Abstract B08: AB598, a therapeutic anti-CD39 antibody, elevates ATP and increases immunogenicity in the tumor microenvironment

AB598, an IgG1 Fc-silent antibody that blocks CD39 (ENTPD1) enzymatic activity, is being developed as a novel cancer immunotherapy. CD39 is highly expressed on immune and stromal cells within the tumor microenvironment (TME) and is responsible for the conversion of adenosine triphosphate (ATP) into adenosine monophosphate (AMP). AB598 can bind and inhibit CD39 activity on primary human immune cells, leading to an increase in local levels of immunostimulatory ATP. In the TME, elevated ATP exerts its effects by signaling through the purinergic family of P2X and P2Y receptors. Using a combined approach of nanostring profiling of myeloid cell subsets derived from healthy donors, flow cytometry on healthy human peripheral blood, and bioinformatic analysis of the MET500 and TCGA databases, we define a profile of relevant receptors that can act as effectors to promote anti-tumor responses upon CD39 inhibition. Nanostring and flow cytometry show CD39 and P2X7 are ubiquitously expressed across the myeloid cell lineage. P2RX7, CASP1, and GSDMD gene expression is highest in M1 macrophages, a finding corroborated by the boost in inflammasome activation seen on in vitro-derived macrophages with AB598 treatment. P2RY11 gene expression shows a bimodal distribution with the highest expression in monocyte-derived dendritic cells (moDCs) and M2 macrophages, a finding that supports previously published work identifying P2Y11 as the receptor responsible for ATP-induced maturation of moDCs. Using CD83 and CD86 as markers, we show that AB598 enhances ATP-induced moDC activation in a concentration-dependent manner. Supportive of the broad expression of CD39 on myeloid cell subsets, analysis of TCGA data shows an inverse correlation of ENTPD1 gene expression and tumor purity. ENTPD1 expression is positively correlated with P2RX7, NLRP3, ITGAM (CD11b), and ITGAX (CD11c) expression, establishing the presence of the machinery for AB598 inhibition of CD39 to promote myeloid cell activation in the TME. Clinically, immunostimulation in the TME can be achieved by the administration of an immunogenic cell death (ICD)-inducing chemotherapy capable of releasing ATP; however, the ATP can be degraded by CD39. Using continuous ATP monitoring, we show that AB598 treatment increases and maintains the pool of extracellular ATP from human cancer cell lines treated with ICD-inducing agents. Our results demonstrate that the TME has the machinery to respond to an environment rich in immunostimulatory ATP, common chemotherapeutic agents can cause tumor cells to release ATP extracellularly, and AB598 can effect immunogenic change through inflammasome activation and dendritic cell maturation when ATP is present in the TME. Overall, the findings presented here establish AB598 as a promising agent targeting CD39 for cancer immunotherapy and provide a rationale for the combination of AB598 with ICD-inducing chemotherapy in the clinic.

Citation Format: Kaustubh Parashar, Julie Clor, Dana Piovesan, Casey Mitchell, LC Stetson, Ke Jin, Gonzalo Barajas, Sean Cho, Janine Kline, Stephen W. Young, Nigel P. Walker, Matthew J. Walters, Ester Fernandez-Salas, Christine E. Bowman. AB598, a therapeutic anti-CD39 antibody, elevates ATP and increases immunogenicity in the tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr B08.

Inflammatory Bowel Disease Risk Variants Are Associated with an Increased Risk of Skin Cancer

BACKGROUND

Inflammatory bowel disease is associated with an increased risk of skin cancer. The aims of this study were to determine whether IBD susceptibility variants are also associated with skin cancer susceptibility and if such risk is augmented by use of immune-suppressive therapy.

METHODS

The discovery cohort included participants in the UK Biobank. The validation cohort included participants in the Michigan Genomics Initiative. The primary outcome of interest was skin cancer, subgrouped into nonmelanoma skin cancers (NMSC) and melanoma skin cancers (MSC). Multivariable logistic regression with matched controls (3 controls:1 case) was performed to identify genomic predictors of skin malignancy in the discovery cohort. Variants with P < .05 were tested for replication in the validation cohort. Validated Single nucleotide polymorphisms were then evaluated for effect modification by immune-suppressive medications.

RESULTS

The discovery cohort included 10,247 cases of NMSC and 1883 cases of MSC. The validation cohort included 7334 cases of NMSC and 3304 cases of MSC. Twenty-nine variants were associated with risk of NMSC in the discovery cohort, of which 5 replicated in the validation cohort (increased risk, rs7773324-A [DUSP22; IRF4], rs2476601-G [PTPN22], rs1847472-C [BACH2], rs72810983-A [CPEB4]; decreased risk, rs6088765-G [PROCR; MMP24]). Twelve variants were associated with risk of MSC in the discovery cohort, of which 4 were replicated in the validation cohort (increased risk, rs61839660-T [IL2RA]; decreased risk, rs17391694-C [GIPC2; MGC27382], rs6088765-G [PROCR; MMP24], and rs1728785-C [ZFP90]). No effect modification was observed.

CONCLUSIONS

The results of this study highlight shared genetic susceptibility across IBD and skin cancer, with increased risk of NMSC in those who carry risk variants in IRF4, PTPN22, CPEB4, and BACH2 and increased risk of MSC in those who carry a risk variant in IL2RA.

Single cell RNA sequencing of AML initiating cells reveals RNA-based evolution during disease progression

The prognosis of most patients with AML is poor due to frequent disease relapse. The cause of relapse is thought to be from the persistence of leukemia initiating cells (LIC's) following treatment. Here we assessed RNA based changes in LICs from matched patient diagnosis and relapse samples using single-cell RNA sequencing. Previous studies on AML progression have focused on genetic changes at the DNA mutation level mostly in bulk AML cells and demonstrated the existence of DNA clonal evolution. Here we identified in LICs that the phenomenon of RNA clonal evolution occurs during AML progression. Despite the presence of vast transcriptional heterogeneity at the single cell level, pathway analysis identified common signaling networks involving metabolism, apoptosis and chemokine signaling that evolved during AML progression and become a signature of relapse samples. A subset of this gene signature was validated at the protein level in LICs by flow cytometry from an independent AML cohort and functional studies were performed to demonstrate co-targeting BCL2 and CXCR4 signaling may help overcome therapeutic challenges with AML heterogeneity. It is hoped this work will facilitate a greater understanding of AML relapse leading to improved prognostic biomarkers and therapeutic strategies to target LIC's.

A Noncoding Variant Near PPP1R3B Promotes Liver Glycogen Storage and MetS, but Protects Against Myocardial Infarction

CONTEXT

Glycogen storage diseases are rare. Increased glycogen in the liver results in increased attenuation.

OBJECTIVE

Investigate the association and function of a noncoding region associated with liver attenuation but not histologic nonalcoholic fatty liver disease.

DESIGN

Genetics of Obesity-associated Liver Disease Consortium.

SETTING

Population-based.

MAIN OUTCOME

Computed tomography measured liver attenuation.

RESULTS

Carriers of rs4841132-A (frequency 2%-19%) do not show increased hepatic steatosis; they have increased liver attenuation indicative of increased glycogen deposition. rs4841132 falls in a noncoding RNA LOC157273 ~190 kb upstream of PPP1R3B. We demonstrate that rs4841132-A increases PPP1R3B through a cis genetic effect. Using CRISPR/Cas9 we engineered a 105-bp deletion including rs4841132-A in human hepatocarcinoma cells that increases PPP1R3B, decreases LOC157273, and increases glycogen perfectly mirroring the human disease. Overexpression of PPP1R3B or knockdown of LOC157273 increased glycogen but did not result in decreased LOC157273 or increased PPP1R3B, respectively, suggesting that the effects may not all occur via affecting RNA levels. Based on electronic health record (EHR) data, rs4841132-A associates with all components of the metabolic syndrome (MetS). However, rs4841132-A associated with decreased low-density lipoprotein (LDL) cholesterol and risk for myocardial infarction (MI). A metabolic signature for rs4841132-A includes increased glycine, lactate, triglycerides, and decreased acetoacetate and beta-hydroxybutyrate.

CONCLUSIONS

These results show that rs4841132-A promotes a hepatic glycogen storage disease by increasing PPP1R3B and decreasing LOC157273. rs4841132-A promotes glycogen accumulation and development of MetS but lowers LDL cholesterol and risk for MI. These results suggest that elevated hepatic glycogen is one cause of MetS that does not invariably promote MI.

Sexually dimorphic impact of the iron-regulating gene, HFE, on survival in glioblastoma

Background

The median survival for patients with glioblastoma (GBM), the most common primary malignant brain tumor in adults, has remained approximately 1 year for more than 2 decades. Recent advances in the field have identified GBM as a sexually dimorphic disease. It is less prevalent in females and they have better survival compared to males. The molecular mechanism of this difference has not yet been established. Iron is essential for many biological processes supporting tumor growth and its regulation is impacted by sex. Therefore, we interrogated the expression of a key component of cellular iron regulation, the HFE (homeostatic iron regulatory) gene, on sexually dimorphic survival in GBM.

Methods

We analyzed TCGA microarray gene expression and clinical data of all primary GBM patients (IDH-wild type) to compare tumor mRNA expression of HFE with overall survival, stratified by sex.

Results

In low HFE expressing tumors (below median expression, n = 220), survival is modulated by both sex and MGMT status, with the combination of female sex and MGMT methylation resulting in over a 10-month survival advantage (P < .0001) over the other groups. Alternatively, expression of HFE above the median (high HFE, n = 240) is associated with significantly worse overall survival in GBM, regardless of MGMT methylation status or patient sex. Gene expression analysis uncovered a correlation between high HFE expression and expression of genes associated with immune function.

Conclusions

The level of HFE expression in GBM has a sexually dimorphic impact on survival. Whereas HFE expression below the median imparts a survival benefit to females, high HFE expression is associated with significantly worse overall survival regardless of established prognostic factors such as sex or MGMT methylation.

Gliomas display distinct sex-based differential methylation patterns based on molecular subtype

Background

Gliomas are the most common type of primary brain tumor and one of many cancers where males are diagnosed with greater frequency than females. However, little is known about the sex-based molecular differences in glioblastomas (GBMs) or lower grade glioma (non-GBM) subtypes. DNA methylation is an epigenetic mechanism involved in regulating gene transcription. In glioma and other cancers, hypermethylation of specific gene promoters downregulates transcription and may have a profound effect on patient outcome. The purpose of this study was to determine if sex-based methylation differences exist in different glioma subtypes.

Methods

Molecular and clinical data from glioma patients were obtained from The Cancer Genome Atlas and grouped according to tumor grade and molecular subtype (IDH1/2 mutation and 1p/19q chromosomal deletion). Sex-specific differentially methylated probes (DMPs) were identified in each subtype and further analyzed to determine if they were part of differentially methylated regions (DMRs) or associated with differentially methylated DNA transcription regulatory binding motifs.

Results

Analysis of methylation data in 4 glioma subtypes revealed unique sets of both sex-specific DMPs and DMRs in each subtype. Motif analysis based on DMP position also identified distinct sex-based sets of DNA-binding motifs that varied according to glioma subtype. Downstream targets of 2 of the GBM-specific transcription binding sites, NFAT5 and KLF6, showed differential gene expression consistent with increased methylation mediating downregulation.

Conclusion

DNA methylation differences between males and females in 4 glioma molecular subtypes suggest an important, sex-specific role for DNA methylation in epigenetic regulation of gliomagenesis.

Proteins inform survival-based differences in patients with glioblastoma

BACKGROUND

Improving the care of patients with glioblastoma (GB) requires accurate and reliable predictors of patient prognosis. Unfortunately, while protein markers are an effective readout of cellular function, proteomics has been underutilized in GB prognostic marker discovery.

METHODS

For this study, GB patients were prospectively recruited and proteomics discovery using liquid chromatography-mass spectrometry analysis (LC-MS/MS) was performed for 27 patients including 13 short-term survivors (STS) (≤10 months) and 14 long-term survivors (LTS) (≥18 months).

RESULTS

Proteomics discovery identified 11 941 peptides in 2495 unique proteins, with 469 proteins exhibiting significant dysregulation when comparing STS to LTS. We verified the differential abundance of 67 out of these 469 proteins in a small previously published independent dataset. Proteins involved in axon guidance were upregulated in STS compared to LTS, while those involved in p53 signaling were upregulated in LTS. We also assessed the correlation between LS MS/MS data with RNAseq data from the same discovery patients and found a low correlation between protein abundance and mRNA expression. Finally, using LC-MS/MS on a set of 18 samples from 6 patients, we quantified the intratumoral heterogeneity of more than 2256 proteins in the multisample dataset.

CONCLUSIONS

These proteomic datasets and noted protein variations present a beneficial resource for better predicting patient outcome and investigating potential therapeutic targets.

Sex is an important prognostic factor for glioblastoma but not for nonglioblastoma

Background

Glioblastoma (GBM) is the most common and most malignant glioma. Nonglioblastoma (non-GBM) gliomas (WHO Grades II and III) are invasive and also often fatal. The goal of this study is to determine whether sex differences exist in glioma survival.

Methods

Data were obtained from the National Cancer Database (NCDB) for years 2010 to 2014. GBM (WHO Grade IV; N = 2073) and non-GBM (WHO Grades II and III; N = 2963) were defined using the histology grouping of the Central Brain Tumor Registry of the United States. Non-GBM was divided into oligodendrogliomas/mixed gliomas and astrocytomas. Sex differences in survival were analyzed using Kaplan-Meier and multivariable Cox proportional hazards models adjusted for known prognostic variables.

Results

There was a female survival advantage in patients with GBM both in the unadjusted (P = .048) and adjusted (P = .003) models. Unadjusted, median survival was 20.1 months (95% CI: 18.7-21.3 months) for women and 17.8 months (95% CI: 16.9-18.7 months) for men. Adjusted, median survival was 20.4 months (95% CI: 18.9-21.6 months) for women and 17.5 months (95% CI: 16.7-18.3 months) for men. When stratifying by age group (18-55 vs 56+ years at diagnosis), this female survival advantage appeared only in the older group, adjusting for covariates (P = .017). Women (44.1%) had a higher proportion of methylated MGMT (O⁶-methylguanine-DNA methyltransferase) than men (38.4%). No sex differences were found for non-GBM.

Conclusions

Using the NCDB data, there was a statistically significant female survival advantage in GBM, but not in non-GBM.

Abstract 4220: Heterogeneous distribution of prognostic protein markers in glioblastoma

Background: Glioblastoma (GBM) is the most common and lethal primary malignant brain tumor in adults. The heterogeneity of the disease leads to significant variability in response to standard therapy (surgery plus concurrent radiation and temozolomide). An accurate and reliable predictor of patient prognosis represents an unmet need to improve the care of GBM patients. While protein markers are an effective readout of cellular function, proteomics has rarely been utilized in GBM prognostic marker discovery. Experimental Procedures: GBM patients were prospectively recruited (Ohio Brain Tumor Study) and proteomics discovery using liquid chromatography mass spectrometry analysis (LC MS/MS) was performed in a discovery set of 27 patients including 13 short-term survivors (&lt; 9 months, STS) and 14 long-term survivors (&gt;= 18 months, LTS). Statistically significant proteins were evaluated in two independent datasets, including in18 samples micro-dissected from multiple tumor areas of 6 GBM patients. Results: Proteomics discovery identified 11,941 peptides in 2,495 unique proteins, with 172 proteins exhibiting significant dysregulation when comparing STS and LTS. Proteins involved in glycolysis/TCA cycle were up-regulated in STS compared to LTS by examination of individual targets as well as upon application of a novel protein and peptide pathway enrichment analysis. Validation of these dysregulated proteins and other protein markers from the literature in our first validation set (18 samples micro-dissected from n=6 patients) demonstrated that they were very unevenly distributed throughout individual patients' tumors. Several proteins overcame the heterogeneous nature of the tumors and were both prognostic markers differentially expressed between LTS and STS, as well as potential drug targets owing to their even distribution throughout the tumor. Protein abundance of significant marker proteins were verified in a second independent validation set using Western immunoblots. Conclusion: The current study verified the importance of metabolism in GBM pathology and demonstrated the heterogeneous nature of GBMs at the protein level.

Citation Format: Lindsay C. Stetson, Quinn T. Ostrom, Peter Liao, Andrew E. Sloan, Mark R. Chance, Jill S. Barnholtz-Sloan. Heterogeneous distribution of prognostic protein markers in glioblastoma [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 4220.

Abstract 780: Multi-omic profiling of gliomas reveals distinct DNA methylation changes at tumor recurrence

Varying possibilities of tumor relapse for lower grade glioma (LGG, WHO grade II and III) and glioblastoma (GBM, WHO grade IV) have led to heterogenous clinical outcomes for patients. Our current study aims to establish a molecular profile of recurrence of matched primary and recurrent LGG (n = 28) and recurrent GBM (n = 24) tumor samples. The Cancer Genome Atlas (TCGA) has comprehensively profiled these matched primary/recurrent tumor sets; whole genomes, coding exomes, methylomes, and transcriptomes have been sequenced, and the samples have undergone targeted profiling of the proteome. While unsupervised analysis techniques have not led to a clear recurrence signature, supervised analysis methods have revealed interesting patterns. Protein profiling has shown that recurrent gliomas retain the overall molecular signature of their primary counterpart, but the DNA damage response, apoptosis and RTK pathways are downregulated in the recurrent gliomas, in contrast to RAS/MAPK, PI3K/AKT, and EMT pathways, which are upregulated. Whole genome sequencing and rearrangement analysis have revealed increased genomic complexity among most recurrent gliomas as well as new fusions of interest in recurrent LGG samples (PTPRZ1-MET and involving ATRX). Using genome-wide Illumina HumanMethylation 450K data we observed that 78.6% of LGGs showed depletion of DNA methylation at recurrence and 50% of GBM tumors showed an enrichment of DNA methylation at recurrence. Patient centric enrichment analysis allowed us to discover a candidate biological subgroup characterized by a subset of LGG recurrences (50%) exhibiting an aberrant CpG methylation loss at inintergenic opensea regions when compared with canonical CpG islands and shores (fold &gt; 1.3 and confidence intervals of 99%). Importantly, inspection of CpG sites significantly hypomethylated at openseas showed that this pronounced epigenetic signature maps to candidate TSS distal and hypomethylated enhancers. The gene-targets of these hypomethylated CpG sites show a corresponding up-regulation of expression. Pathway analysis has demonstrated that these upregulated genes are involved in cellular growth and proliferation, cellular function and maintenance, and cell cycle regulation. Our results provide evidence that DNA methylation may represent a stable signature of glioma recurrence and that the crosstalk between DNA hypomethylation at openseas and chromosomal instability may be involved in glioma recurrence. We plan to further integrate our findings between data types and correlate with treatment and patient clinical outcome.

Citation Format: Lindsay C. Stetson, Camila Ferreira de Souza, Tathiane Maistro Malta, Thais Sarraf Sabedot, Quinn Ostrom, Peter Liao, Daniela Pretti da Cunha Tirapelli, Luciano Neder, Carlos Gilberto Carlotti, Rehan Akbani, Sofie Salama, Laila Poisson, Daniel Brat, The Cancer Genome Atlas Network, Houtan Noushmehr, Jill Barnholtz-Sloan. Multi-omic profiling of gliomas reveals distinct DNA methylation changes at tumor recurrence. [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 780.

Protein Markers Predict Survival in Glioma Patients

Glioblastoma multiforme (GBM) is a genomically complex and aggressive primary adult brain tumor, with a median survival time of 12-14 months. The heterogeneous nature of this disease has made the identification and validation of prognostic biomarkers difficult. Using reverse phase protein array data from 203 primary untreated GBM patients, we have identified a set of 13 proteins with prognostic significance. Our protein signature predictive of glioblastoma (PROTGLIO) patient survival model was constructed and validated on independent data sets and was shown to significantly predict survival in GBM patients (log-rank test: p = 0.0009). Using a multivariate Cox proportional hazards, we have shown that our PROTGLIO model is distinct from other known GBM prognostic factors (age at diagnosis, extent of surgical resection, postoperative Karnofsky performance score (KPS), treatment with temozolomide (TMZ) chemoradiation, and methylation of the MGMT gene). Tenfold cross-validation repetition of our model generation procedure confirmed validation of PROTGLIO. The model was further validated on an independent set of isocitrate dehydrogenase wild-type (IDHwt) lower grade gliomas (LGG)-a portion of these tumors progress rapidly to GBM. The PROTGLIO model contains proteins, such as Cox-2 and Annexin 1, involved in inflammatory response, pointing to potential therapeutic interventions. The PROTGLIO model is a simple and effective predictor of overall survival in glioblastoma patients, making it potentially useful in clinical practice of glioblastoma multiforme.

Computational identification of multi-omic correlates of anticancer therapeutic response

Background

A challenge in precision medicine is the transformation of genomic data into knowledge that can be used to stratify patients into treatment groups based on predicted clinical response. Although clinical trials remain the only way to truly measure drug toxicities and effectiveness, as a scientific community we lack the resources to clinically assess all drugs presently under development. Therefore, an effective preclinical model system that enables prediction of anticancer drug response could significantly speed the broader adoption of personalized medicine.

Results

Three large-scale pharmacogenomic studies have screened anticancer compounds in greater than 1000 distinct human cancer cell lines. We combined these datasets to generate and validate multi-omic predictors of drug response. We compared drug response signatures built using a penalized linear regression model and two non-linear machine learning techniques, random forest and support vector machine. The precision and robustness of each drug response signature was assessed using cross-validation across three independent datasets. Fifteen drugs were common among the datasets. We validated prediction signatures for eleven out of fifteen tested drugs (17-AAG, AZD0530, AZD6244, Erlotinib, Lapatinib, Nultin-3, Paclitaxel, PD0325901, PD0332991, PF02341066, and PLX4720).

Conclusions

Multi-omic predictors of drug response can be generated and validated for many drugs. Specifically, the random forest algorithm generated more precise and robust prediction signatures when compared to support vector machines and the more commonly used elastic net regression. The resulting drug response signatures can be used to stratify patients into treatment groups based on their individual tumor biology, with two major benefits: speeding the process of bringing preclinical drugs to market, and the repurposing and repositioning of existing anticancer therapies.

Abstract 297: Protein markers predict overall survival in glioblastoma multiforme

Unrealized needs in the care of patients diagnosed with primary glioblastoma multiforme (GBM) are accurate and clinically relevant predictors of patient prognosis. Patients receiving standard therapy (surgery plus concurrent radiation and temozolomide) have variable clinical outcomes. Available prognostic indicators such as MGMT DNA methylation, IDH1 mutation, and the G-CIMP phenotype are only relevant for a small proportion of those diagnosed with primary GBM. Protein markers of GBM prognosis would not only provide a potential route for classifying and stratifying patients into treatment groups they could also provide an opportunity to identify potential novel drug targets. In this study, using reverse-phase protein array data from Cancer Genome Atlas (TCGA) GBMs, we have constructed and validated a PROTein signature predictive of GLIOblastoma survival (PROTGLIO).

Using L1 penalized cox regression, we have identified six protein markers most associated with overall survival in a training set of 107 TCGA GBMs. Three proteins (annexin, cox-2, and FOX03) were associated with shorter overall survival, and three proteins (phosphorylated RPS6KA1, phosphorylated RB1, and TGM2) were associated with longer overall survival. PROTGLIO scores were defined as a linear combination of protein expression levels of the six proteins and the associated Cox regression coefficients, where a higher score indicates a worse prognosis. Based on PROTGLIO scores cases were classified into high and low risk groups. Kaplan-Meier survival analysis showed a significant difference (p = 0.01) in overall survival between the high and low risk groups in our training set. The performance of the PROTGLIO score was validated in a testing set, which consisted of 107 TCGA cases not included in the training set. In the validation set there was a significant difference in overall survival between the high and low risk groups (p = 0.02). We have verified that our signature is independent of known prognostic variables such as age, treatment pattern, and molecular subtype by applying multivariate analysis using a Cox proportional hazard model.

The annexin family of proteins has been previously associated with glioma migration and growth and the cox-2 protein has been reported as a marker of poor prognosis among diffuse glioma patients. Our work points to these proteins, along with FOX03, as being negative prognosticators for GBMs and potential avenues for therapeutic intervention. Additionally, we report on the protective effects of phosphorylated RB1 expression, which is supported by previous studies recommending clinical stratification of patients based on RB1 alterations. Further work is needed to elucidate the protective mechanisms of RPS6KA1 and TGM2.

Note: This abstract was not presented at the meeting.

Citation Format: Lindsay C. Stetson, Jill S. Barnholtz-Sloan. Protein markers predict overall survival in glioblastoma multiforme. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 297. doi:10.1158/1538-7445.AM2014-297