LSD1 promotes prostate cancer reprogramming by repressing TP53 signaling independently of its demethylase function.

Lysine-specific demethylase 1 (LSD1) is a histone demethylase that promotes stemness and cell survival in cancers such as prostate cancer. Most prostate malignancies are adenocarcinomas with luminal differentiation. However, some tumors undergo cellular reprogramming to a more lethal subset termed neuroendocrine prostate cancer (NEPC) with neuronal differentiation. The frequency of NEPC is increasing since the widespread use of potent androgen receptor signaling inhibitors. Currently, there are no effective treatments for NEPC. We previously determined that LSD1 promotes survival of prostate adenocarcinoma tumors. However, the role of LSD1 in NEPC is unknown. Here, we determined that LSD1 is highly upregulated in NEPC versus adenocarcinoma patient tumors. LSD1 suppression with RNAi or allosteric LSD1 inhibitors - but not catalytic inhibitors - reduced NEPC cell survival. RNA-Seq analysis revealed that LSD1 represses pathways linked to luminal differentiation, and TP53 was the top reactivated pathway. We confirmed that LSD1 suppressed the TP53 pathway by reducing TP53 occupancy at target genes while LSD1's catalytic function was dispensable for this effect. Mechanistically, LSD1 inhibition disrupted LSD1-HDAC interactions, increasing histone acetylation at TP53 targets. Finally, LSD1 inhibition suppressed NEPC tumor growth in vivo. These findings suggest that blocking LSD1's noncatalytic function may be a promising treatment strategy for NEPC.

Efficient Inference of Spatially-Varying Gaussian Markov Random Fields With Applications in Gene Regulatory Networks.

In this paper, we study the problem of inferring spatially-varying Gaussian Markov random fields (SV-GMRF) where the goal is to learn a network of sparse, context-specific GMRFs representing network relationships between genes. An important application of SV-GMRFs is in inference of gene regulatory networks from spatially-resolved transcriptomics datasets. The current work on inference of SV-GMRFs are based on the regularized maximum likelihood estimation (MLE) and suffer from overwhelmingly high computational cost due to their highly nonlinear nature. To alleviate this challenge, we propose a simple and efficient optimization problem in lieu of MLE that comes equipped with strong statistical and computational guarantees. Our proposed optimization problem is extremely efficient in practice: we can solve instances of SV-GMRFs with more than 2 million variables in less than 2 minutes. We apply the developed framework to study how gene regulatory networks in Glioblastoma are spatially rewired within tissue, and identify prominent activity of the transcription factor HES4 and ribosomal proteins as characterizing the gene expression network in the tumor peri-vascular niche that is known to harbor treatment resistant stem cells.

Inflammatory memory restrains intestinal stem cell regeneration.

Intestinal stem cells (ISC) encounter inflammatory insults in immune mediated gastro-intestinal (GI) diseases. It remains unknown whether, and how, they adapt, and if the adaptation leaves scars on the ISCs that affects their subsequent regeneration capacity. We investigated the consequences of inflammation on Lgr5+ISCs in well-defined clinically relevant models of gastro-intestinal acute graft-versus-host disease (GI GVHD). Utilizing single cell transcriptomics, organoid, metabolic, epigenomic and in vivo models we found that Lgr5+ISCs undergo metabolic changes that lead to accumulation of succinate, which reprograms its epigenome. These changes reduced the ability of ISCs to differentiate and regenerate ex vivo in serial organoid cultures demonstrating the persistence of the maladaptive impact of an in vivo inflammatory encounter by the ISCs. Thus, inflammation from GI GVHD leaves a memory of its effects on ISCs that persist and are likely to affect their sensitivity to adapt to future stress or challenges.

Metabolomic Profiles of Human Glioma Inform Patient Survival.

Aims: Targeting tumor metabolism may improve the outcomes for patients with glioblastoma (GBM). To further preclinical efforts targeting metabolism in GBM, we tested the hypothesis that brain tumors can be stratified into distinct metabolic groups with different patient outcomes. Therefore, to determine if tumor metabolites relate to patient survival, we profiled the metabolomes of human gliomas and correlated metabolic information with clinical data. Results: We found that isocitrate dehydrogenase-wildtype (IDHwt) GBMs are metabolically distinguishable from IDH mutated (IDHmut) astrocytomas and oligodendrogliomas. Survival of patients with IDHmut gliomas was expectedly more favorable than those with IDHwt GBM, and metabolic signatures can stratify IDHwt GBMs subtypes with varying prognoses. Patients whose GBMs were enriched in amino acids had improved survival, while those whose tumors were enriched for nucleotides, redox molecules, and lipid metabolites fared more poorly. These findings were recapitulated in validation cohorts using both metabolomic and transcriptomic data. Innovation: Our results suggest the existence of metabolic subtypes of GBM with differing prognoses, and further support the concept that metabolism may drive the aggressiveness of human gliomas. Conclusions: Our data show that metabolic signatures of human gliomas can inform patient survival. These findings may be used clinically to tailor novel metabolically targeted agents for GBM patients with different metabolic phenotypes. Antioxid. Redox Signal. 39, 942-956.

Subclonal evolution and expansion of spatially distinct THY1-positive cells is associated with recurrence in glioblastoma.

PURPOSE: Glioblastoma(GBM) is a lethal disease characterized by inevitable recurrence. Here we investigate the molecular pathways mediating resistance, with the goal of identifying novel therapeutic opportunities. EXPERIMENTAL DESIGN: We developed a longitudinal in vivo recurrence model utilizing patient-derived explants to produce paired specimens(pre- and post-recurrence) following temozolomide(TMZ) and radiation(IR). These specimens were evaluated for treatment response and to identify gene expression pathways driving treatment resistance. Findings were clinically validated using spatial transcriptomics of human GBMs. RESULTS: These studies reveal in replicate cohorts, a gene expression profile characterized by upregulation of mesenchymal and stem-like genes at recurrence. Analyses of clinical databases revealed significant association of this transcriptional profile with worse overall survival and upregulation at recurrence. Notably, gene expression analyses identified upregulation of TGFß signaling, and more than one-hundred-fold increase in THY1 levels at recurrence. Furthermore, THY1-positive cells represented <10% of cells in treatment-naïve tumors, compared to 75-96% in recurrent tumors. We then isolated THY1-positive cells from treatment-naïve patient samples and determined that they were inherently resistant to chemoradiation in orthotopic models. Additionally, using image-guided biopsies from treatment-naïve human GBM, we conducted spatial transcriptomic analyses. This revealed rare THY1+ regions characterized by mesenchymal/stem-like gene expression, analogous to our recurrent mouse model, which co-localized with macrophages within the perivascular niche. We then inhibited TGFBRI activity in vivo which decreased mesenchymal/stem-like protein levels, including THY1, and restored sensitivity to TMZ/IR in recurrent tumors. CONCLUSIONS: These findings reveal that GBM recurrence may result from tumor repopulation by pre-existing, therapy-resistant, THY1-positive, mesenchymal cells within the perivascular niche.

Investigating Useful Features for Overall Survival Prediction in Patients with Low-Grade Glioma Using Histology Slides.

Glioma, characterized by neoplastic growth in the brain, is a life-threatening condition that, in most cases, ultimately leads to death. Typical analysis of glioma development involves observation of brain tissue in the form of a histology slide under a microscope. Although brain histology images have much potential for predicting patient outcomes such as overall survival (OS), they are rarely used as the sole predictors due challenges presented by unique characteristics of brain tissue histology. However, utilizing histology in predicting overall survival can be useful for treatment and quality-of-life for patients with early-stage glioma. In this study, we investigate the use of deep learning models on histology slides combined with simple descriptor data (age and glioma subtype) as a predictor of (OS) in patients with low-grade glioma (LGG). Using novel clinical data, we show that models which are more attentive to discriminative features of the image will confer better predictions than generic models (82.7 and 65.3 AUC RFD-Net and Baseline VGG16 model, respectively). Additionally, we show that adding age and subtype information to a histology image-based model may provide greater robustness in the model than using the image alone (3.8 and 4.3 stds for RFD-Net and Baseline VGG16 model with 3-fold CV, respectively), while a model based on image and age but not subtype may confer the best predictive results (83.7 and 82.0 AUC for RFD-Net + age and RFD-Net + age + subtype, respectively). Clinical relevance- This study establishes important criteria for deep learning models which predict OS using histology and basic clinical data from LGG patients.

H3.3-G34 mutations impair DNA repair and promote cGAS/STING-mediated immune responses in pediatric high-grade glioma models.

Pediatric high-grade gliomas (pHGGs) are the leading cause of cancer-related deaths in children in the USA. Sixteen percent of hemispheric pediatric and young adult HGGs encode Gly34Arg/Val substitutions in the histone H3.3 (H3.3-G34R/V). The mechanisms by which H3.3-G34R/V drive malignancy and therapeutic resistance in pHGGs remain unknown. Using a syngeneic, genetically engineered mouse model (GEMM) and human pHGG cells encoding H3.3-G34R, we demonstrate that this mutation led to the downregulation of DNA repair pathways. This resulted in enhanced susceptibility to DNA damage and inhibition of the DNA damage response (DDR). We demonstrate that genetic instability resulting from improper DNA repair in G34R-mutant pHGG led to the accumulation of extrachromosomal DNA, which activated the cyclic GMP-AMP synthase/stimulator of IFN genes (cGAS/STING) pathway, inducing the release of immune-stimulatory cytokines. We treated H3.3-G34R pHGG-bearing mice with a combination of radiotherapy (RT) and DNA damage response inhibitors (DDRi) (i.e., the blood-brain barrier-permeable PARP inhibitor pamiparib and the cell-cycle checkpoint CHK1/2 inhibitor AZD7762), and these combinations resulted in long-term survival for approximately 50% of the mice. Moreover, the addition of a STING agonist (diABZl) enhanced the therapeutic efficacy of these treatments. Long-term survivors developed immunological memory, preventing pHGG growth upon rechallenge. These results demonstrate that DDRi and STING agonists in combination with RT induced immune-mediated therapeutic efficacy in G34-mutant pHGG.

Epigenetically defined therapeutic targeting in H3.3G34R/V high-grade gliomas.

High-grade gliomas with arginine or valine substitutions of the histone H3.3 glycine-34 residue (H3.3G34R/V) carry a dismal prognosis, and current treatments, including radiotherapy and chemotherapy, are not curative. Because H3.3G34R/V mutations reprogram epigenetic modifications, we undertook a comprehensive epigenetic approach using ChIP sequencing and ChromHMM computational analysis to define therapeutic dependencies in H3.3G34R/V gliomas. Our analyses revealed a convergence of epigenetic alterations, including (i) activating epigenetic modifications on histone H3 lysine (K) residues such as H3K36 trimethylation (H3K36me3), H3K27 acetylation (H3K27ac), and H3K4 trimethylation (H3K4me3); (ii) DNA promoter hypomethylation; and (iii) redistribution of repressive histone H3K27 trimethylation (H3K27me3) to intergenic regions at the leukemia inhibitory factor (LIF) locus to drive increased LIF abundance and secretion by H3.3G34R/V cells. LIF activated signal transducer and activator of transcription 3 (STAT3) signaling in an autocrine/paracrine manner to promote survival of H3.3G34R/V glioma cells. Moreover, immunohistochemistry and single-cell RNA sequencing from H3.3G34R/V patient tumors revealed high STAT3 protein and RNA expression, respectively, in tumor cells with both inter- and intratumor heterogeneity. We targeted STAT3 using a blood-brain barrier­penetrable small-molecule inhibitor, WP1066, currently in clinical trials for adult gliomas. WP1066 treatment resulted in H3.3G34R/V tumor cell toxicity in vitro and tumor suppression in preclinical mouse models established with KNS42 cells, SJ-HGGx42-c cells, or in utero electroporation techniques. Our studies identify the LIF/STAT3 pathway as a key epigenetically driven and druggable vulnerability in H3.3G34R/V gliomas. This finding could inform development of targeted, combination therapies for these lethal brain tumors.

RNA-seq of human T cells after hematopoietic stem cell transplantation identifies Linc00402 as a regulator of T cell alloimmunity.

Mechanisms governing allogeneic T cell responses after solid organ and allogeneic hematopoietic stem cell transplantation (HSCT) are incompletely understood. To identify lncRNAs that regulate human donor T cells after clinical HSCT, we performed RNA sequencing on T cells from healthy individuals and donor T cells from three different groups of HSCT recipients that differed in their degree of major histocompatibility complex (MHC) mismatch. We found that lncRNA differential expression was greatest in T cells after MHC-mismatched HSCT relative to T cells after either MHC-matched or autologous HSCT. Differential expression was validated in an independent patient cohort and in mixed lymphocyte reactions using ex vivo healthy human T cells. We identified Linc00402, an uncharacterized lncRNA, among the lncRNAs differentially expressed between the mismatched unrelated and matched unrelated donor T cells. We found that Linc00402 was conserved and exhibited an 88-fold increase in human T cells relative to all other samples in the FANTOM5 database. Linc00402 was also increased in donor T cells from patients who underwent allogeneic cardiac transplantation and in murine T cells. Linc00402 was reduced in patients who subsequently developed acute graft-versus-host disease. Linc00402 enhanced the activity of ERK1 and ERK2, increased FOS nuclear accumulation, and augmented expression of interleukin-2 and Egr-1 after T cell receptor engagement. Functionally, Linc00402 augmented the T cell proliferative response to an allogeneic stimulus but not to a nominal ovalbumin peptide antigen or polyclonal anti-CD3/CD28 stimulus. Thus, our studies identified Linc00402 as a regulator of allogeneic T cell function.

Laser Interstitial Thermal Therapy for Glioblastoma: A Single-Center Experience.

BACKGROUND: Surgical resection has been shown to prolong survival in patients with glioblastoma multiforme (GBM), although this benefit has not been demonstrated for reoperation following tumor recurrence. Laser interstitial thermal therapy (LITT) is a minimally invasive ablation technique that has been shown to effectively reduce tumor burden in some patients with intracranial malignancy. The aim of this study was to describe the safety and efficacy of LITT for recurrent and newly diagnosed GBM at a large tertiary referral center. METHODS: Patients with GBM receiving LITT were retrospectively analyzed. Overall survival from the time of LITT was the primary end point measured. RESULTS: There were 69 patients identified for inclusion in this study. The median age of the cohort was 56 years (range, 15-77 years). Median tumor volume was 10.4 cm3 (range, 1.0-64.0 cm3). A Kaplan-Meier estimate of median overall survival for the series from the time of LITT was 12 months (95% confidence interval 8-16 months). Median progression-free survival for the cohort from LITT was 4 months (95% confidence interval 3-7 months). Adjuvant chemotherapy significantly prolonged progression-free survival and overall survival (P < 0.01 for both) in the cohort. Gross total ablation was not significantly associated with progression-free survival (P = 0.09). CONCLUSIONS: LITT can safely reduce intracranial tumor burden in patients with GBM who have exhausted other adjuvant therapies or are poor candidates for conventional resection techniques.

Computational Drug Repositioning Identifies Potentially Active Therapies for Chordoma.

BACKGROUND: Chordomas are aggressive bone tumors that often recur despite maximal resection and adjuvant radiation. To date there are no Food and Drug Administration (FDA)-approved chemotherapies. Computational drug repositioning is an expanding approach to identify pharmacotherapies for clinical trials. OBJECTIVE: To identify FDA-approved compounds for repurposing in chordoma. METHODS: Previously identified highly differentially expressed genes from chordoma tissue samples at our institution were compared with pharmacogenomic interactions in the Comparative Toxicogenomics Database (CTD) using ksRepo, a drug-repositioning platform. Compounds selected by ksRepo were then validated in CH22 and UM-Chor1 human chordoma cells in Vitro. RESULTS: A total of 13 chemical compounds were identified in silico from the CTD, and 6 were selected for preclinical validation in human chordoma cell lines based on their clinical relevance. Of these, 3 identified drugs are FDA-approved chemotherapies for other malignancies (cisplatin, cytarabine, and lucanthone). Cytarabine, a deoxyribonucleic acid polymerase inhibitor approved for the treatment of various leukemias, exhibited a significant concentration-dependent effect against CH22 and UM-Chor1 cells when compared to positive (THZ1) and negative (venetoclax) controls. Tretinoin exhibited a significant concentration-dependent cytotoxic effect in CH22, sacral chordoma-derived cell lines but to a much lesser extent in UM-Chor1, a cell line derived from skull base chordoma. CONCLUSION: Cytarabine administration reduces the viability of human chordoma cells. The equally effective reduction in viability seen with tretinoin seems to be cell line dependent. Based on our findings, we recommend the evaluation of cytarabine and tretinoin in an expanded set of human chordoma cell lines and animal models.

Mature myelin maintenance requires Qki to coactivate PPARß-RXRα-mediated lipid metabolism.

Lipid-rich myelin forms electrically insulating, axon-wrapping multilayers that are essential for neural function, and mature myelin is traditionally considered metabolically inert. Surprisingly, we discovered that mature myelin lipids undergo rapid turnover, and quaking (Qki) is a major regulator of myelin lipid homeostasis. Oligodendrocyte-specific Qki depletion, without affecting oligodendrocyte survival, resulted in rapid demyelination, within 1 week, and gradually neurological deficits in adult mice. Myelin lipids, especially the monounsaturated fatty acids and very-long-chain fatty acids, were dramatically reduced by Qki depletion, whereas the major myelin proteins remained intact, and the demyelinating phenotypes of Qki-depleted mice were alleviated by a high-fat diet. Mechanistically, Qki serves as a coactivator of the PPARß-RXRα complex, which controls the transcription of lipid-metabolism genes, particularly those involved in fatty acid desaturation and elongation. Treatment of Qki-depleted mice with PPARß/RXR agonists significantly alleviated neurological disability and extended survival durations. Furthermore, a subset of lesions from patients with primary progressive multiple sclerosis were characterized by preferential reductions in myelin lipid contents, activities of various lipid metabolism pathways, and expression level of QKI-5 in human oligodendrocytes. Together, our results demonstrate that continuous lipid synthesis is indispensable for mature myelin maintenance and highlight an underappreciated role of lipid metabolism in demyelinating diseases.

Engineered 3D Model of Cancer Stem Cell Enrichment and Chemoresistance.

Intraperitoneal dissemination of ovarian cancers is preceded by the development of chemoresistant tumors with malignant ascites. Despite the high levels of chemoresistance and relapse observed in ovarian cancers, there are no in vitro models to understand the development of chemoresistance in situ. METHOD: We describe a highly integrated approach to establish an in vitro model of chemoresistance and stemness in ovarian cancer, using the 3D hanging drop spheroid platform. The model was established by serially passaging non-adherent spheroids. At each passage, the effectiveness of the model was evaluated via measures of proliferation, response to treatment with cisplatin and a novel ALDH1A inhibitor. Concomitantly, the expression and tumor initiating capacity of cancer stem-like cells (CSCs) was analyzed. RNA-seq was used to establish gene signatures associated with the evolution of tumorigenicity, and chemoresistance. Lastly, a mathematical model was developed to predict the emergence of CSCs during serial passaging of ovarian cancer spheroids. RESULTS: Our serial passage model demonstrated increased cellular proliferation, enriched CSCs, and emergence of a platinum resistant phenotype. In vivo tumor xenograft assays indicated that later passage spheroids were significantly more tumorigenic with higher CSCs, compared to early passage spheroids. RNA-seq revealed several gene signatures supporting the emergence of CSCs, chemoresistance, and malignant phenotypes, with links to poor clinical prognosis. Our mathematical model predicted the emergence of CSC populations within serially passaged spheroids, concurring with experimentally observed data. CONCLUSION: Our integrated approach illustrates the utility of the serial passage spheroid model for examining the emergence and development of chemoresistance in ovarian cancer in a controllable and reproducible format.

A Pan-Cancer Analysis Reveals High-Frequency Genetic Alterations in Mediators of Signaling by the TGF-ß Superfamily.

We present an integromic analysis of gene alterations that modulate transforming growth factor ß (TGF-ß)-Smad-mediated signaling in 9,125 tumor samples across 33 cancer types in The Cancer Genome Atlas (TCGA). Focusing on genes that encode mediators and regulators of TGF-ß signaling, we found at least one genomic alteration (mutation, homozygous deletion, or amplification) in 39% of samples, with highest frequencies in gastrointestinal cancers. We identified mutation hotspots in genes that encode TGF-ß ligands (BMP5), receptors (TGFBR2, AVCR2A, and BMPR2), and Smads (SMAD2 and SMAD4). Alterations in the TGF-ß superfamily correlated positively with expression of metastasis-associated genes and with decreased survival. Correlation analyses showed the contributions of mutation, amplification, deletion, DNA methylation, and miRNA expression to transcriptional activity of TGF-ß signaling in each cancer type. This study provides a broad molecular perspective relevant for future functional and therapeutic studies of the diverse cancer pathways mediated by the TGF-ß superfamily.

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers.

We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories.

High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma.

BACKGROUND: Imaging features derived from MRI scans can be used for not only breast cancer detection and measuring disease extent, but can also determine gene expression and patient outcomes. The relationships between imaging features, gene/protein expression, and response to therapy hold potential to guide personalized medicine. We aim to characterize the relationship between radiologist-annotated tumor phenotypic features (based on MRI) and the underlying biological processes (based on proteomic profiling) in the tumor. METHODS: Multiple-response regression of the image-derived, radiologist-scored features with reverse-phase protein array expression levels generated association coefficients for each combination of image-feature and protein in the RPPA dataset. Significantly-associated proteins for features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis determined which features were most strongly correlated with pathway activity and cellular functions. RESULTS: Each of the twenty-nine imaging features was found to have a set of significantly correlated molecules, associated biological functions, and pathways. CONCLUSIONS: We interrogated the pathway alterations represented by the protein expression associated with each imaging feature. Our study demonstrates the relationships between biological processes (via proteomic measurements) and MRI features within breast tumors.

Salmonella escapes antigen presentation through K63 ubiquitination mediated endosomal proteolysis of MHC II via modulation of endosomal acidification in dendritic cells.

CD4+ T-cell response is vital for successful clearance of Salmonella Typhimurium infection. Efficient antigen presentation is crucial for effective CD4+ T-cell response. Previous study has reported that Salmonella abrogates antigen presentation capacity of dendritic cells in order to escape host adaptive immune response. In this study, we have elucidated the mechanism of Salmonella-mediated downregulation of the total cellular Major Histocompatibility Complex (MHC) II pool in dendritic cells. Infected dendritic cells show upregulation of E3 ubiquitin ligase, MARCH1 expression and K63-linked ubiquitination of MHC II. Salmonella infection also enhances the internalisation of ubiquitin-tagged MHC II molecules that are subsequently degraded by endosomal proteases. In addition, Salmonella regulates the activation of endosomal proteases by lowering the pH of endosomes. In infected dendritic cells, Salmonella delays NOX2 recruitment to the phagosomes thereby preventing its alkalinisation. NOX2 is a significant part of innate immune response against pathogens as it is responsible for Reactive Oxygen Species (ROS) production. In this study, we have demonstrated how Salmonella evades MHC II-mediated adaptive immune response in dendritic cells through enhanced endosomal proteolysis. To escape host CD4+T response, Salmonella delays NOX2 recruitment, an innate immune response element to the phagosomes.

Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma.

BACKGROUND AND PURPOSE: Lower grade gliomas (LGGs), lesions of WHO grades II and III, comprise 10-15% of primary brain tumors. In this first-of-a-kind study, we aim to carry out a radioproteomic characterization of LGGs using proteomics data from the TCGA and imaging data from the TCIA cohorts, to obtain an association between tumor MRI characteristics and protein measurements. The availability of linked imaging and molecular data permits the assessment of relationships between tumor genomic/proteomic measurements with phenotypic features. MATERIALS AND METHODS: Multiple-response regression of the image-derived, radiologist scored features with reverse-phase protein array (RPPA) expression levels generated correlation coefficients for each combination of image-feature and protein or phospho-protein in the RPPA dataset. Significantly-associated proteins for VASARI features were analyzed with Ingenuity Pathway Analysis software. Hierarchical clustering of the results of the pathway analysis was used to determine which feature groups were most strongly correlated with pathway activity and cellular functions. RESULTS: The multiple-response regression approach identified multiple proteins associated with each VASARI imaging feature. VASARI features were found to be correlated with expression of IL8, PTEN, PI3K/Akt, Neuregulin, ERK/MAPK, p70S6K and EGF signaling pathways. CONCLUSION: Radioproteomics analysis might enable an insight into the phenotypic consequences of molecular aberrations in LGGs.