Treatment with immune checkpoint inhibitors (ICIs) can bring remarkable responses in some cancer types. However, only 20% - 30% of patients achieved durable clinical benefit (DCB), while a larger proportion of patients developed early disease progression. Moreover, about 10% of patients receiving ICIs have been observed to experience hyper-progressive diseases. Therefore, biomarkers to identify therapy-responsive patients before and during treatment courses are highly needed. Currently, the most widely used biomarkers for predicting response to ICIs include PD-L1 protein expression and tumor mutational burden (TMB). However, major limitations have restricted their clinical application, including intra/intertumor heterogeneity, non-standardized cut-off value, and difficulty in obtaining tissues before and after therapy.
An alternative option for predicting ultimate clinical benefit would be early response evaluation. Though molecular imaging has shown promising results in patient response evaluation, it is usually performed 6 - 12 weeks after initial treatment, thus the early evaluation window has been missed. Therefore, non-invasive biomarkers for early and dynamic identification of therapeutic benefits from cancer immunotherapy is urgently needed and holds great promise. Preliminary molecular data on non-invasive liquid biopsies has demonstrated the possibility of early response prediction in potential responders. Although several biomarkers from blood draws have been proposed, gaps remain in standardized cutoff values and specific time points for these biomarkers. Besides, some liquid biomarkers, such as bTMB, are still under evaluation in ongoing clinical trials.
This Research Topic focuses on the discovery and development of reliable and innovative non-invasive liquid biomarkers or biomarker combination models for early and dynamic identification of therapeutic benefits from cancer immunotherapy. Besides, studies discussing precise timing and standardized cutoff values about existing biomarkers are also welcome. We welcome Original Research and Review Articles that focus on, but not restrict to, the following research areas in non-invasive biomarkers for early and dynamic identification or prediction of therapeutic benefits of immunotherapy.
• Liquid biomarkers related to genetic alterations from the blood, such as bTMB, bCNA, or specific gene mutations.
• RNAs including coding and non-coding RNAs (microRNA, lncRNA, cirRNA) from blood samples for immunotherapy response prediction.
• CTC, ctDNA, or exosomes in plasma for selection of responders and non-responders before or during course of treatment.
• Integrated models established from non-invasive biomarkers are also welcome.
* Studies consisting solely of bioinformatic investigation of publicly available genomic / transcriptomic data without experimental or in situ validation to support conclusions are not in scope of this Research Topic
* Studies focused on proteomic and metabolomic investigation are not in scope of this Research Topic
Treatment with immune checkpoint inhibitors (ICIs) can bring remarkable responses in some cancer types. However, only 20% - 30% of patients achieved durable clinical benefit (DCB), while a larger proportion of patients developed early disease progression. Moreover, about 10% of patients receiving ICIs have been observed to experience hyper-progressive diseases. Therefore, biomarkers to identify therapy-responsive patients before and during treatment courses are highly needed. Currently, the most widely used biomarkers for predicting response to ICIs include PD-L1 protein expression and tumor mutational burden (TMB). However, major limitations have restricted their clinical application, including intra/intertumor heterogeneity, non-standardized cut-off value, and difficulty in obtaining tissues before and after therapy.
An alternative option for predicting ultimate clinical benefit would be early response evaluation. Though molecular imaging has shown promising results in patient response evaluation, it is usually performed 6 - 12 weeks after initial treatment, thus the early evaluation window has been missed. Therefore, non-invasive biomarkers for early and dynamic identification of therapeutic benefits from cancer immunotherapy is urgently needed and holds great promise. Preliminary molecular data on non-invasive liquid biopsies has demonstrated the possibility of early response prediction in potential responders. Although several biomarkers from blood draws have been proposed, gaps remain in standardized cutoff values and specific time points for these biomarkers. Besides, some liquid biomarkers, such as bTMB, are still under evaluation in ongoing clinical trials.
This Research Topic focuses on the discovery and development of reliable and innovative non-invasive liquid biomarkers or biomarker combination models for early and dynamic identification of therapeutic benefits from cancer immunotherapy. Besides, studies discussing precise timing and standardized cutoff values about existing biomarkers are also welcome. We welcome Original Research and Review Articles that focus on, but not restrict to, the following research areas in non-invasive biomarkers for early and dynamic identification or prediction of therapeutic benefits of immunotherapy.
• Liquid biomarkers related to genetic alterations from the blood, such as bTMB, bCNA, or specific gene mutations.
• RNAs including coding and non-coding RNAs (microRNA, lncRNA, cirRNA) from blood samples for immunotherapy response prediction.
• CTC, ctDNA, or exosomes in plasma for selection of responders and non-responders before or during course of treatment.
• Integrated models established from non-invasive biomarkers are also welcome.
* Studies consisting solely of bioinformatic investigation of publicly available genomic / transcriptomic data without experimental or in situ validation to support conclusions are not in scope of this Research Topic
* Studies focused on proteomic and metabolomic investigation are not in scope of this Research Topic
