Sebastian M. Waszak
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View article: Supplementary Data from ONC201 in Combination with Paxalisib for the Treatment of H3K27-Altered Diffuse Midline Glioma
Supplementary Data from ONC201 in Combination with Paxalisib for the Treatment of H3K27-Altered Diffuse Midline Glioma Open
All Supplementary Tables
View article: Supplementary Data from ONC201 in Combination with Paxalisib for the Treatment of H3K27-Altered Diffuse Midline Glioma
Supplementary Data from ONC201 in Combination with Paxalisib for the Treatment of H3K27-Altered Diffuse Midline Glioma Open
All Supplementary Figures and their captions.
View article: EXTH-15. Combinatorial targeting of avapritinib-driven MAPK activation in pediatric high-grade glioma
EXTH-15. Combinatorial targeting of avapritinib-driven MAPK activation in pediatric high-grade glioma Open
PDGFRA is a frequently altered gene in pHGG, driving aggressive behavior and worse prognoses. Avapritinib, a CNS-penetrant inhibitor of mutated PDGFRα and KIT kinases, has shown promise in vitro, in vivo, and in pHGG patients. Single-agent…
View article: EPCO-11. ENHANCING GENOME ANALYSIS WITH WHOLE PROTEOME PROFILING FOR IMPROVED THERAPEUTIC DECISION MAKING IN DIFFUSE MIDLINE GLIOMA
EPCO-11. ENHANCING GENOME ANALYSIS WITH WHOLE PROTEOME PROFILING FOR IMPROVED THERAPEUTIC DECISION MAKING IN DIFFUSE MIDLINE GLIOMA Open
Diffuse midline glioma (DMG) is a devastating brain tumor with a median overall survival (OS) of 11 months. Although more patients are now participating in precision medicine clinical trials, DMGs often lack clearly druggable genomic targe…
View article: EXTH-107. Effective targeting of EGFR-driven diffuse midline glioma with BLU5082, a novel brain-penetrant EGFR-targeting tyrosine kinase inhibitor (TKI)
EXTH-107. Effective targeting of EGFR-driven diffuse midline glioma with BLU5082, a novel brain-penetrant EGFR-targeting tyrosine kinase inhibitor (TKI) Open
Diffuse midline gliomas (DMGs) are lethal pediatric high-grade brain tumors with a prognosis of less than two years from diagnosis, the majority of which harbor the H3K27M histone mutation. A subgroup of DMGs harbor alterations in epiderma…
View article: ANGI-18. DISRUPTING INTEGRIN SIGNALING IMPAIRS MIGRATION, MYC-DRIVEN PURINE BIOSYNTHESIS, AND STEMNESS IN H3K27M DIFFUSE MIDLINE GLIOMAS
ANGI-18. DISRUPTING INTEGRIN SIGNALING IMPAIRS MIGRATION, MYC-DRIVEN PURINE BIOSYNTHESIS, AND STEMNESS IN H3K27M DIFFUSE MIDLINE GLIOMAS Open
Diffuse midline glioma (DMG) is an aggressive pediatric brain tumor driven by the H3K27M histone mutation and represents the leading cause of cancer-related death in children. These tumors are highly infiltrative and can occasionally migra…
View article: The DIPG/DMG National Tumor Board: The power of advocacy
The DIPG/DMG National Tumor Board: The power of advocacy Open
Background Diffuse intrinsic pontine gliomas (DIPG) and diffuse midline gliomas (DMG) are fatal brain tumors and clinical trial enrollment remains a cornerstone of treatment; however, barriers to trial identification, access and enrollment…
View article: 3D spatial sampling to quantify morphologic heterogeneity in isocitrate dehydrogenase-wildtype glioblastoma
3D spatial sampling to quantify morphologic heterogeneity in isocitrate dehydrogenase-wildtype glioblastoma Open
Advances in digital pathology and machine learning have the potential to revolutionize diagnostic neuropathology. Current brain tumor models are typically trained and validated using morphologic features from a single hematoxylin and eosin…
View article: Genetic modeling of ELP1-associated Sonic hedgehog medulloblastoma identifies MDM2 as a selective therapeutic target
Genetic modeling of ELP1-associated Sonic hedgehog medulloblastoma identifies MDM2 as a selective therapeutic target Open
Germline loss-of-function (LOF) variants in Elongator acetyltransferase complex subunit 1 (ELP1) are the most prevalent predisposing genetic events in childhood medulloblastoma (MB), accounting for ∼30% of the Sonic hedgehog (SHH) 3 subtyp…
View article: Supplementary Table 9 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 9 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 9 summarizes the characterization of 16 SNPs associated with 23 concordant dQTLs.
View article: Data from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Data from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Newly diagnosed prostate cancers differ dramatically in mutational composition and lethality. The most accurate clinical predictor of lethality is tumor tissue architecture, quantified as tumor grade. To interrogate the evolutionary origin…
View article: Supplementary Table 2 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 2 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 2 displays results from driver selection, driver groupings and driver associations.
View article: Figure 5 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Figure 5 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Mutational hallmarks of prostate cancer grade. A, A linear model was fit to relate each mutational density measure to ISUP GG using tumor and normal sequencing coverage as covariates. Dot size and color represents the effect size fo…
View article: Supplementary Table 7 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 7 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 7 provides summary statistics from distal dQTL associations
View article: Figure 7 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Figure 7 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Characterization of dQTLs. A, Summary of all 35 dQTLs involving 25 unique SNPs. Dot size and color indicate the magnitude and direction of association (as OR), and background shading indicates dQTL discovered strategy. B, For…
View article: Figure 4 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Figure 4 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Mutational subtypes of localized prostate cancer. A, Mutation densities (rows) differ by ETS fusion and NKX3-1 CNA status (columns). Dot size and color gives effect-size as a Z-score, scaled to ETS-negative, NKX3-1<…
View article: Supplementary Table 3 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 3 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 3 illustrates driver co-occurrence analysis, driver clusters, and associations of drivers with clinical features
View article: Supplementary Table 4 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 4 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 4 shows driver selection for dQTL nomination and prevalence of drivers in cohorts
View article: Supplementary Figures from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Figures from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Figures & Figure Legends. Supplementary Figure 1 | Cohort Structure and Analysis. Supplementary Figure 2 | CNA Evolution & Transcriptomic Effects. Supplementary Figure 3 | Properties of Driver Mutations. Supplementary Figure …
View article: Supplementary Table 8 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 8 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 8 shows summary statistics of 16 SNPs associated with 23 concordant dQTLs across cohorts
View article: Figure 3 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Figure 3 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Functional characterization of driver mutations. A, Network diagrams represent multimodal pathway enrichment analysis of driver genes. Mutation types (i.e., the type of driver analysis) are indicated by shading of circles. Circle si…
View article: Figure 6 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Figure 6 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
dQTLs bias somatic mutational landscape. A, Schematic of dQTL detection. The PRS used was by Schumacher and colleagues (16). Linear local dQTLs were assessed within ±500 kbp around a driver. Spatial local dQTLs were evaluated using …
View article: Supplementary Table 1 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 1 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 1 shows a feature-by-patient summary matrix. For each patient, this table provides version information of bioinformatics tools, summary sequencing statistics, mutational density metrics, clinical information and driver …
View article: Supplementary Table 5 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 5 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 5 displays summary statistics from PRS and HOXB13 associated with somatic drivers. β and P-value from logistic regression correcting for five genetic principal components, age and somatic mutation burden. FDR = false di…
View article: Supplementary Table 6 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 6 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 6 displays the number of dQTLs identified for each somatic driver in each analysis strategy. Summary statistics from local dQTL associations. Statistics from logistic regression correcting for five genetic principal com…
View article: Supplementary Table 10 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 10 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 10 lists dQTL SNPs identified as eQTLs in prostate tissue in GTEx.
View article: Supplementary Table 11 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Supplementary Table 11 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Supplementary Table 11 reports percentages of cross-individual contamination for each sample and sequencing lane.
View article: Figure 2 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity
Figure 2 from The Germline and Somatic Origins of Prostate Cancer Heterogeneity Open
Somatic driver mutations in localized prostate cancer. Driver mutation discovery in 666 localized prostate tumors. The top barplot shows the distribution of the number of drivers in patients; the covariates on the left show the region type…
View article: Automated microinjection for zebrafish xenograft models
Automated microinjection for zebrafish xenograft models Open
Zebrafish xenograft models are increasingly recognized for predicting patient responses to cancer therapeutics, suggesting their potential as clinical diagnostic tools. However, precise microinjection of cancer cells into numerous small an…
View article: Germline analysis of an international cohort of pediatric diffuse midline glioma patients
Germline analysis of an international cohort of pediatric diffuse midline glioma patients Open
Background Factors that drive the development of diffuse midline gliomas (DMG) are unknown. Our study aimed to determine the prevalence of pathogenic/likely pathogenic (P/LP) germline variants in pediatric patients with DMG. Methods We ass…