Tran, Nhan L.

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.

Broad-spectrum therapeutics in non-small cell lung cancer (NSCLC) are in demand. Most human solid tumors express proteoglycans modified with distinct oncofetal chondroitin sulfate (CS) chains that can be detected and targeted with recombinant VAR2CSA (rVAR2) proteins and rVAR2-derived therapeutics. Here, we investigated expression and targetability of oncofetal CS expression in human NSCLC. High oncofetal CS expression is associated with shorter disease-free survival and poor overall survival of clinically annotated stage I and II NSCLC patients (n = 493). Oncofetal CS qualifies as an independent prognosticator of NSCLC in males and smokers, and high oncofetal CS levels are more prevalent in EGFR/KRAS wild-type cases, as compared to mutation cases. NSCLC cell lines express oncofetal CS-modified proteoglycans that can be specifically detected and targeted by rVAR2 proteins in a CSA-dependent manner. Importantly, a novel VAR2-drug conjugate (VDC-MMAE) efficiently eliminates NSCLC cells in vitro and in vivo. In summary, oncofetal CS is a prognostic biomarker and an actionable glycosaminoglycan target in NSCLC.

AbstractHigh‐grade gliomas (HGGs) are aggressive, treatment‐resistant, and often fatal human brain cancers. The TNF‐like weak inducer of apoptosis (TWEAK)/fibroblast growth factor‐inducible 14 (Fn14) signaling axis is involved in tissue repair after injury and constitutive signaling has been implicated in the pathogenesis of numerous solid cancers. The Fn14 gene is expressed at low levels in the normal, uninjured brain but is highly expressed in primary isocitrate dehydrogenase wild‐type and recurrent HGGs. Fn14 signaling is implicated in numerous aspects of glioma biology including brain invasion and chemotherapy resistance, but whether Fn14 overexpression can directly promote tumor malignancy has not been reported. Here, we used the replication‐competent avian sarcoma‐leukosis virus/tumor virus A system to examine the impact of Fn14 expression on glioma development and pathobiology. We found that the sole addition of Fn14 to an established oncogenic cocktail previously shown to generate proneural‐like gliomas led to the development of highly invasive and lethal brain cancer with striking biological features including extensive pseudopalisading necrosis, constitutive canonical and noncanonical NF‐κB pathway signaling, and high plasminogen activator inhibitor‐1 (PAI‐1) expression. Analyses of HGG patient datasets revealed that high human PAI‐1 gene (SERPINE1) expression correlates with shorter patient survival, and that the SERPINE1 and Fn14 (TNFRSF12A) genes are frequently co‐expressed in bulk tumor tissues, in tumor subregions, and in malignant cells residing in the tumor microenvironment. These findings provide new insights into the potential importance of Fn14 in human HGG pathobiology and designate both the NF‐κB signaling node and PAI‐1 as potential targets for therapeutic intervention.Main PointsThis work demonstrates that elevated levels of the TWEAK receptor Fn14 in tumor‐initiating, neural progenitor cells leads to the transformation of proneural‐like gliomas into more aggressive and lethal tumors that exhibit constitutive NF‐κB pathway activation and plasminogen activator inhibitor‐1 overexpression.

Abstract Glioblastoma (GBM) is the one of the most aggressive and common primary brain malignancies, with a poor median overall survival of less than 15 months. While the immune system is activated and brain-resident microglia and blood-derived macrophages combat the tumor, the tumor can convert some microglia and macrophages to instead exhibit an immune-suppressive phenotype. These co-opted immune cells are thereby termed ‘glioma-associated microglia and macrophages’ (GAMMs), as they allow for continued tumor growth. However, limited clinical data has been collected to understand this phenomenon. As a result, we have collected spatially-distributed image-localized biopsies from a cohort of patients and performed RNA sequencing on each sample. Correlations between normalized RNA counts of genetic markers for macrophages (i.e., CD68, CD163), tumor populations (i.e., SOX2, OLIG2), and key cell functions (i.e., KI67, CASP3) were analyzed. To further investigate the temporal effects that GAMMs have on GBM growth, we proposed the Proliferation-Invasion-Macrophage (PIM) model. This system of partial differential equations incorporates the proliferative and invasive behavior of GBM, as well as populations for both ‘healthy’ and ‘glioma-associated’ macrophages. By exploring the parameter space, we classified the various dynamics of tumor progression and how they relate to the immune response. With further insights of the interactions between GBM and macrophage populations, we can begin to parameterize the model on a patient-specific basis and provide insights to personalized immunotherapies and other novel immune-targeted treatments.

Glioblastoma (GBM), a highly invasive and vascular malignancy is shown to rapidly develop resistance and evolve to a more invasive phenotype following bevacizumab (Bev) therapy. Rho Guanine Nucleotide Exchange Factor proteins (RhoGEFs) are mediators of key components in Bev resistance pathways, GBM and Bev-induced invasion. To identify GEFs with enhanced mRNA expression in the leading edge of GBM tumours, a cohort of GEFs was assessed using a clinical dataset. The GEF βPix/COOL-1 was identified, and the functional effect of gene depletion assessed using 3D-boyden chamber, proliferation, and colony formation assays in GBM cells. Anti-angiogenic effects were assessed in endothelial cells using tube formation and wound healing assays. In vivo effects of βPix/COOL-1-siRNA delivered via RGD-Nanoparticle in combination with Bev was studied in an invasive model of GBM. We found that siRNA-mediated knockdown of βPix/COOL-1 in vitro decreased cell invasion, proliferation and increased apoptosis in GBM cell lines. Moreover βPix/COOL-1 mediated endothelial cell migration in vitro. Mice treated with βPix/COOL-1 siRNA-loaded RGD-Nanoparticle and Bev demonstrated a trend towards improved median survival compared with Bev monotherapy. Our hypothesis generating study suggests that the RhoGEF βPix/COOL-1 may represent a target of vulnerability in GBM, in particular to improve Bev efficacy.

Lung cancer is the deadliest cancer worldwide, mainly due to its advanced stage at the time of diagnosis. A non-invasive method for its early detection remains mandatory to improve patients’ survival. Plasma levels of 351 proteins were quantified by Liquid Chromatography-Parallel Reaction Monitoring (LC-PRM)-based mass spectrometry in 128 lung cancer patients and 93 healthy donors. Bootstrap sampling and least absolute shrinkage and selection operator (LASSO) penalization were used to find the best protein combination for outcome prediction. The PanelomiX platform was used to select the optimal biomarker thresholds. The panel was validated in 48 patients and 49 healthy volunteers. A 6-protein panel clearly distinguished lung cancer from healthy individuals. The panel displayed excellent performance: area under the receiver operating characteristic curve (AUC) = 0.999, positive predictive value (PPV) = 0.992, negative predictive value (NPV) = 0.989, specificity = 0.989 and sensitivity = 0.992. The panel detected lung cancer independently of the disease stage. The 6-protein panel and other sub-combinations displayed excellent results in the validation dataset. In conclusion, we identified a blood-based 6-protein panel as a diagnostic tool in lung cancer. Used as a routine test for high- and average-risk individuals, it may complement currently adopted techniques in lung cancer screening.

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.