Project description:Optimal treatment of brain metastases is often hindered by limitations in diagnostic capabilities. To meet this challenge, here we profile DNA methylomes of the three most frequent types of brain metastases: melanoma, breast, and lung cancers (n = 96). Using supervised machine learning and integration of DNA methylomes from normal, primary, and metastatic tumor specimens (n = 1860), we unravel epigenetic signatures specific to each type of metastatic brain tumor and constructed a three-step DNA methylation-based classifier (BrainMETH) that categorizes brain metastases according to the tissue of origin and therapeutically relevant subtypes. BrainMETH predictions are supported by routine histopathologic evaluation. We further characterize and validate the most predictive genomic regions in a large cohort of brain tumors (n = 165) using quantitative-methylation-specific PCR. Our study highlights the importance of brain tumor-defining epigenetic alterations, which can be utilized to further develop DNA methylation profiling as a critical tool in the histomolecular stratification of patients with brain metastases.
Project description:Genome-wide DNA methylation profiling of brain metastases from lung cancer, breast cancer, and melanoma samples. The Illumina Infinium 450K Human DNA methylation Beadchip was used to obtain DNA methylation profiles across approximately 450,000 methylation sites in formalin-fixed paraffin-embedded (FFPE) samples from brain metastases. Samples included 30 breast cancer brain metastases, 18 lung cancer brain metastases, 37 melanoma brain metastases, and 4 samples with brain metastases from patients with uncertain primary.
Project description:Ependymal tumors across age groups have been classified solely by histopathology. It is, however, commonly accepted that this classification has limited clinical utility based on its poor reliability. We aimed at establishing a reliable and reproducible molecular classification using DNA methylation fingerprints of the tumors. Studying a cohort of 500 tumors allowed for the delineation of nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS). Two of the supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification by far and thus might serve as a basis for the upcoming update of the WHO classification of CNS tumors. DNA methylation patterns in tumors have been shown to represent a very stable molecular memory of the respective cell of origin throughout the disease course, thus making them particularly suitable for tumor classification purposes. Methylation fingerprinting of a large series of ependymal tumors of all grades revealed a highly reliable way of classifying this clinically extremely heterogeneous group of malignancies. In fact, out of nine highly reproducible molecular subgroups identified in the supratentorial, infratentorial and spinal regions, only two harbor the vast majority of clinical high-risk patients (mostly children) for whom novel therapeutic concepts are desperately needed. Since this analysis can be performed from minute amounts of DNA extracted from archived material, it is ideally suited for routine clinical application. We investigated a set of 562 ependymal tumors using the Illumina 450k methylation array.
Project description:Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patients' outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling. Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, supratentorial. Two supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification and thus might serve as a basis for the next World Health Organization classification of CNS tumors.
Project description:Metastatic prostate cancers are recognized to exhibit subtypes categorized by underlying genomic alterations and phenotypes largely partitioned by androgen receptor signaling and neuroendocrine activity. In the present study we evaluated a phenotypic classification approach originally developed for subtyping breast carcinomas using the PAM50 gene signature. PAM50 subtypes associated with specific genotypes such as RB1 loss and phenotypes such as small cell/neuroendocrine carcinoma as well as tumor histology including cribriform morphology. In the context of clinical translation, PAM50 classification segregated tumors into groups with distinct druggable targets such as cell surface proteins amenable to antibody-drug-conjugates (ADCs). Classification into Luminal A, Luminal B and Basal tumors associated with time on androgen receptor signaling inhibitors, and responses to taxane chemotherapy. These findings support further clinical investigation of PAM50-based classification for prostate cancer patient stratification in therapeutic studies.
Project description:Microarray analysis in the mouse metastatic tumor after ɣ-irradiation(ɣ-IR): non-irradiated primary tumor vs. radiated primary tumor vs. metastatic tumor after ɣ-irradiation Metastatic tumors in C6-L (rat glioma cells ) xenografted mice were studied after local treatment with fractionated γ-IR. To accurately detect the metastatic nodules after γ-IR, we observed the effect of γ-IR on distant metastatic tumor growth. Metastatic nodules after γ-IR indicated extensive colonization of C6-L cells in the lungs within 6 weeks after γ-IR. Identified and described the molecular events occurring after γ-IR through gene expression profiling to elucidate genetic changes (differentially expressed genes between the γ-IR primary tumors vs. non-γ-IR primary tumors and metastatic lung nodules vs. γ-IR primary tumors). We investigated the change of gene expression profile in the γ-IR primary tumors vs. non-γ-IR primary tumors and metastatic lung nodules vs. γ-IR primary tumors in rat glioma (C6-L cell) xenograft model.
Project description:Microarray analysis in the mouse metastatic tumor after ɣ-irradiation(ɣ-IR): non-irradiated primary tumor vs. radiated primary tumor vs. metastatic tumor after ɣ-irradiation Metastatic tumors in C6-L (rat glioma cells ) xenografted mice were studied after local treatment with fractionated γ-IR. To accurately detect the metastatic nodules after γ-IR, we observed the effect of γ-IR on distant metastatic tumor growth. Metastatic nodules after γ-IR indicated extensive colonization of C6-L cells in the lungs within 6 weeks after γ-IR. Identified and described the molecular events occurring after γ-IR through gene expression profiling to elucidate genetic changes (differentially expressed genes between the γ-IR primary tumors vs. non-γ-IR primary tumors and metastatic lung nodules vs. γ-IR primary tumors).