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Study Workflow Diagram. Key steps in the study are outlined, including the number of patients at each stage. BEV: bevacizumab.

Additional Longitudinal Analysis of Relapsed and Refractory Childhood Solid Tumors.

Table S1. Extended Cohort Annotations. Table S2. Mutational Signatures. Table S3. GISTIC Copy Number Analysis. Table S4. Somatic Variants in Relapsed/Refractory Childhood Solid Tumors (n=184 Patients with T/N WES). Table S5. Clinvar Pathogenic and Likely Pathogenic Germline Variants in Relapsed/Refractory Childhood Solid Tumors(n=184 Patients with T/N WES). Table S6. Gene Lists. Table S7. Log2(TPM+1) Values for the 2,199 Most Variable Genes Expressed Across the Cohort of Relapsed/Refractory Childhood Solid Tumors with RNA-seq (n=245). Table S8. Differential Expression Analysis of 2,199 Most Variable Genes Among Clusters. Table S9. Genes Filtered for COSMIC, Transcription Factors and Potential Drug Targets from Table S8 with log2FC greater than or equal to 2. Table S10. Differential Expression Analysis Among C3a, C3b, and C3c Subclusters. Table S11. Samples Falling in Clusters C3a-C3c and Genes that are Uniformly Highly Expressed in the Clusters. Table S12. Longitudinal Samples.

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

Children with treatment-refractory or relapsed (R/R) tumors face poor prognoses. As the genomic underpinnings driving R/R disease are not well defined, we describe here the genomic and transcriptomic landscapes of R/R solid tumors from 202 patients enrolled in Beat Childhood Cancer Consortium clinical trials. Tumor mutational burden (TMB) was elevated relative to untreated tumors at diagnosis, with one-third of tumors classified as having a pediatric high TMB. Prior chemotherapy exposure influenced the mutational landscape of these R/R tumors, with more than 40% of tumors demonstrating mutational signatures associated with platinum or temozolomide chemotherapy and two tumors showing treatment-associated hypermutation. Immunogenomic profiling found a heterogenous pattern of neoantigen and MHC class I expression and a general absence of immune infiltration. Transcriptional analysis and functional gene set enrichment analysis identified cross-pathology clusters associated with development, immune signaling, and cellular signaling pathways. While the landscapes of these R/R tumors reflected those of their corresponding untreated tumors at diagnosis, important exceptions were observed, suggestive of tumor evolution, treatment resistance mechanisms, and mutagenic etiologies of treatment.Significance:Tumor heterogeneity, chemotherapy exposure, and tumor evolution contribute to the molecular profiles and increased mutational burden that occur in treatment-refractory and relapsed childhood solid tumors.

Children with treatment-refractory or relapsed (R/R) tumors face poor prognoses. As the genomic underpinnings driving R/R disease are not well defined, we describe here the genomic and transcriptomic landscapes of R/R solid tumors from 202 patients enrolled in Beat Childhood Cancer Consortium clinical trials. Tumor mutational burden (TMB) was elevated relative to untreated tumors at diagnosis, with one-third of tumors classified as having a pediatric high TMB. Prior chemotherapy exposure influenced the mutational landscape of these R/R tumors, with more than 40% of tumors demonstrating mutational signatures associated with platinum or temozolomide chemotherapy and two tumors showing treatment-associated hypermutation. Immunogenomic profiling found a heterogenous pattern of neoantigen and MHC class I expression and a general absence of immune infiltration. Transcriptional analysis and functional gene set enrichment analysis identified cross-pathology clusters associated with development, immune signaling, and cellular signaling pathways. While the landscapes of these R/R tumors reflected those of their corresponding untreated tumors at diagnosis, important exceptions were observed, suggestive of tumor evolution, treatment resistance mechanisms, and mutagenic etiologies of treatment. Significance: Tumor heterogeneity, chemotherapy exposure, and tumor evolution contribute to the molecular profiles and increased mutational burden that occur in treatment-refractory and relapsed childhood solid tumors.

Cancer genomic heterogeneity presents significant challenges for understanding oncogenic processes and for cancer’s clinical management. Variation in driver mutation frequency between patients with the same tumor type as well as within individual patients’ cancers can limit the power of mutations to serve as diagnostic, prognostic, and predictive biomarkers. We have characterized genomic heterogeneity between and within patients in canine splenic hemangiosarcoma (HSA), a common naturally occurring cancer in pet dogs that is similar to human angiosarcoma (AS). HSA is a clinically, physiologically, and genomically complex canine cancer that may serve as a valuable model for understanding the origin and clinical impact of cancer heterogeneity. We conducted a prospective collection of 52 splenic masses from 44 dogs (28 HSA, 15 benign masses, and 1 stromal sarcoma) presenting to emergency care with hemoperitoneum secondary to a ruptured splenic mass. Multi-platform genomic analysis included matched tumor/normal cancer gene panel and exome sequencing. We found candidate somatic cancer driver mutations in 14/28 (50%) HSAs. Among recurrent candidate driver mutations, TP53 was most commonly mutated (29%) followed by PIK3CA (14%), AKT1 (11%), and CDKN2AIP (11%). We also identified significant intratumoral genomic heterogeneity, consistent with a branched evolution model, through multi-region exome sequencing of three distinct tumor regions from selected primary splenic tumors. These data provide new perspective on the genomic landscape and comparative value of understanding HSA in pet dogs, particularly as a naturally occurring cancer bearing intratumoral heterogeneity.

Here we present a novel statistical approach to splicing outlier and differential splicing detection, implemented in a software package called Bisbee. We leverage Bisbee’s prediction of protein level effects to benchmark using matched RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches. We applied Bisbee to confirm a pathogenic splicing event in a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic splice factor mutation. We also identified common tumor associated splice isoforms replicated in an independent dataset, demonstrating the utility of Bisbee in discovering disease relevant splice variants.

Background Tumor heterogeneity underlies resistance and disease progression in glioblastoma (GBM), and tumors most commonly recur adjacent to the surgical resection margins in contrast non-enhancing (NE) regions. To date, no targeted therapies have meaningfully altered overall patient survival in the up-front setting. The aim of this study was to characterize intratumoral heterogeneity in recurrent GBM using bulk samples from primary resection and recurrent samples taken from contrast-enhancing (EN) and contrast NE regions. Methods Whole exome and RNA sequencing were performed on matched bulk primary and multiple recurrent EN and NE tumor samples from 16 GBM patients who received standard of care treatment alone or in combination with investigational clinical trial regimens. Results Private mutations emerge across multi-region sampling in recurrent tumors. Genomic clonal analysis revealed increased enrichment in gene alterations regulating the G2M checkpoint, Kras signaling, Wnt signaling, and DNA repair in recurrent disease. Subsequent functional studies identified augmented PI3K/AKT transcriptional and protein activity throughout progression, validated by phospho-protein levels. Moreover, a mesenchymal transcriptional signature was observed in recurrent EN regions, which differed from the proneural signature in recurrent NE regions. Conclusions Subclonal populations observed within bulk resected primary GBMs transcriptionally evolve across tumor recurrence (EN and NE regions) and exhibit aberrant gene expression of common signaling pathways that persist despite standard or targeted therapy. Our findings provide evidence that there are both adaptive and clonally mediated dependencies of GBM on key pathways, such as the PI3K/AKT axis, for survival across recurrences.

10006 Background: The major genomic profiling studies that have helped define the molecular landscapes of pediatric cancers have typically focused on untreated pediatric cancers at diagnosis. Despite improvements in overall survival for childhood cancers, patients with treatment-refractory or relapsed (R/R) solid tumors face a poor prognosis. The genomic underpinnings of R/R disease are less well-characterized. Here, we describe the integrated genomic and transcriptomic analysis of 250 R/R solid tumors from 202 children profiled within precision medicine studies (NCT01355679, NCT01802567, NCT02162732) conducted by the Beat Childhood Cancer Consortium. Methods: Tumor-normal whole-exome and tumor mRNA sequencing was performed by Ashion Analytics (Phoenix, Arizona), a CAP-accredited, CLIA-certified laboratory, or within the research setting at TGen. Longitudinal tumor samples were sequenced for 20 patients. Variant calling included single nucleotide variants, indels, copy number alterations, and fusions. Integrated genomic and transcriptomic research analysis included microsatellite instability assessment, immunogenomic profiling, and functional gene set enrichment analysis. Results: Forty-six tumor types were represented, grouped into four general categories: sarcomas (36.1%; n = 73), neuroblastomas (29.2%; n = 59), CNS tumors (23.3%; n = 47), and other rare tumors (11.4%; n = 23). For patients with whole exome sequencing data, 78.3% (n = 144/184) of tumors bore a somatic alteration in at least one known cancer gene. Over one-third (39.1%; 72/184) of the cohort bore oncogenic fusions and/or oncogenic/likely-oncogenic hotspot mutations in a known cancer gene. Pathognomonic fusions were identified in 25% (46/184) of tumors, occurring most frequently in sarcomas. Pathogenic or likely pathogenic germline variants were identified in 8.7% (16/184) of patients. Microsatellite instability was detected in five different tumor types. Despite nearly all tumors (94%, 173/184) having at least one predicted strong binding neoantigen, over a quarter of tumors lacked transcript expression of these neoantigens or exhibited low MHC class I expression. Further, a subset of tumors showed elevated expression of the co-inhibitory immune checkpoint molecule PDL1. Transcriptional analysis and functional gene set enrichment analysis identified cross-pathology tumor clusters associated with immune signaling, development, and cellular signaling pathways. Longitudinal analysis revealed temporal heterogeneity pointing to the importance of re-biopsy at relapse for targeted treatment planning. Conclusions: Together, these data suggest R/R childhood solid tumors exhibit shared molecular features that are reflective of underlying biology, demonstrating the importance of comprehensive profiling to inform molecularly-guided treatment of R/R disease.

Background Significant clinical and research applications are driving large scale adoption of individualized tumor sequencing in cancer in order to identify tumors-specific mutations. When a matched germline sample is available, somatic mutations may be identified using comparative callers. However, matched germline samples are frequently not available such as with archival tissues, which makes it difficult to distinguish somatic from germline variants. While population databases may be used to filter out known germline variants, recent studies have shown private germline variants result in an inflated false positive rate in unmatched tumor samples, and the number germline false positives in an individual may be related to ancestry. Methods First, we examined the relationship between the germline false positives and ancestry. Then we developed and implemented a tumor only caller (LumosVar) that leverages differences in allelic frequency between somatic and germline variants in impure tumors. We used simulated data to systematically examine how copy number alterations, tumor purity, and sequencing depth should affect the sensitivity of our caller. Finally, we evaluated the caller on real data. Results We find the germline false-positive rate is significantly higher for individuals of non-European Ancestry largely due to the limited diversity in public polymorphism databases and due to population-specific characteristics such as admixture or recent expansions. Our Bayesian tumor only caller (LumosVar) is able to greatly reduce false positives from private germline variants, and our sensitivity is similar to predictions based on simulated data. Conclusions Taken together, our results suggest that studies of individuals of non-European ancestry would most benefit from our approach. However, high sensitivity requires sufficiently impure tumors and adequate sequencing depth. Even in impure tumors, there are copy number alterations that result in germline and somatic variants having similar allele frequencies, limiting the sensitivity of the approach. We believe our approach could greatly improve the analysis of archival samples in a research setting where the normal is not available. Electronic supplementary material The online version of this article (10.1186/s12920-017-0296-8) contains supplementary material, which is available to authorized users.

Current understanding of the mutation spectrum of relapsed/refractory (RR) tumors is limited. We performed whole exome sequencing (WES) on 47 diffuse large B cell lymphoma (DLBCL) tumors that persisted after R-CHOP treatment, 8 matched to primary biopsies. We compared genomic alterations from the RR cohort against two treatment-naïve DLBCL cohorts (n=112). While the overall number and types of mutations did not differ significantly, we identified frequency changes in DLBCL driver genes. The overall frequency of MYD88 mutant samples increased (12% to 19%), but we noted a decrease in p.L265P (8% to 4%) and increase in p.S219C mutations (2% to 6%). CARD11 p.D230N, PIM1 p.K115N and CD79B p.Y196C mutations were not observed in the RR cohort, although these mutations were prominent in the primary DLBCL samples. We observed an increase in BCL2 mutations (21% to 38% of samples), BCL2 amplifications (3% to 6% of samples) and CREBBP mutations (31% to 42% of samples) in the RR cohort, supported by acquisition of mutations in these genes in relapsed compared to diagnostic biopsies from the same patient. These increases may reflect the genetic characteristics of R-CHOP RR tumors expected to be enriched for during clinical trial enrollment. These findings hold significance for a number of emerging targeted therapies aligned to genetic targets and biomarkers in DLBCL, reinforcing the importance of time-of-treatment biomarker screening during DLBCL therapy selection.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated multiplexed immunofluorescence single cell data for 43 protein markers across cancer hallmarks, in addition to cell spatial metrics, genomic sequencing and magnetic resonance imaging (MRI) quantitative features. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion differ between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. Longer overall survival for IDH1mt glioma patients may reflect generalized altered cellular, molecular, spatial heterogeneity which manifest in discernable radiological manifestations.

Glioma is recognized to be a highly heterogeneous CNS malignancy, whose diverse cellular composition and cellular interactions have not been well characterized. To gain new clinical- and biological-insights into the genetically-bifurcated IDH1 mutant (mt) vs wildtype (wt) forms of glioma, we integrated data from protein, genomic and MR imaging from 20 treatment-naïve glioma cases and 16 recurrent GBM cases. Multiplexed immunofluorescence (MxIF) was used to generate single cell data for 43 protein markers representing all cancer hallmarks, Genomic sequencing (exome and RNA (normal and tumor) and magnetic resonance imaging (MRI) quantitative features (protocols were T1-post, FLAIR and ADC) from whole tumor, peritumoral edema and enhancing core vs equivalent normal region were also collected from patients. Based on MxIF analysis, 85,767 cells (glioma cases) and 56,304 cells (GBM cases) were used to generate cell-level data for 24 biomarkers. K-means clustering was used to generate 7 distinct groups of cells with divergent biomarker profiles and deconvolution was used to assign RNA data into three classes. Spatial and molecular heterogeneity metrics were generated for the cell data. All features were compared between IDH mt and IDHwt patients and were finally combined to provide a holistic/integrated comparison. Protein expression by hallmark was generally lower in the IDHmt vs wt patients. Molecular and spatial heterogeneity scores for angiogenesis and cell invasion also differed between IDHmt and wt gliomas irrespective of prior treatment and tumor grade; these differences also persisted in the MR imaging features of peritumoral edema and contrast enhancement volumes. A coherent picture of enhanced angiogenesis in IDHwt tumors was derived from multiple platforms (genomic, proteomic and imaging) and scales from individual proteins to cell clusters and heterogeneity, as well as bulk tumor RNA and imaging features. Longer overall survival for IDH1mt glioma patients may reflect mutation-driven alterations in cellular, molecular, and spatial heterogeneity which manifest in discernable radiological manifestations.

Splicing dysregulation is a common feature of cancer, and may produce tumor specific proteins that have altered function or antigenicity. While many tools are available to detect splicing in RNAseq data, robust methods for translating the effects of alternative splicing to altered protein sequences are lacking. In addition, statistical approaches for detecting splicing defects in a tumor compared to normal tissues are only now being considered by bioinformaticians. We have developed a protein sequence generation method and splicing outlier detection strategy and validated this pipeline using a dataset with matched RNAseq and mass spectrometry data from normal tissues. Splice events were detected using SplAdder and our protein sequence generation and annotation tools were implemented in python. We developed a novel approach to outlier detection using a beta binomial model, where splice isoform read counts are modeled with a binomial distribution, and the expected proportion of each splice isoform (‘percent spliced in' or ‘PSI') is modeled as the beta distribution based on the PSI observed in a reference dataset. In a normal tissue validation dataset, we detected isoform-specific peptides for 77,369 splice events, including 2,171 that encode novel protein sequences. Both isoforms were detected for 1,476 of these events, and 271 events showed tissue exclusive detection patterns. To evaluate our proposed outlier detection method, we used a set of gastrointestinal (GI) tissues as a reference set and looked for outlier splice events in normal brain, tonsil, and ovarian tissues. We identified examples of peptides where one isoform was exclusively detected in the GI tissues and the other isoform was detected in one of the other tissues. Our outlier detection method was able to predict these events from the RNAseq data with better specificity compared to thresholds set using the distribution of PSIs. We also implemented a differential splicing test using the beta binomial model and benchmarked it against the more commonly used negative binomial model using the normal tissue dataset, and found our proposed method improved sensitivity and specificity. We then applied our splicing outlier detection pipeline to tumor data from TCGA using GTEx as a reference set, and were able to identify tumor specific splice events that generated novel protein sequences. Our splicing pipeline enables the identification of tumor-specific isoforms which may be candidate targets for immunotherapies. Citation Format: Rebecca F. Halperin, Apurva Hegde, Jessica Lang, Elizabeth Raupach, Patrick Pirrotte, Nicholas Schork. A proteomics validated pipeline for detection of differential and tumor-specific splice events [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 LB-244.

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

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

The therapeutic HER2-targeting antibody trastuzumab has been shown to elicit tumor immune response in a subset of HER2-positive (HER2+) breast cancer. We performed genomic and immunohistochemical profiling of tumors from eight patients who have completed multiple rounds of neoadjuvant trastuzumabb to identify predictive biomarkers for trastuzumab-elicited tumor immune responses. Immunohistochemistry showed that all tumors had an activated tumor immune microenvironment positive for nuclear NF-&kappa, B/p65RelA, CD4, and CD8 T cell markers, but only four out of eight tumors were positive for the PD-1 immune checkpoint molecule, which is indicative of an exhausted immune environment. Exome sequencing showed no specific driver mutations correlating with PD-1 positivity. Hierarchical clustering of the RNA sequencing data revealed two distinct groups, of which Group 2 represented the PD-1 positive tumors. A gene expression signature that was derived from this clustering composed of 89 genes stratified HER2+ breast cancer patients in the TCGA dataset and it was named PD-1-Associated Gene Expression Signature in HER2+ Breast Cancer (PAGES-HBC). Patients with the Group 2 PAGES-HBC composition had significantly more favorable survival outcomes with mortality reduced by 83% (hazard ratio 0.17, 95% CI, 0.05 to 0.60, p = 0.011). Analysis of three longitudinal samples from a single patient showed that PAGES-HBC might be transiently induced by trastuzumab, independent of clonal tumor expansion over time. We conclude that PAGES-HBC could be further developed as a prognostic predictor of trastuzumab response in HER2+ breast cancer patients and be potentially used as an alternative biomarker for anti-PD-1 therapy trials.

Up to 20% of breast cancer is clinically defined as triple-negative breast cancer (TNBC) lacking estrogen, progesterone, and HER2 receptors. Because no targeted therapy is available, cytotoxic chemotherapy is the primary mode of adjuvant TNBC therapy, but is effective in ~30% patients. In order to determine molecular underpinnings of chemotherapy resistance in TNBC, we analyzed 12 TNBC patient tumor samples collected post neoadjuvant chemotherapy using DNA/RNA sequencing. DNA analysis showed two tumors contained TP53 inactivating mutations and two tumors PIK3CA activating mutations. In addition, a number of mutations in the DNA repair pathway genes were identified including XRCC1, XRCC3, and ATXR, suggesting that DNA damaging nature of chemotherapy agents may have enriched these mutations. In addition, we found mutations in the genes involved in microtubule assembly including BUB3 and APC2, suggesting that these gene mutations may confer resistance to taxol, an anti-microtubule chemotherapy agent. RNA sequencing revealed a true heterogeneous nature of TNBE in that unsupervised clustering did not identify any distinct gene signature correlative of chemotherapy resistance. We are currently evaluating phenotypes related to chemotherapy resistance using cells genetically engineered with the BUB3 or APC2 mutations. Citation Format: Michael Grant, George Snipes, Rebecca Halperin, Paul Heaton, Suwon Kim. Mutations in DNA repair and microtubule assembly genes found in triple negative breast tumors treated with neoadjuvant chemotherapy [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 3425.

Genomic analyses of cutaneous melanoma (CM) have yielded biological and therapeutic insights, but understanding of non-ultraviolet (UV)-derived CMs remains limited. Deeper analysis of acral lentiginous melanoma (ALM), a rare sun-shielded melanoma subtype associated with worse survival than CM, is needed to delineate non-UV oncogenic mechanisms. We thus performed comprehensive genomic and transcriptomic analysis of 34 ALM patients. Unlike CM, somatic alterations were dominated by structural variation and absence of UV-derived mutation signatures. Only 38% of patients demonstrated driver BRAF/NRAS/NF1 mutations. In contrast with CM, we observed PAK1 copy gains in 15% of patients, and somatic TERT translocations, copy gains, and missense and promoter mutations, or germline events, in 41% of patients. We further show that in vitro TERT inhibition has cytotoxic effects on primary ALM cells. These findings provide insight into the role of TERT in ALM tumorigenesis and reveal preliminary evidence that TERT inhibition represents a potential therapeutic strategy in ALM.

We developed and deployed a workflow for generating multi-scale, multiparametric imaging data, feature extraction and/or converting to higher scales which equips multiple analysis approaches to differentiate clinically variable phenotypes of glial tumors. The workflow quantifies spatial heterogeneity (concordance of adjoining cells) and molecular heterogeneity (varied cell states determined by protein abundance) of glial tumors at the genomic, tissue, and medical imaging scales including IDH mutation status and progression/recurrence status. A panel of 24 multiplexed immunofluorescence (MxIF) markers (addressing 9 hallmarks of cancer) was used to profile single cells (in the thousands) in tissue sections from each of 31 glial tumors (ranging from primary grade II to IV, and recurrent grade IV). Pre-resection multi-parameter MR images were feature extracted from discreet habitats (necrosis, enhancing, and edema); whole exome and transcriptome sequencing from bulk viable tumor were analyzed. By MxIF, the various states of individual cells from treatment-naive patient specimens resolved unsupervised into 7 clusters, for which Cluster 2 (including cells from 9 patients) and Cluster 6 (including cells from 8 patients) contained the two larger bundles of patient cases. When separated into IDHmt and IDHwt cases, cells from IDHmt cases frequently contained cell populations dominated by a single cluster (low molecular heterogeneity); cells from cases with IDHwt represented multiple different clusters (high molecular heterogeneity). In grade III astrocytomas, and grade IV recurrent glioblastomas, spatial heterogeneity of the hallmark “inducing angiogenesis” was elevated in the IDHmt tumors compared to IDHwt, while between the same groups, molecular heterogeneity was lower in the IDHmt cases than wild type. Edema from T1w post contrast MR imaging was found to be elevated in IDHwt gliomas relative to IDHmt, while enhancement was reduced in IDHwt compared to IDHmt tumors. The findings demonstrate that IDHmt gliomas, irrespective of grade, show less edema, greater enhancement, and greater spatial heterogeneity of the “inducing angiogenesis” hallmark but lower molecular heterogeneity than IDHwt tumors. Molecular heterogeneity of “cancer invasion” also differed between IDHmt and IDHwt cases. Longer survival duration following diagnosis for patients with IDHmt gliomas may reflect generalized altered molecular and spatial heterogeneity, which is a phenotype evident on medical imaging. [Clinically-annotated specimens originated from the Ohio Brain Tumor Study and the Ivy GBM Clinical Trials Consortium] Citation Format: Michael E. Berens, Jill S. Barnholtz-Sloan, Miribella Rusu, John Graf, Anup Sood, Sanghee Cho, Maria Zavodszky, Sara Byron, Rebecca Halperin, Yi Fritz, Seungchan Kim, Fiona Ginty. Role of IDH mutation status on molecular and spatial heterogeneity in glial tumors across progression and recurrence [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 3039.

While genomic profiling and therapeutic selection support individualized GBM treatment, such therapeutic decision-making is usually made with reference to tumor obtained from the enhancing core region. GBM is known to be heterogeneous and exhibits a high resistance to standard therapies. To address whether non-enhancing tumor (representing the majority of tumor left behind after surgery) shows distinct genomic characteristics and therapeutic targets compared to the enhancing tumor core, we performed genome-wide exome-sequencing and RNA-sequencing for 12 patients with matched enhancing region and at least one non-enhancing region. Non-enhancing biopsies show a surprisingly high level of tumor content, with a median of 28% tumor cells and 6 of the 22 samples having greater than 50% tumor cells. Cognate non-enhancing and enhancing specimens demonstrated overall concordance in therapeutically actionable alterations (single nucleotide variants) and copy number alterations. However, non-enhancing regions were not genetically identical and did reveal additional and distinct variants compared to enhancing cores. For example, the non-enhancing region of patient 1 showed two nonsense NF1 mutations (R1534X; R2517X) while the enhancing region showed an NF1 frameshift mutation (F1247fs). Clonality analysis by LumosVar also indicated that 7 out of 12 patients harbored dissimilar cellular prevalence patterns between enhancing and non-enhancing regions. In addition, comparison of alternative polyadenylation between enhancing and non-enhancing regions uncovered distinct 3' UTR usage: e.g. SGMS2 and TOB1 tended to have longer 3' UTR in enhancing regions whereas longer 3' UTR of SYNPO and NOS1AP were prevalent in non-enhancing regions. We posit that the enhancing component of glioblastoma probably underrepresents the genomic alterations in patients' tumors. Given non-enhancing tumor is left behind after surgical debulking, genomic profiling of this region would potentially reveal more accurate tumor vulnerabilities and lead to more effective therapy. Supported by a grant from the Ben & Catherine Ivy Foundation. Citation Format: Sen Peng, Rebecca Halperin, Harshil Dhruv, Sara Byron, Christophe Legendre, Joanna Phillips, Michael Prados, Michael Berens, Nhan Tran. Probing the non-enhancing component of glioblastoma: Targeting what is left behind [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 289.

Contains fulltext : 80661.pdf (Publisher’s version ) (Closed access) Age-related hearing impairment (ARHI), or presbycusis, is the most prevalent sensory impairment in the elderly. ARHI is a complex disease caused by an interaction between environmental and genetic factors. Here we describe the results of the first whole genome association study for ARHI. The study was performed using 846 cases and 846 controls selected from 3434 individuals collected by eight centers in six European countries. DNA pools for cases and controls were allelotyped on the Affymetrix 500K GeneChip for each center separately. The 252 top-ranked single nucleotide polymorphisms (SNPs) identified in a non-Finnish European sample group (1332 samples) and the 177 top-ranked SNPs from a Finnish sample group (360 samples) were confirmed using individual genotyping. Subsequently, the 23 most interesting SNPs were individually genotyped in an independent European replication group (138 samples). This resulted in the identification of a highly significant and replicated SNP located in GRM7, the gene encoding metabotropic glutamate receptor type 7. Also in the Finnish sample group, two GRM7 SNPs were significant, albeit in a different region of the gene. As the Finnish are genetically distinct from the rest of the European population, this may be due to allelic heterogeneity. We performed histochemical studies in human and mouse and showed that mGluR7 is expressed in hair cells and in spiral ganglion cells of the inner ear. Together these data indicate that common alleles of GRM7 contribute to an individual's risk of developing ARHI, possibly through a mechanism of altered susceptibility to glutamate excitotoxicity.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressively disabling impairments in memory, cognition, and non-cognitive behavioural symptoms. Sporadic AD is multifactorial and genetically complex. While several monogenic mutations cause early-onset AD and gene alleles have been suggested as AD susceptibility factors, the only extensively validated susceptibility gene for late-onset AD is the apolipoprotein E (APOE) Ε4 allele. Alleles of the APOE gene do not account for all of the genetic load calculated to be responsible for AD predisposition. Recently, polymorphisms across the neuronal sortilin-related receptor (SORL1) gene were shown to be significantly associated with AD in several cohorts. Here we present the results of our large case-control whole-genome scan at over 500,000 polymorphisms which presents weak evidence for association and potentially narrows the association interval.

Approximately 90% of persons with amyotrophic lateral sclerosis (ALS) have the sporadic form, which may be caused by the interaction of multiple environmental factors and previously unknown genes.We performed a genomewide association analysis using 766,955 single-nucleotide polymorphisms (SNPs) found in 386 white patients with sporadic ALS and 542 neurologically normal white controls (the discovery series). Associations of SNPs with sporadic ALS were confirmed in two independent replication populations: replication series 1, with 766 case patients with the disease and 750 neurologically normal controls, and replication series 2, with 135 case patients and 275 controls.We identified 10 genetic loci that are significantly associated (P0.05) with sporadic ALS in three independent series of case patients and controls and an additional 41 loci that had significant associations in two of the three series. The most significant association with disease in white case patients as compared with controls was found for a SNP near an uncharacterized gene known as FLJ10986 (P=3.0x10(-4); odds ratio for having the genotype in patients vs. controls, 1.35; 95% confidence interval, 1.13 to 1.62). The FLJ10986 protein was found to be expressed in the spinal cord and cerebrospinal fluid of patients and of controls. Specific SNPs seem to be associated with sex, age at onset, and site of onset of sporadic ALS.Variants of FLJ10986 may confer susceptibility to sporadic ALS. FLJ10986 and 50 other candidate loci warrant further investigation for their potential role in conferring susceptibility to the disease.

OBJECTIVE: While the apolipoprotein E (APOE) epsilon allele is a well-established risk factor for late-onset Alzheimer's disease (AD), initial genome scans using microsatellite markers in late-onset AD failed to identify this locus on chromosome 19. Recently developed methods for the simultaneous assessment of hundreds of thousands of single nucleotide polymorphisms (SNPs) promise to help more precisely identify loci that contribute to the risk of AD and other common multigenic conditions. We sought here to demonstrate that more precise identification of loci that are associated with complex, multi-genic genetic disorders can be achieved using ultra-high-density whole-genome associations by demonstrating their ability to identify the APOE locus as a major susceptibility gene for late-onset AD, despite the absence of SNPs within the APOE locus itself, as well as to refine odds ratios (ORs) based on gold-standard phenotyping of the study population. METHOD: An individualized genome-wide association study using 502,627 SNPs was performed in 1086 his-topathologically verified AD cases and controls to determine the OR associated with genes predisposing to Alzheimer's disease. RESULTS: As predicted, ultra-high-density SNP genotyping, in contrast to traditional microsatellite-based genome screening approaches, precisely identified the APOE locus as having a significant association with late-onset AD. SNP rs4420638 on chromosome 19, located 14 kilobase pairs distal to the APOE epsilon variant, significantly distinguished between AD cases and controls (Bonferroni corrected p value = 5.30 x 10(-34), OR = 4.01) and was far more strongly associated with the risk of AD than any other SNP of the 502,627 tested. CONCLUSION: This study provides empirical support for the suggestion that the APOE locus is the major susceptibility gene for late-onset AD in the human genome, with an OR significantly greater than any other locus in the human genome. It also supports the feasibility of the ultra-high-density whole-genome association approach to the study of AD and other heritable phenotypes. These whole-genome association studies show great promise to identify additional genes that contribute to the risk of AD.

We report the development and validation of experimental methods, study designs, and analysis software for pooling-based genomewide association (GWA) studies that use high-throughput single-nucleotide–polymorphism (SNP) genotyping microarrays. We first describe a theoretical framework for establishing the effectiveness of pooling genomic DNA as a low-cost alternative to individually genotyping thousands of samples on high-density SNP microarrays. Next, we describe software called “GenePool,” which directly analyzes SNP microarray probe intensity data and ranks SNPs by increased likelihood of being genetically associated with a trait or disorder. Finally, we apply these methods to experimental case-control data and demonstrate successful identification of published genetic susceptibility loci for a rare monogenic disease (sudden infant death with dysgenesis of the testes syndrome), a rare complex disease (progressive supranuclear palsy), and a common complex disease (Alzheimer disease) across multiple SNP genotyping platforms. On the basis of these theoretical calculations and their experimental validation, our results suggest that pooling-based GWA studies are a logical first step for determining whether major genetic associations exist in diseases with high heritability.

The role of mitochondrial dysfunction in the pathogenesis of Alzheimer's disease (AD) has been well documented. Though evidence for the role of mitochondria in AD seems incontrovertible, the impact of mitochondrial DNA (mtDNA) mutations in AD etiology remains controversial. Though mutations in mitochondrially encoded genes have repeatedly been implicated in the pathogenesis of AD, many of these studies have been plagued by lack of replication as well as potential contamination of nuclear-encoded mitochondrial pseudogenes. To assess the role of mtDNA mutations in the pathogenesis of AD, while avoiding the pitfalls of nuclear-encoded mitochondrial pseudogenes encountered in previous investigations and showcasing the benefits of a novel resequencing technology, we sequenced the entire coding region (15,452 bp) of mtDNA from 19 extremely well-characterized AD patients and 18 age-matched, unaffected controls utilizing a new, reliable, high-throughput array-based resequencing technique, the Human MitoChip. High-throughput, array-based DNA resequencing of the entire mtDNA coding region from platelets of 37 subjects revealed the presence of 208 loci displaying a total of 917 sequence variants. There were no statistically significant differences in overall mutational burden between cases and controls, however, 265 independent sites of statistically significant change between cases and controls were identified. Changed sites were found in genes associated with complexes I (30.2%), III (3.0%), IV (33.2%), and V (9.1%) as well as tRNA (10.6%) and rRNA (14.0%). Despite their statistical significance, the subtle nature of the observed changes makes it difficult to determine whether they represent true functional variants involved in AD etiology or merely naturally occurring dissimilarity. Regardless, this study demonstrates the tremendous value of this novel mtDNA resequencing platform, which avoids the pitfalls of erroneously amplifying nuclear-encoded mtDNA pseudogenes, and our proposed analysis paradigm, which utilizes the availability of raw signal intensity values for each of the four potential alleles to facilitate quantitative estimates of mtDNA heteroplasmy. This information provides a potential new target for burgeoning diagnostics and therapeutics that could truly assist those suffering from this devastating disorder.

Electron microscopy has a pivotal role as an analytical tool in pharmaceutical research. However, digital image data have proven to be too large for efficient quantitative analysis. We describe here the development and application of an automated image processing (AIP) program that rapidly quantifies shape measurements of recombinant adenovirus (rAd) obtained from digitized field emission scanning electron microscope (FESEM) images. The program was written using the macro-recording features within Image-Pro® Plus software. The macro program, which is linked to a Microsoft Excel spreadsheet, consists of a series of subroutines designed to automatically measure rAd vector objects from the FESEM images. The application and utility of this macro program has enabled us to rapidly and efficiently analyze very large data sets of rAd samples while minimizing operator time.

Genomic analyses of cutaneous melanoma (CM) have yielded biological and therapeutic insights, but understanding of non-ultraviolet (UV)-derived CMs remains limited. Deeper analysis of acral lentiginous melanoma (ALM), a rare sun-shielded melanoma subtype associated with worse survival than CM, is needed to delineate non-UV oncogenic mechanisms. We thus performed comprehensive genomic and transcriptomic analysis of 34 ALM patients. Unlike CM, somatic alterations were dominated by structural variation and absence of UV-derived mutation signatures. Only 38% of patients demonstrated driver BRAF/NRAS/NF1 mutations. Contrasting with CM, we observed PAK1 copy gains in 15% of patients, and somatic TERT translocations, copy gains, and missense and promoter mutations, or germline events, in 41% of patients. We further show that in vitro TERT inhibition has cytotoxic effects on primary ALM cells. These findings provide insight into the role of TERT in ALM tumorigenesis, and reveal preliminary evidence that TERT inhibition represents a potential therapeutic strategy in ALM. Citation Format: Winnie S. Liang, William Hendricks, Jeffrey Kiefer, Jessica Schmidt, Shobana Sekar, John Carpten, David W. Craig, Jonathan Adkins, Lori Cuyugan, Zarko Manojlovic, Rebecca F. Halperin, Adrienne Helland, Sara Nasser, Christophe Legendre, Laurence H. Hurley, Karthigayini Sivaprakasam, Douglas B. Johnson, Holly Crandall, Klaus J. Busam, Victoria Zismann, Valerie De Luca, Jeeyun Lee, Aleksandar Sekulic, Charlotte E. Ariyan, Jeffrey Sosman, Jeffrey Trent. Integrated genomic analyses reveal frequent TERT aberrations in acral melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3389. doi:10.1158/1538-7445.AM2017-3389

Archival tumor samples present a rich resource of annotated specimens for genomics research. However, standard variant calling approaches require a matched normal sample from the same individual, which is often not available with archival tissue. Without a matched normal sample, it is very difficult to distinguish between true somatic variants and germline variants that are private to the individual. Archival FFPE sections often contain adjacent normal tissue, but this normal tissue is often contaminated with infiltrating tumor cells. Comparative somatic variant callers are designed to exclude variants present in the normal sample, so a novel approach is required to leverage sequencing of adjacent normal tissue. Here we present LumosVar 2.0, a software package designed to jointly analyze multiple samples from the same patient. The approach is based on the concept that the allelic fraction of somatic variants, but not germline variants, would be diluted by the presence of normal tissue. Given the allele specific copy number state and expected tumor fraction of each sample, one can model the expected allelic fractions of somatic and germline variants. LumosVar estimates allele specific copy number and tumor sample fractions from the data, and uses the model to call somatic and germline variants. LumosVar is also able to detect sub clonal events and spatial heterogeneity between samples. To evaluate this approach, we used a glioblastoma dataset, where enhancing (high tumor content) and non-enhancing (low tumor content) samples were available for each patient, as well as the matched normal sample to define the true somatic variants. We show that both sensitivity and positive predictive value are improved by analyzing the high tumor and low tumor jointly compared to analyzing the samples individually or in silico pooling of the two samples. Finally, we apply this approach to a set of breast and prostate archival FFPE tumor samples where normal samples were not available for germline sequencing. Citation Format: Rebecca F. Halperin, Winnie S. Liang, Erica Tassone, Jonathan Adkins, Megan Russell, Nhan Tran, Nicole Hank, James Newell, Sandeep Gupta, Michael Berens, Ronald Korn, David W. Craig, Sara A. Byron. Leveraging spatial heterogeneity in tumor purity for improved somatic variant calling of archival tumor-only samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-007. doi:10.1158/1538-7445.AM2017-LB-007

2031Background: Pts with recurrent glioblastoma have median survival between 4 to 8 months. "Precision-based" therapies have not been used in this patient population. The goal of this trial was to determine the feasibility to make individualized treatment recommendations within at least 35 days of tumor tissue collection, using whole exome and RNA sequencing based upon those alterations. A sample size of at least 15 patients with sufficient tumor RNA and DNA was used to determine feasibility. Pts. had the option of accepting the recommendation or being treated using other treatment strategies. Adult patients with recurrent glioblastoma who were undergoing tumor resection at the time of relapse as part of their standard of care management were eligible. Methods: Tumor tissue was removed from both enhancing and non-enhancing regions of tumor and characterized by whole exome and RNA sequencing. Molecular profiles were done at Translational Genomics Research Institute (TGen), in a CLIA lab, matching genomic a...

Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.

The effort to make medicine preventative should include the development of systems to detect disease before the appearance of major symptoms. The value of early detection is widely accepted and has been the spur to develop new biomarkers of disease that enable earlier diagnosis and treatment. Over 100,000 biomarkers have been reported in the literature to date 1 yet there are only 43 approved by the FDA 2 including 19 genomic markers 3. This low return on investment for biomarker discovery suggests that new approaches are needed. Here we characterize a method that has been proposed as an alternative strategy for biomarker discovery. Discovery of biomarkers for early diagnosis of disease poses exceptional demands. For example, in the case of cancer, in order to detect the small number of cells in an early tumor one has to overcome the blood dilution problem. For example, if 106 initiating cancer cells release 1000 molecules each of a biomarker into five liters of blood at steady state, the concentration of this biomarker would only be 3 × 10−14 m. Clearly, it would be an advantage if the response to the biomarker could be amplified. Antibodies are ideal in this sense. An activated B cell produces 5000–20,000 antibodies per minute 4, 5 and the cell itself replicates every ∼70 h 6 with a lifespan of up to 4 ½ months 7, 8 leading to ∼1011 amplification of a specific signal in 1 week. Unpurified antibodies are stable in blood, unlike other biomarkers, opening up the possibility of testing historical samples 9. There are three key issues relative to using antibodies as biomarkers of early disease. Do they respond to diseases other than infections? Do they respond early in the course of disease? Can these antibodies be identified with a simple and inexpensive detection system? There are reports in diabetes 10, arthritis 11, and cancer 12 that the humoral response is activated specifically and early in these chronic diseases. A number of autoantibodies have been identified that appear months or years before the disease is first diagnosed 13–15. In the case of Type I diabetes, antibodies against GAD, IA2 and insulin are found in various combinations well before the onset of clinical disease 16. In patients with paraneoplastic syndrome, specific neurological symptoms appear years before a cancer is detected 17–19. The immune response to the nascent tumor reacts with neurons to elicit neurological symptoms 20 that correlate with future tumor appearance. These examples for cancer, diabetes and arthritis also address the second issue: is there an immune response among different individuals that appears early in patients with the same disease? The fact that the same autoantigens, or symptoms in the case of paraneoplastic syndrome, commonly occur indicates that antibodies might also be consistent across patients. The third issue, and the one we address here, is how to detect the informative antibodies in an efficient and simple way. Most antibody biomarkers were the product of arduous research. Protein microarrays have facilitated this process 21 by immobilizing most of the proteins from a pathogen or human onto a glass slide, but these arrays are expensive, exclude non-transcribed antigens, and are pathogen or auto-antibody specific. The ProtoArrayTM v5 of Invitrogen currently has ∼9000 unique human proteins; these can detect autoantigens associated with a specific disease. However, only autoantigens can be discovered and the cost impedes epidemiology-sized studies. A more complicated approach has been to biochemically fractionated cellular proteins, spot and then react these fractions with patient sera 22. Although this method does use authentic material, it is limited by having no control over the relative amounts of proteins spotted, and it requires cells from the case subjects' own tissue. Screening for antibody reactivity to random peptides has been generally successful when using phage or mRNA display of random 8–12 amino acid sequences. Pasqualini and Ruosiahti 23 panned a phage library against sera from cancer and healthy subjects to find phage that were preferentially bound by the cancer associated antibodies. This method is unbiased as to the nature of the antigen, and the antibody can eventually be captured (if arduously). Given that random sequence peptides can yield mimotopes of almost any type of antigen 24, any disease-associated antigen could theoretically be detected. However promising this method appeared, to date this approach has not produced disease biomarkers for a number of reasons. A serious limitation is that the recurrent panning of the phage is subject to many influences besides just binding of the antibody, it does not lend itself to large numbers of samples, and there is no simple way to measure intermediate or low binding. In order to discover and display relevant antibodies contained in the 1010 antibody complexity in humans, we explored a technology (PCT/US2010/039269, “Compound Arrays for Sample Profiling”) for antibody biomarker discovery that combines simple, rapid and inexpensive assays from microarrays with the enhanced breadth of the ligand repertoire found in phage-based systems. We created microarrays with only 10,000 random sequence peptides but chose a relatively long length (17 amino acids + 3 residue linker) to allow each peptide to encompass much more complexity than typical epitope peptides. The random sequences allow an unbiased display of antibody binding; the length provides many possible epitope positions per peptide and (potentially) allows for some structural complexity. The array format allows the assay to be run without the biological complications of phage display and high-speed piezo printing onto commercially produced substrate allows thousands of microarrays to be consistently produced each month. We recently demonstrated the potential utility of these arrays by immunosignaturing vaccines, infections, and Alzheimer's disease 25,26. In order to utilize this technology as a clinical diagnostic, we must first characterize the physical and chemical properties of antibody binding to these peptide microarrays.

Spinocerebellar ataxia type 1 (SCA1) is an autosomal dominant neurological disorder caused by the expansion of a polyglutamine tract in the mutant protein ataxin-1. The cerebellar Purkinje cells (PCs) are the major targets of mutant ataxin-1. The mechanism of PC death in SCA1 is not known; however, previous work indicates that downregulation of specific proteins involved in calcium homeostasis and signaling by mutant ataxin-1 is the probable cause of PC degeneration in SCA1. In this study, we explored if targeted deprivation of PC specific calcium-binding protein calbindin-D28k (CaB) exacerbates ataxin-1 mediated toxicity in SCA1 transgenic (Tg) mice. Using behavioral tests, we found that though both SCA1/+ and SCA1/+: CaB null (−/+) double mutants exhibited progressive impaired performance on the rotating rod, a simultaneous enhancement of exploratory activity, and absence of deficits in coordination, the double mutants were more severely impaired than SCA1/+ mice. With increasing age, SCA1/+ mice showed a progressive loss in the expression and localization of CaB and other PC specific calcium-binding and signaling proteins. In double mutants, these changes were more pronounced and had an earlier onset. Gene expression profiling of young mice exhibiting no behavior or biochemical deficits revealed a differential expression of many genes common to SCA1/+ and CaB−/+ lines, and unique to SCA1/+: CaB−/+ phenotype. Our study provides further evidence for a critical role of CaB in SCA1 pathogenesis, which may help identify new therapeutic targets to treat SCA1 or other cerebellar ataxias.

A universal platform for efficiently mapping antibody epitopes would be of great use for many applications, ranging from antibody therapeutic development to vaccine design. Here we tested the feasibility of using a random peptide microarray to map antibody epitopes. Although peptide microarrays are physically constrained to ∼10(4) peptides per array, compared with 10(8) permitted in library panning approaches such as phage display, they enable a much more high though put and direct measure of binding. Long (20 mer) random sequence peptides were chosen for this study to look at an unbiased sampling of sequence space. This sampling of sequence space is sparse, as an exact epitope sequence is unlikely to appear. Commercial monoclonal antibodies with known linear epitopes or polyclonal antibodies raised against engineered 20-mer peptides were used to evaluate this array as an epitope mapping platform. Remarkably, peptides with the most sequence similarity to known epitopes were only slightly more likely to be recognized by the antibody than other random peptides. We explored the ability of two methods singly and in combination to predict the actual epitope from the random sequence peptides bound. Though the epitopes were not directly evident, subtle motifs were found among the top binding peptides for each antibody. These motifs did have some predictive ability in searching for the known epitopes among a set of decoy sequences. The second approach using a windowing alignment strategy, was able to score known epitopes of monoclonal antibodies well within the test dataset, but did not perform as well on polyclonals. Random peptide microarrays of even limited diversity may serve as a useful tool to prioritize candidates for epitope mapping or antigen identification.

Previous genome-wide linkage studies applied the affected sib-pair design; one investigated extended pedigrees of a genetic isolate. Here, results of a genome-wide high-density linkage scan of attention-deficit/hyperactivity disorder (ADHD) using an array-based genotyping of approximately 50 K single nucleotide polymorphism (SNPs) markers are presented. We investigated eight extended pedigrees of German origin that were non-related, not part of a genetic isolate and ascertained on the basis of clinical referral. Two parametric analyses maximizing LOD scores (MOD) and a non-parametric analysis for both a broad and a narrow phenotype approach were conducted. Novel linkage loci across all families were detected at 2q35, 5q13.1, 6q22-23 and 14q12, within individual families at 18q11.2-12.3. Further linkage regions at 7q21.11, 9q22 and 16q24.1 in all families, and at 1q25.1, 1q25.3, 9q31.1-33.1, 9q33, 12p13.33, 15q11.2-13.3 and 16p12.3-12.2 in individual families replicate previous findings. High-resolution linkage mapping points to several novel candidate genes characterized by dense expression in the brain and potential impact on disorder-relevant synaptic transmission. Our study provides further evidence for common gene effects throughout different populations despite the complex multifactorial etiology of ADHD.

A genome-wide association (GWA) study with pooled DNA in adult attention-deficit/hyperactivity disorder (ADHD) employing approximately 500K SNP markers identifies novel risk genes and reveals remarkable overlap with findings from recent GWA scans in substance use disorders. Comparison with results from our previously reported high-resolution linkage scan in extended pedigrees confirms several chromosomal loci, including 16q23.1-24.3 which also reached genome-wide significance in a recent meta-analysis of seven linkage studies (Zhou et al. in Am J Med Genet Part B, 2008). The findings provide additional support for a common effect of genes coding for cell adhesion molecules (e.g., CDH13, ASTN2) and regulators of synaptic plasticity (e.g., CTNNA2, KALRN) despite the complex multifactorial etiologies of adult ADHD and addiction vulnerability.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressively disabling impairments in memory, cognition, and non-cognitive behavioural symptoms. Sporadic AD is multifactorial and genetically complex. While several monogenic mutations cause early-onset AD and gene alleles have been suggested as AD susceptibility factors, the only extensively validated susceptibility gene for late-onset AD is the apolipoprotein E (APOE) epsilon4 allele. Alleles of the APOE gene do not account for all of the genetic load calculated to be responsible for AD predisposition. Recently, polymorphisms across the neuronal sortilin-related receptor (SORL1) gene were shown to be significantly associated with AD in several cohorts. Here we present the results of our large case-control whole-genome scan at over 500,000 polymorphisms which presents weak evidence for association and potentially narrows the association interval.

Background It has been estimated that more than 50% of patients with Neurofibromatosis type 1 (NF1) have neurobehavioral impairments which include attention deficit/hyperactivity disorder, visual/spatial learning disabilities, and a myriad of other cognitive developmental problems. The biological mechanisms by which NF1 gene mutations lead to such cognitive deficits are not well understood, although excessive Ras signaling and increased GABA mediated inhibition have been implicated. It is proposed that the cognitive deficits in NF1 are the result of dysfunctional cellular trafficking and localization of molecules downstream of the primary gene defect. Results To elucidate genes involved in the pathogenic process, gene expression analysis was performed comparing the expression profiles in various brain regions for control and Nf1 +/- heterozygous mice. Gene expression analysis was performed for hippocampal samples dissected from postnatal day 10, 15, and 20 mice utilizing the Affymetrix Mouse Genome chip (Murine 430 2.0). Analysis of expression profiles between Nf1 +/-and wild-type animals was focused on the hippocampus because of previous studies demonstrating alterations in hippocampal LTP in the Nf1 +/- mice, and the region's importance in visual/spatial learning. Network analysis identified links between neurofibromin and kinesin genes, which were down regulated in the Nf1 +/- mice at postnatal days 15 and 20. Conclusion Through this analysis, it is proposed that neurofibromin forms a binding complex with amyloid precursor protein (APP) and through filamin proteins interacts with a dopamine receptor (Drd3). Though the effects of these interactions are not yet known, this information may provide novel ideas about the pathogenesis of cognitive defects in NF1 and may facilitate the development of novel targeted therapeutic interventions.