In recent years, there has been a significant increase in the number of FDA-approved pan-tumor biomarkers. This is driven by the growing realization among patients and oncologists of the potential benefits of personalized oncology, including treatment regimens tailored to their unique tumor profiles. To meet this demand, there has been a surge of research programs aimed at identifying these molecular markers, facilitated by the decreasing cost of next-generation sequencing. These cancer biomarkers, whether predictive, prognostic, or for early detection, are proving to be valuable tools for patient stratification and improving clinical outcomes in cancer care
In the era of precision medicine, targeted therapies based on specific cancer biomarkers are gaining increasing approval, resulting in a growing need for next-generation sequencing to identify patient populations with key mutations who are likely to benefit from the drugs. In addition, oncologists have a significant unmet need for better prognostic, predictive, and monitoring tools for their patients. This research topic aims to consolidate studies focused on patient stratification, treatment response markers, and early detection tools based on molecular markers, including NGS technologies for DNA or RNA analysis and investigations of both tissue and circulating tumor DNA markers.
This research topic will focus on studies related to next-generation sequencing (NGS) technologies, both tissue-based and liquid-based, for DNA or RNA sequencing, and will require experimental validation of the identified biomarkers. The clinical utility of these biomarkers need to be clear. The scope of the research will include investigating the role of tissue NGS in treating patients with disease progression, as well as the potential of liquid biopsy (NGS) for patient monitoring and detecting minimal residual disease. The topic will also explore technologies for early detection of cancer and RNA-based signatures that can serve as predictive biomarkers.
This topic will not accept papers based solely on standard bioinformatic analyses of one or few well-known databases such as TCGA.
In recent years, there has been a significant increase in the number of FDA-approved pan-tumor biomarkers. This is driven by the growing realization among patients and oncologists of the potential benefits of personalized oncology, including treatment regimens tailored to their unique tumor profiles. To meet this demand, there has been a surge of research programs aimed at identifying these molecular markers, facilitated by the decreasing cost of next-generation sequencing. These cancer biomarkers, whether predictive, prognostic, or for early detection, are proving to be valuable tools for patient stratification and improving clinical outcomes in cancer care
In the era of precision medicine, targeted therapies based on specific cancer biomarkers are gaining increasing approval, resulting in a growing need for next-generation sequencing to identify patient populations with key mutations who are likely to benefit from the drugs. In addition, oncologists have a significant unmet need for better prognostic, predictive, and monitoring tools for their patients. This research topic aims to consolidate studies focused on patient stratification, treatment response markers, and early detection tools based on molecular markers, including NGS technologies for DNA or RNA analysis and investigations of both tissue and circulating tumor DNA markers.
This research topic will focus on studies related to next-generation sequencing (NGS) technologies, both tissue-based and liquid-based, for DNA or RNA sequencing, and will require experimental validation of the identified biomarkers. The clinical utility of these biomarkers need to be clear. The scope of the research will include investigating the role of tissue NGS in treating patients with disease progression, as well as the potential of liquid biopsy (NGS) for patient monitoring and detecting minimal residual disease. The topic will also explore technologies for early detection of cancer and RNA-based signatures that can serve as predictive biomarkers.
This topic will not accept papers based solely on standard bioinformatic analyses of one or few well-known databases such as TCGA.
