell subgroups, and overall response to anti-PD-L1 therapy were determined. Results. Our results showed that high risk scores were indicative of undesirable survival outcomes both in the training set (p < 0.0001) and the validation set (p = 0.002). Moreover, this signature could independently predict patients' survival (HR: 2.656 (1.919-3.676) and p < 0.001). Subgroup analysis confirmed the sensitivity of this signature in predicting prognosis (all p < 0.05). Cancer-related pathways were primarily enriched in high-risk samples, such as MAPK and TGF-β pathways (p < 0.05). By incorporating stage and the risk score, we established a nomogram for predicting one-, three-, and five-year survival probability. Patients with high-risk scores were more sensitive to chemotherapy drugs (p < 0.05). There was heterogeneity in immune cells between high- and low-risk samples (p < 0.05). Samples with progressive disease exhibited the highest risk score, and those with complete response had the lowest risk score (p < 0.05). Conclusion. This immune-based gene signature might be representative of a promising prognostic classifier for predicting risk stratification and immunotherapeutic efficacy in gastric cancer, assisting personalized therapy and follow-up plan. [ABSTRACT FROM AUTHOR]

Purpose. Gliosarcoma is a histopathological variant of glioblastoma, which is characterized by a biphasic growth pattern consisting of glial and sarcoma components. Owing to its scarcity, data regarding the impact of available treatments on the clinical outcomes of gliosarcoma are inadequate. The purpose of this retrospective cohort study was to analyze the prognostic factors of gliosarcoma. Methods. By screening the clinical database of neurosurgical cases at a single center, patients with gliosarcoma diagnosed histologically from 2013 to 2021 were identified. Clinical, pathological, and molecular data were gathered founded on medical records and follow-up interviews. Prognostic factors were derived using the Cox proportional hazards model with backward stepwise regression analysis. Results. Forty-five GSM patients were included. Median overall survival was 25.6 months (95% CI 8.0–43.1), and median relapse-free survival was 15.2 months (95% CI 9.7–20.8). In multivariable analysis, total resection (p = 0.023 , HR = 0.192 , 95% CI 0.046–0.797) indicated an improved prognosis. And low expression of Ki-67 (p = 0.059 , HR = 2.803 , 95% CI 0.963–8.162) would be likely to show statistical significance. However, there might be no statistically significant survival benefit from radiotherapy with concurrent temozolomide (n = 33 , 73.3%, log-rank p = 0.99) or adjuvant temozolomide (n = 32 , 71.1%, log-rank p = 0.74). Conclusion. This single-center retrospective study with a limited cohort size has demonstrated the treatment of gross total resection and low expression of Ki-67 which are beneficial for patients with GSM, while radiotherapy or temozolomide is not. [ABSTRACT FROM AUTHOR]