Glioblastoma (GB), also referred to as a grade IV astrocytoma, is a fast-growing and aggressive brain tumor. It diffusely invades the nearby brain tissue, but generally does not spread to distant organs. GBs can arise in the brain de novo or may evolve from lower-grade astrocytoma.
Glioblastoma represents one of the deadliest human cancers, with an average survival at diagnosis of about 1 year. This poor prognosis is due to diffuse tissue invasion, tumor recurrence after surgical removal as well as resistance to existing therapies. One of the most important hallmarks of GB is its biological heterogeneity. As in many cancer types intertumor heterogeneity is mostly characterized by distinct genetic alterations that occur in individual tumors. However, the molecular diversity within individual tumors has become a focus of research in the past few years, with tumor cell plasticity representing a special area of interest.
Cancers progress through the accumulation of somatic mutations, allowing some cells to proliferate in an uncontrolled way driven by latent evolutionary forces moulding the genetic and epigenetic composition of tumor sub-populations. The adoption of next-generation sequencing technologies opens the possibility of measuring molecular profiles of Glioblastomas at multiple resolutions, across one or multiple patients’ tumors to disentangle evolutionary trajectories in these aggressive cancers. This Research Topic focuses on the application of genomic screening methods and the analysis of genomic datasets in the exploration of Glioblastoma oncogenesis and disease evolution.
We welcome manuscripts dealing with the following:
• insights into the pathogenesis of glioblastoma from molecular screening studies, especially relating to clonal complexity and molecular changes during disease progression.
• molecular studies of the cellular components of the tumor microenvironment in Glioblastomas
• methodologies for and studies of clonal evolution, including determination of temporal order of mutational events and mutational landscape analyses
• application of single-cell multi-omics analysis to decipher clonal evolution across several stages of disease development
• studies integrating multiple types of molecular data (e.g. genomics, expression, methylation, chromatin accessibility, protein abundance) in the study of Glioblastoma oncogenesis
Glioblastoma (GB), also referred to as a grade IV astrocytoma, is a fast-growing and aggressive brain tumor. It diffusely invades the nearby brain tissue, but generally does not spread to distant organs. GBs can arise in the brain de novo or may evolve from lower-grade astrocytoma.
Glioblastoma represents one of the deadliest human cancers, with an average survival at diagnosis of about 1 year. This poor prognosis is due to diffuse tissue invasion, tumor recurrence after surgical removal as well as resistance to existing therapies. One of the most important hallmarks of GB is its biological heterogeneity. As in many cancer types intertumor heterogeneity is mostly characterized by distinct genetic alterations that occur in individual tumors. However, the molecular diversity within individual tumors has become a focus of research in the past few years, with tumor cell plasticity representing a special area of interest.
Cancers progress through the accumulation of somatic mutations, allowing some cells to proliferate in an uncontrolled way driven by latent evolutionary forces moulding the genetic and epigenetic composition of tumor sub-populations. The adoption of next-generation sequencing technologies opens the possibility of measuring molecular profiles of Glioblastomas at multiple resolutions, across one or multiple patients’ tumors to disentangle evolutionary trajectories in these aggressive cancers. This Research Topic focuses on the application of genomic screening methods and the analysis of genomic datasets in the exploration of Glioblastoma oncogenesis and disease evolution.
We welcome manuscripts dealing with the following:
• insights into the pathogenesis of glioblastoma from molecular screening studies, especially relating to clonal complexity and molecular changes during disease progression.
• molecular studies of the cellular components of the tumor microenvironment in Glioblastomas
• methodologies for and studies of clonal evolution, including determination of temporal order of mutational events and mutational landscape analyses
• application of single-cell multi-omics analysis to decipher clonal evolution across several stages of disease development
• studies integrating multiple types of molecular data (e.g. genomics, expression, methylation, chromatin accessibility, protein abundance) in the study of Glioblastoma oncogenesis