Rapid, economical diagnostic classification of ATRT molecular subgroup using NanoString nCounter platform.

Background: Despite genomic simplicity, recent studies have reported at least 3 major atypical teratoid rhabdoid tumor (ATRT) subgroups with distinct molecular and clinical features. Reliable ATRT subgrouping in clinical settings remains challenging due to a lack of suitable biological markers, sample rarity, and the relatively high cost of conventional subgrouping methods. This study aimed to develop a reliable ATRT molecular stratification method to implement in clinical settings. Methods: We have developed an ATRT subgroup predictor assay using a custom genes panel for the NanoString nCounter System and a flexible machine learning classifier package. Seventy-one ATRT primary tumors with matching gene expression array and NanoString data were used to construct a multi-algorithms ensemble classifier. Additional validation was performed using an independent gene expression array against the independently generated dataset. We also analyzed 11 extra-cranial rhabdoid tumors with our classifier and compared our approach against DNA methylation classification to evaluate the result consistency with existing methods. Results: We have demonstrated that our novel ensemble classifier has an overall average of 93.6% accuracy in the validation dataset, and a striking 98.9% accuracy was achieved with the high-prediction score samples. Using our classifier, all analyzed extra-cranial rhabdoid tumors are classified as MYC subgroups. Compared with the DNA methylation classification, the results show high agreement, with 84.5% concordance and up to 95.8% concordance for high-confidence predictions. Conclusions: Here we present a rapid, cost-effective, and accurate ATRT subgrouping assay applicable for clinical use.

Tumor genomic, transcriptomic, and immune profiling characterizes differential response to first-line platinum chemotherapy in high grade serous ovarian cancer.

BACKGROUND: In high grade serous ovarian cancer (HGSOC), there is a spectrum of sensitivity to first line platinum-based chemotherapy. This study molecularly characterizes HGSOC patients from two distinct groups of chemotherapy responders (good vs. poor). METHODS: Following primary debulking surgery and intravenous carboplatin/paclitaxel, women with stage III-IV HGSOC were grouped by response. Patients in the good response (GR) and poor response (PR) groups respectively had a progression-free intervals (PFI) of ≥12 and ≤6 months. Analysis of surgical specimens interrogated genomic and immunologic features using whole exome sequencing. RNA-sequencing detected gene expression outliers and inference of immune infiltrate, with validation by targeted NanoString arrays. PD-L1 expression was scored by immunohistochemistry (IHC). RESULTS: A total of 39 patient samples were analyzed (GR = 20; PR = 19). Median PFI for GR and PR patient cohorts was 32 and 3 months, respectively. GR tumors were enriched for loss-of-function BRCA2 mutations and had a significantly higher nonsynonymous mutation rate compared to PR tumors (p = 0.001). Samples from the PR cohort were characterized by mutations in MGA and RAD51B and trended towards a greater rate of amplification of PIK3CA, MECOM, and ATR in comparison to GR tumors. Gene expression analysis by NanoString correlated increased PARP4 with PR and increased PD-L1 and EMSY with GR. There was greater tumor immune cell infiltration and higher immune cell PD-L1 protein expression in the GR group. CONCLUSIONS: Our research demonstrates that tumors from HGSOC patients responding poorly to first line chemotherapy have a distinct molecular profile characterized by actionable drug targets including PARP4.

A C19MC-LIN28A-MYCN Oncogenic Circuit Driven by Hijacked Super-enhancers Is a Distinct Therapeutic Vulnerability in ETMRs: A Lethal Brain Tumor.

Embryonal tumors with multilayered rosettes (ETMRs) are highly lethal infant brain cancers with characteristic amplification of Chr19q13.41 miRNA cluster (C19MC) and enrichment of pluripotency factor LIN28A. Here we investigated C19MC oncogenic mechanisms and discovered a C19MC-LIN28A-MYCN circuit fueled by multiple complex regulatory loops including an MYCN core transcriptional network and super-enhancers resulting from long-range MYCN DNA interactions and C19MC gene fusions. Our data show that this powerful oncogenic circuit, which entraps an early neural lineage network, is potently abrogated by bromodomain inhibitor JQ1, leading to ETMR cell death.

Intertumoral Heterogeneity within Medulloblastoma Subgroups.

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 medulloblastoma. Integrative analysis using SNF further delineates group 3 from group 4 medulloblastoma, which is not as readily apparent through analyses of individual data types. Two clear subtypes of infants with Sonic Hedgehog medulloblastoma with disparate outcomes and biology are identified. Medulloblastoma subtypes identified through integrative clustering have important implications for stratification of future clinical trials.

Spatial heterogeneity in medulloblastoma.

Spatial heterogeneity of transcriptional and genetic markers between physically isolated biopsies of a single tumor poses major barriers to the identification of biomarkers and the development of targeted therapies that will be effective against the entire tumor. We analyzed the spatial heterogeneity of multiregional biopsies from 35 patients, using a combination of transcriptomic and genomic profiles. Medulloblastomas (MBs), but not high-grade gliomas (HGGs), demonstrated spatially homogeneous transcriptomes, which allowed for accurate subgrouping of tumors from a single biopsy. Conversely, somatic mutations that affect genes suitable for targeted therapeutics demonstrated high levels of spatial heterogeneity in MB, malignant glioma, and renal cell carcinoma (RCC). Actionable targets found in a single MB biopsy were seldom clonal across the entire tumor, which brings the efficacy of monotherapies against a single target into question. Clinical trials of targeted therapies for MB should first ensure the spatially ubiquitous nature of the target mutation.

Integrated (epi)-Genomic Analyses Identify Subgroup-Specific Therapeutic Targets in CNS Rhabdoid Tumors.

We recently reported that atypical teratoid rhabdoid tumors (ATRTs) comprise at least two transcriptional subtypes with different clinical outcomes; however, the mechanisms underlying therapeutic heterogeneity remained unclear. In this study, we analyzed 191 primary ATRTs and 10 ATRT cell lines to define the genomic and epigenomic landscape of ATRTs and identify subgroup-specific therapeutic targets. We found ATRTs segregated into three epigenetic subgroups with distinct genomic profiles, SMARCB1 genotypes, and chromatin landscape that correlated with differential cellular responses to a panel of signaling and epigenetic inhibitors. Significantly, we discovered that differential methylation of a PDGFRB-associated enhancer confers specific sensitivity of group 2 ATRT cells to dasatinib and nilotinib, and suggest that these are promising therapies for this highly lethal ATRT subtype.

Molecular subgroups of atypical teratoid rhabdoid tumours in children: an integrated genomic and clinicopathological analysis.

BACKGROUND: Rhabdoid brain tumours, also called atypical teratoid rhabdoid tumours, are lethal childhood cancers with characteristic genetic alterations of SMARCB1/hSNF5. Lack of biological understanding of the substantial clinical heterogeneity of these tumours restricts therapeutic advances. We integrated genomic and clinicopathological analyses of a cohort of patients with atypical teratoid rhabdoid tumours to find out the molecular basis for clinical heterogeneity in these tumours. METHODS: We obtained 259 rhabdoid tumours from 37 international institutions and assessed transcriptional profiles in 43 primary tumours and copy number profiles in 38 primary tumours to discover molecular subgroups of atypical teratoid rhabdoid tumours. We used gene and pathway enrichment analyses to discover group-specific molecular markers and did immunohistochemical analyses on 125 primary tumours to evaluate clinicopathological significance of molecular subgroup and ASCL1-NOTCH signalling. FINDINGS: Transcriptional analyses identified two atypical teratoid rhabdoid tumour subgroups with differential enrichment of genetic pathways, and distinct clinicopathological and survival features. Expression of ASCL1, a regulator of NOTCH signalling, correlated with supratentorial location (p=0·004) and superior 5-year overall survival (35%, 95% CI 13-57, and 20%, 6-34, for ASCL1-positive and ASCL1-negative tumours, respectively; p=0·033) in 70 patients who received multimodal treatment. ASCL1 expression also correlated with superior 5-year overall survival (34%, 7-61, and 9%, 0-21, for ASCL1-positive and ASCL1-negative tumours, respectively; p=0·001) in 39 patients who received only chemotherapy without radiation. Cox hazard ratios for overall survival in patients with differential ASCL1 enrichment treated with chemotherapy with or without radiation were 2·02 (95% CI 1·04-3·85; p=0·038) and 3·98 (1·71-9·26; p=0·001). Integrated analyses of molecular subgroupings with clinical prognostic factors showed three distinct clinical risk groups of tumours with different therapeutic outcomes. INTERPRETATION: An integration of clinical risk factors and tumour molecular groups can be used to identify patients who are likely to have improved long-term radiation-free survival and might help therapeutic stratification of patients with atypical teratoid rhabdoid tumours. FUNDING: C17 Research Network, Genome Canada, b.r.a.i.n.child, Mitchell Duckman, Tal Doron and Suri Boon foundations.

Chemical and biosynthetic evolution of the antimycin-type depsipeptides.

Evolution of natural products, and particularly those resulting from microbial assembly line-like enzymes, such as polyketide (PK) and nonribosomal peptides (NRP), has resulted in a variety of pharmaceutically important and chemically diverse families of molecules. The antimycin-type depsipeptides are one such grouping, with a significant level of diversity and members that have noted activities against key targets governing human cellular apoptosis (e.g. Bcl-xL and GRP78). Chemical variance originates from ring size, with 9-, 12-, 15-, and 18-membered classes, and we show that such distinctions influence their molecular targeting. Further, we present here a systematic interrogation of the chemistry and assembly line evolution of antimycin-type analogues by conducting metabolomic profiling and biosynthetic gene cluster comparative analysis of the depsipeptide assembly lines for each member of the antimycin-group. Natural molecular evolution principles of such studies should assist in artificial re-combinatorializing of PK and NRP assembly lines.

Structures and biosynthesis of 12-membered macrocyclic depsipeptides from Streptomyces sp. ML55.

Two novel depsipeptides (1-2) were isolated from Streptomyces sp. ML55 together with two known analogues (3-4). Their structures were elucidated using a combination of NMR experiments, as well as detailed MS/MS experiments. The biosynthetic pathway of isolated compounds was dissected by genome sequencing data analysis for a hybrid nonribosomal peptide synthetase (NRPS) and polyketide synthetase (PKS) assembly line.