Scientists generate detailed map of glioblastoma genes, proteins, infiltrating cells and signaling
A study by researchers at Washington University School of Medicine in St. Louis, the Pacific Northwest National Laboratory, Case Western Reserve University, and the National Cancer Institute (NCI), revealed a detailed map of genes, proteins, infiltrating cells and signaling. pathways that play a key role in the conduct of glioblastoma (GBM).
The researchers say the study, through which they analyzed 99 patient tumors, offers the largest and most detailed picture of this deadly brain tumor, and could help design clinical trials and potentially point to new ones. therapeutic strategies. The research is part of NCI’s Clinical Proteomic Tumor Analysis Consortium (CPTAC).
“To improve therapies for this deadly cancer, understanding the tumor cells themselves is important but not enough,” said Li Ding, PhD, professor of medicine and genetics and director of computational biology at the Oncology Division of the University of Washington. “We also need to understand the interactions of tumor cells with the surrounding environment, including immune cells, connective tissues and blood vessels. In our study, we performed high-resolution, high-depth analyzes on 99 glioblastoma tumors. Exploiting new technologies, including proteomics, metabolomics and single-cell sequencing, this study is an extremely deep dive into the biology of glioblastoma tumors, revealing new therapeutic possibilities.
Ding is the co-lead author of the team’s article, which is published in Cancer cell, and titled “Proteogenomic and Metabolomic Characterization of Human Glioblastoma”.
Glioblastoma is one of the most aggressive and devastating cancers. Although it is rare compared to other cancers – the incidence is approximately 12,000 new cases in the United States each year – glioblastoma is the most common type of brain cancer. The current standard of care includes surgery, chemotherapy and radiation therapy. “Promising immunotherapies have been proposed, including immune checkpoint inhibitors, vaccines, chimeric antigen receptor (CAR-T) T cell therapy, and viral therapy, although none have permitted them. phase III trials, ”the authors noted.
Yet even with intensive treatment, relatively few patients survive more than two years after diagnosis, and less than 10% of patients survive beyond five years. And despite extensive studies focused on the genomic characteristics of glioblastoma, relatively little progress has been made in improving the treatment of patients with this deadly disease. “The GBM was one of the first subjects of in-depth genomic and transcriptomic analyzes and targeted studies in MS,” the researchers continued. “However, most patients are still treated with a standard of care developed almost two decades ago, which underscores the need for further knowledge.
For their recently published study, the researchers performed an integrated analysis of genomic, proteomic, post-translational modification, and metabolomic data for 99 treatment-naïve GBMs. “Here, we have extended classical sequencing approaches with full integration of proteome, phosphoproteome, acetyloma, metabolome and lipidome and single-cell transcriptomics analyzes,” they wrote.
Among their reported findings, the study results identified new activated proteins, in particular PTPN11 and PLCG1, which serve as signaling hubs leading to tumor growth in some patients. “Phosphoproteomic data indicate that PLCG1 and PTPN11 act as a common signaling hub for several RTKs [receptor tyrosine kinases]”, Noted the authors. The results also revealed gene expression patterns involved in the epithelial-mesenchymal transition (EMT) which is common in tumor formation.
Interestingly, the analysis identified four different categories by which to classify glioblastoma, based on the number and types of immune cells present in the tumors. “RNA and protein expression data from bulk tumors indicate that GBM subtypes differ in macrophage infiltration and distribution of specific immune cell types,” the team noted. “What is particularly interesting about this study is the grouping of glioblastomas into four groups based on immune subtypes that emerged by combining a comprehensive proteomic and genomic analysis,” added Henry Rodriguez, director of the Office. of Cancer Clinical Proteomics Research at NCI. “It may open the door to effective responses to immune therapy.”
With the discovery that the immune landscape of these tumors varied widely and fell into four distinct categories, the new data could indicate how individual tumors are likely to respond differently to targeted therapies. For example, type 1 tumors contain a large number of immune cells called macrophages and a few T cells. Type 2 tumors have a moderate number of macrophages. Type 3 tumors include a high number of T cells and some macrophages. And type 4 tumors are what Ding calls an immune desert, with little or no immune cells of any type. So, immunotherapy that targets macrophages, for example, might work well in patients with type 1 tumors, but not at all in patients with type 4. Additionally, it is possible that a clinical trial in which all patients grouped together does not show that a drug is working at all, when averaged over all patients.
Co-author added Albert H. Kim, MD, PhD, professor of neurological surgery at the University of Washington and director of the Brain Tumor Center at Siteman: “Clinical trials of immunotherapy in glioblastoma have been negative so far. . And the fact that there are four different immune subgroups may be one of the reasons behind this. We cannot treat all glioblastoma tumors as one disease.
The study also determined how a little-studied protein modification, acetylation, may explain some functional differences between glioblastoma subtypes. “Acetylation changes the shape of a protein and often results in the opening of DNA-protein complexes to facilitate gene expression,” said senior author Karin Rodland, PhD, chief scientist for biomedical research at Pacific Northwest National Laboratory. “By adding protein acetylation to our study, we were able to complete the loop from proteins to genes and gene expression, highlighting important regulatory changes in glioblastoma.”
A group led by co-lead author Tao Liu, PhD, of the Pacific Northwest National Laboratory, measured all proteins in tumor samples as well as phosphorylation and acetylation, which affect biological functions such as cell signaling. Adding these data to the genomic analysis of tumors revealed a small subset of glioblastomas that did not match any of the typical genomic subtypes. “Multi-omic analysis identified a subset of patients with mixed subtypes compared to traditional sequencing-based subtypes, who exhibit shortened overall survival.
These mixed subtype tumors were associated with poor clinical outcome, providing researchers with clues about factors affecting tumor aggressiveness that were not evident from genetic information alone. “These models provide additional information for researchers to understand how the glioblastoma subtypes they have identified may vary in their biological function,” Liu said. “This multifaceted analysis provides an unprecedented level of detail, which begins to connect the missing dots in glioblastoma.”
Summarizing their findings, the authors noted: “The multidimensional analysis of patient samples described in this investigation adds context to previous GBM genomic and transcriptional investigations and suggests avenues for further mechanistic studies. “
Co-author Milan G. Chheda, MD, assistant professor of medicine who treats patients at the Siteman Cancer Center at Barnes-Jewish Hospital and the Washington University School of Medicine, added, “The most immediate implications of these findings are better test design. For most clinical trials, we take all comers and give them the same treatment. We do not design the trials as precisely as possible because we did not fully understand the molecular differences between tumors in each patient. This leads us to characterize treatment as failure when in fact it can help specific people. The researchers are conducting further studies to identify the best drugs to study in patients with glioblastoma, based on where their diseases are on the new tumor map.
The authors concluded: “Rapid advances in single-cell genomics and proteomics technologies will facilitate further analyzes of GBM heterogeneity and TME interactions. We hope that these advances will improve patient stratification for clinical trials and ultimately lead to personalized treatments. Chheda added, “This document is an example of the progress that can be made when there is close collaboration between many experts across the country that the National Cancer Institute has the capacity to bring together.”