The field of signature genes in cancer prognosis and therapy resistance is pivotal in the understanding and management of cancer. These genes, specific sets of genes whose expression levels can accurately predict patient outcomes, also determine the response to various treatments. Despite the identification of signature genes in different cancer types, providing valuable insights into tumor behavior and treatment outcomes, there are still gaps in understanding their genetic mechanisms. These genes are crucial in stratifying patients into different risk groups and are implicated in therapy resistance, a significant challenge in cancer treatment. Therefore, a better investigation into the genetic mechanisms underlying these signature genes is needed to develop novel therapeutic interventions and strategies to overcome therapy resistance and improve patient responses.
The primary aim of this research topic is to create a discussion forum for novel discoveries integrating genomic information, molecular profiling of tumors, drug resistance mechanisms, and patient outcomes. This forum will support the development of new drugs and assist clinicians in making informed decisions about treatment selection and optimizing treatment strategies. The research topic seeks to answer specific questions about the role of signature genes in cancer prognosis and therapy resistance and test hypotheses related to their genetic mechanisms and implications in therapy resistance.
To gather further insights into the role of signature genes in cancer prognosis and therapy resistance, we welcome articles addressing the following themes:
- Differentiation of risk groups based on signature genes
- Mechanisms of drug resistance related to signature genes
- Pathways and regulation of targeted genes
- Discovery of new signature genes for targeted therapy
Please note that manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases that are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of the scope of this collection and will not be accepted as part of this Research Topic.
The field of signature genes in cancer prognosis and therapy resistance is pivotal in the understanding and management of cancer. These genes, specific sets of genes whose expression levels can accurately predict patient outcomes, also determine the response to various treatments. Despite the identification of signature genes in different cancer types, providing valuable insights into tumor behavior and treatment outcomes, there are still gaps in understanding their genetic mechanisms. These genes are crucial in stratifying patients into different risk groups and are implicated in therapy resistance, a significant challenge in cancer treatment. Therefore, a better investigation into the genetic mechanisms underlying these signature genes is needed to develop novel therapeutic interventions and strategies to overcome therapy resistance and improve patient responses.
The primary aim of this research topic is to create a discussion forum for novel discoveries integrating genomic information, molecular profiling of tumors, drug resistance mechanisms, and patient outcomes. This forum will support the development of new drugs and assist clinicians in making informed decisions about treatment selection and optimizing treatment strategies. The research topic seeks to answer specific questions about the role of signature genes in cancer prognosis and therapy resistance and test hypotheses related to their genetic mechanisms and implications in therapy resistance.
To gather further insights into the role of signature genes in cancer prognosis and therapy resistance, we welcome articles addressing the following themes:
- Differentiation of risk groups based on signature genes
- Mechanisms of drug resistance related to signature genes
- Pathways and regulation of targeted genes
- Discovery of new signature genes for targeted therapy
Please note that manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases that are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of the scope of this collection and will not be accepted as part of this Research Topic.