Iavarone, Antonio

Abstract High grade glioma (HGG) represents a group of devastating diseases with dismal prognosis. Surgical resection of the contrast enhancing (CE) region of HGG remains the mainstay of treatment, but recurrence inevitably arises from the unresected non-contrast enhancing (NE) region, surgically inaccessible due to cancer cell invasion into healthy brain tissue. Due to its critical role in recurrence, understanding of the NE region is central to the improvement of clinical outcomes. We reveal the biological characteristics of this region through image localized multi-regional sampling. We linked microenvironmental characteristics measured by multi-parametric MRI to genomic mutations and transcriptional phenotypes using mixed effect modeling which allowed us to control for individualized patient effects. We first confirmed that T2 is a significant indicator of IDH mutation status in the NE region, being the first description of such a relationship in a HGG cohort. We found the combination of EGFR amplification and CDKN2A homozygous loss was associated with a significantly lower mean diffusivity (MD) compared to double wild type tumors in the NE region, indicating the presence of greater cellular packing and proliferation in EGFR amplification/CDKN2A loss regions. Finally, using single cell pathway based tumor classifications, we showed that nK2, a DSC-MRI metric representing cell size heterogeneity, correlated positively with neuronal signature and negatively with glycolytic/plurimetabolic signature within the NE tumor, indicating that glycolytic/plurimetobolic tumors possessed a high amount of cell size heterogeneity compared to neuronal samples. This hypothesis was supported using digital reference object (DRO) modeling which confirmed that cell size and heterogeneity drove the differential nK2 signal between neuronal and glycolytic/plurimetabolic samples. We identified immune cell infiltrate as one possible mechanism of increased cell size heterogeneity using transcriptomic signature analysis which found more immune cell signatures within glycolytic/plurimetobolic tumors compared to neuronal. Collectively this study demonstrates the central role of multi-parametric MRI as a non-invasive measure of tumor biology and a tool for understanding the clinically critical NE region which can then inform new therapies targeting this region of HGG recurrence. Citation Format: Matthew Flick, Taylor Weiskittel, Kevin Meng-Lin, Fulvio D'Angelo, Francesca Caruso, Shannon Ensign, Mylan Blomquist, Luija Wang, Christopher Sereduk, Gustavo De Leon, Ashley Nespodzany, Javier Urcuyo, Ashlynn Gonzalez, Lee Curtin, Kyle Singleton, Aliya Anil, Natenael Simmineh, Erika Lewis, Teresa Noviello, Reyna Patel, Panwen Wang, Junwen Wang, Jennifer Eschbacher, Andrea Hawkins-Daarud, Pamela Jackson, Kris Smith, Peter Nakaji, Bernard Bendok, Richard Zimmerman, Chandan Krishna, Devi Patra, Naresh Patel, Mark Lyons, Matthew Neal, Kliment Donev, Maciej Mrugala, Alyx Porter, Scott Beeman, Yuxiang Zhou, Leslie Baxter, Christopher Plaisier, Jing Li, Hu Li, Anna Lasorella, Chad Quarles, Kristin Swanson, Michele Ceccarelli, Antonio Iavarone, Nhan Tran, Leland Hu. Multi-parametric MRI maps regional heterogeneity of high grade glioma phenotypes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5621.

Abstract High grade gliomas (HGG) are aggressive primary brain malignancies typified by diffuse invasion, genetic heterogeneity, and a universally fatal outcome. MRI-defined contrast-enhancing (CE) tumor burden serves as the clinical standard that guides maximal surgical resection and post-therapy response assessment. However, HGGs also comprise an invasive non-enhancing (NE) tumor margin that extends beyond the CE core and harbors the cells that contribute to recurrence. Sampling restrictions have hindered the comprehensive study of these NE HGG cell populations driving tumor progression. Herein, we present an integrated multi-omic analysis of 313 spatially matched multi-regional CE and NE tumor biopsies from 68 HGG patients, performing whole exome and RNA sequencing of both IDH wild-type and IDH mutant HGGs. We report spatially restricted molecular profiles in IDH-mutant HGG, highlighting a concern for sampling bias given the importance of molecular diagnosis and prognostication in IDH-mutant HGG. Regardless of IDH status, we found that NE tumor regions harbored the highest proportion of private mutations, which reflects an increased development of regional genomic complexity in infiltrative tumor. The multiregional genomic profiling of our IDH wild-type HGG cohort reveals that EGFR and NF1 somatic alterations occur as mutually exclusive events in 98.7% of tumors. However, we resolved rare low allele frequency co-alterations of EGFR and NF1 within the NE region. We find this co-occurrence enriched in recurrent tumors, pointing to the early emergence of NF1 inactivation in the NE regions. We constructed genomic models predictive of recurrent disease from both NE and CE regions, which highlight the occurrence of clonal EGFR copy number alterations and NF1 loss as clonal or subclonal events, respectively, emphasizing the regional and temporal complexity of well-studied canonical driver alterations. We detailed the spatially unique acquisition of multiple distinct EGFR alterations giving rise to intra-tumoral EGFR mosaicism, a challenge in the implementation of EGFR directed therapies. Our study also identified two transcriptomic clusters delineated by the significant overrepresentation of neuronal (NEU) and glycolytic/plurimetabolic (GPM) pathway-based functional states in the NE region. NE regions of the NEU subtype harbor the greatest proportion of private mutations, suggesting these infiltrative tumor cells accumulate alterations without clonal expansion. GPM populations conversely displayed a less branched phylogeny and were transcriptionally enriched in immune cell signatures. This phenotypic dichotomy between GPM and NEU populations supports the growing body of evidence that invasive GBM cells either take on a neuronal phenotype for active invasion or a more metabolic phenotype involving interaction with astrocytes, other glial cells, and infiltrating immune cells. Citation Format: Mylan R. Blomquist, Leland S. Hu, Fulvio D'Angelo, Taylor M. Weiskittel, Francesca P. Caruso, Shannon P. Fortin Ensign, Christopher Sereduk, Gustavo De Leon, Lee Curtin, Javier Urcuyo, Ashlynn Gonzalez, Ashley Nespodzany, Teresa Noviello, Jennifer M. Eschbacher, Kris A. Smith, Peter Nakaji, Bernard R. Bendok, Richard S. Zimmerman, Chandan Krishna, Devi Patra, Naresh Patel, Mark Lyons, Kliment Donev, Maciej Mrugala, Alyx Porter, Anna Lasorella, Kristin R. Swanson, Michele Ceccarelli, Antonio Iavarone, Nhan L. Tran. Multiregional sampling of high grade glioma identifies regional biologic signatures [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1507.

Abstract Current transcriptomic classification of Glioblastoma Multiforme (GBM) has been ineffective to predict survival and therapeutic vulnerabilities. Recently, we proposed a four-group functional classification of GBM that included proliferative/progenitor, neuronal, mitochondrial and glycolytic/plurimetabolic subtypes with prognostic and therapeutic implications as the mitochondrial subtype carries the best survival and exhibits distinct sensitivity to mitochondrial OXPHOS inhibitors. To uncover novel therapeutic targets for each functional GBM subtype, we focused on protein kinases for their attractive features as both drivers and drug targets, with current availability of 62 FDA-approved inhibitors available for cancer precision therapeutics. We designed an unbiased integrative, machine learning-based proteomics/phosphoproteomics network for the identification of Master Kinases (MKs) responsible for effecting key phenotypic hallmarks of each of the four GBM subtypes. Here we report the identification and validation of protein kinase C delta (PRKCd) and DNA-PKcs as MKs that sustain the glycolytic/plurimetabolic and proliferative/progenitor GBM subtypes, respectively. Genetic and pharmacologic inactivation of PKCd in GBM patient-derived organoids of the glycolytic/plurimetabolic subtype blocked glucose uptake and lipid accumulation, resulting in marked anti-tumor effects. We also validated the role of PKCd in oncometabolic processes at the intersection between insulin, IGF, and lipid metabolism. DNA-PKcs was qualified as MK for the proliferative/progenitor GBM subtype, which is characterized by high basal level of replication stress. Biochemical experiments showed activation of DNA-PK in GBM patient-derived organoids of the proliferative/progenitor subgroup. Targeting DNA-PK in proliferative/progenitor GBM organoids with the clinically tested DNA-PKcs inhibitor nedisertib in association with gamma irradiation, the essential component of the standard of care for patients with GBM, led to an unsustainable level of DNA damage and massive GBM cell death selectively in this GBM subtype. As DNA-PKcs inhibitors have been introduced into clinical trials, our findings suggest that pre-selection of patient with PPR tumors is likely to enhance therapeutic success.

Abstract Tumor heterogeneity and broad therapeutic resistance are major challenges when treating patients with glioblastoma (GBM). Moreover, different from other cancer types, the absence of clinically useful classifiers for glioblastoma has hampered the translation of genomic and proteomic information to improve diagnosis and design precision therapeutics for patients. We analyzed a large dataset of human GBM to determine the multi-omics features characterizing the four GBM subtypes that we have recently identified through single-cell RNA sequencing and validated in bulk tumor analysis. Each subtype exhibits activation of unique functional traits that confer distinct therapeutic vulnerabilities. The examination of proteomics, phosphoproteomics, metabolomics, lipidomics and acetylomics data revealed that each GBM subtype has a coherent molecular structure driving the dominant function traceable in each analytical platform. Functional classes are not a specific attribute of GBM as we identified the same subtypes in breast and lung cancer. To test the translational impact of proteomic data in GBM, we developed an unbiased protein kinase signaling network approach for the selection of master kinases (MKs) aberrantly activated in each GBM subtype. We identified therapeutically actionable MKs and novel phosphorylation substrates that we experimentally validated. To provide rapid translation of the functional classifier for precision medicine in GBM, we developed a probabilistic classification tool which determines the probability that a patient’s GBM belongs to one of the four subtypes, exhibiting optimal performance when using RNA extracted from either frozen and paraffin-embedded tissues. The algorithm is publicly accessible and can be used to evaluate the association of therapeutic response with GBM subtypes and as tool for selection criteria in prospective clinical trials.

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 The proteogenomic characterization of human tumors has begun to uncover molecular attributes enriched in different tumor subtypes and proposed a panoply of subtype-specific targets. As these studies lacked experimental testing of potential targets in high-quality cell models accurately reflecting individual tumor subtypes, it remains unclear whether any of the proposed targets retained value for precision medicine. The absence of clinically useful classifiers further hampered translation of proteogenomic information to better diagnose and treat cancer patients. In the case of the brain tumor glioblastoma (GBM), such challenges are exacerbated by tumor heterogeneity and broad therapeutic resistance. Here, we analyzed a large dataset of human GBM to determine the multi-omics features that characterize four GBM subtypes we recently identified through single cell RNAseq analysis. Each subtype exhibits activation of unique hallmark functional traits including distinct sensitivity to inhibitors of mitochondrial respiration for the mitochondrial subtype. The inspection of proteomics, phosphoproteomics, metabolomics, lipidomics and acetylomics data revealed that each GBM subtype has a coherent molecular structure that drives the dominant function and can be extracted by each analytical platform. Stratification of tumors in four functional classes is not a specific attribute of GBM as we were able to unbiasedly identify the same subtypes in breast and lung cancer. To identify actionable targets in GBM we developed an unbiased protein kinase signaling network approach for the selection of master kinases aberrantly activated in each GBM subtype. The experimental follow-up using a library of annotated GBM patient derived organoids (PDOs) established that inhibition of DNA-PK with the clinically tested compound nedisertib radiosensitizes proliferative/progenitor PDOs by exacerbating replication stress-induced DNA damage in this GBM subtype. Furthermore, genetic and pharmacological tools qualified PKCδ as vulnerable target for the broadly resistant glycolytic/plurimetabolic GBM subtype. Thus, together with the targeting of mitochondrial GBM with OXPHOS inhibitors, the functional classification delivers experimentally validated actionable targets for three GBM subtypes. To provide rapid translation of the classifier for precision medicine in GBM, we developed a probabilistic classification tool which determines the probability that a patient’s GBM belongs to one of the four subtypes based on transcriptomic features and exhibits optimal performance when using RNA extracted from either frozen and paraffin embedded tissues. The algorithm is publicly accessible. It can be used in retrospective studies to evaluate the association of therapeutic response with GBM subtypes and as tool for selection criteria in prospective clinical trials. Citation Format: Simona Migliozzi, Young Taek Oh, Luciano Garofano, Hasanain Mohammad, Fulvio D'Angelo, Ryan D. Najac, Franck Bielle, Karima Mokhtari, Jann N. Sarkaria, Michele Ceccarelli, Marc Sanson, Anna Lasorella, Antonio Iavarone. Pathway based analysis of glioblastoma by multi-omics with applications in targeted therapy, prognosis and probabilistic classification [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 4014.

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.

Abstract Background Tumor heterogeneity underlies resistance and disease progression in glioblastoma (GBM), and tumors most commonly recur adjacent to the surgical resection margins in contrast non-enhancing (NE) regions. To date, no targeted therapies have meaningfully altered overall patient survival in the up-front setting. The aim of this study was to characterize intratumoral heterogeneity in recurrent GBM using bulk samples from primary resection and recurrent samples taken from contrast-enhancing (EN) and contrast NE regions. Methods Whole exome and RNA sequencing were performed on matched bulk primary and multiple recurrent EN and NE tumor samples from 16 GBM patients who received standard of care treatment alone or in combination with investigational clinical trial regimens. Results Private mutations emerge across multi-region sampling in recurrent tumors. Genomic clonal analysis revealed increased enrichment in gene alterations regulating the G2M checkpoint, Kras signaling, Wnt signaling, and DNA repair in recurrent disease. Subsequent functional studies identified augmented PI3K/AKT transcriptional and protein activity throughout progression, validated by phospho-protein levels. Moreover, a mesenchymal transcriptional signature was observed in recurrent EN regions, which differed from the proneural signature in recurrent NE regions. Conclusions Subclonal populations observed within bulk resected primary GBMs transcriptionally evolve across tumor recurrence (EN and NE regions) and exhibit aberrant gene expression of common signaling pathways that persist despite standard or targeted therapy. Our findings provide evidence that there are both adaptive and clonally mediated dependencies of GBM on key pathways, such as the PI3K/AKT axis, for survival across recurrences.