TTSBBC: triplex target site biomarkers and barcodes in cancer.

The technology of triplex-forming oligonucleotides (TFOs) provides an approach to manipulate genes at the DNA level. TFOs bind to specific sites on genomic DNA, creating a unique intermolecular triple-helix DNA structure through Hoogsteen hydrogen bonding. This targeting by TFOs is site-specific and the locations TFOs bind are referred to as TFO target sites (TTS). Triplexes have been observed to selectively influence gene expression, homologous recombination, mutations, protein binding, and DNA damage. These sites typically feature a poly-purine sequence in duplex DNA, and the characteristics of these TTS sequences greatly influence the formation of the triplex. We introduce TTSBBC, a novel analysis and visualization platform designed to explore features of TTS sequences to enable users to design and validate TTSs. The web server can be freely accessed at https://kowalski-labapps.dellmed.utexas.edu/TTSBBC/.

MoCoLo: a testing framework for motif co-localization.

Sequence-level data offers insights into biological processes through the interaction of two or more genomic features from the same or different molecular data types. Within motifs, this interaction is often explored via the co-occurrence of feature genomic tracks using fixed-segments or analytical tests that respectively require window size determination and risk of false positives from over-simplified models. Moreover, methods for robustly examining the co-localization of genomic features, and thereby understanding their spatial interaction, have been elusive. We present a new analytical method for examining feature interaction by introducing the notion of reciprocal co-occurrence, define statistics to estimate it and hypotheses to test for it. Our approach leverages conditional motif co-occurrence events between features to infer their co-localization. Using reverse conditional probabilities and introducing a novel simulation approach that retains motif properties (e.g. length, guanine-content), our method further accounts for potential confounders in testing. As a proof-of-concept, motif co-localization (MoCoLo) confirmed the co-occurrence of histone markers in a breast cancer cell line. As a novel analysis, MoCoLo identified significant co-localization of oxidative DNA damage within non-B DNA-forming regions that significantly differed between non-B DNA structures. Altogether, these findings demonstrate the potential utility of MoCoLo for testing spatial interactions between genomic features via their co-localization.

Whole-Exome Sequencing Reveals High Mutational Concordance between Primary and Matched Recurrent Triple-Negative Breast Cancers.

PURPOSE: Triple-negative breast cancer (TNBC) is a molecularly complex and heterogeneous breast cancer subtype with distinct biological features and clinical behavior. Although TNBC is associated with an increased risk of metastasis and recurrence, the molecular mechanisms underlying TNBC metastasis remain unclear. We performed whole-exome sequencing (WES) analysis of primary TNBC and paired recurrent tumors to investigate the genetic profile of TNBC. METHODS: Genomic DNA extracted from 35 formalin-fixed paraffin-embedded tissue samples from 26 TNBC patients was subjected to WES. Of these, 15 were primary tumors that did not have recurrence, and 11 were primary tumors that had recurrence (nine paired primary and recurrent tumors). Tumors were analyzed for single-nucleotide variants and insertions/deletions. RESULTS: The tumor mutational burden (TMB) was 7.6 variants/megabase in primary tumors that recurred (n = 9); 8.2 variants/megabase in corresponding recurrent tumors (n = 9); and 7.3 variants/megabase in primary tumors that did not recur (n = 15). MUC3A was the most frequently mutated gene in all groups. Mutations in MAP3K1 and MUC16 were more common in our dataset. No alterations in PI3KCA were detected in our dataset. CONCLUSIONS: We found similar mutational profiles between primary and paired recurrent tumors, suggesting that genomic features may be retained during local recurrence.

myCMIE: My cancer molecular information exchange.

Molecular profiling reports (MPRs) are critical for determining treatment options for cancer patients. They include several pages of information on genomic findings, drugs, and trial options that are challenging to synthesize for effectively and expeditiously informing on treatment. Xu and Kowalski present a web application, myCMIE, that synthesizes MPR content to define a patient-centric, information system in which molecular profiles are exchanged between a query case(s) and public resources or user-input case series for context-informed treatment and conjecture with therapeutic implication. myCMIE offers an interactive build of coordinately connected digital-twin communities to expand our understanding of treatment context with multiple visuals to stimulate discussions among diverse stakeholders in care.

NBBC: a non-B DNA burden explorer in cancer.

Alternate (non-B) DNA-forming structures, such as Z-DNA, G-quadruplex, triplex have demonstrated a potential role in cancer etiology. It has been found that non-B DNA-forming sequences can stimulate genetic instability in human cancer genomes, implicating them in the development of cancer and other genetic diseases. While there exist several non-B prediction tools and databases, they lack the ability to both analyze and visualize non-B data within a cancer context. Herein, we introduce NBBC, a non-B DNA burden explorer in cancer, that offers analyses and visualizations for non-B DNA forming motifs. To do so, we introduce 'non-B burden' as a metric to summarize the prevalence of non-B DNA motifs at the gene-, signature- and genomic site-levels. Using our non-B burden metric, we developed two analyses modules within a cancer context to assist in exploring both gene- and motif-level non-B type heterogeneity among gene signatures. NBBC is designed to serve as a new analysis and visualization platform for the exploration of non-B DNA, guided by non-B burden as a novel marker.

A Case Series Exploration of Multi-Regional Expression Heterogeneity in Triple-Negative Breast Cancer Patients.

Extensive intratumoral heterogeneity (ITH) is believed to contribute to therapeutic failure and tumor recurrence, as treatment-resistant cell clones can survive and expand. However, little is known about ITH in triple-negative breast cancer (TNBC) because of the limited number of single-cell sequencing studies on TNBC. In this study, we explored ITH in TNBC by evaluating gene expression-derived and imaging-derived multi-region differences within the same tumor. We obtained tissue specimens from 10 TNBC patients and conducted RNA sequencing analysis of 2-4 regions per tumor. We developed a novel analysis framework to dissect and characterize different types of variability: between-patients (inter-tumoral heterogeneity), between-patients across regions (inter-tumoral and region heterogeneity), and within-patient, between-regions (regional intratumoral heterogeneity). We performed a Bayesian changepoint analysis to assess and classify regional variability as low (convergent) versus high (divergent) within each patient feature (TNBC and PAM50 subtypes, immune, stroma, tumor counts and tumor infiltrating lymphocytes). Gene expression signatures were categorized into three types of variability: between-patients (108 genes), between-patients across regions (183 genes), and within-patients, between-regions (778 genes). Based on the between-patient gene signature, we identified two distinct patient clusters that differed in menopausal status. Significant intratumoral divergence was observed for PAM50 classification, tumor cell counts, and tumor-infiltrating T cell abundance. Other features examined showed a representation of both divergent and convergent results. Lymph node stage was significantly associated with divergent tumors. Our results show extensive intertumoral heterogeneity and regional ITH in gene expression and image-derived features in TNBC. Our findings also raise concerns regarding gene expression based TNBC subtyping. Future studies are warranted to elucidate the role of regional heterogeneity in TNBC as a driver of treatment resistance.

Covalent JNK Inhibitor, JNK-IN-8, Suppresses Tumor Growth in Triple-Negative Breast Cancer by Activating TFEB- and TFE3-Mediated Lysosome Biogenesis and Autophagy.

The heterogeneity and aggressiveness of triple-negative breast cancer (TNBC) contribute to its early recurrence and metastasis. Despite substantial research to identify effective therapeutic targets, TNBC remains elusive in terms of improving patient outcomes. Here, we report that a covalent JNK inhibitor, JNK-IN-8, suppresses TNBC growth both in vitro and in vivo. JNK-IN-8 reduced colony formation, cell viability, and organoid growth in vitro and slowed patient-derived xenograft and syngeneic tumor growth in vivo. Cells treated with JNK-IN-8 exhibited large, cytoplasmic vacuoles with lysosomal markers. To examine the molecular mechanism of this phenotype, we looked at the master regulators of lysosome biogenesis and autophagy transcription factor EB (TFEB) and TFE3. JNK-IN-8 inhibited TFEB phosphorylation and induced nuclear translocation of unphosphorylated TFEB and TFE3. This was accompanied by an upregulation of TFEB/TFE3 target genes associated with lysosome biogenesis and autophagy. Depletion of both TFEB and TFE3 diminished the JNK-IN-8-driven upregulation of lysosome biogenesis and/or autophagy markers. TFEB and TFE3 are phosphorylated by a number of kinases, including mTOR. JNK-IN-8 reduced phosphorylation of mTOR targets in a concentration-dependent manner. Knockout of JNK1 and/or JNK2 had no impact on TFEB/TFE3 activation or mTOR inhibition by JNK-IN-8 but inhibited colony formation. Similarly, reexpression of either wildtype or drug-nonbinding JNK (C116S) in JNK knockout cells did not reverse JNK-IN-8-induced TFEB dephosphorylation. In summary, JNK-IN-8 induced lysosome biogenesis and autophagy by activating TFEB/TFE3 via mTOR inhibition independently of JNK. Together, these findings demonstrate the efficacy of JNK-IN-8 as a targeted therapy for TNBC and reveal its novel lysosome- and autophagy-mediated mechanism of action.

Distinct Gene Expression Profiles of Matched Primary and Metastatic Triple-Negative Breast Cancers.

Background: Although triple-negative breast cancer (TNBC) is associated with an increased risk of recurrence and metastasis, the molecular mechanisms underlying metastasis in TNBC remain unknown. To identify transcriptional changes and genes regulating metastatic progression in TNBC, we compared the transcriptomic profiles of primary and matched metastatic tumors using massively parallel RNA sequencing. Methods: We performed gene expression profiling using formalin-fixed paraffin-embedded (FFPE) TNBC tissues of patients from two cohorts: the Zurich cohort (n = 31) and the Stavanger cohort (n = 5). Among the 31 patients in the Zurich cohort, 18 had primary TNBC tumors that did not metastasize, and 13 had primary tumors that metastasized (11 paired primary and locoregional recurrences). The Stavanger cohort included five matched primary and metastatic TNBC tumors. Significantly differentially expressed genes (DEGs; absolute fold change ≥2, p < 0.05) were identified and subjected to functional analyses. We investigated if there was any overlap between DEGs from both the cohorts with epithelial-to-mesenchymal-to-amoeboid transition (EMAT) gene signature. xCell was used to estimate relative fractions of 64 immune and stromal cell types in each RNA-seq sample. Results: In the Zurich cohort, we identified 1624 DEGs between primary TNBC tumors and matched metastatic lesions. xCell analysis revealed a significantly higher immune scores for metastatic lesions compared to paired primary tumors in the Zurich cohort. We also found significant upregulation of three MammaPrint signature genes (HRASLS, TGFB3 and RASSF7) in primary tumors that metastasized compared to primary tumors that remained metastasis-free. In the Stavanger cohort, we identified 818 DEGs between primary tumors and matched metastatic lesions. No significant differences in xCell immune scores were observed. We found that 21 and 14 DEGs from Zurich and Stavanger cohort, respectively, overlapped with the EMAT gene signature. In both cohorts, genes belonging to the MMP, FGF, and PDGFR families were upregulated in primary tumors compared to matched metastatic lesions. Conclusions: Our results suggest that distinct gene expression patterns exist between primary TNBCs and matched metastatic tumors. Further studies are warranted to explore whether these discrete expression profiles underlie or result from disease status.

An experimental-mathematical approach to predict tumor cell growth as a function of glucose availability in breast cancer cell lines.

We present the development and validation of a mathematical model that predicts how glucose dynamics influence metabolism and therefore tumor cell growth. Glucose, the starting material for glycolysis, has a fundamental influence on tumor cell growth. We employed time-resolved microscopy to track the temporal change of the number of live and dead tumor cells under different initial glucose concentrations and seeding densities. We then constructed a family of mathematical models (where cell death was accounted for differently in each member of the family) to describe overall tumor cell growth in response to the initial glucose and confluence conditions. The Akaikie Information Criteria was then employed to identify the most parsimonious model. The selected model was then trained on 75% of the data to calibrate the system and identify trends in model parameters as a function of initial glucose concentration and confluence. The calibrated parameters were applied to the remaining 25% of the data to predict the temporal dynamics given the known initial glucose concentration and confluence, and tested against the corresponding experimental measurements. With the selected model, we achieved an accuracy (defined as the fraction of measured data that fell within the 95% confidence intervals of the predicted growth curves) of 77.2 ± 6.3% and 87.2 ± 5.1% for live BT-474 and MDA-MB-231 cells, respectively.

Acetylation of KLF5 maintains EMT and tumorigenicity to cause chemoresistant bone metastasis in prostate cancer.

Advanced prostate cancer (PCa) often develops bone metastasis, for which therapies are very limited and the underlying mechanisms are poorly understood. We report that bone-borne TGF-ß induces the acetylation of transcription factor KLF5 in PCa bone metastases, and acetylated KLF5 (Ac-KLF5) causes osteoclastogenesis and bone metastatic lesions by activating CXCR4, which leads to IL-11 secretion, and stimulating SHH/IL-6 paracrine signaling. While essential for maintaining the mesenchymal phenotype and tumorigenicity, Ac-KLF5 also causes resistance to docetaxel in tumors and bone metastases, which is overcome by targeting CXCR4 with FDA-approved plerixafor. Establishing a mechanism for bone metastasis and chemoresistance in PCa, these findings provide a rationale for treating chemoresistant bone metastasis of PCa with inhibitors of Ac-KLF5/CXCR4 signaling.

Melanoma Cell Intrinsic GABAA Receptor Enhancement Potentiates Radiation and Immune Checkpoint Inhibitor Response by Promoting Direct and T Cell-Mediated Antitumor Activity.

PURPOSE: Most patients with metastatic melanoma show variable responses to radiation therapy and do not benefit from immune checkpoint inhibitors. Improved strategies for combination therapy that leverage potential benefits from radiation therapy and immune checkpoint inhibitors are critical. METHODS AND MATERIALS: We analyzed metastatic melanoma tumors in the TCGA cohort for expression of genes coding for subunits of type A γ-aminobutyric acid (GABA) receptor (GABAAR), a chloride ion channel and major inhibitory neurotransmitter receptor. Electrophysiology was used to determine whether melanoma cells possess intrinsic GABAAR activity. Melanoma cell viability studies were conducted to test whether enhancing GABAAR mediated chloride transport using benzodiazepine-impaired viability. A syngeneic melanoma mouse model was used to assay the effect of benzodiazepine on tumor volume and its ability to potentiate radiation therapy or immunotherapy. Treated tumors were analyzed for changes in gene expression by RNA sequencing and presence of tumor-infiltrating lymphocytes by flow cytometry. RESULTS: Genes coding for subunits of GABAARs express functional GABAARs in melanoma cells. By enhancing GABAAR-mediated anion transport, benzodiazepines depolarize melanoma cells and impair their viability. In vivo, benzodiazepine alone reduces tumor growth and potentiates radiation therapy and α-PD-L1 antitumor activity. The combination of benzodiazepine, radiation therapy, and α-PD-L1 results in near complete regression of treated tumors and a potent abscopal effect, mediated by increased infiltration of polyfunctional CD8+ T cells. Treated tumors show expression of cytokine-cytokine receptor interactions and overrepresentation of p53 signaling. CONCLUSIONS: This study identifies an antitumor strategy combining radiation and/or an immune checkpoint inhibitor with modulation of GABAARs in melanoma using benzodiazepine.

Evaluating patient-specific neoadjuvant regimens for breast cancer via a mathematical model constrained by quantitative magnetic resonance imaging data.

The ability to accurately predict response and then rigorously optimize a therapeutic regimen on a patient-specific basis, would transform oncology. Toward this end, we have developed an experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into a biophysical model to predict patient-specific treatment response of locally advanced breast cancer to neoadjuvant therapy. Diffusion-weighted and dynamic contrast-enhanced MRI data is collected prior to therapy, after 1 cycle of therapy, and at the completion of the first therapeutic regimen. The model is initialized and calibrated with the first 2 patient-specific MRI data sets to predict response at the third, which is then compared to patient outcomes (N = 18). The model's predictions for total cellularity, total volume, and the longest axis at the completion of the regimen are significant within expected measurement precision (P< 0.05) and strongly correlated with measured response (P < 0.01). Further, we use the model to investigate, in silico, a range of (practical) alternative treatment plans to achieve the greatest possible tumor control for each individual in a subgroup of patients (N = 13). The model identifies alternative dosing strategies predicted to achieve greater tumor control compared to the standard of care for 12 of 13 patients (P < 0.01). In summary, a predictive, mechanism-based mathematical model has demonstrated the ability to identify alternative treatment regimens that are forecasted to outperform the therapeutic regimens the patients clinically. This has important implications for clinical trial design with the opportunity to alter oncology care in the future.

Signatures of somatic mutations and gene expression from p16INK4A positive head and neck squamous cell carcinomas (HNSCC).

Human papilloma virus (HPV) causes a subset of head and neck squamous cell carcinomas (HNSCC) of the oropharynx. We combined targeted DNA- and genome-wide RNA-sequencing to identify genetic variants and gene expression signatures respectively from patients with HNSCC including oropharyngeal squamous cell carcinomas (OPSCC). DNA and RNA were purified from 35- formalin fixed and paraffin embedded (FFPE) HNSCC tumor samples. Immuno-histochemical evaluation of tumors was performed to determine the expression levels of p16INK4A and classified tumor samples either p16+ or p16-. Using ClearSeq Comprehensive Cancer panel, we examined the distribution of somatic mutations. Somatic single-nucleotide variants (SNV) were called using GATK-Mutect2 ("tumor-only" mode) approach. Using RNA-seq, we identified a catalog of 1,044 and 8 genes as significantly expressed between p16+ and p16-, respectively at FDR 0.05 (5%) and 0.1 (10%). The clinicopathological characteristics of the patients including anatomical site, smoking and survival were analyzed when comparing p16+ and p16- tumors. The majority of tumors (65%) were p16+. Population sequence variant databases, including gnomAD, ExAC, COSMIC and dbSNP, were used to identify the mutational landscape of somatic sequence variants within sequenced genes. Hierarchical clustering of The Cancer Genome Atlas (TCGA) samples based on HPV-status was observed using differentially expressed genes. Using RNA-seq in parallel with targeted DNA-seq, we identified mutational and gene expression signatures characteristic of p16+ and p16- HNSCC. Our gene signatures are consistent with previously published data including TCGA and support the need to further explore the biologic relevance of these alterations in HNSCC.

Epigenetically heterogeneous tumor cells direct collective invasion through filopodia-driven fibronectin micropatterning.

Tumor heterogeneity drives disease progression, treatment resistance, and patient relapse, yet remains largely underexplored in invasion and metastasis. Here, we investigated heterogeneity within collective cancer invasion by integrating DNA methylation and gene expression analysis in rare purified lung cancer leader and follower cells. Our results showed global DNA methylation rewiring in leader cells and revealed the filopodial motor MYO10 as a critical gene at the intersection of epigenetic heterogeneity and three-dimensional (3D) collective invasion. We further identified JAG1 signaling as a previously unknown upstream activator of MYO10 expression in leader cells. Using live-cell imaging, we found that MYO10 drives filopodial persistence necessary for micropatterning extracellular fibronectin into linear tracks at the edge of 3D collective invasion exclusively in leaders. Our data fit a model where epigenetic heterogeneity and JAG1 signaling jointly drive collective cancer invasion through MYO10 up-regulation in epigenetically permissive leader cells, which induces filopodia dynamics necessary for linearized fibronectin micropatterning.

Prognostic significance of an invasive leader cell-derived mutation cluster on chromosome 16q.

BACKGROUND: Intratumoral heterogeneity is defined by subpopulations with varying genotypes and phenotypes. Specialized, highly invasive leader cells and less invasive follower cells are phenotypically distinct subpopulations that cooperate during collective cancer invasion. Because leader cells are a rare subpopulation that would be missed by bulk sequencing, a novel image-guided genomics platform was used to precisely select this subpopulation. This study identified a novel leader cell mutation signature and tested its ability to predict prognosis in non-small cell lung cancer (NSCLC) patient cohorts. METHODS: Spatiotemporal genomic and cellular analysis was used to isolate and perform RNA sequencing on leader and follower populations from the H1299 NSCLC cell line, and it revealed a leader-specific mutation cluster on chromosome 16q. Genomic data from patients with lung squamous cell carcinoma (LUSC; n = 475) and lung adenocarcinoma (LUAD; n = 501) from The Cancer Genome Atlas were stratified by 16q mutation cluster (16qMC) status (16qMC+ vs 16qMC-) and compared for overall survival (OS), progression-free survival (PFS), and gene set enrichment analysis (GSEA). RESULTS: Poorer OS, poorer PFS, or both were found across all stages and among early-stage patients with 16qMC+ tumors within the LUSC and LUAD cohorts. GSEA revealed 16qMC+ tumors to be enriched for the expression of metastasis- and survival-associated gene sets. CONCLUSIONS: This represents the first leader cell mutation signature identified in patients and has the potential to better stratify high-risk NSCLC and ultimately improve patient outcomes.

Impact of Sequencing Radiation Therapy and Immune Checkpoint Inhibitors in the Treatment of Melanoma Brain Metastases.

PURPOSE: Melanoma brain metastases (MBM) occur in ∼50% of melanoma patients. Although both radiation therapy (RT) and immune checkpoint inhibitor (ICI) are used alone or in combination for MBM treatment, the role of this combination and how these treatments could best be sequenced remains unclear. METHODS AND MATERIALS: We conducted a retrospective analysis of patients with resected MBM who underwent treatment with RT, ICI, or a combination of RT and ICI. Among the latter, we specifically investigated the differential gene expression via RNA-sequencing between patients who received RT first then ICI (RT → ICI) versus ICI first then RT (ICI → RT). We used a glycoprotein-transduced syngeneic melanoma mouse model for validation experiments. RESULTS: We found that for patients with resected MBM, a combination of RT and ICI confers superior survival compared with RT alone. Specifically, we found that RT → ICI was superior compared with ICI → RT. Transcriptome analysis of resected MBM revealed that the RT → ICI cohort demonstrated deregulation of genes involved in apoptotic signaling and key modulators of inflammation that are most implicated in nuclear factor kappa-light-chain-enhancer of activated B cells signaling. In a preclinical model, we showed that RT followed by anti-programmed death-ligand 1 therapy was superior to the reverse sequence of therapy, supporting the observations we made in patients with MBM. CONCLUSIONS: Our study provides initial insights into the optimal sequence of RT and ICI in the treatment of MBM after surgical resection. Prospective studies examining the best sequence of RT and ICI are necessary, and our study contributes to the rationale to pursue these.

ETV2/ER71 regulates the generation of FLK1+ cells from mouse embryonic stem cells through miR-126-MAPK signaling.

Previous studies including ours have demonstrated a critical function of the transcription factor ETV2 (ets variant 2; also known as ER71) in determining the fate of cardiovascular lineage development. However, the underlying mechanisms of ETV2 function remain largely unknown. In this study, we demonstrated the novel function of the miR (micro RNA)-126-MAPK (mitogen-activated protein kinase) pathway in ETV2-mediated FLK1 (fetal liver kinase 1; also known as VEGFR2)+ cell generation from the mouse embryonic stem cells (mESCs). By performing a series of experiments including miRNA sequencing and ChIP (chromatin immunoprecipitation)-PCR, we found that miR-126 is directly induced by ETV2. Further, we identified that miR-126 can positively regulate the generation of FLK1+ cells by activating the MAPK pathway through targeting SPRED1 (sprouty-related EVH1 domain containing 1). Further, we showed evidence that JUN/FOS activate the enhancer region of FLK1 through AP1 (activator protein 1) binding sequences. Our findings provide insight into the novel molecular mechanisms of ETV2 function in regulating cardiovascular lineage development from mESCs.

Genetic heterogeneity within collective invasion packs drives leader and follower cell phenotypes.

Collective invasion, the coordinated movement of cohesive packs of cells, has become recognized as a major mode of metastasis for solid tumors. These packs are phenotypically heterogeneous and include specialized cells that lead the invasive pack and others that follow behind. To better understand how these unique cell types cooperate to facilitate collective invasion, we analyzed transcriptomic sequence variation between leader and follower populations isolated from the H1299 non-small cell lung cancer cell line using an image-guided selection technique. We now identify 14 expressed mutations that are selectively enriched in leader or follower cells, suggesting a novel link between genomic and phenotypic heterogeneity within a collectively invading tumor cell population. Functional characterization of two phenotype-specific candidate mutations showed that ARP3 enhances collective invasion by promoting the leader cell phenotype and that wild-type KDM5B suppresses chain-like cooperative behavior. These results demonstrate an important role for distinct genetic variants in establishing leader and follower phenotypes and highlight the necessity of maintaining a capacity for phenotypic plasticity during collective cancer invasion.

Gliosarcoma: distinct molecular pathways and genomic alterations identified by DNA copy number/SNP microarray analysis.

PURPOSE: Gliosarcoma is a histologic variant of glioblastoma (GBM), and like GBM carries a poor prognosis. Median survival is less than one (1) year with less than 5% of patients alive after 5 years. Although there is no cure, standard treatment includes surgery, radiation and chemotherapy. While very similar to GBM, gliosarcoma exhibits several distinct differences, morphologically and molecularly. Therefore, we report a comprehensive analysis of DNA copy number changes in gliosarcoma using a cytogenomic DNA copy number (CN) microarray (OncoScan®). METHODS: Cytogenomic DNA copy number microarray (OncoScan®) was performed on 18 cases of gliosarcoma. MetaCore™ enrichment was applied to the array results to detect associated molecular pathways. RESULTS: The most frequent alteration was copy number loss, comprising 57% of total copy number changes. The number of losses far exceeded the number of amplifications (***, < 0.001) and loss of heterozygosity events (***, < 0.001). Amplifications were infrequent (4.6%), particularly for EGFR. Chromosomes 9 and 10 had the highest number of losses; a large portion of which correlated to CDKN2A/B loss. Copy number gains were the second most common alteration (26.2%), with the majority occurring on chromosome 7. MetaCore™ enrichment detected notable pathways for copy number gains including: HOXA, Rho family of GTPases, and EGFR; copy number loss including: WNT, NF-kß, and CDKN2A; and copy number loss of heterozygosity including: WNT and p53. CONCLUSIONS: The pathways and copy number alterations detected in this study may represent key drivers in gliosarcoma oncogenesis and may provide a starting point toward targeted oncologic analysis with therapeutic potential.

Host Genome Variation is Associated with Neurocognitive Outcome in Survivors of Pediatric Medulloblastoma.

Host genome analysis is a promising source of predictive information for long-term morbidity in cancer survivors. However, studies on genetic predictors of long-term outcome, particularly neurocognitive function following chemoradiation in pediatric oncology, are limited. Here, we evaluated variation in host genome of long-term survivors of medulloblastoma and its association with neurocognitive outcome. Whole-genome sequencing was conducted on peripheral blood of long-term survivors of pediatric medulloblastoma who also completed neuropsychological testing. Cognitively impaired and less impaired survivors did not differ in exposure to chemoradiation therapy or age at treatment. Unsupervised consensus clustering yielded two distinct variant clusters that were significantly associated with neurocognitive outcome. Interestingly, 34 of the 36 significant variants were found in noncoding DNA regions with unknown regulatory function. A separate unsupervised cluster analysis of variants within DNA repair genes identified discrete variant groups that were not associated with neurocognitive outcome, suggesting that variations in genes corresponding to a single functional group may be insufficient to predict long-term outcome alone. These findings are supportive of the presence of a genetic diathesis for treatment-related neurocognitive morbidity in medulloblastoma that may be driven by variation in noncoding regulatory elements.