Metabolism has been demonstrated to play pivotal roles in human cancers. The composition of branches such as glucose, lipids, amino acids and nucleotides…etc. All of these have been identified during tumorigenesis. These events include aberrant metabolism-related expression, the production of oncometabolites, and their involvement in carcinogenic signals/networks. Although scientists have investigated the glycolysis/OHPHOs ratio in various cancer subtypes and side-populations. Lactate and 2-Hydroxyglutarate are considered to reflect hypoxia and IDH1 mutations, respectively. However, specific mechanisms and contributions still need to be explored. With the maturity of next-generation sequencing technology, a huge amount of transcriptomics-based data has been established, and existing proteomics and metabolomics have been integrated to contribute to new cancer research directions. In addition, the new biomedical imaging system also acquires real-time images through metabolites, and uses visualization as positioning to quantify and strengthen clinical treatment strategies.
In this Research Topic, we would like to focus on the metabolism in human cancers. We welcome submissions of Mini-reviews, Reviews and Original Research articles related to expression levels/enzyme activities and metabolites of metabolism-related genes, as well as the consequences for human cancers such as signal transduction, preclinical trials, and prognostic/diagnostic factors.
1. Pan-cancer collects patient specimens (with clinical parameters) using target metabolic genes/events as prognostic or diagnostic targets, and compares them with currently known biomarkers.
2. Genome-wide metabolism-related gene landscape research for pan-cancer cell lines or tissues. We welcome all omics profiles, recruitment, integration and interpretation. Please establish in vitro and in vivo models to verify the prediction results and provide applicability.
3. Application of cancer imaging models and molecular mechanisms of biosensors and drug carriers derived from the field of metabolism.
Manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) will not be accepted in Frontiers in Oncology.
Metabolism has been demonstrated to play pivotal roles in human cancers. The composition of branches such as glucose, lipids, amino acids and nucleotides…etc. All of these have been identified during tumorigenesis. These events include aberrant metabolism-related expression, the production of oncometabolites, and their involvement in carcinogenic signals/networks. Although scientists have investigated the glycolysis/OHPHOs ratio in various cancer subtypes and side-populations. Lactate and 2-Hydroxyglutarate are considered to reflect hypoxia and IDH1 mutations, respectively. However, specific mechanisms and contributions still need to be explored. With the maturity of next-generation sequencing technology, a huge amount of transcriptomics-based data has been established, and existing proteomics and metabolomics have been integrated to contribute to new cancer research directions. In addition, the new biomedical imaging system also acquires real-time images through metabolites, and uses visualization as positioning to quantify and strengthen clinical treatment strategies.
In this Research Topic, we would like to focus on the metabolism in human cancers. We welcome submissions of Mini-reviews, Reviews and Original Research articles related to expression levels/enzyme activities and metabolites of metabolism-related genes, as well as the consequences for human cancers such as signal transduction, preclinical trials, and prognostic/diagnostic factors.
1. Pan-cancer collects patient specimens (with clinical parameters) using target metabolic genes/events as prognostic or diagnostic targets, and compares them with currently known biomarkers.
2. Genome-wide metabolism-related gene landscape research for pan-cancer cell lines or tissues. We welcome all omics profiles, recruitment, integration and interpretation. Please establish in vitro and in vivo models to verify the prediction results and provide applicability.
3. Application of cancer imaging models and molecular mechanisms of biosensors and drug carriers derived from the field of metabolism.
Manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) will not be accepted in Frontiers in Oncology.
