In oncology, the manipulation of metabolic processes within tumors has surfaced as a pivotal strategy for influencing cancer progression and therapy resistance. Tumor cells often undergo metabolic transformations to support their increased growth and survival rates, prominently under adverse conditions such as hypoxia. This reorientation, famously encapsulated by the "Warburg effect," sees cancer cells favoring glycolysis for energy over more oxygen-requiring processes, thus reducing oxidative stress and bolstering resilience against environmental pressures. For instance, specific lung cancer variants manipulate their metabolic routes to thrive on limited nutrients, inadvertently promoting not just survival but also an increased metastatic ability. These adaptative metabolic tactics allow tumors to outpace their normal counterparts by finely tuning their energy production to meet the demands of rapid cell division.This research topic seeks to delve deep into the crucial interplays between metabolic reprogramming and tumor progression, exploring how these mechanisms can be harnessed to develop novel therapeutic interventions. It particularly looks to shed light on metabolic alterations as viable targets for enhancing drug efficacy in cancer treatment, backed by burgeoning evidence from metabolic profiling technologies and clinical trials that suggest targeting such pathways can dynamically improve treatment outcomes.This Research Topic invites submissions that focus on the role of metabolic reprogramming in tumor treatment. The specific scope includes: 1) key mechanisms of metabolism in tumor development; 2) interactions between metabolic reprogramming and the tumor microenvironment; 3) identification of metabolism-related drug development targets; 4) applications of metabolomics in tumor research; 5) potential of AI and machine learning in analyzing metabolic data; 6) new metabolic intervention strategies and their clinical trial results; 7) connections between metabolic reprogramming and immune escape.Please note that manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this Research Topic.
In oncology, the manipulation of metabolic processes within tumors has surfaced as a pivotal strategy for influencing cancer progression and therapy resistance. Tumor cells often undergo metabolic transformations to support their increased growth and survival rates, prominently under adverse conditions such as hypoxia. This reorientation, famously encapsulated by the "Warburg effect," sees cancer cells favoring glycolysis for energy over more oxygen-requiring processes, thus reducing oxidative stress and bolstering resilience against environmental pressures. For instance, specific lung cancer variants manipulate their metabolic routes to thrive on limited nutrients, inadvertently promoting not just survival but also an increased metastatic ability. These adaptative metabolic tactics allow tumors to outpace their normal counterparts by finely tuning their energy production to meet the demands of rapid cell division.This research topic seeks to delve deep into the crucial interplays between metabolic reprogramming and tumor progression, exploring how these mechanisms can be harnessed to develop novel therapeutic interventions. It particularly looks to shed light on metabolic alterations as viable targets for enhancing drug efficacy in cancer treatment, backed by burgeoning evidence from metabolic profiling technologies and clinical trials that suggest targeting such pathways can dynamically improve treatment outcomes.This Research Topic invites submissions that focus on the role of metabolic reprogramming in tumor treatment. The specific scope includes: 1) key mechanisms of metabolism in tumor development; 2) interactions between metabolic reprogramming and the tumor microenvironment; 3) identification of metabolism-related drug development targets; 4) applications of metabolomics in tumor research; 5) potential of AI and machine learning in analyzing metabolic data; 6) new metabolic intervention strategies and their clinical trial results; 7) connections between metabolic reprogramming and immune escape.Please note that manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this Research Topic.