The medical care for cancer and patients’ prognosis is highly improved in the last 3 decades. The survival for most cancer types, including melanoma, prostate cancer, and breast cancer, is also highly increased. However, some types of cancers still exhibit very little improvement since the early 1970s, including pancreas and brain tumors. Particularly, glioblastoma, which accounts for the majority of primary malignant brain tumors in adults. The median survival of glioblastoma patients is only ~14-16 months after the initial diagnosis, surgery, and combined chemoradiotherapy to the involved field. The standard treatment for glioblastoma is temozolomide (TMZ)-mediated chemotherapy conjugated with radiotherapy (CCRT) after surgery. Unfortunately, the efficacy of CCRT is always restricted within a short period due to the high prevalence of tumor recurrence. Recurrent tumor always exhibits higher and higher tolerance in response to TMZ treatment cycle, leading to drug resistance which is the main obstacle to improving patients’ prognosis. In contrast to normal cells, tumor cells are highly dependent on glucose uptake followed by glycolysis in the presence of oxygen. This metabolic reprogramming by cancer cells is known as the Warburg effect or aerobic glycolysis. However, it is still unknown whether the Warburg effect is a common metabolic strategy shared by each kind of cancer. According to different metabolic features, lung, colorectal, and leukemia rely heavily on glycolysis; whereas glioblastoma is an oxidative tumor characterized by mitochondrial OXPHOS-mediated ATP production. Nevertheless, it still lacks evidence to show how metabolic reprogramming is initiated, processed, and optimized in glioblastoma receiving chemo- and radiotherapy. Therefore, these mysterious mechanisms increase the value of further studies on glioblastoma.
Despite rapid progress in discovering tumor therapeutic strategies, the prognosis of glioblastoma patients remains very poor. For this reason, we must clearly understand the underlying mechanism of the high recurrence rate and drug resistance of glioblastoma. Particularly, we would like to know what genes/proteins/metabolites are affected by metabolic reprogramming and to discover potential drugs to rescue the abnormality. We welcome submissions covering, but not limited to, the following:
• Multi-omics analysis for metabolic pathways associated with chemo- and radio-resistance of glioblastoma
• Metabolic reprogramming-related molecular markers, subtyping, and predictive factors associated with therapeutic resistance or recurrence of glioblastoma
• Potential strategies targeting metabolic pathways for the treatment of glioblastoma, including drugs, cell therapy, and nanotechnology
• Novel mechanisms contributing to metabolic reprogramming for inducing glioblastoma recurrence
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.
The medical care for cancer and patients’ prognosis is highly improved in the last 3 decades. The survival for most cancer types, including melanoma, prostate cancer, and breast cancer, is also highly increased. However, some types of cancers still exhibit very little improvement since the early 1970s, including pancreas and brain tumors. Particularly, glioblastoma, which accounts for the majority of primary malignant brain tumors in adults. The median survival of glioblastoma patients is only ~14-16 months after the initial diagnosis, surgery, and combined chemoradiotherapy to the involved field. The standard treatment for glioblastoma is temozolomide (TMZ)-mediated chemotherapy conjugated with radiotherapy (CCRT) after surgery. Unfortunately, the efficacy of CCRT is always restricted within a short period due to the high prevalence of tumor recurrence. Recurrent tumor always exhibits higher and higher tolerance in response to TMZ treatment cycle, leading to drug resistance which is the main obstacle to improving patients’ prognosis. In contrast to normal cells, tumor cells are highly dependent on glucose uptake followed by glycolysis in the presence of oxygen. This metabolic reprogramming by cancer cells is known as the Warburg effect or aerobic glycolysis. However, it is still unknown whether the Warburg effect is a common metabolic strategy shared by each kind of cancer. According to different metabolic features, lung, colorectal, and leukemia rely heavily on glycolysis; whereas glioblastoma is an oxidative tumor characterized by mitochondrial OXPHOS-mediated ATP production. Nevertheless, it still lacks evidence to show how metabolic reprogramming is initiated, processed, and optimized in glioblastoma receiving chemo- and radiotherapy. Therefore, these mysterious mechanisms increase the value of further studies on glioblastoma.
Despite rapid progress in discovering tumor therapeutic strategies, the prognosis of glioblastoma patients remains very poor. For this reason, we must clearly understand the underlying mechanism of the high recurrence rate and drug resistance of glioblastoma. Particularly, we would like to know what genes/proteins/metabolites are affected by metabolic reprogramming and to discover potential drugs to rescue the abnormality. We welcome submissions covering, but not limited to, the following:
• Multi-omics analysis for metabolic pathways associated with chemo- and radio-resistance of glioblastoma
• Metabolic reprogramming-related molecular markers, subtyping, and predictive factors associated with therapeutic resistance or recurrence of glioblastoma
• Potential strategies targeting metabolic pathways for the treatment of glioblastoma, including drugs, cell therapy, and nanotechnology
• Novel mechanisms contributing to metabolic reprogramming for inducing glioblastoma recurrence
Please note: manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic.