Traditionally cancers are diagnosed by tissue biopsy obtained from the primary or metastatic sites. Even though tissue biopsy is a well-established method of histological characterization of tumours, it has numerous disadvantages such as invasiveness, increased risks for adverse events, and long turn around time. Additionally, it does not provide important information regarding the heterogeneity and evolution of the tumour in real time. Therefore, repeated biopsies are often required to fully evaluate cancer progression or response to treatment. The blood-based liquid biopsy has emerged as an attractive alternative to the traditional tissue biopsy as it offers a fast, convenient and non-invasive way to assess the genetic tumour landscape in real time. It also provides broader and more comprehensive tumour analysis, as it reflects the primary and metastatic molecular profiles (‘fingerprint’). As such liquid biopsy-based molecular profiling offers a unique opportunity in biomarker and drug discovery.
As liquid biopsy provides potentially a real-time answer to tumour evolution, it can serve as an excellent pharmacological tool to dynamically evaluate potentially novel drug targets (on/off-target effects), as well as, new biomarkers in order to assess the mechanisms of response or resistance to current therapies in patients. This information can further guide the treatment decisions, improve diagnosis and patient outcomes and provide valuable information of the mechanism of action of the drug. Identification of the novel therapeutic targets can facilitate the launch of new drug discovery platforms to combat ever changing tumour evolution. The goal of this Research Topic is to identify novel approaches in drug discovery guided by the liquid biopsy, as well as identification of new sophisticated methods in biomarker discovery and validation which can include artificial intelligence and machine learning algorithms. In addition, this research topic aims to uncover potentially additional epigenetic mechanisms involved in the real time epigenetic changes triggered by drug responses or acquired resistance to therapies. These findings in epigenetic reprogramming may facilitate the development of novel targeted therapeutics and corresponding detection of associated pharmacological effects.
This Research Topics encourages authors to contribute original articles, as well as reviews, mini reviews and case studies.
This Research Topic will be focused on these areas:
1. Liquid-biopsy guided biomarker discovery and identification of novel targets in oncology enabling characterization disease evolution in real time.
2. Research focused on novel approaches in identifying new biomarkers in oncology including early detection and disease progression.
3. Novel approaches in precision oncology focused on identification of new therapeutic targets in immune-oncology and progressive disease.
4. Methods including artificial intelligence and machine learning algorithms facilitating biomarker discovery and validation.
5. Novel immune-oncology mechanisms of cancer progression and resistance and associated biomarkers.
6. New methodology and technologies on improving sensitivity of liquid biopsies.
7. Epigenetic reprogramming involved in the mechanisms of resistance to therapies and methods to detect disease in real time.
Traditionally cancers are diagnosed by tissue biopsy obtained from the primary or metastatic sites. Even though tissue biopsy is a well-established method of histological characterization of tumours, it has numerous disadvantages such as invasiveness, increased risks for adverse events, and long turn around time. Additionally, it does not provide important information regarding the heterogeneity and evolution of the tumour in real time. Therefore, repeated biopsies are often required to fully evaluate cancer progression or response to treatment. The blood-based liquid biopsy has emerged as an attractive alternative to the traditional tissue biopsy as it offers a fast, convenient and non-invasive way to assess the genetic tumour landscape in real time. It also provides broader and more comprehensive tumour analysis, as it reflects the primary and metastatic molecular profiles (‘fingerprint’). As such liquid biopsy-based molecular profiling offers a unique opportunity in biomarker and drug discovery.
As liquid biopsy provides potentially a real-time answer to tumour evolution, it can serve as an excellent pharmacological tool to dynamically evaluate potentially novel drug targets (on/off-target effects), as well as, new biomarkers in order to assess the mechanisms of response or resistance to current therapies in patients. This information can further guide the treatment decisions, improve diagnosis and patient outcomes and provide valuable information of the mechanism of action of the drug. Identification of the novel therapeutic targets can facilitate the launch of new drug discovery platforms to combat ever changing tumour evolution. The goal of this Research Topic is to identify novel approaches in drug discovery guided by the liquid biopsy, as well as identification of new sophisticated methods in biomarker discovery and validation which can include artificial intelligence and machine learning algorithms. In addition, this research topic aims to uncover potentially additional epigenetic mechanisms involved in the real time epigenetic changes triggered by drug responses or acquired resistance to therapies. These findings in epigenetic reprogramming may facilitate the development of novel targeted therapeutics and corresponding detection of associated pharmacological effects.
This Research Topics encourages authors to contribute original articles, as well as reviews, mini reviews and case studies.
This Research Topic will be focused on these areas:
1. Liquid-biopsy guided biomarker discovery and identification of novel targets in oncology enabling characterization disease evolution in real time.
2. Research focused on novel approaches in identifying new biomarkers in oncology including early detection and disease progression.
3. Novel approaches in precision oncology focused on identification of new therapeutic targets in immune-oncology and progressive disease.
4. Methods including artificial intelligence and machine learning algorithms facilitating biomarker discovery and validation.
5. Novel immune-oncology mechanisms of cancer progression and resistance and associated biomarkers.
6. New methodology and technologies on improving sensitivity of liquid biopsies.
7. Epigenetic reprogramming involved in the mechanisms of resistance to therapies and methods to detect disease in real time.
