Guanzhang Li

Patients with high ALDH1A3-expressing glioblastoma (ALDH1A3hi GBM) show limited benefit from postoperative chemoradiotherapy. Understanding the mechanisms underlying such resistance in these patients is crucial for the development of new treatments. Here, we show that the interaction between ALDH1A3 and PKM2 enhances the latter’s tetramerization and promotes lactate accumulation in glioblastoma stem cells (GSCs). By scanning the lactylated proteome in lactate-accumulating GSCs, we show that XRCC1 undergoes lactylation at lysine 247 (K247). Lactylated XRCC1 shows a stronger affinity for importin α, allowing for greater nuclear transposition of XRCC1 and enhanced DNA repair. Through high-throughput screening of a small-molecule library, we show that D34-919 potently disrupts the ALDH1A3-PKM2 interaction, preventing the ALDH1A3-mediated enhancement of PKM2 tetramerization. In vitro and in vivo treatment with D34-919 enhanced chemoradiotherapy-induced apoptosis of GBM cells. Together, our findings show that ALDH1A3-mediated PKM2 tetramerization is a potential therapeutic target to improve the response to chemoradiotherapy in ALDH1A3hi GBM.

Glioma is a fatal brain tumor characterized by rapid proliferation and treatment resistance. Ferroptosis is a newly discovered programmed cell death and plays a crucial role in the occurrence and progression of tumors. In this study, we identified ferroptosis specific markers to reveal the relationship between ferroptosis-related genes and glioma by analyzing whole transcriptome data from Chinese Glioma Genome Atlas, The Cancer Genome Atlas dataset, GSE16011 dataset, and the Repository of Molecular Brain Neoplasia Data dataset. Nineteen ferroptosis-related genes with clinical and pathological features of glioma were identified as highly correlated. Functional assays in glioma cell lines indicated the association of ferroptosis with temozolomide resistance, autophagy, and glioma cell migration. Therefore, the identified ferroptosis-related genes were significantly correlated with glioma progression.

Chimeric antigen receptor (CAR) T-cell therapy has demonstrated clinical response in treating both hematologic malignancies and solid tumors. Although instances of rapid tumor remissions have been observed in animal models and clinical trials, tumor relapses occur with multiple therapeutic resistance mechanisms. Furthermore, while the mechanisms underlying the long-term therapeutic resistance are well-known, short-term adaptation remains less understood. However, more views shed light on short-term adaptation and hold that it provides an opportunity window for long-term resistance. In this study, we explore a previously unreported mechanism in which tumor cells employ trogocytosis to acquire CAR molecules from CAR-T cells, a reversal of previously documented processes. This mechanism results in the depletion of CAR molecules and subsequent CAR-T cell dysfunction, also leading to short-term antigen loss and antigen masking. Such type of intercellular communication is independent of CAR downstream signaling, CAR-T cell condition, target antigen, and tumor cell type. However, it is mainly dependent on antigen density and CAR sensitivity, and is associated with tumor cell cholesterol metabolism. Partial mitigation of this trogocytosis-induced CAR molecule transfer can be achieved by adaptively administering CAR-T cells with antigen density-individualized CAR sensitivities. Together, our study reveals a dynamic process of CAR molecule transfer and refining the framework of clinical CAR-T therapy for solid tumors.

Background: Immunotherapy provided unprecedented advances in the treatment of several previously untreated cancers. However, these immunomodulatory maneuvers showed limited response to patients with glioma in clinical trials. Our aim was to depict the immune characteristics of glioma with immune cytolytic activity at genetic and transcriptome levels. Methods: In total, 325 gliomas from CGGA dataset as training cohort and 699 gliomas from TCGA dataset as validation cohort were enrolled in our analysis. We calculated the immune cytolytic activity for thousands of gliomas. The characteristics of immune cytolytic activity in gliomas were interpreted by the corresponding clinical, molecular genetics and radiological information. Results: We found that immune cytolytic activity was highly associated with molecular, clinical and edema extent. High cytolytic activity gliomas were more likely to be diagnosed as glioblastoma and might be a potential marker of mesenchymal subtype. Moreover, those gliomas exhibited significantly increased copy number alterations including recurrent focal amplifications of PDGFA and EGFR, as well as recurrent deletions of CDKN2A/B. Subsequent biological function analysis revealed that the immune response and immune checkpoints expression were significantly correlated with the cytolytic activity of gliomas. Immune cytolytic activity was significantly positively associated with the extent of peri-tumor edema and was independently correlated with reduced survival time. Conclusion: Our results highlighted the immunoregulatory mechanism heterogeneity of gliomas. Cytolytic activity, indirectly reflected by the extent of peri-tumor edema, may provide a potential index to evaluate the status of immune microenvironment and immune checkpoints in glioma, which should be fully valued for precision classification and immunotherapy.

AIMS: We aimed to create a tumor recurrent-based prediction model to predict recurrence and survival in patients with low-grade glioma. METHODS: This study enrolled 291 patients (188 in the training group and 103 in the validation group) with clinicopathological information and transcriptome sequencing data. LASSO-COX algorithm was applied to shrink predictive factor size and build a predictive recurrent signature. GO, KEGG, and GSVA analyses were performed for function annotations of the recurrent signature. The calibration curves and C-Index were assessed to evaluate the nomogram's performance. RESULTS: This study found that DNA repair functions of tumor cells were significantly enriched in recurrent low-grade gliomas. A predictive recurrent signature, built by the LASSO-COX algorithm, was significantly associated with overall survival and progression-free survival in low-grade gliomas. Moreover, function annotations analysis of the predictive recurrent signature exhibited that the signature was associated with DNA repair functions. The nomogram, combining the predictive recurrent signature and clinical prognostic predictors, showed powerful prognostic ability in the training and validation groups. CONCLUSION: An individualized prediction model was created to predict 1-, 2-, 3-, 5-, and 10-year survival and recurrent rate of patients with low-grade glioma, which may serve as a potential tool to guide postoperative individualized care.