About this Research Topic
This Research Topic is the second volume of the “Community Series in Novel Biomarkers for Predicting Response to Cancer Immunotherapy". Please see Volume I here.
Immunotherapy has revolutionized the treatment of malignancies. Targeting of immune checkpoints cytotoxic T-lymphocyte-associated protein 4, programmed cell death protein 1 (PD-1) and its ligand (PD-L1) has led to improving survival in a subset of patients. Despite their remarkable success, clinical benefit remains limited to only a subset of patients. A significant limitation behind these current treatment modalities is an irregularity in clinical response, which is especially pronounced among checkpoint inhibition.
Currently, relevant predictors of cancer immunotherapy response include microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR), expression of PD-L1, tumor mutation burden (TMB), immune genomic characteristics, and tumor infiltrating lymphocytes (TILs). However, none of them have sufficient evidence to be a stratification factor. Moreover, as the combined strategies for effective cancer immunotherapy had been developed in multiple tumors, such as Immunotherapy combined with chemotherapy, radiotherapy, targeted therapy and anti-angiogenesis therapy. Therefore, the development of novel biomarkers endowed with high sensitivity, specificity and accuracy able to identify which patients may truly benefit from the treatment with cancer immunotherapy would allow to refine the therapeutic selection and to better tailor the treatment strategy.
This research topic aims to focus on the advances in the discoveries of novel biomarkers for predicting response to cancer immunotherapy in various tumors. We welcome the submission of original research and review articles that include biomarkers in clinical study and applications, as well as technologies or discoveries in experimental approaches.
Potential topics include but are not limited to the following:
1. New technologies or methods employed in discover biomarkers for cancer immunotherapy.
2.Novel Serum markers to predict the immunotherapy response in cancer patients.
3. The application of Next-Generation Sequencing (NGS) for predicting response to cancer immunotherapy.
4. Integrated genomic analysis identifies clinically relevant subtypes of patients sensitive to cancer immunotherapy.
5. Novel molecules and its mechanisms involved in the response or sensibility of cancer immunotherapy.
6. circulating cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), mRNA, microRNAs (miRNAs), circular RNA (circRNA), exosomal RNAs (exRNAs), and long non-coding RNAs (IncRNAs) in tumor cells and serum as biomarkers for prognosis or cancer immunotherapy.
7. The relationship between the diversity of gut microbiota and the efficacy of immunotherapy.
8. Immune neoantigen of tumor involved in immune response during cancer immunotherapy.
9. Novel pathological features relate to the response or sensibility of cancer immunotherapy.
10. Bioinformatics research with validation to identify novel biomarkers base on patients receive cancer immunotherapy.
*NOTE: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation are considered out of the scope of this Research Topic.
Immunotherapy has revolutionized the treatment of malignancies. Targeting of immune checkpoints cytotoxic T-lymphocyte-associated protein 4, programmed cell death protein 1 (PD-1) and its ligand (PD-L1) has led to improving survival in a subset of patients. Despite their remarkable success, clinical benefit remains limited to only a subset of patients. A significant limitation behind these current treatment modalities is an irregularity in clinical response, which is especially pronounced among checkpoint inhibition.
Currently, relevant predictors of cancer immunotherapy response include microsatellite instability-high/deficient mismatch repair (MSI-H/dMMR), expression of PD-L1, tumor mutation burden (TMB), immune genomic characteristics, and tumor infiltrating lymphocytes (TILs). However, none of them have sufficient evidence to be a stratification factor. Moreover, as the combined strategies for effective cancer immunotherapy had been developed in multiple tumors, such as Immunotherapy combined with chemotherapy, radiotherapy, targeted therapy and anti-angiogenesis therapy. Therefore, the development of novel biomarkers endowed with high sensitivity, specificity and accuracy able to identify which patients may truly benefit from the treatment with cancer immunotherapy would allow to refine the therapeutic selection and to better tailor the treatment strategy.
This research topic aims to focus on the advances in the discoveries of novel biomarkers for predicting response to cancer immunotherapy in various tumors. We welcome the submission of original research and review articles that include biomarkers in clinical study and applications, as well as technologies or discoveries in experimental approaches.
Potential topics include but are not limited to the following:
1. New technologies or methods employed in discover biomarkers for cancer immunotherapy.
2.Novel Serum markers to predict the immunotherapy response in cancer patients.
3. The application of Next-Generation Sequencing (NGS) for predicting response to cancer immunotherapy.
4. Integrated genomic analysis identifies clinically relevant subtypes of patients sensitive to cancer immunotherapy.
5. Novel molecules and its mechanisms involved in the response or sensibility of cancer immunotherapy.
6. circulating cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), mRNA, microRNAs (miRNAs), circular RNA (circRNA), exosomal RNAs (exRNAs), and long non-coding RNAs (IncRNAs) in tumor cells and serum as biomarkers for prognosis or cancer immunotherapy.
7. The relationship between the diversity of gut microbiota and the efficacy of immunotherapy.
8. Immune neoantigen of tumor involved in immune response during cancer immunotherapy.
9. Novel pathological features relate to the response or sensibility of cancer immunotherapy.
10. Bioinformatics research with validation to identify novel biomarkers base on patients receive cancer immunotherapy.
*NOTE: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation are considered out of the scope of this Research Topic.
Keywords: #CollectionSeries, Biomarkers, Cancer Immunotherapy, Treatment
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
