Intertumoral Heterogeneity within Medulloblastoma Subgroups.
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ABSTRACT:
SUBMITTER: Cavalli FMG
PROVIDER: S-EPMC6163053 | biostudies-literature | 2017 Jun
REPOSITORIES: biostudies-literature
Publications
Intertumoral Heterogeneity within Medulloblastoma Subgroups.
Cavalli Florence M G FMG Remke Marc M Rampasek Ladislav L Peacock John J Shih David J H DJH Luu Betty B Garzia Livia L Torchia Jonathon J Nor Carolina C Morrissy A Sorana AS Agnihotri Sameer S Thompson Yuan Yao YY Kuzan-Fischer Claudia M CM Farooq Hamza H Isaev Keren K Daniels Craig C Cho Byung-Kyu BK Kim Seung-Ki SK Wang Kyu-Chang KC Lee Ji Yeoun JY Grajkowska Wieslawa A WA Perek-Polnik Marta M Vasiljevic Alexandre A Faure-Conter Cecile C Jouvet Anne A Giannini Caterina C Nageswara Rao Amulya A AA Li Kay Ka Wai KKW Ng Ho-Keung HK Eberhart Charles G CG Pollack Ian F IF Hamilton Ronald L RL Gillespie G Yancey GY Olson James M JM Leary Sarah S Weiss William A WA Lach Boleslaw B Chambless Lola B LB Thompson Reid C RC Cooper Michael K MK Vibhakar Rajeev R Hauser Peter P van Veelen Marie-Lise C MC Kros Johan M JM French Pim J PJ Ra Young Shin YS Kumabe Toshihiro T López-Aguilar Enrique E Zitterbart Karel K Sterba Jaroslav J Finocchiaro Gaetano G Massimino Maura M Van Meir Erwin G EG Osuka Satoru S Shofuda Tomoko T Klekner Almos A Zollo Massimo M Leonard Jeffrey R JR Rubin Joshua B JB Jabado Nada N Albrecht Steffen S Mora Jaume J Van Meter Timothy E TE Jung Shin S Moore Andrew S AS Hallahan Andrew R AR Chan Jennifer A JA Tirapelli Daniela P C DPC Carlotti Carlos G CG Fouladi Maryam M Pimentel José J Faria Claudia C CC Saad Ali G AG Massimi Luca L Liau Linda M LM Wheeler Helen H Nakamura Hideo H Elbabaa Samer K SK Perezpeña-Diazconti Mario M Chico Ponce de León Fernando F Robinson Shenandoah S Zapotocky Michal M Lassaletta Alvaro A Huang Annie A Hawkins Cynthia E CE Tabori Uri U Bouffet Eric E Bartels Ute U Dirks Peter B PB Rutka James T JT Bader Gary D GD Reimand Jüri J Goldenberg Anna A Ramaswamy Vijay V Taylor Michael D MD
Cancer cell 20170601 6
While molecular subgrouping has revolutionized medulloblastoma classification, the extent of heterogeneity within subgroups is unknown. Similarity network fusion (SNF) applied to genome-wide DNA methylation and gene expression data across 763 primary samples identifies very homogeneous clusters of patients, supporting the presence of medulloblastoma subtypes. After integration of somatic copy-number alterations, and clinical features specific to each cluster, we identify 12 different subtypes of ...[more]
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Project description:PurposeMedulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication.Patients and methodsMolecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models.ResultsSubgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas.ConclusionCombining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.
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Project description:There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumors, and found post-translational modifications of MYC that are associated with poor outcomes in group 3 tumors. We found kinases associated with subtypes and showed that inhibiting PRKDC sensitizes MYC-driven cells to radiation. Our study shows that proteomics enables a more comprehensive, functional readout, providing a foundation for future therapeutic strategies.
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Project description:Archer TC, Ehrenberger T, Mundt F, Gold MP, Krug K, Mah CK, Mahoney EL, Daniel CJ, LeNail A, Ramamoorthy D, Mertins P, Mani DR, Zhang H, Gillette MA, Clauser K, Noble M, Tang LC, Francois JP, Silterra J, Jensen J, Tamayo P, Korshunov A, Pfister SM, Kool M, Northcott PA, Sears RC, Lipton JO, Carr SA, Mesirov JP, Pomeroy SL, Fraenkel E. Cancer Cell 2018.
There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumors, and found post-translational modifications of MYC that are associated with poor outcomes in Group 3 tumors. We found kinases associated with subtypes and showed that inhibiting PRKDC sensitizes MYC-driven tumors to radiation. Our study shows that proteomics enables a more comprehensive, functional readout, providing a foundation for new therapeutic strategies.
2018-07-20 | MSV000082644 | MassIVE
Project description:Many common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximizing power in comparison to standard variant-by-variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post hoc identification of the contributing genetic variants. We demonstrate the method on a range of simulated and test data sets, for which expected results are already known. We investigate subgroups of individuals with type 1 diabetes (T1D) defined by autoantibody positivity, establishing evidence for differential genetic architecture with positivity for thyroid-peroxidase-specific antibody, driven generally by variants in known T1D-associated genomic regions.
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Project description:PurposeMicroarray studies indicate medulloblastoma comprises distinct molecular disease subgroups, which offer potential for improved clinical management.Experimental designMinimal mRNA expression signatures diagnostic for the Wnt/Wingless (WNT) and Sonic Hedgehog (SHH) subgroups were developed, validated, and used to assign subgroup affiliation in 173 tumors from four independent cohorts, alongside a systematic investigation of subgroup clinical and molecular characteristics.ResultsWNT tumors [12% (21/173)] were diagnosed >5 years of age (peak, 10 years), displayed classic histology, CTNNB1 mutation (19/20), and associated chromosome 6 loss, and have previously been associated with favorable prognosis. SHH cases [24% (42/173)] predominated in infants (<3 years) and showed an age-dependent relationship to desmoplastic/nodular pathology; all infant desmoplastic/nodular cases (previously associated with a good outcome) were SHH-positive, but these relationships broke down in noninfants. PTCH1 mutations were common [34% (11/32)], but PTCH1 exon1c hypermethylation, chromosome 9q and REN (KCTD11) genetic loss were not SHH associated, and SMO or SUFU mutation, PTCH1 exon1a or SUFU hypermethylation did not play a role, indicating novel activating mechanisms in the majority of SHH cases. SHH tumors were associated with an absence of COL1A2 methylation. WNT/SHH-independent medulloblastomas [64% (110/173)] showed all histologies, peaked at 3 and 6 years, and were exclusively associated with chromosome 17p loss.ConclusionsMedulloblastoma subgroups are characterized by distinct genomic, epigenomic and clinicopathologic features, and clinical outcomes. Validated array-independent gene expression assays for the rapid assessment of subgroup affiliation in small biopsies provide a basis for their routine clinical application, in strategies including molecular disease-risk stratification and delivery of targeted therapeutics.
| S-EPMC3071325 | biostudies-literature
Project description:Medulloblastoma is a malignant childhood brain tumour comprising four discrete subgroups. To identify mutations that drive medulloblastoma we sequenced the entire genomes of 37 tumours and matched normal blood. One hundred and thirty-six genes harbouring somatic mutations in this discovery set were sequenced in an additional 56 medulloblastomas. Recurrent mutations were detected in 41 genes not yet implicated in medulloblastoma: several target distinct components of the epigenetic machinery in different disease subgroups, e.g., regulators of H3K27 and H3K4 trimethylation in subgroup-3 and 4 (e.g., KDM6A and ZMYM3), and CTNNB1-associated chromatin remodellers in WNT-subgroup tumours (e.g., SMARCA4 and CREBBP). Modelling of mutations in mouse lower rhombic lip progenitors that generate WNT-subgroup tumours, identified genes that maintain this cell lineage (DDX3X) as well as mutated genes that initiate (CDH1) or cooperate (PIK3CA) in tumourigenesis. These data provide important new insights into the pathogenesis of medulloblastoma subgroups and highlight targets for therapeutic development. A total of 76 pediatric medulloblastoma samples were analyzed, representing 4 expression classes
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Project description:Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups.All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes.Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%-100%), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%-100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%-98%). When we used the MR imaging feature-based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort.Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.
| S-EPMC4819007 | biostudies-literature
Project description:Medulloblastoma is a malignant childhood brain tumour comprising four discrete subgroups. Here, to identify mutations that drive medulloblastoma, we sequenced the entire genomes of 37 tumours and matched normal blood. One-hundred and thirty-six genes harbouring somatic mutations in this discovery set were sequenced in an additional 56 medulloblastomas. Recurrent mutations were detected in 41 genes not yet implicated in medulloblastoma; several target distinct components of the epigenetic machinery in different disease subgroups, such as regulators of H3K27 and H3K4 trimethylation in subgroups 3 and 4 (for example, KDM6A and ZMYM3), and CTNNB1-associated chromatin re-modellers in WNT-subgroup tumours (for example, SMARCA4 and CREBBP). Modelling of mutations in mouse lower rhombic lip progenitors that generate WNT-subgroup tumours identified genes that maintain this cell lineage (DDX3X), as well as mutated genes that initiate (CDH1) or cooperate (PIK3CA) in tumorigenesis. These data provide important new insights into the pathogenesis of medulloblastoma subgroups and highlight targets for therapeutic development.
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Project description:BackgroundA major barrier to effective treatment of glioblastoma (GBM) is the large intertumoral heterogeneity at the genetic and cellular level. In early phase clinical trials, patient heterogeneity in response to therapy is commonly observed; however, how tumor heterogeneity is reflected in individual drug sensitivities in the treatment-naïve glioblastoma stem cells (GSC) is unclear.MethodsWe cultured 12 patient-derived primary GBMs as tumorspheres and validated tumor stem cell properties by functional assays. Using automated high-throughput screening (HTS), we evaluated sensitivity to 461 anticancer drugs in a collection covering most FDA-approved anticancer drugs and investigational compounds with a broad range of molecular targets. Statistical analyses were performed using one-way ANOVA and Spearman correlation.ResultsAlthough tumor stem cell properties were confirmed in GSC cultures, their in vitro and in vivo morphology and behavior displayed considerable tumor-to-tumor variability. Drug screening revealed significant differences in the sensitivity to anticancer drugs (p < 0.0001). The patient-specific vulnerabilities to anticancer drugs displayed a heterogeneous pattern. They represented a variety of mechanistic drug classes, including apoptotic modulators, conventional chemotherapies, and inhibitors of histone deacetylases, heat shock proteins, proteasomes and different kinases. However, the individual GSC cultures displayed high biological consistency in drug sensitivity patterns within a class of drugs. An independent laboratory confirmed individual drug responses.ConclusionsThis study demonstrates that patient-derived and treatment-naïve GSC cultures maintain patient-specific traits and display intertumoral heterogeneity in drug sensitivity to anticancer drugs. The heterogeneity in patient-specific drug responses highlights the difficulty in applying targeted treatment strategies at the population level to GBM patients. However, HTS can be applied to uncover patient-specific drug sensitivities for functional precision medicine.
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