Renal cell carcinoma (RCC) is one of the most common types of cancer in the urinary system. It has showed that 179,000 people died from RCC every year. More than 30% of RCC patients were first diagnosed with metastasis. At present, several studies have explored the molecular typing of renal cell carcinoma. However, it is still lacking a single genomic predictor of treatment response or prognostication feature. There are many classic subtypes of renal cancer, such as VHL and FCC mutations, among which VHL mutations account for the most of them. Even renal cancer patients with the same VHL mutation have different prognosis. Molecular markers are of use to evaluate renal cancer patients. Detailed stratification allows patients to get more precise treatment plans. The problem of lacking predictive and prognostic biomarker in RCC should be addressed urgently.
This Research Topic aims at classifying patients with renal cell carcinoma by using different biomarkers (tissue or fluid) on the basis of TNM staging. In addition, it is more than crucial to establish a marker model for molecular typing of RCC for clinical diagnosis and therapy. We also hope to discuss gene or protein signature with predictive value on prognosis in the localized and metastatic RCC. Moreover, we are committing ourselves to provide more options of postoperative regimen for RCC patients.
We welcome submissions of the following subtopics, include but not limited to:
• Discovery of the specific biomarkers for renal cell carcinoma (RCC) by using transcriptomic sequencing, proteomic sequencing or searching in public databases, accompanied with independent cohort or biological validation
• Preliminary identification of biomarkers for diagnosis, prognosis and treatment for RCC patients with the help of bioinformatics method.
• Further screening of the biomarkers with clinical value via bioinformatics methods and in vitro and vivo experiments.
• Validation of the function and value of the selected biomarkers in vitro and vivo experiments.
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.
Renal cell carcinoma (RCC) is one of the most common types of cancer in the urinary system. It has showed that 179,000 people died from RCC every year. More than 30% of RCC patients were first diagnosed with metastasis. At present, several studies have explored the molecular typing of renal cell carcinoma. However, it is still lacking a single genomic predictor of treatment response or prognostication feature. There are many classic subtypes of renal cancer, such as VHL and FCC mutations, among which VHL mutations account for the most of them. Even renal cancer patients with the same VHL mutation have different prognosis. Molecular markers are of use to evaluate renal cancer patients. Detailed stratification allows patients to get more precise treatment plans. The problem of lacking predictive and prognostic biomarker in RCC should be addressed urgently.
This Research Topic aims at classifying patients with renal cell carcinoma by using different biomarkers (tissue or fluid) on the basis of TNM staging. In addition, it is more than crucial to establish a marker model for molecular typing of RCC for clinical diagnosis and therapy. We also hope to discuss gene or protein signature with predictive value on prognosis in the localized and metastatic RCC. Moreover, we are committing ourselves to provide more options of postoperative regimen for RCC patients.
We welcome submissions of the following subtopics, include but not limited to:
• Discovery of the specific biomarkers for renal cell carcinoma (RCC) by using transcriptomic sequencing, proteomic sequencing or searching in public databases, accompanied with independent cohort or biological validation
• Preliminary identification of biomarkers for diagnosis, prognosis and treatment for RCC patients with the help of bioinformatics method.
• Further screening of the biomarkers with clinical value via bioinformatics methods and in vitro and vivo experiments.
• Validation of the function and value of the selected biomarkers in vitro and vivo experiments.
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.
