Search

Analysis of tumor gene expression is an important approach for the classification and identification of therapeutic vulnerabilities. However, targeting glioblastoma (GBM) based on molecular subtyping has not yet translated into successful therapies. Here, we present an integrative approach based on molecular pathways to expose new potentially actionable targets. We used gene set enrichment analysis to conduct an unsupervised clustering analysis to condense the gene expression data from bulk patient samples and patient-derived gliomasphere lines into new gene signatures. We identified key targets that are predicted to be differentially activated between tumors and were functionally validated in a library of gliomasphere cultures. Resultant cluster-specific gene signatures associated not only with hallmarks of cell cycle and stemness gene expression, but also with cell type–specific markers and different cellular states of GBM. Several upstream regulators, such as PIK3R1 and EBF1 were differentially enriched in cells bearing stem cell like signatures and bear further investigation. We identified the transcription factor E2F1 as a key regulator of tumor cell proliferation and self-renewal in only a subset of gliomasphere cultures predicted to be E2F1 signaling dependent. Our in vivo work also validated the functional significance of E2F1 in tumor formation capacity in the predicted samples. E2F1 inhibition also differentially sensitized E2F1-dependent gliomasphere cultures to radiation treatment. Our findings indicate that this novel approach exploring cancer pathways highlights key therapeutic vulnerabilities for targeting GBM. Significance: Molecular classification of GBM has not yet resulted in the development of effective therapies. We have developed an integrative approach to identify molecular targets differentially utilized by individual tumors. This approach could lead to patient- and tumor-specific therapeutics.

TCGA gene ontology analysis of clusters shows differentially enriched terms

Gliomasphere dataset analysis generates two clusters with clinical relevance

Validation of genelists in additional gliomasphere dataset

GO terms and TF enriched in modules associated with GS clusters

Gene signatures associate differentially to cell cycle, cellular states, and cell identities

Gene Lists for each PC and direction from TCGA and GS datasets

Consensus clustering identifies three clusters for the TCGA dataset

Analysis of tumor gene expression is an important approach for the classification and identification of therapeutic vulnerabilities. However, targeting glioblastoma (GBM) based on molecular subtyping has not yet translated into successful therapies. Here, we present an integrative approach based on molecular pathways to expose new potentially actionable targets. We used gene set enrichment analysis to conduct an unsupervised clustering analysis to condense the gene expression data from bulk patient samples and patient-derived gliomasphere lines into new gene signatures. We identified key targets that are predicted to be differentially activated between tumors and were functionally validated in a library of gliomasphere cultures. Resultant cluster-specific gene signatures associated not only with hallmarks of cell cycle and stemness gene expression, but also with cell type–specific markers and different cellular states of GBM. Several upstream regulators, such as PIK3R1 and EBF1 were differentially enriched in cells bearing stem cell like signatures and bear further investigation. We identified the transcription factor E2F1 as a key regulator of tumor cell proliferation and self-renewal in only a subset of gliomasphere cultures predicted to be E2F1 signaling dependent. Our in vivo work also validated the functional significance of E2F1 in tumor formation capacity in the predicted samples. E2F1 inhibition also differentially sensitized E2F1-dependent gliomasphere cultures to radiation treatment. Our findings indicate that this novel approach exploring cancer pathways highlights key therapeutic vulnerabilities for targeting GBM.Significance:Molecular classification of GBM has not yet resulted in the development of effective therapies. We have developed an integrative approach to identify molecular targets differentially utilized by individual tumors. This approach could lead to patient- and tumor-specific therapeutics.

Gene lists differentially correlate with cell cycle and stemness signatures

E2F1 targeting with multiple sgRNA validate its role in sphere formation capacity in a subset of samples

The great phenotypic heterogeneity of glioblastoma (GBM) – both inter and intratumorally – has hindered therapeutic efforts. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has not translated to a significant extension of patient survival. We hypothesize that, rather than gene expression as a whole, analysis of targetable pathways could yield important insights into the development of novel classification schemes and, most importantly, to targeted therapeutics. Here, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. The Cancer Genome Atlas samples were clustered using gene set enrichment analysis and the resulting 3 clusters were informative of patient survival and only modestly overlapped with prior molecular classification. We validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity, proliferation and in vivo tumor growth when E2F1, our top target, was silenced. Consistent with our theory, E2F1 knockdown had little or no effect on the growth of the non-enriched lines, despite their ability to proliferate in vitro and in vivo. We similarly analyzed single cell RNAseq datasets and correlated cell cycle and stemness signatures with the gene lists we generated as well as with molecular states and cell specific signatures. Finally, we confirmed a connection between E2F1 and cellular inhibitor of PP2A (CIP2A) in a cluster of samples. Loss of function studies reveals a diminished capacity for DNA damage regulation in E2F1 activated samples. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

Recent advances in single cell expression technology have allowed us to appreciate the complexity in tumoral heterogeneity of solid tumors such as glioblastoma (GBM), which remains uniformly fatal despite aggressive therapies. Currently, there is no knowledge about cell identities and functional characteristics of the different tumoral populations. To this end, we created a 28-marker mass cytometry panel composed of signaling markers, including phospho-proteins, and lineage markers that have been associated with GBM or are considered putative cancer stem cell markers. We evaluated lines established from core and edge areas from the same patient and validated to be functionally different with RNA expression and in vivo experiments. We found clusters shared by cells from both regions as well as region-specific ones. In order to better characterize these, we used marker enrichment modeling (MEM) and generated machine-readable labels. These were compared to MEM labels generated after using the same signaling markers to cluster primary samples from newly diagnosed or recurrent patients. Similarly, MEM labels were obtained from patients in a clinical trial treated with capecitabine that had positive or negative responses. Clusters from edge cells were found in higher proportion in recurrent tumors and were correlated with negative responses to chemotherapy. Initial analyses have also been done correlating immune clusters with tumor clusters in the same samples. Edge clusters are characterized by a CD44+ SOX2+ Nestin+ population. Treatment of tumor cells with temozolomide and irradiation results in an increase of this population in vitro. We are currently conducting single cells analyses to characterize this population as well as in vivo studies to validate the tumor-immune interactions. Our studies exploit single cell cytometry to underscore pathways that are preferentially use by different populations and affect immune cells with the goal of establishing therapeutic efforts to extend patient survival.

Targeting glioblastoma (GBM) based on molecular subtyping have not yet translated into successful therapies. Here, we used gene set enrichment analysis (GSEA) to conduct an unsupervised clustering analysis to condense the gene expression data from bulk patient samples and patient-derived gliomasphere lines into new gene lists. We then identified key molecular pathways differentially regulated between tumors. These gene lists associated not only with cell cycle and stemness signatures, but also with cell-type specific markers and different cellular states of GBM. We identified the transcription factor E2F1 as a key regulator of tumor cell proliferation and self-renewal in only the subset of proliferating gliomasphere cultures predicted to be E2F1-activated and validated its functional significance in tumor formation capacity. E2F1 inhibition also sensitized E2F1-activated gliomasphere cultures to radiation treatment. Our findings indicate that a pathway-based approach can be leveraged to deconstruct inter-tumoral heterogeneity and uncover key therapeutic vulnerabilities for targeting GBM.

The great phenotypic heterogeneity of glioblastoma (GBM) – both inter and intratumorally – has hindered therapeutic efforts. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has not translated to a significant extension of patient survival. We hypothesize that, rather than gene expression as a whole, analysis of targetable pathways could yield important insights into the development of novel classification schemes and, most importantly, to targeted therapeutics. Here, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. The Cancer Genome Atlas samples were clustered using gene set enrichment analysis and the resulting 3 clusters were informative of patient survival and only modestly overlapped with prior molecular classification. We validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity, proliferation and in vivo tumor growth when E2F1, our top target, was silenced. Consistent with our theory, E2F1 knockdown had little or no effect on the growth of the non-enriched lines, despite their ability to proliferate in vitro and in vivo. We similarly analyzed single cell RNAseq datasets and correlated cell cycle and stemness signatures with the gene lists we generated, concluding that cells with stem cell signatures were depleted of E2F1 and its downstream targets. Finally, we confirmed a connection between E2F1 and cellular inhibitor of PP2A (CIP2A) in a cluster of samples. Loss of function studies reveal a diminished capacity for DNA damage regulation in E2F1 activated samples. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

Despite efforts to gain a deeper understanding of its molecular architecture, glioblastoma (GBM) remains uniformly fatal. While genome-based molecular subtyping has revealed that GBMs may be parsed into several molecularly distinct categories, this insight has yielded little progress towards extending patient survival. In particular, the great phenotypic heterogeneity of GBM – both inter and intratumorally – has hindered therapeutic efforts. To this end, we interrogated tumor samples using a pathway-based approach to resolve tumoral heterogeneity. Gene set enrichment analysis (GSEA) was applied to gene expression data and used to provide an overview of each sample that can be compared to other samples by generating sample clusters based on overall patterns of enrichment. The Cancer Genome Atlas (TCGA) samples were clustered using the canonical and oncogenic signatures and in both cases the clustering was distinct from the molecular subtype previously reported and clusters were informative of patient survival. We also analyzed single cell RNA sequencing datasets and uniformly found two clusters of cells enriched for cell cycle regulation and survival pathways. We have validated our approach by generating gene lists from common elements found in the top contributing genesets for a particular cluster and testing the top targets in appropriate gliomasphere patient-derived lines. Samples enriched for cell cycle related genesets showed a decrease in sphere formation capacity when E2F1, out top target, was silenced and when treated with fulvestrant and calcitriol, which were identified as potential drugs targeting this genelist. Conversely, no changes were observed in samples not enriched for this gene list. Finally, we interrogated spatial heterogeneity and found higher enrichment of the proliferative signature in contrast enhancing compared with non-enhancing regions. Our studies relate inter- and intratumoral heterogeneity to critical cellular pathways dysregulated in GBM, with the ultimate goal of establishing a pipeline for patient- and tumor-specific precision medicine.

Glioblastoma (GBM) is a highly vascularized, invasive and therapy-resistant brain tumor driven by glioma stem-like cells (GSCs). GSCs reside in three specialized niches or microenvironments: the perivascular, hypoxic and invasive niches. The perivascular and hypoxic niches support the maintenance of GSCs within the tumor bulk, whereas the invasive niche consists of GSCs associated with the pre-existing blood vessels that they co-opt to migrate and invade into other brain regions. Recent findings indicate a bidirectional conversion between the perivascular maintenance and invasive niche propelled by the enormous plasticity of GSCs to transdifferentiate into endothelial-like cells (ECs) and pericytes (PCs). Importantly, these GSC-derived EC-like cells are predominantly found in recurrent tumors than matched primary tumors indicating that therapy may promote GSC plasticity and transdifferentiation into vascular elements. The standard treatment for most GBM patients is maximal surgical resection, fractionated radiation and adjuvant chemotherapy with the drug temozolomide. Prior studies demonstrated that radiation therapy (RT) can induce reprogramming and de-differentiation of tumor cells into a GSC-like state. Based on these findings, we tested the effects of RT in promoting the transdifferentiation potential of GSCs into vascular elements. Our in vitro findings show that RT induces EC gene signature and promotes angiogenic activity in GSCs. We also see that radiated GSCs from tumor core and margins embedded in 3D-hydrogel system with varying stiffness that mimics the tumor ECM and microenvironment exhibit differential capacity to form the vascular elements. Xenografted GBM tumors exposed to RT showed enhanced GSC conversion to vascular cells indicating that RT indeed promotes GSC transdifferentiation into vascular elements in vivo. Ongoing experiments are aimed at determining the molecular mechanism, and functional consequences of ablating the RT-induced GSC-vascular interface on tumor growth and recurrence.