Modeling the sequence dependence of differential antibody binding in the immune response to infectious disease

Past studies have shown that incubation of human serum samples on high density peptide arrays followed by measurement of total antibody bound to each peptide sequence allows detection and discrimination of humoral immune responses to a variety of infectious diseases. This is true even though these arrays consist of peptides with near-random amino acid sequences that were not designed to mimic biological antigens. This "immunosignature" approach, is based on a statistical evaluation of the binding pattern for each sample but it ignores the information contained in the amino acid sequences that the antibodies are binding to. Here, similar array-based antibody profiles are instead used to train a neural network to model the sequence dependence of molecular recognition involved in the immune response of each sample. The binding profiles used resulted from incubating serum from 5 infectious disease cohorts (Hepatitis B and C, Dengue Fever, West Nile Virus and Chagas disease) and an uninfected cohort with 122,926 peptide sequences on an array. These sequences were selected quasi-randomly to represent an even but sparse sample of the entire possible combinatorial sequence space (~1012). This very sparse sampling of combinatorial sequence space was sufficient to capture a statistically accurate representation of the humoral immune response across the entire space. Processing array data using the neural network not only captures the disease-specific sequence-binding information but aggregates binding information with respect to sequence, removing sequence-independent noise and improving the accuracy of array-based classification of disease compared with the raw binding data. Because the neural network model is trained on all samples simultaneously, a highly condensed representation of the differential information between samples resides in the output layer of the model, and the column vectors from this layer can be used to represent each sample for classification or unsupervised clustering applications.

Alpha-methylacyl-CoA racemase (AMACR) protein is upregulated in early proliferative lesions of the breast irrespective of apocrine differentiation

Alpha-methylacyl-CoA racemase (AMACR/P504S) is a mitochondrial and peroxisomal enzyme involved in the branched-chain fatty acid and bile acid metabolism. AMACR is a useful diagnostic biomarker for prostate carcinomas and several other malignancies. Its expression in apocrine breast lesions had been previously reported, but its role in breast cancer progression has not been fully investigated. One hundred fifty breast samples (80 with invasive carcinomas) were studied. The expression of AMACR protein was analyzed using the immunohistochemical method (IHC). Lesions were considered positive if AMACR was detected in ≥10% of the cells at any intensity comprising a histologically defined normal epithelial structure or a pathologic lesion. In addition, AMACR mRNA relative expression was calculated from the whole-transcript RNA-Seq performed on >20,000 diverse tumor samples using a 20,000+ hybrid-capture NGS assay with the transcript capture panel based on the Agilent SureSelect Human All ExonV7. Expression of AMACR protein was restricted to epithelia. It was uncommon in the normal breast (7/81 samples, 9%). Increasing AMACR expression was observed with proliferative epithelial lesions (18% of usual ductal hyperplasias/adenosis, 70% of atypical lesions and 72% of DCIS/LCIS). Invasive ductal carcinomas NST and invasive lobular carcinomas expressed AMACR in 64% and 46%, respectively. The highest AMACR expression was observed in luminal B and HER2-positive breast carcinomas (86-100%). Triple-negative breast carcinomas exhibited AMACR in 50% of the cases. Apocrine lesions showed strong, nearly uniform overexpression of AMACR (100% of metaplasias, hyperplasias and in situ carcinomas and 88% of invasive apocrine carcinomas were positive). RNA-Seq analysis also confirmed AMACR expression in breast carcinomas, although its median value was substantially lower with a lower standard deviation than in prostate carcinomas. Over-expression of AMACR characterizes various proliferative, preinvasive and invasive breast lesions and is not specific to the apocrine morphology. It points to altered lipid metabolism (branched fatty acids) as one of the general characteristics of breast carcinogenesis, like several other malignancies. Its early detection may represent a potential target for cancer progression intervention.

Identification and characterization of recurrent neoantigens in upper gastrointestinal (GI) cancers

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Background: Neoantigens are short peptides derived from tumor-specific somatic mutations that can bind to HLA molecules and be presented on the cell surface to activate the immune system. Recognition of neoantigens by autologous T cells promotes sensitivity to immune checkpoint blockade of mismatch repair deficient (MMRd)/microsatellite instability high (MSI-H) tumors. Neoantigen-targeted reactivity by autologous T cells has also been reported in microsatellite stable (MSS) tumors. We aimed to comprehensively assess the spectrum of neoantigens in upper GI cancers and identify recurrent immunogenic candidate neoantigens. Methods: 600 tumor specimens including 268 esophageal (EC), 211 gastric (GC), and 121 gastroesophageal junction (GEJ) cancers tested at Caris Life Sciences (Phoenix, AZ) with NextGen Sequencing (NGS) on DNA (whole exome) and RNA (whole transcriptome) were analyzed. MSI status was determined by immunohistochemistry of MMR protein and/or NGS. Immune epitope prediction was performed on translated peptide sequences harboring detected mutations using the NetMHCpan v4.0 method in the Immune Epitope Database, with HLA genotyping performed using arcasHLA. Immune/stromal cell abundance was quantified using the Microenvironment Cell Populations Counter method. Gene expression profiles were analyzed for a transcriptional signature predictive of response to immunotherapy (T cell-inflamed signature, TIS). Results: Overall, the median patient age was 66 years (range 22-90), 72.8% were male, and 33.7% of samples were metastatic site biopsies. MMRd/MSI-H rate was 2.2% in EC, 12.4% in GC, and 2.5% in GEJ. A total of 1172 unique recurrent neoantigens with predicted binding-level affinity for patient specific HLA alleles were identified (317 in EC, 786 in GC, 157 in GEJ), with 442 and 552 neoantigens exclusively associated with MSS and MSI-H tumors, respectively. Across each cancer type, a higher positive TIS score correlated with both immune and stromal cell population abundance in the tumor microenvironment, most notably cytotoxic lymphocyte and monocytic cell types (r > 0.80, P < 0.0001). Recurrent peptides associated with highest average TIS scores resulted from mutation of TP53 (R248W, 2 peptides: 2.8%/3.2% of samples, respectively) and CUX1 (L162F, 1.6%) in MSS EC; REL (D318A, 2.3%) and ERBB2 (V842I, 1.2%) in MSS GC; MSH3 (K383fs, 36%) and ASXL1 (G645fs, 24%) in MMRd/MSI-H GC; and HOXD12 (A70-A71dup , 2.8%) and TP53 (R248Q, 3.7%) in MSS GEJ. Conclusions: This is one of the largest studies to investigate the landscape of recurrent neoantigens in upper GI cancers. We were able to identify candidate recurrent peptides with high HLA binding affinity and an association with a positive TIS signature in both MSI and MSS tumors, supporting the role of recurrent neoantigens as potential cancer immunotherapy targets.

Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project

BACKGROUND

Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications.

MATERIALS AND METHODS

Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values.

RESULTS

Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples.

CONCLUSIONS

Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

Pulmonary veins reconnection pattern differences after failed radiofrequency ablation and cryoballoon ablation for atrial fibrillation

 

Point-by-point radiofrequency ablation (RF) and one-shot cryoballoon ablation (CRYO) electrically isolate pulmonary veins (PVs) in atrial fibrillation (AF) using different techniques and energies. This study aimed to examine differences in PVs reconnection pattern and ablation lesions required to re-isolate PVs after failed RF and failed CRYO.

Methods

Twenty-four patients who had their repeat ablation between January 2017-December 2020 were studied with six months of learning curve for CRYO. Fourteen patients had paroxysmal atrial fibrillation (PAF). Failed first ablations were defined by electrocardiogram (ECG) documented AF within twelve months following three months blanking period. Repeat ablations were performed using CARTO3® mapping system, which was utilized to locate ablation lesions and impedance drop details.

Results

2,260 lesions were collected from 63 reconnected PVs (31 isolated after RF vs 32 isolated veins after CRYO). 849 lesions were targeted towards triggers. Repeat ablation procedure time was similar between both cohorts. However, repeat ablation after failed CRYO had longer fluoroscopy time (19.8±2 vs 12.4±2.1 minutes, P=0.019). The right lower pulmonary vein (RLPV) was reconnected after failed CRYO for AF in 92% of patients and 100% in PAF patients.

Although PV reconnection pattern was similar between both cohorts, RLPV and left upper pulmonary vein (LUPV) required more ablation lesions after failed CRYO. Left lower pulmonary vein (LLPV) and right upper pulmonary vein (RUPV) required more ablation lesions after failed RF. Impedance drop was similar in both cohorts.

Conclusion

After failed CRYO for PAF, RLPV was reconnected in all patients. RUPV and LLPV required more ablation lesions after failed RF, while RLPV and LLPV required more ablation lesions after failed CRYO.

Funding Acknowledgement

Type of funding sources: None. PVs reconnection patternLesions number and percentage comparison

Homologous Recombination Deficiency Alterations in Colorectal Cancer: Clinical, Molecular, and Prognostic Implications

BACKGROUND

Tumors with homologous recombination (HR) deficiency (HRD) show high sensitivity to platinum salts and PARP-inhibitors in several malignancies. In colorectal cancer (CRC), the role of HRD alterations is mostly unknown.

METHODS

Next generation sequencing, whole transcriptome sequencing and whole exome sequencing were conducted using CRC samples submitted to a commercial Clinical Laboratory Improvement Amendments (CLIA) certified laboratory. Tumors with pathogenic/presumed pathogenic mutations in 33 genes involved in the HR pathway were considered HRD, the others HR proficient (HRP). Furthermore, tumor samples from patients enrolled in the phase III TRIBE2 study comparing upfront FOLFOXIRI/bevacizumab versus FOLFOX/bevacizumab were analyzed with next generation sequencing. The analyses were separately conducted in microsatellite stable/proficient mismatch repair (MSS/pMMR) and microsatellite instable-high/deficient mismatch repair (MSI-H/dMMR) groups. All statistical tests were 2-sided.

RESULTS

Of 9321 CRC tumors, 1270 (13.6%) and 8051 (86.4%) were HRD and HRP, respectively. HRD tumors were more frequent among MSI-H/dMMR than MSS/pMMR tumors (73.4% vs 9.5%, p and q < 0.001). In MSS/pMMR group, HRD tumors were more frequently tumor mutational burden high (8.1% vs 2.2% P and q < 0.001) and PD-L1 positive (5.0% vs 2.4%, P and q = 0.001), enriched in all immune cell and fibroblast populations, and genomic loss of heterozygosity-high (16.2% vs 9.5%, P = .03). In the TRIBE2 study, patients with MSS/pMMR and HRD tumors (10.7%) showed longer overall survival compared to MSS/pMMR and HRP ones (40.2 vs 23.8 months; hazard ratio = 0.66; 95% confidence interval = 0.45-0.98, P = .04). Consistent results were reported in the multivariable model (hazard ratio = 0.67; 95% confidence ratio = 0.45-1.02, P = .07). No interaction effect was evident between HR groups and treatment arm.

CONCLUSIONS

HRD tumors are a distinctive subgroup of MSS/pMMR CRCs with specific molecular and prognostic characteristics. The potential efficacy of agents targeting the HR system and immune check-point inhibitors in this subgroup is worth of clinical investigation.

The Landscape of Alterations in DNA Damage Response Pathways in Colorectal Cancer

PURPOSE

Defective DNA damage response (DDR) is a hallmark of cancer leading to genomic instability and is associated with chemosensitivity. Although the mismatch repair system has been extensively studied, the clinical implications of other mechanisms associated with DDR alterations in patients with colorectal cancer remain unclear. This study aimed to understand DDR pathways alterations and their association with common clinical features in patients with colorectal cancer.

EXPERIMENTAL DESIGN

Next-generation sequencing and whole-transcriptome sequencing were conducted using formalin-fixed paraffin-embedded samples submitted to a commercial Clinical Laboratory Improvement Amendments-certified laboratory. Samples with pathogenic or presumed pathogenic mutations in 29 specific DDR-related genes were considered as DDR-mutant (DDR-MT) and the remaining samples as DDR-wild type (DDR-WT).

RESULTS

Of 9,321 patients with colorectal cancer, 1,290 (13.8%) were DDR-MT. The frequency of DDR-MT was significantly higher in microsatellite instability-high (MSI-H) cases than in microsatellite stable cases (76.4% vs. 9.5%). The DDR-MT genotype was higher in the right-sided, RAS-wild, BRAF-mutant, and CMS1 subgroups. However, these associations were primarily confounded by the distribution of MSI status. Compared with the DDR-WT tumors, the DDR-MT tumors had a higher mutational burden and gene expression levels in the immune-related pathway, which were independent of MSI status.

CONCLUSIONS

We characterized a distinct subgroup of patients with colorectal cancer with tumors harboring mutations in the DDR-related genes. These patients more commonly had MSI-H tumors and exhibited an activated immune signature regardless of their tumor's MSI status. These findings warrant further investigations to develop personalized treatment strategies in this significant subgroup of patients with colorectal cancer.

Pan-cancer analysis of RNA expression of ANGIOTENSIN-I-CONVERTING ENZYME 2 reveals high variability and possible impact on COVID-19 clinical outcomes

Patients with cancer demonstrate particularly poor outcomes from COVID-19. To provide information essential for understanding the biologic underpinnings of this association, we analyzed whole-transcriptome RNA expression data obtained from a large cohort of cancer patients to characterize expression of ACE2, TMPRSS2, and other proteases that are involved in viral attachment to and entry into target cells. We find substantial variability of expression of these factors across tumor types and identify subpopulations expressing ACE2 at very high levels. In some tumor types, especially in gastrointestinal cancers, expression of ACE2 and TMPRSS2 is highly correlated. Furthermore, we found infiltration with T-cell and natural killer (NK) cell infiltration to be particularly pronounced in ACE2-high tumors. These findings suggest that subsets of cancer patients exist with gene expression profiles that may be associated with heightened susceptibility to SARS-CoV-2 infection, in whom malignant tumors function as viral reservoir and possibly promote the frequently detrimental hyper-immune response in patients infected with this virus.

Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type

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CUP occurs in as many as 3–5% of patients when standard diagnostic tests are not able to determine the origin of cancer.

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MI GPSai (Genomic Prevalence Score) is an AI that uses genomic and transcriptomic data to elucidate tumor origin.

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The algorithm was trained on molecular data from 57,489 cases and validated on 19,555 cases.

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MI GPSai predicted the tumor type out of 21 options in the labeled data set with an accuracy of over 94% on 93% of cases.

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When also considering the second highest prediction, the accuracy increases to 97%.

Cancer of Unknown Primary (CUP) occurs in 3–5% of patients when standard histological diagnostic tests are unable to determine the origin of metastatic cancer. Typically, a CUP diagnosis is treated empirically and has very poor outcomes, with median overall survival less than one year. Gene expression profiling alone has been used to identify the tissue of origin but struggles with low neoplastic percentage in metastatic sites which is where identification is often most needed. MI GPSai, a Genomic Prevalence Score, uses DNA sequencing and whole transcriptome data coupled with machine learning to aid in the diagnosis of cancer. The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai predicted the tumor type in the labeled data set with an accuracy of over 94% on 93% of cases while deliberating amongst 21 possible categories of cancer. When also considering the second highest prediction, the accuracy increases to 97%. Additionally, MI GPSai rendered a prediction for 71.7% of CUP cases. Pathologist evaluation of discrepancies between submitted diagnosis and MI GPSai predictions resulted in change of diagnosis in 41.3% of the time. MI GPSai provides clinically meaningful information in a large proportion of CUP cases and inclusion of MI GPSai in clinical routine could improve diagnostic fidelity. Moreover, all genomic markers essential for therapy selection are assessed in this assay, maximizing the clinical utility for patients within a single test.

Clinical Validation of a Machine-learning-derived Signature Predictive of Outcomes from First-line Oxaliplatin-based Chemotherapy in Advanced Colorectal Cancer

PURPOSE

FOLFOX, FOLFIRI, or FOLFOXIRI chemotherapy with bevacizumab is considered standard first-line treatment option for patients with metastatic colorectal cancer (mCRC). We developed and validated a molecular signature predictive of efficacy of oxaliplatin-based chemotherapy combined with bevacizumab in patients with mCRC.

EXPERIMENTAL DESIGN

A machine-learning approach was applied and tested on clinical and next-generation sequencing data from a real-world evidence (RWE) dataset and samples from the prospective TRIBE2 study resulting in identification of a molecular signature, FOLFOXai. Algorithm training considered time-to-next treatment (TTNT). Validation studies used TTNT, progression-free survival, and overall survival (OS) as the primary endpoints.

RESULTS

A 67-gene signature was cross-validated in a training cohort (N = 105) which demonstrated the ability of FOLFOXai to distinguish FOLFOX-treated patients with mCRC with increased benefit from those with decreased benefit. The signature was predictive of TTNT and OS in an independent RWE dataset of 412 patients who had received FOLFOX/bevacizumab in first line and inversely predictive of survival in RWE data from 55 patients who had received first-line FOLFIRI. Blinded analysis of TRIBE2 samples confirmed that FOLFOXai was predictive of OS in both oxaliplatin-containing arms (FOLFOX HR, 0.629; P = 0.04 and FOLFOXIRI HR, 0.483; P = 0.02). FOLFOXai was also predictive of treatment benefit from oxaliplatin-containing regimens in advanced esophageal/gastro-esophageal junction cancers, as well as pancreatic ductal adenocarcinoma.

CONCLUSIONS

Application of FOLFOXai could lead to improvements of treatment outcomes for patients with mCRC and other cancers because patients predicted to have less benefit from oxaliplatin-containing regimens might benefit from alternative regimens.

Population bias in somatic measurement of microsatellite instability status

Microsatellite instability (MSI) is a key secondary effect of a defective DNA mismatch repair mechanism resulting in incorrectly replicated microsatellites in many malignant tumors. Historically, MSI detection has been performed by fragment analysis (FA) on a panel of representative genomic markers. More recently, using next-generation sequencing (NGS) to analyze thousands of microsatellites has been shown to improve the robustness and sensitivity of MSI detection. However, NGS-based MSI tests can be prone to population biases if NGS results are aligned to a reference genome instead of patient-matched normal tissue. We observed an increased rate of false positives in patients of African ancestry with an NGS-based diagnostic for MSI status utilizing 7317 microsatellite loci. We then minimized this bias by training a modified calling model that utilized 2011 microsatellite loci. With these adjustments 100% (95% CI: 89.1% to 100%) of African ancestry patients in an independent validation test were called correctly using the updated model. This poses not only a significant technical improvement but also has an important clinical impact on directing immune checkpoint inhibitor therapy.

Abstract 5671: Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project

Introduction:

Tumor mutational burden (TMB) is the number of somatic mutations per megabase in a tumor's genome and has shown promise as a predictive biomarker of response to immune checkpoint inhibitors across several cancers. TMB is typically measured by whole exome sequencing (WES TMB) or by targeted next-generation sequencing gene panels (panel TMB). As more assays are developed to estimate TMB, harmonization is emerging as an unmet need and is a key goal of the Friends of Cancer Research (Friends) TMB Harmonization Project. Phase I of the Harmonization Project demonstrated correlation between panel TMB and WES TMB using TCGA data and defined theoretical sources of variability across panels. In phase IIA, sustainable TMB reference standard materials generated from human derived cell lines were used to characterize variability in TMB measurements across panels and assessed for utility in TMB alignment. Phase IIB aims to characterize variability in TMB measurements in clinical samples and to establish best practices for estimating and aligning TMB in order to improve consistency across panels.

Methods:

Fifteen laboratories (16 targeted gene panels) at different stages of development participated in phase IIB. Thirty formalin-fixed paraffin-embedded (FFPE) samples with &gt;30% tumor content were acquired; tumor DNA was isolated by a single reference lab. TMB values were calculated for DNA extracted from lung (N=10), bladder (N=10), and gastric tumors (N=10) using WES and a uniform bioinformatics pipeline agreed upon by all Consortium members. DNA samples were also sent to all laboratories, and each used their own sequencing and bioinformatics pipelines to estimate TMB from the genes represented in their respective panels. For each tumor sample, a median across panel TMB estimates was calculated; individual panel TMB estimates were translated to fold-changes relative to the sample median to quantify variability. Association between WES TMB (reference) and panel TMB will be assessed by regression analysis; dependence of association on cancer type was investigated.

Results:

A subset of tumor samples (9 bladder, 7 lung, and 5 gastric) was analyzed using 11 panels at the time of abstract submission. Median panel TMB values ranged 0.60 - 40.26 across samples, with median of median values of 5.35. Fold-change from sample-level medians ranged 0x - 6.67x. Assessment of these clinical samples by WES and all 16 gene panels, as well as regression analysis results, are forthcoming.

Conclusions:

The Friends TMB Harmonization Project has made substantial progress in characterization of TMB measurement variability and association between WES TMB and panel TMB. These are important steps toward alignment of TMB estimates generated by different gene panels which may improve the interpretation of findings within clinical development programs and ultimately enhance the usefulness of this predictive biomarker in clinical decision making.

Citation Format: Diana M. MERINO, Laura M. Yee, Lisa M. McShane, P. Mickey Williams, Tomas Vilimas, Rajesh Patidar, J. Carl Barrett, Shu-Jen Chen, Jen-Hao Cheng, Jeffrey M. Conroy, Dinesh Cyanam, Kenneth R. Eyring, David A. Fabrizio, Vincent Funari, Elizabeth P. Garcia, Sean T. Glenn, Christopher D. Gocke, Vikas Gupta, Lisa M. Haley, Matthew D. Hellmann, Laurel Keefer, Lauryn R. Keeler, Brett Kennedy, Alexander J. Lazar, Laura E. MacConaill, Kristen L. Meier, Arnaud Papin, Naiyer A. Rizvi, Ethan Sokol, Phillip Stafford, John F. Thompson, Warren Tom, Victor J. Weigman, Mingchao Xie, Chen Zhao, Mark D. Stewart, Jeff Allen. Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5671.

Abstract 3639: Fusion-associated neoantigen burden and predicted immunogenicity of CDK12 biallelic loss-of-function tumors vary substantially across cancer types

Background: Biallelic inactivation of CDK12 is associated with a distinct genomic signature of focal tandem duplications (FTDs). Gene fusions resulting from CDK12-associated FTDs increase neoantigen load, raising interest in CDK12 as a biomarker of response to immune checkpoint inhibitors (ICIs). Although FTDs have been detected at higher rates in CDK12-altered tumors compared to CDK12 WT tumors for multiple cancer types, fusion-associated neoantigen burden has only been evaluated in metastatic castration-resistant prostate cancer.

Methods: By retrospective review of molecular profiles, we identified tumors with CDK12 biallelic loss-of-function (LOF) in a primary cohort of over 9000 patient tumors, representing 39 cancer types, and assessed fusions detected by whole transcriptome sequencing for immune epitopes. Biomarker and fusion results for a second cohort of over 13,000 patient tumors were reviewed for validation of the initial findings.

Results: Tumors with CDK12 biallelic LOF (bLOF) (n=29) had significantly higher mean fusion rates (11.7 fusions/tumor) than CDK12 monoallelic LOF (mLOF) and WT tumors (4.1 and 2.6, respectively). Analysis of fusion topologies and breakpoints indicated a predominance of duplication events for CDK12 bLOF tumors and a bimodal distribution of breakpoint distances (modes at ~250-500 kb and ~1.0-2.5 Mb), consistent with prior reports. Fusion rates correlated with the rate of predicted neoantigens with high, intermediate, and low affinity for MHC class I. Fusion-associated neoantigen burden was significantly higher in CDK12 bLOF tumors (145.0 high affinity peptides/tumor) than mLOF (49.7) and WT (26.6) tumors. Among CDK12-altered tumors, fusion rates were significantly higher in prostate (16.4 fusions/tumor, n=11) and ovarian (19.7, n=6) than other cancer types (3.4 overall, n=12), potentially reflecting cancer type-specific roles for CDK12. Co-occurrence of mismatch repair deficiency (dMMR)/high microsatellite instability (MSI-High) with CDK12 bLOF (n=5), most often in colorectal tumors (n=4), correlated with a lower fusion rate (0.2 fusions/tumor); recurrent CDK12 frameshift mutations in these cases (G1461fs, T1463fs, and Q1291fs) coincide with poly-nucleotide tracts, suggesting CDK12 mutations are a secondary effect. In a separate cohort of over 13,000 patient tumors, additional CDK12 bLOF tumors (n=47) were identified, showing a similar distribution and association with high fusion rate (11.0 fusions/tumor).

Conclusion: Fusion rates and predicted neoantigen load varied significantly between CDK12 biallelic tumors across cancer types, highlighting the value of biomarkers with a quantitative immunogenic/phenotypic readout. We propose that fusion rates are linked to CDK12 alterations and may serve as useful biomarker to enhance our ability to identify responders of ICI therapy.

Citation Format: Andrew Elliott, Phillip Stafford, Jian Zhang, Qing Zhang, Jeff Swensen, Daniel Martin, Joanne Xiu, Zoran Gatalica, Daniel Vaena, Elisabeth Heath, W. Michael Korn. Fusion-associated neoantigen burden and predicted immunogenicity of CDK12 biallelic loss-of-function tumors vary substantially across cancer types [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3639.

128Non-invasive 3D mapping of earliest activation of premature ventricular complexes originating from intracardiac structures to guide catheter ablation

Funding Acknowledgements

Research funding from Catheter Precision, Inc.

Introduction

Catheter ablation for ventricular arrhythmias such as premature ventricular complexes and ventricular tachycardia is an established management approach.  Non-invasive mapping to localise the earliest activation (site of origin) on the myocardium may help guide ablation.  Established ECGi methods using the inverse solution to reconstruct epicardial electrograms are unable to accurately locate arrhythmias from the endocardium or from intracardiac structures.  VIVO™ (Catheter Precision) is a novel vectorcardiography based 3D mapping system that may be able to localise arrhythmias from any part of the ventricle.

Methods

We reviewed our initial experience utilising this mapping system to guide catheter ablation of ventricular ectopics from the inter-ventricular septum, coronary cusp or papillary muscle.  A patient-specific 3D heart and torso model was created using semi-automated segmentation of MRI or CT scan images.  A 3D topographic image of the patient’s torso was taken to accurately position surface ECG electrode locations onto the 3D heart-torso model.  An ECG of the PVC was imported from LabSystemPro (Bard) into VIVO™ for analysis prior to ablation.  The result was then compared with the site of earliest activation identified using invasive electro-anatomical (EA) mapping.

Results

VIVO™ was used in 12 cases where the PVC was localised to an intracardiac structure – six papillary muscle, four to the septum and two from the coronary cusp.  VIVO™ was able to accurately localise the earliest activation site when compared to the invasive map in 5/6 papillary muscle cases, 3/4 septal cases and 2/2 coronary cusp cases.  Ablation was acutely successful in all cases.  One additional patient had a PVC localised non-invasively to the postero-medial papillary muscle, however an invasive 3D electro-anatomical map or ablation was not performed.

In three cases we were able to merge the 3D geometry of the non-invasive map from VIVO™ into the Carto™ system to guide mapping and ablation in real time (see figure).

Conclusion

Our experience shows promising results for accurate non-invasive localisation of ventricular arrhythmias originating from intracardiac structures.  Non-invasive localisation is of particular value in cases where the arrhythmia is infrequent, difficult to induce or poorly tolerated haemodynamically.  The two cases where PVC localisation was inaccurate were performed using an older version of the software. With recent refinements, localisation is anticipated to be improved further.

We also present the first experience of combining the VIVO™ geometry with the real-time invasive EA map.  This has potential to significantly speed up mapping time and reduce the need for expensive multi-polar catheters by allowing the operator to see their target in real time 3D.  Further work is ongoing to validate the accuracy of VIVO™ prospectively and quantitatively.

Abstract Figure. VIVO map merged with Carto LV geometry

The landscape of DNA damage response (DDR) pathway in colorectal cancer (CRC)

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Background: Abnormal DDR is a hallmark of cancer, relating to genome instability, anti-tumor immunity, and sensitivity to chemotherapeutic agents and radiation. We conducted a large-scale investigation to clarify the alteration of DDR pathway in CRC. Methods: Tumor samples from 9321 CRC patients were retrospectively reviewed. Next-Generation Sequencing (NGS) on a custom-designed panel enriching 592 gene targets was performed. Samples with mutations detected in any of 29 DDR-related genes were deemed DDR-mutant (DDR-MT); the rest DDR-wild type (DDR-WT). Microsatellite instability (MSI) status was tested with a combination of immunohistochemistry (IHC), fragment analysis and NGS. Tumor mutational burden (TMB) was calculated based on somatic nonsynonymous missense mutations. PD-L1 was tested by IHC (SP142). Consensus molecular subtype (CMS) was developed using RNA sequencing data. Results: Of 9321 cases, 1290 (13.8%) were DDR-MT. DDR-MT frequency was higher in right vs. left sided (20.9% vs 10.8%, p < 0.001) and MSI-H vs. MSS (76.4% vs 9.5%, p < 0.001) cases. In the MSS cases, right-sided had marginally higher frequency of DDR-MT than left-sided (10.6% vs 9.1%, p = 0.055), with much higher frequency of Fanconi anemia pathway alteration in right-sided (1.5% vs 0.7%, p < 0.01). CMS1 subtype had the highest frequency of DDR-MT (34.8%); CMS2 had the lowest (7.1%). DDR-MT cases (vs. DDR-WT) had higher mutation rate of ARID1A (55.0% vs 19.1%, p < 0.0001), PIK3CA (22.6% vs 15.8%, p < 0.0001) and BRAF (20.4% vs 7.3%, p < 0.0001), and lower mutation rate of TP53 (48.2% vs 76.1%, p < 0.0001), APC (60.5% vs 74.5%, p < 0.0001) and KRAS (44.0% vs 49.8%, p < 0.001). Mean TMB was much greater in DDR-MT than DDR-WT (All: 20.9/Mb vs 7.7/Mb, p < 0.0001; MSS: 13.7/Mb vs 7.6/Mb, p < 0.05). PD-L1 positivity was also higher in DDR-MT compared to DDR-WT (All: 10.1% vs 2.7%, p < 0.0001; MSS: 4.8% vs 2.4%, p < 0.0001). Conclusions: Alteration of the DDR pathway was strongly associated with MSI status in CRC. The primary tumor sidedness might also be related, as DDR-MT was more prevalent in right-sided tumors. Elevated TMB and PD-L1 expression in DDR-MT CRC indicate more activated anti-tumor immune profiles compared to DDR-WT, regardless of MSI status, suggesting possible therapeutic benefit from immune checkpoint inhibitors in DDR-MT CRC.

A whole transcriptome sequencing (WTS)-based cMet dysregulation biomarker assay with correlates to cMet DNA mutations and cMet protein expression

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Background: Selective cMet kinase inhibitors (cMet-i) have demonstrated promising clinical activity as single-agents in non-small cell lung cancer (NSCLC) with cMet exon-14 skip mutations (MET∆14). APL-101 (PLB-1001) is a selective cMet-i and has demonstrated single-agent anti-tumor activity in secondary glioblastoma (GBM) harboring MET∆14 and/or MET fusion with evidence of blood-brain barrier permeability (Cell. 2018, 175: 1665-1678). A WTS-based cMet biomarker assay is being developed under Caris MI Transcriptome platform to predict clinical response to monotherapy APL-101 in tumors with cMet dysregulation (NCT03175224). Methods: In a pilot study, we used Caris WTS to analyze 202 patient samples of NSCLC (78%) and other tumor types (22%) mostly GBM and gastrointestinal tumors to establish key parameters of Caris WTS in detection of cMet dysregulation. These samples were also analyzed by DNA-seq and IHC to understand the correlations of Caris WTS to DNA-based cMet mutation detection and cMet protein expression. The samples included 63 (31%) MET∆14, 48 (24%) MET fusions based on WTS and covered a broad dynamic range in cMet expression and copy number variations. In order to establish a stable baseline against which to compare MET mRNA expression, 123 unique tissue samples from 93 unique non-tumor tissues covering 27 unique tissue types were analyzed for wild-type MET expression. Results: Concordance between WTS and DNA-seq in detection of MET∆14 was 84% based on 67 cases analyzed by both methods. WTS identified 45% positive MET∆14, compared to 35% by DNA-seq. Out of 11 discordant cases, 9 were positive by WTS and 2 positive by DNA-seq. The number of transcripts carrying MET∆14 variants correlated with cMet wild type mRNA expression (n = 63, r = 0.88, p< 0.0001). cMet mRNA expression correlated with total cMet protein by IHC in MET fusion subset (n = 43, ρ = 0.65, p= < 0.0001), MET∆14 subset (n = 55, ρ = 0.64, p< 0.0001), and in all samples (n = 175, ρ = 0.75, p< 0.0001). In 175 cases with both WTS and IHC results, 9 MET∆14 positive cases had no detectable cMet protein on plasma membrane albeit all showed a detectable level of total cMet protein. Conclusions: A cMet WTS assay has been established to identify patients with cMet dysregulation including MET∆14 and MET fusion. cMet IHC and DNA-seq may offer secondary utility to differentiate WTS-identified METΔ14 patients to further strengthen the prediction of clinical response to a cMet inhibitor.

Antibody characterization using immunosignatures

Therapeutic monoclonal antibodies have the potential to work as biological therapeutics. OKT3, Herceptin, Keytruda and others have positively impacted healthcare. Antibodies evolved naturally to provide high specificity and high affinity once mature. These characteristics can make them useful as therapeutics. However, we may be missing characteristics that are not obvious. We present a means of measuring antibodies in an unbiased manner that may highlight therapeutic activity. We propose using a microarray of random peptides to assess antibody properties. We tested twenty-four different commercial antibodies to gain some perspective about how much information can be derived from binding antibodies to random peptide libraries. Some monoclonals preferred to bind shorter peptides, some longer, some preferred motifs closer to the C-term, some nearer the N-term. We tested some antibodies with clinical activity but whose function was blinded to us at the time. We were provided with twenty-one different monoclonal antibodies, thirteen mouse and eight human IgM. These antibodies produced a variety of binding patterns on the random peptide arrays. When unblinded, the antibodies with polyspecific binding were the ones with the greatest therapeutic activity. The protein target to these therapeutic monoclonals is still unknown but using common sequence motifs from the peptides we predicted several human and mouse proteins. The same five highest proteins appeared in both mouse and human lists.

Comparison of the biomarkers for targeted therapies in primary extra-mammary and mammary Paget's disease

Background

Primary Extra‐mammary Paget's disease (EMPD) is a very rare cutaneous adenocarcinoma affecting anogenital or axillary regions. It is characterized by a prolonged course with recurrences and eventually distant metastatic spread for which no specific therapy is known.

Methods

Eighteen EMPD (13 vulvar and five scrotal) and ten mammary Paget's disease (MPD) cases were comprehensively profiled for gene mutations, fusions and copy number alterations, and for therapy‐relevant protein biomarkers).

Results

Mutations in TP53 and PIK3CA were the most frequent in both cohorts: 7/15 and 5/15 in EMPD; 1/6 and 4/7 in MPD HER2 gene amplification was detected in 4/18 EMPD (3 vulvar and 1 scrotal case) in contrast to MPD where it was detected in the majority (7/8) of cases. TOP2A gene amplification was seen in 2/12 EMPD and 1/6 MPD, respectively. Similarly, no difference in estrogen receptor expression was seen between the EMPD (4/15) and MPD (3/10). Androgen receptor was also expressed in the majority of both cohorts (12/16 EMPD) and (7/8 MPD).Here ARv7 splice variant was detected in 1/7 EMPD and 1/4 MPD cases, respectively. PD‐L1 expression on immune cells was exclusively observed in three vulvar EMPD. In contrast to MPD, six EMPDs harbored a “high” tumor mutation burden (≥10 mutations/Mb). All tested cases from both cohorts were MSI stable.

Conclusions

EMPD shares some targetable biomarkers with its mammary counterpart (steroid receptors, PIK3CA signaling pathways, TOP2A amplification). HER2 positivity is notably lower in EMPD while biomarkers to immune checkpoint inhibitors (high TMB and PD‐L1) were observed in some EMPD. Given that no consistent molecular alteration characterizes EMPD, comprehensive theranostic profiling is required to identify individual patients with targetable molecular alterations.

Abstract A035: Therapeutic targets in androgen deprivation therapy-resistant prostatic carcinoma

Background: Androgen deprivation therapy (ADT) for patients with metastatic prostate carcinoma eventually leads to development of castration-resistant prostate cancer (CRPC) with limited therapeutic options. ADT is characterized by the presence of ARv7 splice variant and several resistance mutations in AR gene. We explored potential therapeutic targets in CRPC. Methods: Biopsy samples from 80 patients with prostate carcinomas (39 primary and 41 metastatic samples) were analyzed for mutations using 592 gene NGS panel and a whole transcriptome sequencing (WTS). Tumor mutational burden (TMB) and microsatellite instability (MSI) were calculated from the NGS data. Protein expression of the full length AR and ARv7 variant, as well as mismatch repair (MMR) enzymes (MLH1, MSH2, MSH6 and PMS2) and tumor cells’ (TC) expression of PD-L1 were analyzed using IHC methods. Tests results were correlated with clinical history of androgen deprivation (ADT-Hx). Chi-square analysis was used to compare subgroups. Results: Clinical histories were available for 63 patients (26 with and 37 without ADT-Hx). The median age in this cohort was 67 (range: 45-88). Overall, ARv7 was detected in 20/80 cases. Two out of 15 cases had ARv7 present in biopsies without previous ADT-Hx (one primary prostate and one metastatic bone biopsy). Five patients with ADT-Hx harbored AR gene mutations (ARmut) in exon 8 which are known to confer ADT resistance were detected in the cohort (6% overall; 1 co-occurred with ARv7). Microsatellite instability (MSI-H) was detected in 6 cases (7.5% overall); of note, AR resistance mutation (ARv7 or ARmut) occurred at significantly higher rate in patients with MSI-H/MMRd compared to MSS/MMRp (83%; 5/6 vs. 26%; 19/72, p=0.001). Average total mutational burden (TMB) in microsatellite stable (MSS) cases was low (6/Mb); high TMB (&gt;80th percentile for the prostate carcinoma cohort) was detected in one MSS CRPC. PD-L1 TC-expression was detected in 1 metastatic (ARv7 negative) case. Pathogenic gene fusions were detected in 33 cases, most commonly TMPRSS2:ERG (26/79; 7/17 in ARv7). The most commonly mutated gene was TP53 (30 cases; 9/17 in ARv7). BRCA 1/2 mutations were found in 7 cases (3 in ARv7) and CDK12 mutations in 4 (2 in ARv7) cases. Other DNA repair genes mutations (n=1, each) includied MUTYH, PRKDC, ATM, BRIP1, ERCC2, FANCA and FANCD2. Gene expression analysis identified numerous differently expressed genes between ARv7+/ADT+, ARv7-/ADT+ and ARv7-/ADT- tumor groups, requiring further analysis. Conclusion: Upon failure of ADT, tumor samples from men with CRPC (biopsy positive for ARv7 or ARmut) demonstrate molecular alterations that are potential targets for treatment. Immune-oncology agents in patients harboring evidence of genomic instability (e.g. high MSI or TMB) and PARP inhibitors in patients with alterations in DNA repair pathways (e.g. BRCA1/2, ATM, PRKDC, CDK12, etc.) should be investigated further. Comprehensive tumor profiling is necessary to detect targetable pathways.

Citation Format: Zoran Gatalica, Phillip Stafford, Elma Contreras, Jeff Swensen, Rebecca Feldman. Therapeutic targets in androgen deprivation therapy-resistant prostatic carcinoma [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A035. doi:10.1158/1535-7163.TARG-19-A035

Novel therapeutic targets in salivary duct carcinoma uncovered by comprehensive molecular profiling

Salivary duct carcinoma (SDC) is a rare, aggressive salivary gland malignancy, which often presents at an advanced stage. A proportion of SDC are characterized by HER2 amplification and/or overexpression of androgen receptor (AR), which could be targeted in a subset of patients, but the presence of AR splice variant‐7 (AR‐V7) in some SDC cases could result in resistance to anti‐androgen therapy. We evaluated a cohort of 28 cases of SDC for potentially targetable biomarkers and pathways using immunohistochemistry (IHC) and next‐generation sequencing (DNA and RNA) assays. Pathogenic genetic aberrations were found in all but 1 case and affected TP53 (n = 19), HRAS (n = 7), PIK3CA, ERBB2 (HER2), and NF1 (n = 5 each); KMT2C (MLL3) and PTEN (n = 3 each); BRAF (p.V600E), KDM5C and NOTCH1 (n = 2 each). Androgen receptor was expressed in all cases and 13 of 27 harbored the AR‐V7 splice variant (including a case without any other detectable genetic alteration). HER2 IHC was expressed in 11 of 28 cases. The majority of SDC cases had no biomarkers predictive of immunotherapy response: 5 cases exhibited low (1%‐8%) programmed death ligand 1 (PD‐L1) expression in tumor cells, 2 cases exhibited elevated TMB, and no samples exhibited microsatellite instability. Notably, the pre‐treatment biopsies from 2 patients with metastatic disease, who demonstrated clinical responses to anti‐androgen therapy, showed AR expression and no AR splice variants. We conclude that comprehensive molecular profiling of SDCs can guide the selection of patients for targeted therapies involving AR, HER2, PD‐L1, mitogen‐activated protein kinase, and PIK3CA pathways.

High-Throughput Profiling of Circulating Antibody Signatures for Stroke Diagnosis Using Small Volumes of Whole Blood

Accurate stroke recognition during triage can streamline care and afford patients earlier access to life-saving interventions. However, the tools currently available to clinicians for prehospital and early in-hospital identification of stroke are limited. The peripheral immune system is intricately involved in stroke pathology and thus may be targetable for the development of immunodiagnostics. In this preliminary study, we sought to determine whether the circulating antibody pool is altered early in stroke, and whether such alterations could be leveraged for diagnosis. One hundred microliters of peripheral whole blood was sampled from 19 ischemic stroke patients, 17 hemorrhagic stroke patients, and 20 stroke mimics in the acute phase of care. A custom-fabricated high-density peptide array comprising 125,000 unique probes was used to assess the binding characteristics of blood-borne antibodies, and a random forest-based approach was used to select a parsimonious set of probes with an optimal ability to discriminate between groups. The coordinate antibody binding intensities of the top 17 probes identified in our analysis displayed an ability to differentiate the total pool of stroke patients from stroke mimics with 92% sensitivity and 90% specificity, as well as detect hemorrhage with 88% sensitivity and 87% specificity, as determined using a same-set cross-validation. These preliminary findings suggest that stroke-associated alterations in the circulating antibody pool may have clinical utility for diagnosis during triage, and that such a possibility warrants further investigation.

Abstract 1463: FAST vaccines based on frameshift neoantigens may have advantages over personal vaccines

It is widely hoped that personal cancer vaccines will extend the number of patients benefiting from checkpoint and other immunotherapeutics. However, it is clear creating such vaccines will be challenging. It requires obtaining and sequencing tumor DNA/RNA, predicting potentially immunogenic neoepitopes and manufacturing a one-use vaccine. This process takes time and considerable cost. Importantly, most mutations will not produce an immunogenic peptide and many patient’s tumors do not contain enough DNA mutations to make a vaccine. We have discovered that frameshift peptides (FSP) produced in tumors though errors in RNA production are a rich source of neoantigens. There are ~220K bioinformatically predictable possible FSP allowing us to make arrays representing them as 15aa peptides. These arrays can then be used to screen cancer patient blood antibodies for reactivity to the arrays. In screening many cancer patients blood on these array, we found both personal and cancer-type specific peptides. This suggests a new type of vaccine consisting of pre-made FSP components for a specific type of cancer. We term these FAST vaccines. Here we use the mouse 4T1 breast cancer model to test the relative effectiveness of a FAST and a PERSONAL vaccine. To create the vaccines, we initially challenged mice subcutaneously with 4T1 tumor cells and, seven days later, sera were collected. Pre-challenge and 7-days sera were assayed on peptide microarrays containing 200 FS neoantigens. For the PERSONAL vax, the top 10 candidates (higher median intensity fluorescence) were select and personal vaccines constructed and administrated to respective mice (n=10). For the FAST vax, we selected the top 10 candidates with higher prevalence among all the mice challenged (n=24), a common Breast cancer FAST vax was constructed (mBC FAST-vax). Mice were challenged with 4T1 cells subcutaneously. Vaccines were then, administrated twice with one-week interval, combined or not with checkpoint inhibitor (CPI) (anti- PD-L1/ CTLA-4). Our results demonstrated that both vaccine approaches, FAST and PERSONAL vax, alone reduced tumor growth as well as increased animal survival. Nonetheless, the FAST vax protected 70 % of mice (7/10 - tumor free) even after re-challenge, 29 days after vaccine regimen. For the Personal vax group, co-administration with CPI resulted in enhancement of tumor control with 57 % of the mice strongly controlling the tumor. The FAST vax performance was not improved by CPI. Both vaccine approaches elicited a robust and homogenous B- and T- cell immune response against both vaccine peptides and tumor cells. Additionally, use of Non-reactive FSPs and a Non-Breast cancer FAST vax were not able to control tumor development. We conclude that the FAST technology may open new opportunities to develop a low cost, feasible and efficacious vaccines against cancer.

Citation Format: Milene Tavares Batista, Sierra Nicole Murphy, Ji'an Zhang, Luhui Shen, Phillip Stafford, Stephen A. Johnston. FAST vaccines based on frameshift neoantigens may have advantages over personal vaccines [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 1463.

Abstract 168: Detection of Stroke Using Highly-Parallel Profiling of the Circulating Antibody Pool

Quick and accurate recognition of stroke during triage improves the probability of positive outcome, however the tools currently available to clinicians for prehospital and early in-hospital diagnosis of stroke are limited. The peripheral immune system is intricately involved in stroke pathology, and thus may be targetable for the development of immunodiagnostics. In this study, we sought to determine whether the circulating antibody pool is altered early in stroke, and whether such alterations could be leveraged for diagnosis. 100 uL of peripheral whole blood was sampled from 19 ischemic stroke patients, 17 hemorrhagic stroke patients, and 20 stroke mimics upon stroke team referral. A custom-fabricated high-density peptide array comprised of 125,000 unique probes was used to assess the binding characteristics of blood-borne antibodies, and a random forest-based approach was used to select a parsimonious set of probes with an optimal ability to discriminate between groups. The coordinate antibody binding intensities of the top 17 probes identified in our analysis displayed an ability to differentiate between stroke patients and stroke mimics with 92% sensitivity and 90% specificity, as well as detect hemorrhage with 88% sensitivity and 87% specificity, as determined using a same-set cross-validation. Our findings suggest that stroke-associated alterations in the circulating antibody pool may have clinical utility for diagnosis during triage, and that such a possibility warrants further investigation.

Immunosignature Analysis of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)

A random-sequence peptide microarray can interrogate serum antibodies in a broad, unbiased fashion to generate disease-specific immunosignatures. This approach has been applied to cancer detection, diagnosis of infections, and interrogation of vaccine response. We hypothesized that there is an immunosignature specific to ME/CFS and that this could aid in the diagnosis. We studied two subject groups meeting the Canadian Consensus Definition of ME/CFS. ME/CFS (n = 25) and matched control (n = 25) sera were obtained from a Canadian study. ME/CFS (n = 25) sera were obtained from phase 1/2 Norwegian trials (NCT01156909). Sera from six healthy controls from the USA were included in the analysis. Canadian cases and controls were tested for a disease immunosignature. By combining results from unsupervised and supervised analyses, a candidate immunosignature with 654 peptides was able to differentiate ME/CFS from controls. The immunosignature was tested and further refined using the Norwegian and USA samples. This resulted in a 256-peptide immunosignature with the ability to separate ME/CFS cases from controls in the international data sets. We were able to identify a 256-peptide signature that separates ME/CFS samples from healthy controls, suggesting that the hit-and-run hypothesis of immune dysfunction merits further investigation. By extending testing of both our signature and one previously reported in the literature to larger cohorts, and further interrogating the specific peptides we and others have identified, we may deepen our understanding of the origins of ME/CFS and work towards a clinically meaningful diagnostic biomarker.

Immunosignature Differentiation of Non-Infectious Meningoencephalomyelitis and Intracranial Neoplasia in Dogs

A variety of inflammatory conditions of unknown cause (meningoencephalomyelitis of unknown etiology-MUE) and neoplastic diseases can affect the central nervous system (CNS) of dogs. MUE can mimic intracranial neoplasia both clinically, radiologically and even in some cases, histologically. Serum immunosignature protein microarray assays have been used in humans to identify CNS diseases such as Alzheimer's and neoplasia, and in dogs, to detect lymphoma and its progression. This study evaluated the effectiveness of immunosignature profiles for distinguishing between three cohorts of dogs: healthy, intracranial neoplasia, and MUE. Using the learned peptide patterns for these three cohorts, classification prediction was evaluated for the same groups using a 10-fold cross validation methodology. Accuracy for classification was 100%, as well as 100% specific and 100% sensitive. This pilot study demonstrates that immunosignature profiles may help serve as a minimally invasive tool to distinguish between MUE and intracranial neoplasia in dogs.

Entropy is a Simple Measure of the Antibody Profile and is an Indicator of Health Status: A Proof of Concept

We have previously shown that the diversity of antibodies in an individual can be displayed on chips on which 130,000 peptides chosen from random sequence space have been synthesized. This immunosignature technology is unbiased in displaying antibody diversity relative to natural sequence space, and has been shown to have diagnostic and prognostic potential for a wide variety of diseases and vaccines. Here we show that a global measure such as Shannon's entropy can be calculated for each immunosignature. The immune entropy was measured across a diverse set of 800 people and in 5 individuals over 3 months. The immune entropy is affected by some population characteristics and varies widely across individuals. We find that people with infections or breast cancer, generally have higher entropy values than non-diseased individuals. We propose that the immune entropy as measured from immunosignatures may be a simple method to monitor health in individuals and populations.

Interactions of periodontal pathogens with megakaryocytic cells and platelets

Introduction: Cardiovascular disease (CVD) is a leading cause of morbidity, accounting for around 17.3 million deaths worldwide. Recent studies have linked periodontitis to CVD with the periodonto-pathogens Porphyromonas gingivalis and Tannerella forsythia thought to contribute and exacerbate atherosclerosis through interactions with platelets. To date, while platelet activation following challenge with periodonto-pathogens has been reported, the underlying mechanisms of these interactions are yet to be elucidated. The aim of this study is to determine how periodonto-pathogens interact with platelets using both megakaryocytic cells and isolated platelets.

Methods: To characterise expression levels of surface markers including ubiquitously expressed platelet-specific markers (CD41, CD42b) and platelet activation markers (CD62P, PAC-1), a multi-colour flow cytometry panel was developed using undifferentiated megakaryocytic cells CHRF-288-11 before validation using platelets isolated from healthy donors. Changes in levels of surface markers following bacterial challenge both with megakaryocytic cells and isolated platelets were determined using flow cytometry. Interaction with pathogens was visualised by platelet aggregometry and fluorescence microscopy using pathogen-specific antibodies.

Results and conclusions: Both pathogens invaded megakaryocytic cells as visualised by immunofluorescence microscopy. The pathogens also bound platelets causing increased levels of aggregation and upregulated expression of activation markers including in CD62P in flow cytometric assays.

Humoral Immunity Profiling of Subjects with Myalgic Encephalomyelitis Using a Random Peptide Microarray Differentiates Cases from Controls with High Specificity and Sensitivity

Myalgic encephalomyelitis (ME) is a complex, heterogeneous illness of unknown etiology. The search for biomarkers that can delineate cases from controls is one of the most active areas of ME research; however, little progress has been made in achieving this goal. In contrast to identifying biomarkers that are directly involved in the pathological process, an immunosignature identifies antibodies raised to proteins expressed during, and potentially involved in, the pathological process. Although these proteins might be unknown, it is possible to detect antibodies that react to these proteins using random peptide arrays. In the present study, we probe a custom 125,000 random 12-mer peptide microarray with sera from 21 ME cases and 21 controls from the USA and Europe and used these data to develop a diagnostic signature. We further used these peptide sequences to potentially uncover the naturally occurring candidate antigens to which these antibodies may specifically react with in vivo. Our analysis revealed a subset of 25 peptides that distinguished cases and controls with high specificity and sensitivity. Additionally, Basic Local Alignment Search Tool (BLAST) searches suggest that these peptides primarily represent human self-antigens and endogenous retroviral sequences and, to a minor extent, viral and bacterial pathogens.

Spaceflight modulates gene expression in the whole blood of astronauts

Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1, HSP27, GPX1, XRCC1, BAG-1, HHR23A, FAP48, and C-FOS. No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight.

General Assessment of Humoral Activity in Healthy Humans

The humoral immune system is network of biological molecules designed to maintain a healthy homeostatic equilibrium. Because antibodies are an abundant and highly specific effector of immunological action, they are also an important reservoir of previous host exposures. Antibodies may play a major role in early detection of host challenge. Unfortunately, few practical methods exist for interpreting the information stored in antibody variable regions. Immunosignatures use a microarray of thousands of random sequence peptides to interrogate antibodies in a broad and unbiased fashion. The pattern of binding between antibody and peptide is reproducible. Once the system has been trained on a disease cohort, blinded samples can be reliably predicted. Although immunosignatures of both chronic and infectious disease have been extensively tested, less has been done to demonstrate how healthy immunosignatures change over time or between individuals. Here, we report the results of a study of immunosignatures of healthy persons over brief (12 h sampled once per hour), intermediate (32 days sampled once per day), and long (5 years sampled once every year) time spans. Using this information, we were also able to detect intentional and unintentional immunological perturbations in the form of a vaccine and an infection, respectively. Our findings suggest that, even with the variability inherent in healthy immunosignatures, a single person's immunosignature will remain constant over time. Over this healthy signature, vaccines and infections create subsignatures that are common across multiple people, even subsuming healthy fluctuations. These findings have implications for disease monitoring and early diagnosis.

Abstract WP218: A Blood Test Capable of Discriminating Between Real Strokes and Mimics

Introduction: stroke diagnosis is not always easy. Many non-vascular medical and neurological problems can mimic stroke, featuring focal neurological signs and symptoms of sudden onset. These patients can potentially be harmed by stroke-specific treatments, including fibrinolysis. Hence, a test capable of unveiling stroke mimics would be useful.

Hypothesis: A proteomic platform called immunosignaturing may be useful to distinguish between acute ischemic stroke and imitators.

Methods: plasma samples from 12 patients brought to the ER because of a stroke code were analyzed: 6 were diagnosed with acute ischemic stroke and 6 with seizures mimicking a stroke. Additional 12 samples from healthy volunteers were used as controls. Immunosignatures use microarrays with 10,000 random sequence peptides, which behave as antibody mimotopes. Antibody binding to microarray peptides is detected with secondary antibodies labeled with fluorescent dyes, then scanned with a laser. Resulting profiles are unique to each individual. Samples were run in duplicates, with good correlation between replicates, high signal and low background. Mann-Whitney U-test and Fisher‘s exact test were used to compare groups.

Results: samples were obtained within 130 minutes after symptoms onset. We found no differences between groups related to age, gender, or cardiovascular risk factors. Analysis of signature profiles revealed striking separation between stroke and seizure cases. The Figure depicts a heatmap comparing the stroke (yellow bar underneath) and seizure patients. Peptides with QADAP or QADLP motifs helped differentiate the groups.

Conclusions: We describe the first application of an antibody-profiling platform called immunosignaturing to the study of ischemic stroke and its imitators. Despite the small sample, these very preliminary results suggest that antibody signatures may help distinguish acute ischemic strokes from other conditions, deserving future research.

Pyocystis and prostate abscess in a hemodialysis patient in the emergency department

The urinary tract is an often forgotten and under-appreciated source of infection in anuric hemodialysis patients. Bladder abscess, also called pyocystis, is a severe complication of low urinary flow that can be difficult to detect, leading to delays in treatment and increased morbidity. The emergency physician should maintain a high suspicion for pyocystis, which can be quickly diagnosed by bedside ultrasound. We report a case of a hemodialysis patient with an initially minor presentation who developed sepsis secondary to pyocystis and prostate abscess.

Abstract B35: Use of random peptide array to discover cancer neo-antigens for vaccines and diagnostics

This abstract is being presented as a short talk in the scientific program. A full abstract is printed in the Proffered Abstracts section (PR10) of the Conference Proceedings.

Citation Format: Phillip Stafford, Josh Richer, Stephen Albert Johnston, Luhui Shen. Use of random peptide array to discover cancer neo-antigens for vaccines and diagnostics. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2015;3(10 Suppl):Abstract nr B35.

Abstract PR10: Use of random peptide array to discover cancer neo-antigens for vaccines and diagnostics

The humoral response to tumors could reveal tumor antigens recognized by immunosurveillance. We have developed the immunosignatures diagnostic technology to detect this tumor specific response. The technology profiles reactivity of sera antibodies on the HT330K chip with 330K addressable random peptides. We have shown that subjects with specific cancers have specific immunosignatures that are distinguished from health people and other cancers. Here we demonstrate that the signatures can be deciphered to indicate specific neo-antigens for any cancer.

Neo-antigens caused by mistranscription in tumors can be the sources of tumor antigens. We have set up a database of predicted chimeric tumor antigens encoded by trans-splicing transcripts analyzed from EST databases. These transcripts encode the neo-epitopes by producing frame shift (FS) peptides from shifted reading frames of the downstream genes. We hypothesize that these predicted neo-antigens are frequently expressed in cancers and recognized by the immune system. We predict that these neo-antigens can be deciphered by their immunosignatures.

To test the hypothesis, we assayed the sera from glioblastoma patients (GBM, n=16) and normal controls (NC, n=16) on the HT330K chip. The 1,000 most significantly different peptides between GBM and NC were selected. Recurrent motifs in these peptides were across searched in the neo-antigen database. The seven most frequently matched antigens were selected for further study: 2 of them were encoded by the in-frame fusion transcripts and others were encoded by the FS fusion transcripts.

To validate the antibody reactivity of 7 deciphered neo-antigens, three overlapping peptides encompassing each of the antigens were synthesized and printed with unrelated peptides on the CIM10K array, which contains total 10,000 peptides. We analyzed NC (n=69) and GBM (n=19) with the CIM10K array. The positive cut off value of each peptide is the average plus two fold standard deviations of the NC. A positive sample was indicated as positive to at least one peptide of the antigen. The highest positive rates of 7 antigens is 11.6% in NC and 57.9% in GBM. 34.8% NC were positive to at least one antigen, 15.9% to more than one and only 4.3% positive to more than two antigens. No NC was positive to more than three antigens. This indicated the reactivity to these antigens is random in NC. The positive percentage in GBM were 89.5%, 73.7% and 47.4% respectively. 26.3% GBM was positive to more than three antigens. The implication is that cancer patients had much higher reactivity to these putative neo-antigens.

To test if other cancers elicited reactions to these neo-antigens, we analyzed breast cancer sera (BC, n=95) with the CIM10K. Similar to GBM, 83.15% BC were positive to at least one antigen and 34.7% were positive to more than 3 antigens. Five of seven antigens had positive reactivity in more than 25% of patients in both GBM and BC.

To further characterize these neo-antigens, we designed primers for RT-PCR analysis. We detected and sequence confirmed five fusion transcripts in GBM cDNAs. Two of the FS transcripts were also detected in multiple BC cDNAs and several normal tissues with lower level. Our interpretation is that the processing of the FS variants is primarily post-transcriptional in normal tissue but this processing is defective in tumors.

Here we showed that the neo-antigens from predicted fusion transcripts are the targets of the cancer humoral immune response. The specific antibody response was only in cancer patients indicating that the expression of these antigens in normal tissues was below the sensitivity of the immune system. Most importantly, this work indicates that we can efficiently decipher neo-antigens from the immunosignatures of cancer subjects. This may be a new source of antigens for diagnosis and cancer vaccines.

This abstract is also presented as Poster B35.

Citation Format: Phillip Stafford, Josh Richer, Stephen Albert Johnston, Luhui Shen. Use of random peptide array to discover cancer neo-antigens for vaccines and diagnostics. [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy: A New Chapter; December 1-4, 2014; Orlando, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2015;3(10 Suppl):Abstract nr PR10.

Time-Frequency Analysis of Peptide Microarray Data: Application to Brain Cancer Immunosignatures

One of the gravest dangers facing cancer patients is an extended symptom-free lull between tumor initiation and the first diagnosis. Detection of tumors is critical for effective intervention. Using the body’s immune system to detect and amplify tumor-specific signals may enable detection of cancer using an inexpensive immunoassay. Immunosignatures are one such assay: they provide a map of antibody interactions with random-sequence peptides. They enable detection of disease-specific patterns using classic train/test methods. However, to date, very little effort has gone into extracting information from the sequence of peptides that interact with disease-specific antibodies. Because it is difficult to represent all possible antigen peptides in a microarray format, we chose to synthesize only 330,000 peptides on a single immunosignature microarray. The 330,000 random-sequence peptides on the microarray represent 83% of all tetramers and 27% of all pentamers, creating an unbiased but substantial gap in the coverage of total sequence space. We therefore chose to examine many relatively short motifs from these random-sequence peptides. Time-variant analysis of recurrent subsequences provided a means to dissect amino acid sequences from the peptides while simultaneously retaining the antibody–peptide binding intensities. We first used a simple experiment in which monoclonal antibodies with known linear epitopes were exposed to these random-sequence peptides, and their binding intensities were used to create our algorithm. We then demonstrated the performance of the proposed algorithm by examining immunosignatures from patients with Glioblastoma multiformae (GBM), an aggressive form of brain cancer. Eight different frameshift targets were identified from the random-sequence peptides using this technique. If immune-reactive antigens can be identified using a relatively simple immune assay, it might enable a diagnostic test with sufficient sensitivity to detect tumors in a clinically useful way.

Epitope identification from fixed-complexity random-sequence peptide microarrays

Antibodies play an important role in modern science and medicine. They are essential in many biological assays and have emerged as an important class of therapeutics. Unfortunately, current methods for mapping antibody epitopes require costly synthesis or enrichment steps, and no low-cost universal platform exists. In order to address this, we tested a random-sequence peptide microarray consisting of over 330,000 unique peptide sequences sampling 83% of all possible tetramers and 27% of pentamers. It is a single, unbiased platform that can be used in many different types of tests, it does not rely on informatic selection of peptides for a particular proteome, and it does not require iterative rounds of selection. In order to optimize the platform, we developed an algorithm that considers the significance of k-length peptide subsequences (k-mers) within selected peptides that come from the microarray. We tested eight monoclonal antibodies and seven infectious disease cohorts. The method correctly identified five of the eight monoclonal epitopes and identified both reported and unreported epitope candidates in the infectious disease cohorts. This algorithm could greatly enhance the utility of random-sequence peptide microarrays by enabling rapid epitope mapping and antigen identification.

Scalable high-density peptide arrays for comprehensive health monitoring

There is an increasing awareness that health care must move from post-symptomatic treatment to presymptomatic intervention. An ideal system would allow regular inexpensive monitoring of health status using circulating antibodies to report on health fluctuations. Recently, we demonstrated that peptide microarrays can do this through antibody signatures (immunosignatures). Unfortunately, printed microarrays are not scalable. Here we demonstrate a platform based on fabricating microarrays (~10 M peptides per slide, 330,000 peptides per assay) on silicon wafers using equipment common to semiconductor manufacturing. The potential of these microarrays for comprehensive health monitoring is verified through the simultaneous detection and classification of six different infectious diseases and six different cancers. Besides diagnostics, these high-density peptide chips have numerous other applications both in health care and elsewhere.

The roles of HOXD10 in the development and progression of head and neck squamous cell carcinoma (HNSCC)

Background:

HOX gene expression is altered in many cancers; previous microarray revealed changes in HOX gene expression in head and neck squamous cell carcinoma (HNSCC), particularly HOXD10.

Methods:

HOXD10 expression was assessed by qPCR and immunoblotting in vitro and by immunohistochemistry (IHC) in tissues. Low-expressing cells were stably transfected with HOXD10 and the phenotype assessed with MTS, migration and adhesion assays and compared with the effects of siRNA knockdown in high-HOXD10-expressing cells. Novel HOXD10 targets were identified using expression microarrays, confirmed by reporter assay, and validated in tissues using IHC.

Results:

HOXD10 expression was low in NOKs, high in most primary tumour cells, and low in lymph node metastasis cells, a pattern confirmed using IHC in tissues. Overexpression of HOXD10 decreased cell invasion but increased proliferation, adhesion and migration, with knockdown causing reciprocal effects. There was no consistent effect on apoptosis. Microarray analysis identified several putative HOXD10-responsive genes, including angiomotin (AMOT-p80) and miR-146a. These were confirmed as HOXD10 targets by reporter assay. Manipulation of AMOT-p80 expression resulted in phenotypic changes similar to those on manipulation of HOXD10 expression.

Conclusions:

HOXD10 expression varies by stage of disease and produces differential effects: high expression giving cancer cells a proliferative and migratory advantage, and low expression may support invasion/metastasis, in part, by modulating AMOT-p80 levels.

Diagnosis and early detection of CNS-SLE in MRL/lpr mice using peptide microarrays

Background

An accurate method that can diagnose and predict lupus and its neuropsychiatric manifestations is essential since currently there are no reliable methods. Autoantibodies to a varied panel of antigens in the body are characteristic of lupus. In this study we investigated whether serum autoantibody binding patterns on random-sequence peptide microarrays (immunosignaturing) can be used for diagnosing and predicting the onset of lupus and its central nervous system (CNS) manifestations. We also tested the techniques for identifying potentially pathogenic autoantibodies in CNS-Lupus. We used the well-characterized MRL/lpr lupus animal model in two studies as a first step to develop and evaluate future studies in humans.

Results

In study one we identified possible diagnostic peptides for both lupus and altered behavior in the forced swim test. When comparing the results of study one to that of study two (carried out in a similar manner), we further identified potential peptides that may be diagnostic and predictive of both lupus and altered behavior in the forced swim test. We also characterized five potentially pathogenic brain-reactive autoantibodies, as well as suggested possible brain targets.

Conclusions

These results indicate that immunosignaturing could predict and diagnose lupus and its CNS manifestations. It can also be used to characterize pathogenic autoantibodies, which may help to better understand the underlying mechanisms of CNS-Lupus.

Gingipain-dependent degradation of mammalian target of rapamycin pathway proteins by the periodontal pathogen Porphyromonas gingivalis during invasion

Porphyromonas gingivalis and Tannerella forsythia are gram-negative pathogens strongly associated with periodontitis. Their abilities to interact, invade and persist within host cells are considered crucial to their pathogenicity, but the mechanisms by which they subvert host defences are not well understood. In this study, we set out to investigate whether P. gingivalis and T. forsythia directly target key signalling molecules that may modulate the host cell phenotype to favour invasion and persistence. Our data identify, for the first time, that P. gingivalis, but not T. forsythia, reduces levels of intracellular mammalian target of rapamycin (mTOR) in oral epithelial cells following invasion over a 4-h time course, via the action of gingipains. The ability of cytochalasin D to abrogate P. gingivalis-mediated mTOR degradation suggests that this effect is dependent upon cellular invasion. We also show that levels of several other proteins in the mTOR signalling pathway are modulated by gingipains, either directly or as a consequence of mTOR degradation including p-4E-BP1. Taken together, our data suggest that P. gingivalis manipulates the mTOR pathway, providing evidence for a potentially novel mechanism by which P. gingivalis mediates its effects on host cell responses to infection.

Abstract 4441: The ketogenic diet potentiates radiation therapy in a mouse model of glioma: effects on inflammatory pathways and reactive oxygen species

Patients with malignant brain tumors have a median survival of approximately one year following diagnosis, regardless of currently available treatments which include surgery, radiation and chemotherapy. Although there have been advances in the development of novel treatments, targeted therapies face the challenge of overcoming phenotypic variability resulting from tumor heterogeneity. One phenotypic trait shared by virtually all cancer cells is dysregulation of metabolism. It has therefore been postulated that one approach to treating brain tumors may be through metabolic alteration such as that which occurs through the use of the ketogenic diet (KD). The KD is high-fat, low-carbohydrate diet that has been utilized for the non-pharmacologic treatment of refractory epilepsy. We and others have shown that this diet enhances survival in mouse models of malignant gliomas. Further, radiation in combination with KD was synergistic, and survival was significantly increased over radiation treatment alone. To gain an understanding of the mechanism(s) by which the KD exerts anti-tumor effects and enhances the efficacy of radiation therapy we performed gene expression profiling analyses on tumor tissue and non-tumor containing brain using the Affymetrix GeneChip® Mouse Genome 430 2.0 array. To identify changes in gene expression representing chronic effects of KD and radiation plus KD we harvested tissue when the animals became symptomatic. We previously reported that tissue from animals maintained on the KD in the absence of radiation treatment showed a reduction in reactive oxygen species (ROS) and cyclooxygenase-2 (COX-2) expression compared to those maintained on a standard diet (Stafford et al, Nutr and Metab (7):74, 2010). We now report that peritumoral edema is significantly reduced early in tumor progression in animals fed the KD when compared to those fed a standard rodent diet. Furthermore, gene expression profiling of animals treated with radiation and KD demonstrated alterations in the chronic expression of crucial genes involved in radiation-induced inflammation including COX-2 and the nuclear transcription factor NF-кB, both of which are implicated in radioresistance. We are repeating these studies using tissues harvested shortly after radiation therapy to identify genes acutely affected by radiation therapy in animals fed a KD. Taken together, our data to date suggests that the KD may be interfering with the radiation-induced inflammatory signaling network implicated in tumor progression. A greater understanding of the effects of the ketogenic diet as an adjuvant therapy will allow for a more rational approach to its clinical use.

Citation Format: Eric C. Woolf, Phillip Stafford, Mohammed G. Abdelwahab, Kathryn Fenton, Mark C. Preul, Adrienne C. Scheck. The ketogenic diet potentiates radiation therapy in a mouse model of glioma: effects on inflammatory pathways and reactive oxygen species. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4441. doi:10.1158/1538-7445.AM2013-4441

Feasibility of an early Alzheimer's disease immunosignature diagnostic test

A practical diagnostic test is needed for early Alzheimer's disease (AD) detection. Immunosignaturing, a technology that employs antibody binding to a random-sequence peptide microarray, generates profiles that distinguish transgenic mice engineered with familial AD mutations (APPswe/PSEN1-dE9) from non-transgenic littermates. It can also detect an AD-like signature in humans. Here, we assess the changes in the immunosignature at different time points of the disease in mice and humans. We also evaluate the accuracy of the late-stage signature as a test to discriminate between young mice with familial AD mutations from non-transgenic littermates. Plasma samples from AD patients were assayed 3-12 months apart, while APPswe/PSEN1-dE9 and non-transgenic controls supplied plasma at monthly intervals until they reached 15 months of age. Microarrays with 10,000 random-sequence peptides were used to compare antibody binding patterns. These patterns gradually changed over the life-span of mice. Strong, characteristic signatures were observed in transgenic mice at early, mid and late stages, but these profiles had minimal overlap. The signature of young transgenic mice had an error rate of 18% at classifying plasma samples from late-stage transgenic mice. Conversely, the late-stage transgenic mice signature discriminated between young transgenic mice and littermates with an error rate of 21%. Less distinctive profiles were recognizable throughout the transgenic mice lifespan, being detectable as early as 2 months. The human signature had minimal change on short-term follow-up. Our results call for a reappraisal of the way incipient AD is studied, as biomarkers seen in late-stages of the disease may not be relevant in earlier stages.

Immunosignaturing can detect products from molecular markers in brain cancer

Immunosignaturing shows promise as a general approach to diagnosis. It has been shown to detect immunological signs of infection early during the course of disease and to distinguish Alzheimer’s disease from healthy controls. Here we test whether immunosignatures correspond to clinical classifications of disease using samples from people with brain tumors. Blood samples from patients undergoing craniotomies for therapeutically naïve brain tumors with diagnoses of astrocytoma (23 samples), Glioblastoma multiforme (22 samples), mixed oligodendroglioma/astrocytoma (16 samples), oligodendroglioma (18 samples), and 34 otherwise healthy controls were tested by immunosignature. Because samples were taken prior to adjuvant therapy, they are unlikely to be perturbed by non-cancer related affects. The immunosignaturing platform distinguished not only brain cancer from controls, but also pathologically important features about the tumor including type, grade, and the presence or absence of O⁶-methyl-guanine-DNA methyltransferase methylation promoter (MGMT), an important biomarker that predicts response to temozolomide in Glioblastoma multiformae patients.