Gliomas are the most common and devastating primary malignant brain tumors. Glioblastoma (GBM), one of the most lethal and most prone to recurrence due to inter-and intratumoral heterogeneity. It is vital to note that glioblastoma plasticity explains the high degree of tumor heterogeneity at the histological, cellular, and molecular levels, as well as favoring the selection of new clones during recurrence or therapeutic resistance. One of the key causes of therapy resistance that leads to treatment failure is the molecular heterogeneity of CNS malignancies. Conventional sequencing methods have provided information on which genes are expressed in a given tissue, either by sequencing averaged mRNA output or a single cell. Both technologies lack spatial information about analyzed cells, which is essential for deciphering molecular heterogeneity in diseases such as brain tumors. Accumulating evidence suggests that spatiotemporal heterogeneity likely is the key to understanding treatment failure. However, the extent of spatiotemporal heterogeneity as a result of tumor evolution and plasticity is still poorly understood. Spatial transcriptomics technology can help us understand the complex heterogeneity of tumors by providing localization-indexed gene expression information.
Without a doubt, the tumor microenvironment in CNS malignancy is very complex. Immune cells have a dynamic relationship with tumor cells that involves both direct and indirect interactions and affects the biology of the tumor. Understanding the complexities of cell behavior and interactions requires an understanding of spatial context. Individual cells take on diverse responsibilities depending on their environs or neighborhoods. The identification of dynamic adaptations of cellular states and their spatial interactions within the tumor microenvironment is made possible by thorough characterization of CNS tumors at numerous molecular levels in a spatially defined way. With a better understanding of spatial heterogeneity, physicians and researchers will be able to develop novel targeting strategies or optimally orchestrate combinational treatments aimed at overcoming therapeutic resistance, with the goal of improving clinical benefits against CNS malignancies. In this research topic, we aim at discussing and sharing spatial biology methods currently available to investigate CNS tumor heterogeneity. We invite submissions which develop spatially resolved transcriptomics techniques or apply them to make an original contribution to the field.
In this Research Topic, we aim to provide a current overview of the field with original contributions on molecular mechanism that describe spatial heterogeneity and discuss their therapeutic implications. We welcome submissions of Original Research articles, Reviews and Perspectives covering efficacy and resistance mechanisms to immunotherapies in CNS malignancies and pre-clinical cancer models, and including workflow of spatial analysis, with a focus on the following subtopics:
1. Original articles describing the heterogeneity of CNS tumors using spatial biology techniques.
2. Targeting Immunosuppression in brain tumors employing spatial biology.
3. Articles describing histological, morphological, and dynamic properties of glioma
4. Perspective articles presenting possible applications in Neuro-oncology
5. Protocols and methodologies pertaining to spatial analysis workflow.
Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this topic.
Gliomas are the most common and devastating primary malignant brain tumors. Glioblastoma (GBM), one of the most lethal and most prone to recurrence due to inter-and intratumoral heterogeneity. It is vital to note that glioblastoma plasticity explains the high degree of tumor heterogeneity at the histological, cellular, and molecular levels, as well as favoring the selection of new clones during recurrence or therapeutic resistance. One of the key causes of therapy resistance that leads to treatment failure is the molecular heterogeneity of CNS malignancies. Conventional sequencing methods have provided information on which genes are expressed in a given tissue, either by sequencing averaged mRNA output or a single cell. Both technologies lack spatial information about analyzed cells, which is essential for deciphering molecular heterogeneity in diseases such as brain tumors. Accumulating evidence suggests that spatiotemporal heterogeneity likely is the key to understanding treatment failure. However, the extent of spatiotemporal heterogeneity as a result of tumor evolution and plasticity is still poorly understood. Spatial transcriptomics technology can help us understand the complex heterogeneity of tumors by providing localization-indexed gene expression information.
Without a doubt, the tumor microenvironment in CNS malignancy is very complex. Immune cells have a dynamic relationship with tumor cells that involves both direct and indirect interactions and affects the biology of the tumor. Understanding the complexities of cell behavior and interactions requires an understanding of spatial context. Individual cells take on diverse responsibilities depending on their environs or neighborhoods. The identification of dynamic adaptations of cellular states and their spatial interactions within the tumor microenvironment is made possible by thorough characterization of CNS tumors at numerous molecular levels in a spatially defined way. With a better understanding of spatial heterogeneity, physicians and researchers will be able to develop novel targeting strategies or optimally orchestrate combinational treatments aimed at overcoming therapeutic resistance, with the goal of improving clinical benefits against CNS malignancies. In this research topic, we aim at discussing and sharing spatial biology methods currently available to investigate CNS tumor heterogeneity. We invite submissions which develop spatially resolved transcriptomics techniques or apply them to make an original contribution to the field.
In this Research Topic, we aim to provide a current overview of the field with original contributions on molecular mechanism that describe spatial heterogeneity and discuss their therapeutic implications. We welcome submissions of Original Research articles, Reviews and Perspectives covering efficacy and resistance mechanisms to immunotherapies in CNS malignancies and pre-clinical cancer models, and including workflow of spatial analysis, with a focus on the following subtopics:
1. Original articles describing the heterogeneity of CNS tumors using spatial biology techniques.
2. Targeting Immunosuppression in brain tumors employing spatial biology.
3. Articles describing histological, morphological, and dynamic properties of glioma
4. Perspective articles presenting possible applications in Neuro-oncology
5. Protocols and methodologies pertaining to spatial analysis workflow.
Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by robust and relevant validation (clinical cohort or biological validation in vitro or in vivo) are out of scope for this topic.
