Sereduk, Christopher

Abstract Characterizing intra- and inter-tumoral heterogeneity of glioblastoma has historically relied on discrete classifications of malignant cell populations leaving immune and other cell populations, known to exist admixed with the malignant tumor cells, relatively neglected. Manifold learning algorithms can manage deconvolving multiple cell populations and are often used to track cell state transitions in single cell transcriptomics. We applied a manifold learning approach to TCGA microarray data (Nf525) and bulk transcriptomics of 134 image localized biopsies across 30 patients with primary and 9 with recurrent glioblastoma to further elucidate how to organize biopsies across a spectrum of possible tissue states. The algorithm revealed a low-dimensional manifold graph for which each biopsy lives across 3 polarizing tissue states - one that is associated with diffusely invaded brain, one that is enriched in mesenchymal genes, and one that is enriched in classical proliferative tumor signatures. We deconvolved the bulk transcriptomics of the image-localized biopsies to reveal the relative abundance of 18 malignant, immune, and other cell subpopulations in each biopsy. Overlaying the cellular decomposition onto the manifold graph visualizing the tissue state distributions revealed that transitions between states correlate with changes in cellular cohabitation composition. The tumor cellular cohabitation ecologies have the lowest diversity, as inferred by ecological measures such as Shannon entropy and evenness, at the distal poles of the graph when compared to the transitional arms. Further, we found that the relationship between imaging appearance of contrast enhancement on T1-weighted MRI and the biopsy cellular composition varies with sex and primary vs recurrent biopsy status. The limited spectrum of possible tissue states revealed by the manifold learning is suggestive of a limited continuum along which tumor and non-tumoral cell populations can cohabitate. Such a limited low-dimensional biological space may constrain the dynamics of tumor biology in a predictable manner.

Abstract High-grade gliomas represent the most common type of primary adult malignant brain tumor historically diagnosed and graded from histologic criteria alone. Gliomas harboring isocitrate dehydrogenase (IDH) 1 or 2 mutations, which are present in more than 80% of World Health Organization (WHO) grade 2 or 3 tumors, portend a favorable prognosis as compared to IDH-wildtype tumors. However, recent molecular profiling has identified the presence of additional alterations in these lower grade tumors that transform the biology toward an aggressive high-grade phenotype clinically that are independent of histologic grading and confer a worse clinical prognosis. Of these, the loss of CDKN2A/B is the strongest implicated alteration and is sufficient to define a grade 4 tumor in IDH-mutant astrocytomas regardless of histologic appearance. However, there remain no effective therapies targeted at molecular subgroups in aggressive gliomas to date. Here we have profiled the intratumoral heterogeneity via whole exome and RNA sequencing and copy number alteration analysis within a cohort of de-identified IDH-mutant astrocytoma patient tumors collected through the Mayo Clinic and Barrow Neurological Institute (BNI) biorepositories to determine the spatial evolution of aggressive molecular features. Within this cohort we have collected 42 image-localized intratumoral biopsy specimens representing 13 IDH-mutant patient tumors. We identified 11 biopsies from 3 tumors that harbored loss of CDKN2A/B which included 1 tumor that displayed intratumoral heterogeneity of CDKN2A/B expression across subclones. We performed an unsupervised cluster analysis to profile the transcriptional signatures in IDH-mutant astrocytomas across both differential CDKN2A/B status and tumor geographic location comparing contrast enhancing versus non-enhancing regions, and we analyzed the MRI features in IDH-mutant tumors across CDKN2A/B status. We found that tumors with CDKN2A/B alteration demonstrated lower signal intensity on delayed post-contrast T2*W images, which could represent lower pre-contrast T2*, unique contrast agent kinetics, or dissimilar diffusion properties related to increased cellular density and/or greater heterogeneity of cell size. Interestingly, we uncovered spatial heterogeneity of additional molecular drivers of high-grade glioma including KRAS, MYCN, and PDGFRA. While EGFR alterations are rarely reported in IDH-mutant tumors, we identified one treatment naïve patient tumor that harbored EGFR alteration only in the contrast non-enhancing region. Based on this work we propose there is early spatial evolution of aggressive tumor subclones prior to primary tumor diagnosis, and multiregional molecular profiling may better inform tumor biology and predict therapeutic strategies in IDH-mutant astrocytomas. Citation Format: Shannon P. Fortin Ensign, Fulvio D'Angelo, Francesca P. Caruso, Christopher Sereduk, Kyle Singleton, Jennifer Eschbacher, Gina Mazza, Maciej Mrugala, Alyx Porter, Bernard Bendok, Richard Zimmerman, Kris Smith, Peter Nakaji, Kamala Swanson, Junwen Wang, Nathenael Semmineh, Christopher Quarles, Anna Lasorella, Kristin Swanson, Michele Ceccarelli, Antonio Iavarone, Leland Hu, Nhan L. Tran. Multiregional imaging and genomic analysis in high-grade IDH-mutant astrocytoma identifies intratumor subclones with aggressive features [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 770.

Abstract Glioblastoma (GBM), the most common primary brain tumor in adults, comprises all WHO Grade IV gliomas of astrocytic origin. Despite extensive characterization of the molecular and genetic features of GBM, there remains a paucity of viable treatment options, and this disease confers a dismal 5% 5-year survival rate. Genomic amplification of epidermal growth factor receptor (EGFR) occurs in 40-60% of primary GBM. Half of all EGFR-amplified cases of GBM also harbor EGFRvIII, a constitutively active, truncated variant of EGFR. EGFR and EGFRvIII transduce oncogenic signals via cytoplasmic mediators, including the JAK/STAT signal transduction pathway. The oncogenic role of STAT3 has been well-studied in CNS malignancies; STAT3 has been found to induce the expression of target genes involved in the proliferative and invasive phenotypes of GBM. However, little is known about the mechanism and role of STAT5 activation in GBM progression. Microenvironmental cues and EGFRvIII signaling, lost in adherent cell culture, are required for STAT5 activation, making STAT5 difficult to study by conventional cell culture methods. Our recent data from patient-derived xenograft (PDX) cultures demonstrates that activation of STAT5 is important in GBM cell invasion and survival. Further, STAT5 activation is present predominantly at the invasive periphery of the tumor. In this study, we seek to characterize the mechanism and role of STAT5 activation downstream of EGFRvIII in GBM. RNA sequencing of PDX tumors expressing stable shRNA knockdown of STAT3 or STAT5 indicate both redundant and distinct transcriptional changes induced by STAT3 and STAT5 in GBM. We also find that while STAT3 activation is dependent upon JAK1/2, STAT5 activation is JAK-independent downstream of EGFRvIII in GBM. Depletion of JAK1/2 expression by siRNA oligonucleotides and pharmacologic inhibition of JAK1/2 suppressed STAT3 activation but not STAT5. In fact, targeting JAK2 with kinase inhibitor WP1066 suppressed STAT3 activation, but increased activation of STAT5 in GBM cells expressing EGFR/EGFRvIII. Inhibition of Src family kinases (SFK), a family of upstream signaling effectors of the JAK/STAT pathway, attenuates both STAT3 and STAT5 activation. These results suggest that activation of STAT5 may provide a therapeutic escape mechanism to JAK-STAT3 inhibition in GBM, necessitating dual STAT3 and STAT5 inhibition to successfully inhibit the distinct oncogenic signals transmitted by STAT3 and STAT5 to promote GBM cell survival and resistance. Citation Format: Mylan Blomquist, Serdar Tuncali, Christopher Sereduk, Jean Kloss, Joseph Loftus, Nhan Tran. JAK-independent STAT5 signaling as a node of therapeutic vulnerability in glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 101.

Abstract Background Magnetic Resonance Imaging (MRI) is the mainstay for neurosurgical oncology but not for informing us about glioma biology. An obstacle to developing MR-based glioma biomarkers is the absence of rigorous correlation between MRI features and glioma biology as assessed in multi-regional biopsies, within and across patients. Methods We directly addressed this obstacle by collating a unique cohort of 202 MRI-localized biopsies from 58 patients. We define a low-dimensional transcriptional pseudotime continuum along which heterogeneous high-grade glioma (HGG) samples organize both within and across patients. Results We observe three polarized transcriptional tissue states: infiltrated brain, immune/inflammatory, and proliferative associated with patterns of cohabitation of cellular subpopulations. The states and deconvolved populations show correlation with enhancement status on T1Gd MRI. Moreover, discrete MRI habitats, regions sharing common imaging features, defined as combinations of high or low signal intensity across multiparametric MRI revealed 14 MRI habitats. We order the MRI habitats according to the average pseudotime on the transcriptional continuum. We find that MRI habitats with low pseudotime (associated with early tumor development and diffusely invaded brain tissue) localized at the periphery of the tumor whilst high pseudotime either proliferative or immune/inflammatory states were towards the core of the lesion. We find that composition of MRI habitats are impacted by MGMT status and patient sex. Conclusion This suggests that ongoing aggregation of MRI-localized biopsies may augment our projection of biology onto MRI habitats to support tracking of the evolution of cellular ecologies within and across each patient’s tumor over time. Key Points Trajectory inference of HGG samples reveals a continuum connecting three polarized tissue states reflecting transitions in cellular population ecologies and gene set enrichment Combining multiparametric MRI features into regional MRI habitats reveal clinically-distinct patterns of cell co-habitation and tissue state MGMT methylation status shifts the cellular patterns of cohabitation within MRI habitats Importance of the Study Regional heterogeneity is a defining characteristic of high-grade glioma (HGG). Mapping the transcriptomic biology of multiregionally sampled MRI-localized biopsies from high-grade gliomas onto a low-dimensional space reveals a continuum between three primary tissue states: infiltrated brain, immune/inflammatory, and proliferative. Each state is associated with distinct cell cohabitation ecologies. Transitions between the tissue states coordinate with changes in tumor composition, revealing potential direct connections between tumor biology shifts and their manifestation on clinical imaging.

Abstract INTRODUCTION Dendritic cells (DCs) are potent antigen presenting cells that can be exploited to initiate an adaptive anti-tumoral immune response. DC vaccine clinical trials for primary glioblastoma (GBM) have reported prolonged progression-free survival without any impact on overall survival (OS). We report a radiomics approach that identifies a subpopulation of patients with prolonged OS in clinical trial MC1272. METHODS Twenty adults with primary GBM undergoing standard-of-care therapy were enrolled in MC1272. Autologous DCs were pulsed with allogenic GBM cell lines to generate vaccines that were administered for up to twelve cycles. Standard brain imaging was obtained at the initiation of treatment and two months afterwards. An independent cohort of image-localized biopsies underwent RNA sequencing followed by cellular deconvolution to estimate T cell abundance. A machine learning model was trained to predict intratumoral T cell abundance from imaging features, and the model was applied to MC1272 patient imaging. RESULTS Voxelwise predictions of T cell abundance were generated for each patient’s pre- and post-treatment images. The difference in total intratumoral T cell abundance between imaging timepoints classified patients into increasing or decreasing T cell groups. Patients whose T cells increased had longer OS (median, 21 months) than those whose T cells decreased (median, 10 months; p=0.0035). The significance remained in a Cox proportional hazards analysis that adjusted for patient age and sex (p=0.011). CONCLUSIONS A spatially-resolved radiomics model detected that an intratumoral T cell influx after DC vaccine therapy was associated with prolonged OS. The “post-treatment” imaging in this study was obtained a mere two months after DC vaccine initiation, suggesting that our radiomics model can provide an early indication of treatment responsiveness and prognosis in these patients.

Abstract Intra-tumor genetic heterogeneity is an important cause of treatment failure of GBM. Using MRI and image-localized biopsies, it is possible to train machine learning (ML) models to predict regional genetic status. However, biopsy samples are limited, making it difficult to train a robust ML model. We proposed a data-inclusive model called Weakly Supervised Ordinal Support Vector Machines (WSO-SVM) which leverages the vast amount of MRI data outside the sparsely sampled biopsy regions to augment the biopsy samples to improve ML accuracy. Our study included a unique dataset of 104 image-localized biopsies with spatially matched multiparametric MRI from 30 untreated Glioblastoma (GBM) patients. Each biopsy sample went through genetic sequencing analysis and our study focused on two GBM hallmark genes, EGFR and PDGFRA. For each gene, a biopsy sample was labeled as “altered” if the copy number of this gene was amplified or a mutation was found, and “non-altered” otherwise. From the localized region of six MRI contrasts from T1gd, T2w, diffusion and perfusion imaging, over 300 texture features were extracted. To account for biopsy sample location uncertainty, six neighboring regions of the biopsy sample including four neighbors two pixels away from the biopsy location and two neighbors on adjacent slices were also included in model training. WSO-SVM achieved 0.83 accuracy, 0.77 sensitivity, and 0.86 specificity for classifying EGFR; 0.77 accuracy, 0.74 sensitivity, and 0.79 specificity for classifying PDGFRA, based on 10-fold cross validation. Furthermore, using the trained models, we generated regional EGFR and PDGFRA alteration maps for each patient within the enhancing and non-enhancing tumoral areas. On average we found a greater proportion of enhancing tumor with co-alteration than non-enhancing tumor, while this trend was reversed when considering only one altered gene. The ratio of EGFR vs PDGFRA alterations was higher in non-enhancing tumor than enhancing tumor.

Abstract Glioblastoma (GBM), the most common primary brain tumor in adults, remains uniformly fatal due to the lack of effective targeted therapies for this aggressive malignancy. Genomic amplification of epidermal growth factor receptor (EGFR) occurs in 40-60% of primary GBM. Half of all EGFR-amplified cases of GBM also harbor EGFRvIII, a constitutively active, truncated variant of EGFR. The incidence of EGFR alterations in GBM makes inhibition of EGFR/EGFRvIII an attractive therapeutic approach. Depatuxizumab mafodotin (ABT-414) is an antibody-drug conjugate comprised of ABT-806, a mAB against EGFR, and a cytotoxic payload (monomethyl auristatin F). ABT-414 therapy initially showed promising results as an EGFRvIII therapy in vivo and in vitro; however, ABT414 failed to provide a survival benefit in phase I/II clinical trials, potentially due to therapeutic resistance. In this study, we seek to investigate the mechanisms of resistance to ABT-414 by performing whole exome, transcriptome and single cell RNA seq on ABT-414 resistant GBM PDX tumors. Our data showed an enrichment of mutations unique to the ABT-414 resistant tumors, including a point mutation (S466I) in TEK/TIE2 transmembrane angiopoietin receptor. In vitro expression of TEK S466I in GBM cells showed an increase in activation of ERK and STAT3 and increased TEK/TIE2 immunoprecipitation with EGFR compared to the wild-type TEK receptor. Furthermore, gene ontology analysis reveals that ABT-414-treated flank tumors exhibit increased activation of extracellular matrix organization and CNS developmental processes compared to flank tumors in the control treatment groups. ABT-414-treated tumors also demonstrate increased expression of inhibitor of differentiation (ID)1 and ID3, associated with stem-like phenotype in glioblastoma. Taken together, our data indicate that resistance to ABT-414 is mediated by both de novo mutations not detected in the parent tumor and adaptive dysregulation of pathways which may lead to dedifferentiation and therapeutic resistance.