The ATP-exporting channel Pannexin-1 promotes CD8+ T cell effector and memory responses

Sensing of extracellular ATP (eATP) controls CD8+ T cell function. Their accumulation can occur through export by specialized molecules, such as the release channel Pannexin-1 (Panx1). Whether Panx1 controls CD8+ T cell immune responses in vivo, however, has not been previously addressed. Here, we report that T cell-specific Panx1 is needed for CD8+ T cell responses to viral infections and cancer. We found that CD8-specific Panx1 promotes both effector and memory CD8+ T cell responses. Panx1 favors initial effector CD8+ T cell activation through extracellular ATP (eATP) export and subsequent P2RX4 activation, which helps promote full effector differentiation through extracellular lactate accumulation and its subsequent recycling. In contrast, Panx1 promotes memory CD8+ T cell survival primarily through ATP export and subsequent P2RX7 engagement, leading to improved mitochondrial metabolism. In summary, Panx1-mediated eATP export regulates effector and memory CD8+ T cells through distinct purinergic receptors and different metabolic and signaling pathways.

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm

BACKGROUND AND OBJECTIVE

Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, which motivates the development of non-invasive, MRI-based machine learning (ML) models to quantify intra-tumoral genetic heterogeneity for each patient. This capability holds great promise for enabling better therapeutic selection to improve patient outcome.

METHODS

We proposed a novel Weakly Supervised Ordinal Support Vector Machine (WSO-SVM) to predict regional genetic alteration status within each GBM tumor using MRI. WSO-SVM was applied to a unique dataset of 318 image-localized biopsies with spatially matched multiparametric MRI from 74 GBM patients. The model was trained to predict the regional genetic alteration of three GBM driver genes (EGFR, PDGFRA and PTEN) based on features extracted from the corresponding region of five MRI contrast images. For comparison, a variety of existing ML algorithms were also applied. Classification accuracy of each gene were compared between the different algorithms. The SHapley Additive exPlanations (SHAP) method was further applied to compute contribution scores of different contrast images. Finally, the trained WSO-SVM was used to generate prediction maps within the tumoral area of each patient to help visualize the intra-tumoral genetic heterogeneity.

RESULTS

WSO-SVM achieved 0.80 accuracy, 0.79 sensitivity, and 0.81 specificity for classifying EGFR; 0.71 accuracy, 0.70 sensitivity, and 0.72 specificity for classifying PDGFRA; 0.80 accuracy, 0.78 sensitivity, and 0.83 specificity for classifying PTEN; these results significantly outperformed the existing ML algorithms. Using SHAP, we found that the relative contributions of the five contrast images differ between genes, which are consistent with findings in the literature. The prediction maps revealed extensive intra-tumoral region-to-region heterogeneity within each individual tumor in terms of the alteration status of the three genes.

CONCLUSIONS

This study demonstrated the feasibility of using MRI and WSO-SVM to enable non-invasive prediction of intra-tumoral regional genetic alteration for each GBM patient, which can inform future adaptive therapies for individualized oncology.

Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol

Brain cancers pose a novel set of difficulties due to the limited accessibility of human brain tumor tissue. For this reason, clinical decision-making relies heavily on MR imaging interpretation, yet the mapping between MRI features and underlying biology remains ambiguous. Standard (clinical) tissue sampling fails to capture the full heterogeneity of the disease. Biopsies are required to obtain a pathological diagnosis and are predominantly taken from the tumor core, which often has different traits to the surrounding invasive tumor that typically leads to recurrent disease. One approach to solving this issue is to characterize the spatial heterogeneity of molecular, genetic, and cellular features of glioma through the intraoperative collection of multiple image-localized biopsy samples paired with multi-parametric MRIs. We have adopted this approach and are currently actively enrolling patients for our 'Image-Based Mapping of Brain Tumors' study. Patients are eligible for this research study (IRB #16-002424) if they are 18 years or older and undergoing surgical intervention for a brain lesion. Once identified, candidate patients receive dynamic susceptibility contrast (DSC) perfusion MRI and diffusion tensor imaging (DTI), in addition to standard sequences (T1, T1Gd, T2, T2-FLAIR) at their presurgical scan. During surgery, sample anatomical locations are tracked using neuronavigation. The collected specimens from this research study are used to capture the intra-tumoral heterogeneity across brain tumors including quantification of genetic aberrations through whole-exome and RNA sequencing as well as other tissue analysis techniques. To date, these data (made available through a public portal) have been used to generate, test, and validate predictive regional maps of the spatial distribution of tumor cell density and/or treatment-related key genetic marker status to identify biopsy and/or treatment targets based on insight from the entire tumor makeup. This type of methodology, when delivered within clinically feasible time frames, has the potential to further inform medical decision-making by improving surgical intervention, radiation, and targeted drug therapy for patients with glioma.

Revealing the biology behind MRI signatures in high grade glioma

Magnetic resonance imaging (MRI) measurements are routinely collected during the treatment of high-grade gliomas (HGGs) to characterize tumor boundaries and guide surgical tumor resection. Using spatially matched MRI and transcriptomics we discovered HGG tumor biology captured by MRI measurements. We strategically overlaid the spatially matched omics characterizations onto a pre-existing transcriptional map of glioblastoma multiforme (GBM) to enhance the robustness of our analyses. We discovered that T1+C measurements, designed to capture vasculature and blood brain barrier (BBB) breakdown and subsequent contrast extravasation, also indirectly reveal immune cell infiltration. The disruption of the vasculature and BBB within the tumor creates a permissive infiltrative environment that enables the transmigration of anti-inflammatory macrophages into tumors. These relationships were validated through histology and enrichment of genes associated with immune cell transmigration and proliferation. Additionally, T2-weighted (T2W) and mean diffusivity (MD) measurements were associated with angiogenesis and validated using histology and enrichment of genes involved in neovascularization. Furthermore, we establish an unbiased approach for identifying additional linkages between MRI measurements and tumor biology in future studies, particularly with the integration of novel MRI techniques. Lastly, we illustrated how noninvasive MRI can be used to map HGG biology spatially across a tumor, and this provides a platform to develop diagnostics, prognostics, or treatment efficacy biomarkers to improve patient outcomes.

Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Image-based models of T-cell distribution identify a clinically meaningful response to a dendritic cell vaccine in patients with glioblastoma

BACKGROUND

Glioblastoma is an extraordinarily heterogeneous tumor, yet the current treatment paradigm is a "one size fits all" approach. Hundreds of glioblastoma clinical trials have been deemed failures because they did not extend median survival, but these cohorts are comprised of patients with diverse tumors. Current methods of assessing treatment efficacy fail to fully account for this heterogeneity.

METHODS

Using an image-based modeling approach, we predicted T-cell abundance from serial MRIs of patients enrolled in the dendritic cell (DC) vaccine clinical trial. T-cell predictions were quantified in both the contrast-enhancing and non-enhancing regions of the imageable tumor, and changes over time were assessed.

RESULTS

A subset of patients in a DC vaccine clinical trial, who had previously gone undetected, were identified as treatment responsive and benefited from prolonged survival. A mere two months after initial vaccine administration, responsive patients had a decrease in model-predicted T-cells within the contrast-enhancing region, with a simultaneous increase in the T2/FLAIR region.

CONCLUSIONS

In a field that has yet to see breakthrough therapies, these results highlight the value of machine learning in enhancing clinical trial assessment, improving our ability to prospectively prognosticate patient outcomes, and advancing the pursuit towards individualized medicine.

Genome-wide analysis of aberrant position and sequence of plasma DNA fragment ends in patients with cancer

Genome-wide fragmentation patterns in cell-free DNA (cfDNA) in plasma are strongly influenced by cellular origin due to variation in chromatin accessibility across cell types. Such differences between healthy and cancer cells provide the opportunity for development of novel cancer diagnostics. Here, we investigated whether analysis of cfDNA fragment end positions and their surrounding DNA sequences reveals the presence of tumor-derived DNA in blood. We performed genome-wide analysis of cfDNA from 521 samples and analyzed sequencing data from an additional 2147 samples, including healthy individuals and patients with 11 different cancer types. We developed a metric based on genome-wide differences in fragment positioning, weighted by fragment length and GC content [information-weighted fraction of aberrant fragments (iwFAF)]. We observed that iwFAF strongly correlated with tumor fraction, was higher for DNA fragments carrying somatic mutations, and was higher within genomic regions affected by copy number amplifications. We also calculated sample-level means of nucleotide frequencies observed at genomic positions spanning fragment ends. Using a combination of iwFAF and nine nucleotide frequencies from three positions surrounding fragment ends, we developed a machine learning model to differentiate healthy individuals from patients with cancer. We observed an area under the receiver operative characteristic curve (AUC) of 0.91 for detection of cancer at any stage and an AUC of 0.87 for detection of stage I cancer. Our findings remained robust with as few as 1 million fragments analyzed per sample, demonstrating that analysis of fragment ends can become a cost-effective and accessible approach for cancer detection and monitoring.

WSD-0922, a novel brain-penetrant inhibitor of epidermal growth factor receptor, promotes survival in glioblastoma mouse models

Background

Although the epidermal growth factor receptor (EGFR) is a frequent oncogenic driver in glioblastoma (GBM), efforts to therapeutically target this protein have been largely unsuccessful. The present preclinical study evaluated the novel EGFR inhibitor WSD-0922.

Methods

We employed flank and orthotopic patient-derived xenograft models to characterize WSD-0922 and compare its efficacy to erlotinib, a potent EGFR inhibitor that failed to provide benefit for GBM patients. We performed long-term survival studies and collected short-term tumor, plasma, and whole-brain samples from mice treated with each drug. We utilized mass spectrometry to measure drug concentrations and spatial distribution and to assess the impact of each drug on receptor activity and cellular signaling networks.

Results

WSD-0922 inhibited EGFR signaling as effectively as erlotinib in in vitro and in vivo models. While WSD-0922 was more CNS penetrant than erlotinib in terms of total concentration, comparable concentrations of both drugs were measured at the tumor site in orthotopic models, and the concentration of free WSD-0922 in the brain was significantly less than the concentration of free erlotinib. WSD-0922 treatment provided a clear survival advantage compared to erlotinib in the GBM39 model, with marked suppression of tumor growth and most mice surviving until the end of the study. WSD-0922 treatment preferentially inhibited phosphorylation of several proteins, including those associated with EGFR inhibitor resistance and cell metabolism.

Conclusions

WSD-0922 is a highly potent inhibitor of EGFR in GBM, and warrants further evaluation in clinical studies.

Intersubband Polariton-Polariton Scattering in a Dispersive Microcavity

The ultrafast scattering dynamics of intersubband polaritons in dispersive cavities embedding GaAs/AlGaAs quantum wells are studied directly within their band structure using a noncollinear pump-probe geometry with phase-stable midinfrared pulses. Selective excitation of the lower polariton at a frequency of ∼25  THz and at a finite in-plane momentum k_{‖} leads to the emergence of a narrowband maximum in the probe reflectivity at k_{‖}=0. A quantum mechanical model identifies the underlying microscopic process as stimulated coherent polariton-polariton scattering. These results mark an important milestone toward quantum control and bosonic lasing in custom-tailored polaritonic systems in the mid and far infrared.

Abstract 1556: Long non-coding RNA WNT5A-AS1 shows sex-dimorphic differences in survival for males with glioblastoma

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with a median survival time of 12-15 months and 5-year survival rate of 5%. Despite the application of advanced genetics and biological breakthroughs in GBM, the outcome for GBM remains dismal. Previous genome-wide association studies (GWAS) for GBM shows that the incidence rate for GBM in males is 1.6 times higher in men than women, with men displaying overall worse outcomes. In-vivo studies in gender-matched isogenic murine astrocytic cell lines show that the rate of astrocytic transformation is higher in males than in females, corroborating the GWAS findings in human GBM. Thus, understanding how sex effects GBM biology may provide insight into the mechanism of gliomagenesis and response to therapy. To explore the molecular mechanisms by which transformation of GBM increases in males, we used DESeq2 to assess differentially expressed genes between male and female patients. We found that a long non-coding RNA WNT5A-AS1 is overexpressed in males [log2(fold change) of 1.40; FDR = 0.036], regardless of cofounding factors such as IDH1 status, age, and race. Next, we examined if expression of WNT5A-AS1 is correlated with survival within male patients versus female patients in the TCGA-GBM dataset. In males, WNT5A-AS1’s expression is significantly correlated with patient overall survival (P = 0.042, N=109), but not in female (P = 0.585, N=60). Male patients with high expression of WNT5A-AS1 display poor survival outcomes compared to males with low expression. WNT5A-AS1 is located in the upstream, promoter region of WNT5A. Q-PCR quantification of WNT5A expression increases in male GBM specimens as compared to GBM specimens from females. The role that WNT5A-AS1 plays in regulating WNT5A expression is unclear to date. Interestingly, WNT5A expression shows a positive correlation with patient survival in males, with high expression displaying better survival outcomes (p=0.0272). We have data obtained from a subset of patient samples showing an inverse relationship between WNT5A and WNT5A-AS1 expression. This suggests that there may be an inverse correlation between WNT5A-AS1 and WNT5A expression, which elucidates that WNT5A-AS1 may be regulating WNT5A expression. Current ongoing studies will evaluate the role of WNT5A-AS1/WNT5A in sex-differences of GBM progression.

Citation Format: Aunay Miller, Junwen Wang, Joseph Loftus, Nhan L. Tran. Long non-coding RNA WNT5A-AS1 shows sex-dimorphic differences in survival for males with 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 1556.

Abstract 770: Multiregional imaging and genomic analysis in high-grade IDH-mutant astrocytoma identifies intratumor subclones with aggressive features

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.

Oncofetal Chondroitin Sulfate Is a Highly Expressed Therapeutic Target in Non-Small Cell Lung Cancer

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.

Elevated fibroblast growth factor-inducible 14 expression transforms proneural-like gliomas into more aggressive and lethal brain cancer

High-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 POINTS: This 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.

Nanocell-mediated delivery of miR-34a counteracts temozolomide resistance in glioblastoma

BACKGROUND

Glioblastoma is the most common primary brain tumor and remains uniformly fatal, highlighting the dire need for developing effective therapeutics. Significant intra- and inter-tumor heterogeneity and inadequate delivery of therapeutics across blood-brain barrier continue to be significant impediments towards developing therapies which can significantly enhance survival. We hypothesize that microRNAs have the potential to serve as effective therapeutics for glioblastoma as they modulate the activity of multiple signaling pathways, and hence can counteract heterogeneity if successfully delivered.

METHODS

Using a computational approach, we identified microRNA-34a as a microRNA that maximally reduces the activation status of the three core signaling networks (the receptor tyrosine kinase, p53 and Rb networks) that have been found to be deregulated in most glioblastoma tumors. Glioblastoma cultures were transfected with microRNA-34a or control microRNA to assess biological function and therapeutic potential in vitro. Nanocells were derived from genetically modified bacteria and loaded with microRNA-34a for intravenous administration to orthotopic patient-derived glioblastoma xenografts in mice.

RESULTS

Overexpression of microRNA-34a strongly reduced the activation status of the three core signaling networks. microRNA-34a transfection also inhibited the survival of multiple established glioblastoma cell lines, as well as primary patient-derived xenograft cultures representing the proneural, mesenchymal and classical subtypes. Transfection of microRNA-34a enhanced temozolomide (TMZ) response in in vitro cultures of glioblastoma cells with primary TMZ sensitivity, primary TMZ resistance and acquired TMZ resistance. Mechanistically, microRNA-34a downregulated multiple therapeutic resistance genes which are associated with worse survival in glioblastoma patients and are enriched in specific tumor spatial compartments. Importantly, intravenous administration of nanocells carrying miR-34a and targeted to epidermal growth factor receptor (EGFR) strongly enhanced TMZ sensitivity in an orthotopic patient-derived xenograft mouse model of glioblastoma.

CONCLUSIONS

Targeted bacterially-derived nanocells are an effective vehicle for the delivery of microRNA-34a to glioblastoma tumors. microRNA-34a inhibits survival and strongly sensitizes a wide range of glioblastoma cell cultures to TMZ, suggesting that combination therapy of TMZ with microRNA-34a loaded nanocells may serve as a novel therapeutic approach for the treatment of glioblastoma tumors.

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma

Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients. The model generated predictions for regional EGFR amplification status (a common and important target in GBM) to resolve the intratumoral genetic heterogeneity across each individual tumor-a key factor for future personalized therapeutic paradigms. The model used probability distributions for each sample prediction to quantify uncertainty, and used transductive learning to reduce the overall uncertainty. We compared predictive accuracy and uncertainty of the transductive learning GP model against a standard GP model using leave-one-patient-out cross validation. Additionally, we used a separate dataset containing 24 image-localized biopsies from 7 high-grade glioma patients to validate the model. Predictive uncertainty informed the likelihood of achieving an accurate sample prediction. When stratifying predictions based on uncertainty, we observed substantially higher performance in the group cohort (75% accuracy, n = 95) and amongst sample predictions with the lowest uncertainty (83% accuracy, n = 72) compared to predictions with higher uncertainty (48% accuracy, n = 23), due largely to data interpolation (rather than extrapolation). On the separate validation set, our model achieved 78% accuracy amongst the sample predictions with lowest uncertainty. We present a novel approach to quantify radiogenomics uncertainty to enhance model performance and clinical interpretability. This should help integrate more reliable radiogenomics models for improved medical decision-making.

Targeting the RhoGEF βPIX/COOL-1 in Glioblastoma: Proof of Concept Studies

Simple Summary

Glioblastoma (GBM) is an incurable disease with a 14-month average life-expectancy following diagnosis, and clinical management has not improved in four decades. GBM mortality is due to rapid tumour growth and invasion into surrounding normal brain. Invasive cells make complete surgical removal of the tumour impossible, and result in disease relapse. Thus, it is imperative that any new treatment strategy takes these invading cells into consideration. Bevacizumab (Bev), which prevents the formation of new blood vessels, is an FDA approved therapy, but it has failed to increase overall survival in GBM and has even been shown to increase tumour invasion in some cases. Complementary anti-invasive therapies are therefore urgently required to enhance bevacizumab efficacy. We have identified βPIX/COOL-1, a RhoGEF protein which plays an important role in GBM cell invasion and angiogenesis and could be a useful target in this setting.

Abstract

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.

Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

Glioblastomas (GBMs) are the most aggressive primary brain tumours and have no known cure. Each individual tumour comprises multiple sub-populations of genetically-distinct cells that may respond differently to targeted therapies and may contribute to disappointing clinical trial results. Image-localized biopsy techniques allow multiple biopsies to be taken during surgery and provide information that identifies regions where particular sub-populations occur within an individual GBM, thus providing insight into their regional genetic variability. These sub-populations may also interact with one another in a competitive or cooperative manner; it is important to ascertain the nature of these interactions, as they may have implications for responses to targeted therapies. We combine genetic information from biopsies with a mechanistic model of interacting GBM sub-populations to characterise the nature of interactions between two commonly occurring GBM sub-populations, those with EGFR and PDGFRA genes amplified. We study population levels found across image-localized biopsy data from a cohort of 25 patients and compare this to model outputs under competitive, cooperative and neutral interaction assumptions. We explore other factors affecting the observed simulated sub-populations, such as selection advantages and phylogenetic ordering of mutations, which may also contribute to the levels of EGFR and PDGFRA amplified populations observed in biopsy data.

TROY signals through JAK1-STAT3 to promote glioblastoma cell migration and resistance

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults and carries a discouraging prognosis. Its aggressive and highly infiltrative nature renders the current standard treatment of maximal surgical resection, radiation, and chemotherapy relatively ineffective. Identifying the signaling pathways that regulate GBM migration/invasion and resistance is required to develop more effective therapeutic regimens to treat GBM. Expression of TROY, an orphan receptor of the TNF receptor superfamily, increases with glial tumor grade, inversely correlates with patient overall survival, stimulates GBM cell invasion in vitro and in vivo, and increases resistance to temozolomide and radiation therapy. Conversely, silencing TROY expression inhibits GBM cell invasion, increases sensitivity to temozolomide, and prolongs survival in a preclinical intracranial xenograft model. Here, we have identified for the first time that TROY interacts with JAK1. Increased TROY expression increases JAK1 phosphorylation. In addition, increased TROY expression promotes STAT3 phosphorylation and STAT3 transcriptional activity that is dependent upon JAK1. TROY-mediated activation of STAT3 is independent of its ability to stimulate activity of NF-κB. Inhibition of JAK1 activity by ruxolitinib or knockdown of JAK1 expression by siRNA significantly inhibits TROY-induced STAT3 activation, GBM cell migration, and decreases resistance to temozolomide. Taken together, our data indicate that the TROY signaling complex may represent a potential therapeutic target with the distinctive capacity to exert effects on multiple pathways mediating GBM cell invasion and resistance.

Temporospatial genomic profiling in glioblastoma identifies commonly altered core pathways underlying tumor progression

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.

Identification of a Blood-Based Protein Biomarker Panel for Lung Cancer Detection

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.

Low-Dose Vertical Inhibition of the RAF-MEK-ERK Cascade Causes Apoptotic Death of KRAS Mutant Cancers

We address whether combinations with a pan-RAF inhibitor (RAFi) would be effective in KRAS mutant pancreatic ductal adenocarcinoma (PDAC). Chemical library and CRISPR genetic screens identify combinations causing apoptotic anti-tumor activity. The most potent combination, concurrent inhibition of RAF (RAFi) and ERK (ERKi), is highly synergistic at low doses in cell line, organoid, and rat models of PDAC, whereas each inhibitor alone is only cytostatic. Comprehensive mechanistic signaling studies using reverse phase protein array (RPPA) pathway mapping and RNA sequencing (RNA-seq) show that RAFi/ERKi induced insensitivity to loss of negative feedback and system failures including loss of ERK signaling, FOSL1, and MYC; shutdown of the MYC transcriptome; and induction of mesenchymal-to-epithelial transition. We conclude that low-dose vertical inhibition of the RAF-MEK-ERK cascade is an effective therapeutic strategy for KRAS mutant PDAC.

MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers

SUMMARY

We present MetaMarker, a pipeline for discovering metagenomic biomarkers from whole-metagenome sequencing samples. Different from existing methods, MetaMarker is based on a de novo approach that does not require mapping raw reads to a reference database. We applied MetaMarker on whole-metagenome sequencing of colorectal cancer (CRC) stool samples from France to discover CRC specific metagenomic biomarkers. We showed robustness of the discovered biomarkers by validating in independent samples from Hong Kong, Austria, Germany and Denmark. We further demonstrated these biomarkers could be used to build a machine learning classifier for CRC prediction.

AVAILABILITY AND IMPLEMENTATION

MetaMarker is freely available at https://bitbucket.org/mkoohim/metamarker under GPLv3 license.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Author Correction: Combination of ERK and autophagy inhibition as a treatment approach for pancreatic cancer

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genomic and Phenotypic Characterization of a Broad Panel of Patient-Derived Xenografts Reflects the Diversity of Glioblastoma

PURPOSE

Glioblastoma is the most frequent and lethal primary brain tumor. Development of novel therapies relies on the availability of relevant preclinical models. We have established a panel of 96 glioblastoma patient-derived xenografts (PDX) and undertaken its genomic and phenotypic characterization.

EXPERIMENTAL DESIGN

PDXs were established from glioblastoma, IDH-wildtype (n = 93), glioblastoma, IDH-mutant (n = 2), diffuse midline glioma, H3 K27M-mutant (n = 1), and both primary (n = 60) and recurrent (n = 34) tumors. Tumor growth rates, histopathology, and treatment response were characterized. Integrated molecular profiling was performed by whole-exome sequencing (WES, n = 83), RNA-sequencing (n = 68), and genome-wide methylation profiling (n = 76). WES data from 24 patient tumors was compared with derivative models.

RESULTS

PDXs recapitulate many key phenotypic and molecular features of patient tumors. Orthotopic PDXs show characteristic tumor morphology and invasion patterns, but largely lack microvascular proliferation and necrosis. PDXs capture common and rare molecular drivers, including alterations of TERT, EGFR, PTEN, TP53, BRAF, and IDH1, most at frequencies comparable with human glioblastoma. However, PDGFRA amplification was absent. RNA-sequencing and genome-wide methylation profiling demonstrated broad representation of glioblastoma molecular subtypes. MGMT promoter methylation correlated with increased survival in response to temozolomide. WES of 24 matched patient tumors showed preservation of most genetic driver alterations, including EGFR amplification. However, in four patient-PDX pairs, driver alterations were gained or lost on engraftment, consistent with clonal selection.

CONCLUSIONS

Our PDX panel captures the molecular heterogeneity of glioblastoma and recapitulates many salient genetic and phenotypic features. All models and genomic data are openly available to investigators.

Decreased nonspecific adhesivity, receptor-targeted therapeutic nanoparticles for primary and metastatic breast cancer

Development of effective tumor cell-targeted nanodrug formulations has been quite challenging, as many nanocarriers and targeting moieties exhibit nonspecific binding to cellular, extracellular, and intravascular components. We have developed a therapeutic nanoparticle formulation approach that balances cell surface receptor-specific binding affinity while maintaining minimal interactions with blood and tumor tissue components (termed "DART" nanoparticles), thereby improving blood circulation time, biodistribution, and tumor cell-specific uptake. Here, we report that paclitaxel (PTX)-DART nanoparticles directed to the cell surface receptor fibroblast growth factor-inducible 14 (Fn14) outperformed both the corresponding PTX-loaded, nontargeted nanoparticles and Abraxane, an FDA-approved PTX nanoformulation, in both a primary triple-negative breast cancer (TNBC) model and an intracranial model reflecting TNBC growth following metastatic dissemination to the brain. These results provide new insights into methods for effective development of therapeutic nanoparticles as well as support the continued development of the DART platform for primary and metastatic tumors.

Localized Metabolomic Gradients in Patient-Derived Xenograft Models of Glioblastoma

Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood-brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. SIGNIFICANCE: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment.See related commentary by Tan and Weljie, p. 1231.

The TNF receptor family member Fn14 is highly expressed in recurrent glioblastoma and in GBM patient-derived xenografts with acquired temozolomide resistance

Background

Glioblastoma (GBM) is a difficult to treat brain cancer that nearly uniformly recurs, and recurrent tumors are largely therapy resistant. Our prior work has demonstrated an important role for the tumor necrosis factor-like weak inducer of apoptosis (TWEAK) receptor fibroblast growth factor-inducible 14 (Fn14) in GBM pathobiology. In this study, we investigated Fn14 expression in recurrent GBM and in the setting of temozolomide (TMZ) resistance.

Methods

Fn14 mRNA expression levels in nonneoplastic brain, primary (newly diagnosed) GBM, and recurrent GBM (post-chemotherapy and radiation) specimens were obtained from The Cancer Genome Atlas data portal. Immunohistochemistry was performed using nonneoplastic brain, patient-matched primary and recurrent GBM, and gliosarcoma (GSM) specimens to examine Fn14 protein levels. Western blot analysis was used to compare Fn14 expression in parental TMZ-sensitive or matched TMZ-resistant patient-derived xenografts (PDXs) established from primary or recurrent tumor samples. The migratory capacity of control and Fn14-depleted TMZ-resistant GBM cells was assessed using the transwell migration assay.

Results

We found that Fn14 is more highly expressed in recurrent GBM tumors than their matched primary GBM counterparts. Fn14 expression is also significantly elevated in GSM tumors. GBM PDX cells with acquired TMZ resistance have higher Fn14 levels and greater migratory capacity than their corresponding parental TMZ-sensitive cells, and the migratory difference is due, at least in part, to Fn14 expression in the TMZ-resistant cells.

Conclusions

This study demonstrates that the Fn14 gene is highly expressed in recurrent GBM, GSM, and TMZ-resistant GBM PDX tumors. These findings suggest that Fn14 may be a valuable therapeutic target or drug delivery portal for treatment of recurrent GBM and GSM patients.

mTCTScan: a comprehensive platform for annotation and prioritization of mutations affecting drug sensitivity in cancers

Cancer therapies have experienced rapid progress in recent years, with a number of novel small-molecule kinase inhibitors and monoclonal antibodies now being widely used to treat various types of human cancers. During cancer treatments, mutations can have important effects on drug sensitivity. However, the relationship between tumor genomic profiles and the effectiveness of cancer drugs remains elusive. We introduce Mutation To Cancer Therapy Scan (mTCTScan) web server (http://jjwanglab.org/mTCTScan) that can systematically analyze mutations affecting cancer drug sensitivity based on individual genomic profiles. The platform was developed by leveraging the latest knowledge on mutation-cancer drug sensitivity associations and the results from large-scale chemical screening using human cancer cell lines. Using an evidence-based scoring scheme based on current integrative evidences, mTCTScan is able to prioritize mutations according to their associations with cancer drugs and preclinical compounds. It can also show related drugs/compounds with sensitivity classification by considering the context of the entire genomic profile. In addition, mTCTScan incorporates comprehensive filtering functions and cancer-related annotations to better interpret mutation effects and their association with cancer drugs. This platform will greatly benefit both researchers and clinicians for interrogating mechanisms of mutation-dependent drug response, which will have a significant impact on cancer precision medicine.

Abstract 3701: Fn14 overexpression in RCAS/tv-a rat gliomas promotes tumor progression, increases invasion and decreases survival

Fibroblast growth factor-inducible 14 (Fn14) is the cell surface receptor for the tumor necrosis factor (TNF) family member TNF-like weak inducer of apoptosis (TWEAK). The Fn14 gene is not normally expressed in healthy tissues, but expression is significantly increased in many primary solid tumor types, including glioblastoma (GBM). High Fn14 expression in tumors is often associated with the stimulation of cancer cell invasion leading to diffuse, aggressive tumors and metastasis. To investigate the effects of increased Fn14 expression in brain tumors, two different tumor types were developed using the RCAS/tv-a transgenic rat model: a low-Fn14, “proneural-like” (PDGFA/shP53 derived) tumor and a high-Fn14 (PDGFA/shP53/Fn14-derived) tumor. Interestingly, rats with high-Fn14 brain tumors had a significantly shorter median survival compared to those with low-Fn14 with 42 days and 70 days median survival, respectively. Using MR proton spectroscopy, both tumor types exhibited the markers of a malignant glioma such as increases in choline to creatinine ratio (Cho/Cr) and decreases in neuronal activity (NAA); however, high-Fn14 tumors also displayed an increase in lactate during tumor progression which is often a sign of high grade, necrotic tumors and poor prognosis. Morphologically, the two tumor subtypes appear quite different. H&E staining of the high-Fn14 tumors showed a highly malignant tumor with several areas of pseudopalisading necrosis within the tumor core. This is different than the somewhat more homogeneous morphology of the low-Fn14 proneural-like tumor. The pattern of tumor cell invasion also differs between the two brain cancer subtypes. High-Fn14 tumors show a more human GBM-like pattern by invading along the white matter tracts whereas low-Fn14 tumors appear to invade more locally with minimal white matter invasion. High-Fn14 tumors were positive for Fn14 throughout the tumor including the invasive rim of the tumor, which is also seen in human GBM, whereas the low-Fn14 tumor revealed very little staining even at the invasive rim. These findings indicate that increased Fn14 expression creates a more malignant brain tumors that develops and behaves more aggressively then low-Fn14 tumors.

Citation Format: Nina Connolly, Heather Ames, Nhan L. Tran, Anthony Kim, Jeff Winkles, Graeme Woodworth. Fn14 overexpression in RCAS/tv-a rat gliomas promotes tumor progression, increases invasion and decreases survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3701.

Combination of ERK and autophagy inhibition as a treatment approach for pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by KRAS- and autophagy-dependent tumorigenic growth, but the role of KRAS in supporting autophagy has not been established. We show that, to our surprise, suppression of KRAS increased autophagic flux, as did pharmacological inhibition of its effector ERK MAPK. Furthermore, we demonstrate that either KRAS suppression or ERK inhibition decreased both glycolytic and mitochondrial functions. We speculated that ERK inhibition might thus enhance PDAC dependence on autophagy, in part by impairing other KRAS- or ERK-driven metabolic processes. Accordingly, we found that the autophagy inhibitor chloroquine and genetic or pharmacologic inhibition of specific autophagy regulators synergistically enhanced the ability of ERK inhibitors to mediate antitumor activity in KRAS-driven PDAC. We conclude that combinations of pharmacologic inhibitors that concurrently block both ERK MAPK and autophagic processes that are upregulated in response to ERK inhibition may be effective treatments for PDAC.

Leveraging Spatial Variation in Tumor Purity for Improved Somatic Variant Calling of Archival Tumor Only Samples

Archival tumor samples represent a rich resource of annotated specimens for translational genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available in the retrospective setting, making it difficult to distinguish between true somatic variants and individual-specific germline variants. Archival sections often contain adjacent normal tissue, but this tissue can include infiltrating tumor cells. As existing comparative somatic variant callers are designed to exclude variants present in the normal sample, a novel approach is required to leverage adjacent normal tissue with infiltrating tumor cells for somatic variant calling. Here we present lumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient, built upon our previous single sample tumor only variant caller lumosVar 1.0. The approach assumes that the allelic fraction of somatic variants and germline variants follow different patterns as tumor content and copy number state change. lumosVar 2.0 estimates allele specific copy number and tumor sample fractions from the data, and uses a to model to determine expected allelic fractions for somatic and germline variants and to classify variants accordingly. To evaluate the utility of lumosVar 2.0 to jointly call somatic variants with tumor and adjacent normal samples, we used a glioblastoma dataset with matched high and low tumor content and germline whole exome sequencing data (for true somatic variants) available for each patient. Both sensitivity and positive predictive value were improved when analyzing the high tumor and low tumor samples jointly compared to analyzing the samples individually or in-silico pooling of the two samples. Finally, we applied this approach to a set of breast and prostate archival tumor samples for which tumor blocks containing adjacent normal tissue were available for sequencing. Joint analysis using lumosVar 2.0 detected several variants, including known cancer hotspot mutations that were not detected by standard somatic variant calling tools using the adjacent tissue as presumed normal reference. Together, these results demonstrate the utility of leveraging paired tissue samples to improve somatic variant calling when a constitutional sample is not available.

P2RX7 Deletion in T Cells Promotes Autoimmune Arthritis by Unleashing the Tfh Cell Response

Rheumatoid arthritis (RA) is an autoimmune disease that affects ~1% of the world's population. B cells and autoantibodies play an important role in the pathogenesis of RA. The P2RX7 receptor is an ATP-gated cation channel and its activation results in the release of pro-inflammatory molecules. Thus, antagonists of P2RX7 have been considered to have potential as novel anti-inflammatory therapies. Although originally identified for its role in innate immunity, P2RX7 has recently been found to negatively control Peyer's patches (PP) T follicular helper cells (Tfh), which specialize in helping B cells, under homeostatic conditions. We have previously demonstrated that PP Tfh cells are required for the augmentation of autoimmune arthritis mediated by gut commensal segmented filamentous bacteria (SFB). Thus, we hypothesized that P2RX7 is required to control autoimmune disease by keeping the Tfh cell response in check. To test our hypothesis, we analyzed the impact of P2RX7 deficiency in vivo using both the original K/BxN autoimmune arthritis model and T cell transfers in the K/BxN system. We also examined the impact of P2RX7 ablation on autoimmune development in the presence of the gut microbiota SFB. Our data illustrate that contrary to exerting an anti-inflammatory effect, P2RX7 deficiency actually enhances autoimmune arthritis. Interestingly, SFB colonization can negate the difference in disease severity between WT and P2RX7-deficient mice. We further demonstrated that P2RX7 ablation in the absence of SFB caused reduced apoptotic Tfh cells and enhanced the Tfh response, leading to an increase in autoantibody production. It has been shown that activation of TIGIT, a well-known T cell exhaustion marker, up-regulates anti-apoptotic molecules and promotes T cell survival. We demonstrated that the reduced apoptotic phenotype of P2rx7^−/− Tfh cells is associated with their increased expression of TIGIT. This suggested that while P2RX7 was regulating the Tfh population by promoting cell death, TIGIT may have been opposing P2RX7 by inhibiting cell death. Together, these results demonstrated that systemic administration of general P2RX7 antagonists may have detrimental effects in autoimmune therapies, especially in Tfh cell-dependent autoimmune diseases, and cell-specific targeting of P2RX7 should be considered in order to achieve efficacy for P2RX7-related therapy.

Accurate Patient-Specific Machine Learning Models of Glioblastoma Invasion Using Transfer Learning

BACKGROUND AND PURPOSE

MR imaging-based modeling of tumor cell density can substantially improve targeted treatment of glioblastoma. Unfortunately, interpatient variability limits the predictive ability of many modeling approaches. We present a transfer learning method that generates individualized patient models, grounded in the wealth of population data, while also detecting and adjusting for interpatient variabilities based on each patient's own histologic data.

MATERIALS AND METHODS

We recruited patients with primary glioblastoma undergoing image-guided biopsies and preoperative imaging, including contrast-enhanced MR imaging, dynamic susceptibility contrast MR imaging, and diffusion tensor imaging. We calculated relative cerebral blood volume from DSC-MR imaging and mean diffusivity and fractional anisotropy from DTI. Following image coregistration, we assessed tumor cell density for each biopsy and identified corresponding localized MR imaging measurements. We then explored a range of univariate and multivariate predictive models of tumor cell density based on MR imaging measurements in a generalized one-model-fits-all approach. We then implemented both univariate and multivariate individualized transfer learning predictive models, which harness the available population-level data but allow individual variability in their predictions. Finally, we compared Pearson correlation coefficients and mean absolute error between the individualized transfer learning and generalized one-model-fits-all models.

RESULTS

Tumor cell density significantly correlated with relative CBV (r = 0.33, P < .001), and T1-weighted postcontrast (r = 0.36, P < .001) on univariate analysis after correcting for multiple comparisons. With single-variable modeling (using relative CBV), transfer learning increased predictive performance (r = 0.53, mean absolute error = 15.19%) compared with one-model-fits-all (r = 0.27, mean absolute error = 17.79%). With multivariate modeling, transfer learning further improved performance (r = 0.88, mean absolute error = 5.66%) compared with one-model-fits-all (r = 0.39, mean absolute error = 16.55%).

CONCLUSIONS

Transfer learning significantly improves predictive modeling performance for quantifying tumor cell density in glioblastoma.

Integrated mapping of pharmacokinetics and pharmacodynamics in a patient-derived xenograft model of glioblastoma

Therapeutic options for the treatment of glioblastoma remain inadequate despite concerted research efforts in drug development. Therapeutic failure can result from poor permeability of the blood-brain barrier, heterogeneous drug distribution, and development of resistance. Elucidation of relationships among such parameters could enable the development of predictive models of drug response in patients and inform drug development. Complementary analyses were applied to a glioblastoma patient-derived xenograft model in order to quantitatively map distribution and resulting cellular response to the EGFR inhibitor erlotinib. Mass spectrometry images of erlotinib were registered to histology and magnetic resonance images in order to correlate drug distribution with tumor characteristics. Phosphoproteomics and immunohistochemistry were used to assess protein signaling in response to drug, and integrated with transcriptional response using mRNA sequencing. This comprehensive dataset provides simultaneous insight into pharmacokinetics and pharmacodynamics and indicates that erlotinib delivery to intracranial tumors is insufficient to inhibit EGFR tyrosine kinase signaling.

Developments in Blood-Brain Barrier Penetrance and Drug Repurposing for Improved Treatment of Glioblastoma

Glioblastoma (GBM) is one of the most common, deadly, and difficult-to-treat adult brain tumors. Surgical removal of the tumor, followed by radiotherapy (RT) and temozolomide (TMZ) administration, is the current treatment modality, but this regimen only modestly improves overall patient survival. Invasion of cells into the surrounding healthy brain tissue prevents complete surgical resection and complicates treatment strategies with the goal of preserving neurological function. Despite significant efforts to increase our understanding of GBM, there have been relatively few therapeutic advances since 2005 and even fewer treatments designed to effectively treat recurrent tumors that are resistant to therapy. Thus, while there is a pressing need to move new treatments into the clinic, emerging evidence suggests that key features unique to GBM location and biology, the blood-brain barrier (BBB) and intratumoral molecular heterogeneity, respectively, stand as critical unresolved hurdles to effective therapy. Notably, genomic analyses of GBM tissues has led to the identification of numerous gene alterations that govern cell growth, invasion and survival signaling pathways; however, the drugs that show pre-clinical potential against signaling pathways mediated by these gene alterations cannot achieve effective concentrations at the tumor site. As a result, identifying BBB-penetrating drugs and utilizing new and safer methods to enhance drug delivery past the BBB has become an area of intensive research. Repurposing and combining FDA-approved drugs with evidence of penetration into the central nervous system (CNS) has also seen new interest for the treatment of both primary and recurrent GBM. In this review, we discuss emerging methods to strategically enhance drug delivery to GBM and repurpose currently-approved and previously-studied drugs using rational combination strategies.

Abstract 4910: Development of an antagonist to the TWEAK-Fn14 ligand-receptor interaction with enhanced efficacy/potency in glioblastoma cells

Glioblastoma multiforme (GBM) remains the most common and deadly primary brain tumor with minimal advances in therapeutic development for pharmacological treatment. Tumor resection followed by temozolomide (TMZ) and radiotherapy adds months to survival; however, tumor recurrence usually occurs. The fibroblast growth factor-inducible 14 (Fn14) receptor has been shown to be up-regulated in the GBM cells left behind after surgery and contributes to an invasive and pro-survival phenotype, providing a desirable molecule to target after removal of the primary tumor. Previously, L524-0366 was reported by our lab to be the first antagonist of Fn14 signaling; however, minimal efficacy/potency has limited this drug from progressing from a useful research tool to preclinical studies. Structure activity relationship (SAR) studies using the parent L524-0366 compound gave rise to K78, which was found to bind to Fn14 with enhanced affinity, while showing no binding to the structurally-related TNFα receptor. Furthermore, K78 was able to abate the downstream signaling effects initiated by the Fn14 ligand, tumor necrosis factor-like weak inducer of apoptosis (TWEAK), as well as sensitize GBM cells to the cytotoxic effects of TMZ. TWEAK-induced cellular migration was also mitigated with co-treatment of K78 in GBM cells, compared to a vehicle control. It is anticipated that further development of Fn14 antagonists will be of great importance for the advancement of GBM patient treatment and warrant further investigation as primary and combination therapy, especially for the prevention of recurrent disease.

Citation Format: Bryan Harder, Chris Sereduk, Harshil Dhruv, Nghia Millard, Anthony Kim, Jeffrey Winkles, Graeme Woodworth, Holly Yin, Nhan L. Tran. Development of an antagonist to the TWEAK-Fn14 ligand-receptor interaction with enhanced efficacy/potency in glioblastoma cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4910.

Abstract 3462: EGFRvIII-Stat5 signaling enhances glioblastoma cell invasion

Glioblastoma Multiforme (GBM) is the most common malignant brain tumor in adults. Most GBM patients succumb to the disease less than one-year post diagnosis due to the highly invasive nature of the tumor, which prevents complete surgical resection and gives rise to tumor recurrence. The invasive phenotype also confers radio and chemoresistant properties to the tumor cells; therefore, there is a need to develop new therapeutics that target drivers of GBM invasion. Amplification of EGFR is observed in over 50% of GBM tumors, of which half concurrently overexpress the variant EGFRvIII, and expression of both receptors confers a worse prognosis. EGFR and EGFRvIII cooperate to promote tumor progression and invasion, in part, through activation of the Stat-signaling pathway. Here we report that EGFRvIII activates Stat5 and GBM invasion, in part, by inducing the expression of a previously established mediator of glioma cell invasion and survival, fibroblast growth factor-inducible 14 (Fn14). EGFRvIII-mediated induction of Fn14 expression is dependent upon Stat5 and requires activation of Src, whereas EGFR regulation of Fn14 is dependent upon MEK/ERK-Stat3 activation. Notably, treatment of EGFRvIII expressing GBM cells with the FDA approved Stat5 inhibitor pimozide blocked Stat5 phosphorylation, Fn14 expression, and cell migration. Since EGFR inhibitors display limited therapeutic efficacy in GBM patients, we hypothesize that the EGFRvIII-Stat5-Fn14 signaling pathway represents a node of vulnerability in the invasive GB cell population and that targeting critical effectors in this pathway will limit GBM tumor dispersion, mitigate therapeutic resistance, and increase survival.

Citation Format: Alison Roos, Harshil D. Dhruv, Sen Peng, Landon J. Inge, Serdar Tuncali, Michael Pineda, Nghia Millard, Jeffrey A. Winkles, Joseph C. Loftus, Nhan L. Tran. EGFRvIII-Stat5 signaling enhances glioblastoma cell invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3462.

EGFRvIII-Stat5 Signaling Enhances Glioblastoma Cell Migration and Survival

Glioblastoma multiforme (GBM) is the most common brain malignancies in adults. Most GBM patients succumb to the disease less than 1 year after diagnosis due to the highly invasive nature of the tumor, which prevents complete surgical resection and gives rise to tumor recurrence. The invasive phenotype also confers radioresistant and chemoresistant properties to the tumor cells; therefore, there is a critical need to develop new therapeutics that target drivers of GBM invasion. Amplification of EGFR is observed in over 50% of GBM tumors, of which half concurrently overexpress the variant EGFRvIII, and expression of both receptors confers a worse prognosis. EGFR and EGFRvIII cooperate to promote tumor progression and invasion, in part, through activation of the Stat signaling pathway. Here, it is reported that EGFRvIII activates Stat5 and GBM invasion by inducing the expression of a previously established mediator of glioma cell invasion and survival: fibroblast growth factor-inducible 14 (Fn14). EGFRvIII-mediated induction of Fn14 expression is Stat5 dependent and requires activation of Src, whereas EGFR regulation of Fn14 is dependent upon Src-MEK/ERK-Stat3 activation. Notably, treatment of EGFRvIII-expressing GBM cells with the FDA-approved Stat5 inhibitor pimozide blocked Stat5 phosphorylation, Fn14 expression, and cell migration and survival. Because EGFR inhibitors display limited therapeutic efficacy in GBM patients, the EGFRvIII-Stat5-Fn14 signaling pathway represents a node of vulnerability in the invasive GBM cell populations.Implications: Targeting critical effectors in the EGFRvIII-Stat5-Fn14 pathway may limit GBM tumor dispersion, mitigate therapeutic resistance, and increase survival. Mol Cancer Res; 16(7); 1185-95. ©2018 AACR.

Integrated genomic analysis of survival outliers in glioblastoma

Background

To elucidate molecular features associated with disproportionate survival of glioblastoma (GB) patients, we conducted deep genomic comparative analysis of a cohort of patients receiving standard therapy (surgery plus concurrent radiation and temozolomide); "GB outliers" were identified: long-term survivor of 33 months (LTS; n = 8) versus short-term survivor of 7 months (STS; n = 10).

Methods

We implemented exome, RNA, whole genome sequencing, and DNA methylation for collection of deep genomic data from STS and LTS GB patients.

Results

LTS GB showed frequent chromosomal gains in 4q12 (platelet derived growth factor receptor alpha and KIT) and 12q14.1 (cyclin-dependent kinase 4), and deletion in 19q13.33 (BAX, branched chain amino-acid transaminase 2, and cluster of differentiation 33). STS GB showed frequent deletion in 9p11.2 (forkhead box D4-like 2 and aquaporin 7 pseudogene 3) and 22q11.21 (Hypermethylated In Cancer 2). LTS GB showed 2-fold more frequent copy number deletions compared with STS GB. Gene expression differences showed the STS cohort with altered transcriptional regulators: activation of signal transducer and activator of transcription (STAT)5a/b, nuclear factor-kappaB (NF-κB), and interferon-gamma (IFNG), and inhibition of mitogen-activated protein kinase (MAPK1), extracellular signal-regulated kinase (ERK)1/2, and estrogen receptor (ESR)1. Expression-based biological concepts prominent in the STS cohort include metabolic processes, anaphase-promoting complex degradation, and immune processes associated with major histocompatibility complex class I antigen presentation; the LTS cohort features genes related to development, morphogenesis, and the mammalian target of rapamycin signaling pathway. Whole genome methylation analyses showed that a methylation signature of 89 probes distinctly separates LTS from STS GB tumors.

Conclusion

We posit that genomic instability is associated with longer survival of GB (possibly with vulnerability to standard therapy); conversely, genomic and epigenetic signatures may identify patients where up-front entry into alternative, targeted regimens would be a preferred, more efficacious management.

Differential expression of the TWEAK receptor Fn14 in IDH1 wild-type and mutant gliomas

The TNF receptor superfamily member Fn14 is overexpressed by many solid tumor types, including glioblastoma (GBM), the most common and lethal form of adult brain cancer. GBM is notable for a highly infiltrative growth pattern and several groups have reported that high Fn14 expression levels can increase tumor cell invasiveness. We reported previously that the mesenchymal and proneural GBM transcriptomic subtypes expressed the highest and lowest levels of Fn14 mRNA, respectively. Given the recent histopathological re-classification of human gliomas by the World Health Organization based on isocitrate dehydrogenase 1 (IDH1) gene mutation status, we extended this work by comparing Fn14 gene expression in IDH1 wild-type (WT) and mutant (R132H) gliomas and in cell lines engineered to overexpress the IDH1 R132H enzyme. We found that both low-grade and high-grade (i.e., GBM) IDH1 R132H gliomas exhibit low Fn14 mRNA and protein levels compared to IDH1 WT gliomas. Forced overexpression of the IDH1 R132H protein in glioma cells reduced Fn14 expression, while treatment of IDH1 R132H-overexpressing cells with the IDH1 R132H inhibitor AGI-5198 or the DNA demethylating agent 5-aza-2'-deoxycytidine increased Fn14 expression. These results support a role for Fn14 in the more aggressive and invasive phenotype associated with IDH1 WT tumors and indicate that the low levels of Fn14 gene expression noted in IDH1 R132H mutant gliomas may be due to epigenetic regulation via changes in DNA methylation.

A Novel Signaling Complex between TROY and EGFR Mediates Glioblastoma Cell Invasion

Glioblastoma is the most frequent primary brain tumor in adults and a highly lethal malignancy with a median survival of about 15 months. The aggressive invasion of the surrounding normal brain makes complete surgical resection impossible, increases the resistance to radiation and chemotherapy, and assures tumor recurrence. Thus, there is an urgent need to develop innovative therapeutics to target the invasive tumor cells for improved treatment outcomes of this disease. Expression of TROY (TNFRSF19), a member of the tumor necrosis factor (TNF) receptor family, increases with increasing glial tumor grade and inversely correlates with patient survival. Increased expression of TROY stimulates glioblastoma cell invasion in vitro and in vivo and increases resistance to temozolomide and radiation therapy. Conversely, silencing TROY expression inhibits glioblastoma cell invasion, increases temozolomide sensitivity, and prolongs survival in an intracranial xenograft model. Here, a novel complex is identified between TROY and EGFR, which is mediated predominantly by the cysteine-rich CRD3 domain of TROY. Glioblastoma tumors with elevated TROY expression have a statistically positive correlation with increased EGFR expression. TROY expression significantly increases the capacity of EGF to stimulate glioblastoma cell invasion, whereas depletion of TROY expression blocks EGF stimulation of glioblastoma cell invasion. Mechanistically, TROY expression modulates EGFR signaling by facilitating EGFR activation and delaying EGFR receptor internalization. Moreover, the association of EGFR with TROY increases TROY-induced NF-κB activation. These findings substantiate a critical role for the TROY-EGFR complex in regulation of glioblastoma cell invasion.Implications: The TROY-EGFR signaling complex emerges as a potential therapeutic target to inhibit glioblastoma cell invasion. Mol Cancer Res; 16(2); 322-32. ©2017 AACR.

Prospective Feasibility Trial for Genomics-Informed Treatment in Recurrent and Progressive Glioblastoma

Purpose: Glioblastoma is an aggressive and molecularly heterogeneous cancer with few effective treatment options. We hypothesized that next-generation sequencing can be used to guide treatment recommendations within a clinically acceptable time frame following surgery for patients with recurrent glioblastoma.Experimental Design: We conducted a prospective genomics-informed feasibility trial in adults with recurrent and progressive glioblastoma. Following surgical resection, genome-wide tumor/normal exome sequencing and tumor RNA sequencing were performed to identify molecular targets for potential matched therapy. A multidisciplinary molecular tumor board issued treatment recommendations based on the genomic results, blood-brain barrier penetration of the indicated therapies, drug-drug interactions, and drug safety profiles. Feasibility of generating genomics-informed treatment recommendations within 35 days of surgery was assessed.Results: Of the 20 patients enrolled in the study, 16 patients had sufficient tumor tissue for analysis. Exome sequencing was completed for all patients, and RNA sequencing was completed for 14 patients. Treatment recommendations were provided within the study's feasibility time frame for 15 of 16 (94%) patients. Seven patients received treatment based on the tumor board recommendations. Two patients reached 12-month progression-free survival, both adhering to treatments based on the molecular profiling results. One patient remained on treatment and progression free 21 months after surgery, 3 times longer than the patient's previous time to progression. Analysis of matched nonenhancing tissue from 12 patients revealed overlapping as well as novel putatively actionable genomic alterations.Conclusions: Use of genome-wide molecular profiling is feasible and can be informative for guiding real-time, central nervous system-penetrant, genomics-informed treatment recommendations for patients with recurrent glioblastoma. Clin Cancer Res; 24(2); 295-305. ©2017 AACRSee related commentary by Wick and Kessler, p. 256.

Identification of aurintricarboxylic acid as a selective inhibitor of the TWEAK-Fn14 signaling pathway in glioblastoma cells

The survival of patients diagnosed with glioblastoma (GBM), the most deadly form of brain cancer, is compromised by the proclivity for local invasion into the surrounding normal brain, which prevents complete surgical resection and contributes to therapeutic resistance. Tumor necrosis factor-like weak inducer of apoptosis (TWEAK), a member of the tumor necrosis factor (TNF) superfamily, can stimulate glioma cell invasion and survival via binding to fibroblast growth factor-inducible 14 (Fn14) and subsequent activation of the transcription factor NF-κB. To discover small molecule inhibitors that disrupt the TWEAK-Fn14 signaling axis, we utilized a cell-based drug-screening assay using HEK293 cells engineered to express both Fn14 and a NF-κB-driven firefly luciferase reporter protein. Focusing on the LOPAC1280 library of 1280 pharmacologically active compounds, we identified aurintricarboxylic acid (ATA) as an agent that suppressed TWEAK-Fn14-NF-κB dependent signaling, but not TNFα-TNFR-NF-κB driven signaling. We demonstrated that ATA repressed TWEAK-induced glioma cell chemotactic migration and invasion via inhibition of Rac1 activation but had no effect on cell viability or Fn14 expression. In addition, ATA treatment enhanced glioma cell sensitivity to both the chemotherapeutic agent temozolomide (TMZ) and radiation-induced cell death. In summary, this work reports a repurposed use of a small molecule inhibitor that targets the TWEAK-Fn14 signaling axis, which could potentially be developed as a new therapeutic agent for treatment of GBM patients.

Abstract 1878: PDZ-RhoGEF functions as a critical signaling effector for TROY

Glioblastoma Multiforme (GBM) is the most common tumor of the CNS with a median survival of approximately 15 months. The highly aggressive invasion of malignant cells into the surrounding normal brain tissue renders complete surgical resection impossible, increases therapeutic resistance, and virtually assures tumor recurrence. We have previously demonstrated that TROY (TNFRSF19) has an important role in GBM invasion and resistance. TROY expression is correlated with glial tumor grade and inversely correlated with patient survival. Increased TROY expression stimulated cell migration/invasion in vitro and in vivo and confers resistance to both ionizing radiation- and temozolomide-induced apoptosis via activation of Akt and NF-κB. These data indicate that TROY stimulated migration/invasion is associated with signaling pathways that also increase survival and therapeutic resistance, however, the mechanistic basis of this signaling remains unclear. To investigate the mechanism by which TROY induces GBM cell invasion, we performed immunoprecipitation of the TROY receptor coupled with MALDI-TOF and MS/MS analysis and identified PDZ-RhoGEF as a binding partner for TROY. We validated the interaction of TROY with PDZ-RhoGEF by immunoprecipitation and western blotting, and demonstrated that PDZ-RhoGEF can exchange for both RhoA and RhoC in glioma cells and is implicated in GBM cell invasion, proliferation, and survival. In order to assess the specific role of PDZ-RhoGEF in TROY signaling, we examined the effects of PDZ-RhoGEF on TROY-mediated activation of NF-κB. While overexpression of TROY alone strongly stimulated NF-κB transcriptional activity in serum-free conditions, increased expression of PDZ-RhoGEF alone had no effect on NF-κB activity. Co-transfection of PDZ-RhoGEF with TROY synergistically promoted NF-κB activation. Mutation of the TRAF binding domain (TBD) in the cytoplasmic domain of TROY abolished its capacity to activate NF-κB, even in the presence of PDZ-RhoGEF, suggesting that the TBD is important for TROY induced NF-κB activation. Furthermore, knockdown of PDZ-RhoGEF by shRNA attenuated NF-κB activation in TROY expressing cells, blocked TROY mediated invasion of primary GBM xenograft cells and increased sensitivity to temozolomide. Collectively, these data indicate that PDZ-RhoGEF plays an important role in TROY signaling and provides insights into a potential node of vulnerability to limit GBM cell invasion and decrease therapeutic resistance.

Citation Format: Zonghui Ding, Alison Roos, Jean Kloss, Harshil Dhruv, Marc Symons, Nhan L. Tran, Joseph C. Loftus. PDZ-RhoGEF functions as a critical signaling effector for TROY [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1878. doi:10.1158/1538-7445.AM2017-1878

Molecular and Microenvironmental Determinants of Glioma Stem-Like Cell Survival and Invasion

Glioblastoma multiforme (GBM) is the most frequent primary brain tumor in adults with a 5-year survival rate of 5% despite intensive research efforts. The poor prognosis is due, in part, to aggressive invasion into the surrounding brain parenchyma. Invasion is a complex process mediated by cell-intrinsic pathways, extrinsic microenvironmental cues, and biophysical cues from the peritumoral stromal matrix. Recent data have attributed GBM invasion to the glioma stem-like cell (GSC) subpopulation. GSCs are slowly dividing, highly invasive, therapy resistant, and are considered to give rise to tumor recurrence. GSCs are localized in a heterogeneous cellular niche, and cross talk between stromal cells and GSCs cultivates a fertile environment that promotes GSC invasion. Pro-migratory soluble factors from endothelial cells, astrocytes, macrophages, microglia, and non-stem-like tumor cells can stimulate peritumoral invasion of GSCs. Therefore, therapeutic efforts designed to target the invasive GSCs may enhance patient survival. In this review, we summarize the current understanding of extrinsic pathways and major stromal and immune players facilitating GSC maintenance and survival.

RNA sequencing and transcriptome arrays analyses show opposing results for alternative splicing in patient derived samples

Background

RNA sequencing (RNA-seq) and microarrays are two transcriptomics techniques aimed at the quantification of transcribed genes and their isoforms. Here we compare the latest Affymetrix HTA 2.0 microarray with Illumina 2000 RNA-seq for the analysis of patient samples - normal lung epithelium tissue and squamous cell carcinoma lung tumours. Protein coding mRNAs and long non-coding RNAs (lncRNAs) were included in the study.

Results

Both platforms performed equally well for protein-coding RNAs, however the stochastic variability was higher for the sequencing data than for microarrays. This reduced the number of differentially expressed genes and genes with predictive potential for RNA-seq compared to microarray data. Analysis of this variability revealed a lack of reads for short and low abundant genes; lncRNAs, being shorter and less abundant RNAs, were found especially susceptible to this issue. A major difference between the two platforms was uncovered by analysis of alternatively spliced genes. Investigation of differential exon abundance showed insufficient reads for many exons and exon junctions in RNA-seq while the detection on the array platform was more stable. Nevertheless, we identified 207 genes which undergo alternative splicing and were consistently detected by both techniques.

Conclusions

Despite the fact that the results of gene expression analysis were highly consistent between Human Transcriptome Arrays and RNA-seq platforms, the analysis of alternative splicing produced discordant results. We concluded that modern microarrays can still outperform sequencing for standard analysis of gene expression in terms of reproducibility and cost.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3819-y) contains supplementary material, which is available to authorized users.

IgA-coated E. coli enriched in Crohn's disease spondyloarthritis promote TH17-dependent inflammation

Peripheral spondyloarthritis (SpA) is a common extraintestinal manifestation in patients with active inflammatory bowel disease (IBD) characterized by inflammatory enthesitis, dactylitis, or synovitis of nonaxial joints. However, a mechanistic understanding of the link between intestinal inflammation and SpA has yet to emerge. We evaluated and functionally characterized the fecal microbiome of IBD patients with or without peripheral SpA. Coupling the sorting of immunoglobulin A (IgA)-coated microbiota with 16S ribosomal RNA-based analysis (IgA-seq) revealed a selective enrichment in IgA-coated Escherichia coli in patients with Crohn's disease-associated SpA (CD-SpA) compared to CD alone. E. coli isolates from CD-SpA-derived IgA-coated bacteria were similar in genotype and phenotype to an adherent-invasive E. coli (AIEC) pathotype. In comparison to non-AIEC E. coli, colonization of germ-free mice with CD-SpA E. coli isolates induced T helper 17 cell (TH17) mucosal immunity, which required the virulence-associated metabolic enzyme propanediol dehydratase (pduC). Modeling the increase in mucosal and systemic TH17 immunity we observed in CD-SpA patients, colonization of interleukin-10-deficient or K/BxN mice with CD-SpA-derived E. coli lead to more severe colitis or inflammatory arthritis, respectively. Collectively, these data reveal the power of IgA-seq to identify immunoreactive resident pathosymbionts that link mucosal and systemic TH17-dependent inflammation and offer microbial and immunophenotype stratification of CD-SpA that may guide medical and biologic therapy.

Tumor-targeted nanotherapeutics: overcoming treatment barriers for glioblastoma

Glioblastoma (GBM) is a highly aggressive and lethal form of primary brain cancer. Numerous barriers exist to the effective treatment of GBM including the tightly controlled interface between the bloodstream and central nervous system termed the 'neurovascular unit,' a narrow and tortuous tumor extracellular space containing a dense meshwork of proteins and glycosaminoglycans, and genomic heterogeneity and instability. A major goal of GBM therapy is achieving sustained drug delivery to glioma cells while minimizing toxicity to adjacent neurons and glia. Targeted nanotherapeutics have emerged as promising drug delivery systems with the potential to improve pharmacokinetic profiles and therapeutic efficacy. Some of the key cell surface molecules that have been identified as GBM targets include the transferrin receptor, low-density lipoprotein receptor-related protein, α_v β₃ integrin, glucose transporter(s), glial fibrillary acidic protein, connexin 43, epidermal growth factor receptor (EGFR), EGFR variant III, interleukin-13 receptor α chain variant 2, and fibroblast growth factor-inducible factor 14. However, most targeted therapeutic formulations have yet to demonstrate improved efficacy related to disease progression or survival. Potential limitations to current targeted nanotherapeutics include: (1) adhesive interactions with nontarget structures, (2) low density or prevalence of the target, (3) lack of target specificity, and (4) genetic instability resulting in alterations of either the target itself or its expression level in response to treatment. In this review, we address these potential limitations in the context of the key GBM targets with the goal of advancing the understanding and development of targeted nanotherapeutics for GBM. WIREs Nanomed Nanobiotechnol 2017, 9:e1439. doi: 10.1002/wnan.1439 For further resources related to this article, please visit the WIREs website.

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

BACKGROUND

Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments.

METHODS

We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV).

RESULTS

We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32).

CONCLUSION

MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.

Abstract 700: Regulation of Fn14 expression by EGFRvIII-STAT signaling enhances glioblastoma cell invasion and survival

Glioblastoma Multiforme (GBM) is the most common malignant brain tumor in adults. Most GBM patients succumb to the disease less than one-year post diagnosis due to the highly invasive nature of the tumor, which prevents complete surgical resection and gives rise to tumor recurrence. The invasive phenotype also confers radio-and chemoresistant properties to the tumor cells; therefore, there is a need to develop new therapeutics that target drivers of GBM invasion. Amplification of EGFR is observed in over 50% of GBM tumors, of which half concurrently overexpress the variant EGFRvIII, and expression of both receptors confers a worse prognosis. EGFR and EGFRvIII cooperate to promote tumor progression and invasion, in part, through activation of the JAK/STAT-signaling pathway. Here we report that GBM cells expressing EGFRvIII show increased expression of a previously established mediator of glioma cell invasion and survival, fibroblast growth factor-inducible 14 (Fn14), at the mRNA and protein level. Treatment with STAT3, STAT5, JAK, or Src inhibitors decreased Fn14 mRNA and protein expression. Finally, knockdown of Fn14 levels in the EGFRvIII-expressing glioma cells decreased both cell survival after temozolomide (TMZ) treatment and cell invasion, which suggests that Fn14, in part, mediates the oncogenic phenotypes conferred by EGFRvIII signaling. Since EGFR inhibitors display limited therapeutic efficacy in GBM patients, we hypothesize that Fn14-targeted therapies could potentially limit invasiveness and chemoresistance in EGFRvIII-dependent GBM tumors.

Citation Format: Alison Roos, Zachary Mayo, Heather Sonnemann, Michael Pineda, Gil Lambert, Harshil D. Dhruv, Jeffrey A. Winkles, Michael E. Berens, Nhan L. Tran. Regulation of Fn14 expression by EGFRvIII-STAT signaling enhances glioblastoma cell invasion and survival. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 700.