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Metastasis-Associated in Colon Cancer 1 (MACC1) is a strong prognostic marker for human colorectal cancers (CRC). The gene is a key regulator of the HGF/c-Met pathway and its overexpression is associated with cancer cell proliferation, migration, invasiveness and metastasis. The contexture of MACC1 overexpression in cancers is still poorly understood. Here we used the data released by The Cancer Genome Atlas (TCGA) and in silico approaches for a deep and integrative analysis of MACC1 expression modalities in CRCs. First, we curated COAD-READ TCGA datasets and obtained full clinical, genomic, and transcriptomic annotation for a total of 259 CRC samples. In tumors, we showed high heterogeneity of MACC1 mRNA expression levels with data varying from 5.58 to 13.07 U (RNAseq log transformed data - RSEM normalized). By correlating MACC1 expression to clinical data, we showed its levels were associated with anatomic regions of the disease (p=6.35.10-5). The tumors from descending colon and rectum having higher levels than those of the ascending colon and caecum (p=7.44-06). High MACC1 was also associated with higher tumor stages (p=0.01) and nodal invasion (p=0.03). At genomic level, MACC1 mutation was not frequent in CRCs ( normal in 155/259: 60%). Correlation analysis indicated strong positive association between MACC1 copy number variations and mRNA expression levels (p Citation Format: Vincent Vuaroqueaux, Hoor Al-Hasani, Dennis Kobelt, Thomas Risch, Susen Burock, Marie-Laure Yaspo, Heinz-Herbert Fiebig, Ulrike Stein. MACC1 overexpression in colorectal cancer is driven by chromosomal instability and is associated with molecular subtype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2879.

Current therapies for medulloblastoma, a highly malignant childhood brain tumour, impose debilitating effects on the developing child, and highlight the need for molecularly targeted treatments with reduced toxicity. Previous studies have been unable to identify the full spectrum of driver genes and molecular processes that operate in medulloblastoma subgroups. Here we analyse the somatic landscape across 491 sequenced medulloblastoma samples and the molecular heterogeneity among 1,256 epigenetically analysed cases, and identify subgroup-specific driver alterations that include previously undiscovered actionable targets. Driver mutations were confidently assigned to most patients belonging to Group 3 and Group 4 medulloblastoma subgroups, greatly enhancing previous knowledge. New molecular subtypes were differentially enriched for specific driver events, including hotspot in-frame insertions that target KBTBD4 and 'enhancer hijacking' events that activate PRDM6. Thus, the application of integrative genomics to an extensive cohort of clinical samples derived from a single childhood cancer entity revealed a series of cancer genes and biologically relevant subtype diversity that represent attractive therapeutic targets for the treatment of patients with medulloblastoma.

Medulloblastoma is a highly malignant paediatric brain tumour, often inflicting devastating consequences on the developing child. Genomic studies have revealed four distinct molecular subgroups with divergent biology and clinical behaviour. An understanding of the regulatory circuitry governing the transcriptional landscapes of medulloblastoma subgroups, and how this relates to their respective developmental origins, is lacking. Here, using H3K27ac and BRD4 chromatin immunoprecipitation followed by sequencing (ChIP-seq) coupled with tissue-matched DNA methylation and transcriptome data, we describe the active cis-regulatory landscape across 28 primary medulloblastoma specimens. Analysis of differentially regulated enhancers and super-enhancers reinforced inter-subgroup heterogeneity and revealed novel, clinically relevant insights into medulloblastoma biology. Computational reconstruction of core regulatory circuitry identified a master set of transcription factors, validated by ChIP-seq, that is responsible for subgroup divergence, and implicates candidate cells of origin for Group 4. Our integrated analysis of enhancer elements in a large series of primary tumour samples reveals insights into cis-regulatory architecture, unrecognized dependencies, and cellular origins.

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I–IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab., The heterogeneity of colorectal cancer has important clinical and therapeutic implications. Here the authors analysed the responses of a large biobank of organoids and xenografts derived from colorectal patients to a panel of clinically relevant therapeutic agents to identify genes signatures associated with drug response.

Summary Identifying the earliest somatic changes in prostate cancer can give important insights into tumor evolution and aids in stratifying high- from low-risk disease. We integrated whole genome, transcriptome and methylome analysis of early-onset prostate cancers (diagnosis ???55 years). Characterization across 292 prostate cancer genomes revealed age-related genomic alterations and a clock-like enzymatic-driven mutational process contributing to the earliest mutations in prostate cancer patients. Our integrative analysis identified four molecular subgroups, including a particularly aggressive subgroup with recurrent duplications associated with increased expression of ESRP1, which we validate in 12,000 tissue microarray tumors. Finally, we combined the patterns of molecular co-occurrence and risk-based subgroup information to deconvolve the molecular and clinical trajectories of prostate cancer from single patient samples.

We investigated parent-of-origin and allele-specific expression effects on obesity and hepatic gene expression in reciprocal crosses between the Berlin Fat Mouse Inbred line (BFMI) and C57Bl/6NCrl (B6N).We found that F1-males with a BFMI mother developed 1.8 times more fat mass on a high fat diet at 10 weeks than F1-males of a BFMI father. The phenotype was detectable from six weeks on and was preserved after cross-fostering. RNA-seq data of liver provided evidence for higher biosynthesis and elongation of fatty acids (p = 0.00635) in obese male offspring of a BFMI mother versus lean offspring of a BFMI father. Furthermore, fatty acid degradation (p = 0.00198) and the peroxisome pathway were impaired (p = 0.00094). The circadian rhythm was affected as well (p = 0.00087). Among the highest up-regulated protein coding genes in obese males were Acot4 (1.82 fold, p = 0.022), Cyp4a10 (1.35 fold, p = 0.026) and Cyp4a14 (1.32 fold, p = 0.012), which hydroxylize fatty acids and which are known to be increased in liver steatosis. Obese males showed lower expression of the genetically imprinted and paternally expressed 3 (Peg3) gene (0.31 fold, p = 0.046) and higher expression of the androgen receptor (Ar) gene (2.38 fold, p = 0.068). Allelic imbalance was found for expression of ATP-binding cassette transporter gene Abca8b. Several of the differentially expressed genes contain estrogen response elements.Parent-of-origin effects during gametogenesis and/or fetal development in an obese mother epigenetically modify the transcription of genes that lead to enhanced fatty acid synthesis and impair β-oxidation in the liver of male, but not female F1 offspring. Down-regulation of Peg3 could contribute to trigger this metabolic setting. At puberty, higher amounts of the androgen receptor and altered access to estrogen response elements in affected genes are likely responsible for male specific expression of genes that were epigenetically triggered. A suggestive lack of estrogen binding motifs was found for highly down-regulated genes in adult hepatocytes of obese F1 males (p = 0.074).

Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation, and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoural heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and Group 4 subgroup medulloblastomas account for the majority of paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to Groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family protooncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1/GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate ‘enhancer hijacking’ as an efficient mechanism driving oncogene activation in a childhood cancer.

Ovarian cancer is the fifth leading cause of cancer death for women in the U.S. and the seventh most fatal worldwide. Although ovarian cancer is notable for its initial sensitivity to platinum-based therapies, the vast majority of patients eventually develop recurrent cancer and succumb to increasingly platinum-resistant disease. Modern, targeted cancer drugs intervene in cell signaling, and identifying key disease mechanisms and pathways would greatly advance our treatment abilities. In order to shed light on the molecular diversity of ovarian cancer, we performed comprehensive transcriptional profiling on 129 advanced stage, high grade serous ovarian cancers. We implemented a, re-sampling based version of the ISIS class discovery algorithm (rISIS: robust ISIS) and applied it to the entire set of ovarian cancer transcriptional profiles. rISIS identified a previously undescribed patient stratification, further supported by micro-RNA expression profiles, and gene set enrichment analysis found strong biological support for the stratification by extracellular matrix, cell adhesion, and angiogenesis genes. The corresponding "angiogenesis signature" was validated in ten published independent ovarian cancer gene expression datasets and is significantly associated with overall survival. The subtypes we have defined are of potential translational interest as they may be relevant for identifying patients who may benefit from the addition of anti-angiogenic therapies that are now being tested in clinical trials.

Medulloblastoma is a highly malignant paediatric brain tumour, often inflicting devastating consequences on the developing child. Genomic studies have revealed four distinct molecular subgroups with divergent biology and clinical behaviour. An understanding of the regulatory circuitry governing the transcriptional landscapes of medulloblastoma subgroups, and how this relates to their respective developmental origins, is currently lacking. Using H3K27ac and BRD4 ChIP-Seq, coupled with tissue-matched DNA methylation and transcriptome data, we describe the active cis-regulatory landscape across 28 primary medulloblastoma specimens. Analysis of differentially regulated enhancers and super-enhancers reinforced inter-subgroup heterogeneity and revealed novel, clinically relevant insights into medulloblastoma biology. Computational reconstruction of core regulatory circuitry identified a master set of transcription factors responsible for subgroup divergence that validated by ChIP-Seq and implicated candidate cells-of-origin for Group 4. Our integrated analysis of cis-regulatory elements in a large series of primary tumour samples reveals insights into cis-regulatory architecture, unrecognized dependencies, and cellular origins. Citation Format: Charles Y. Lin, Serap Erkek, Yiai Tong, Linlin Yang, Alexander J. Federation, Marc Zapatka, Parthiv Haldipur, Daisuke Kawauchi, Thomas Risch, Hans-Jörg Warnatz, Barbara Worst, Bensheng Ju, Brent A. Orr, Rhamy Zeid, Donald R. Polaski, Maia Segura-Wang, Sebastian M. Waszak, David TW Jones, Marcel Kool, Volker Hovestadt, Ivo Buchhalter, Laura Sieber, Pascal Johann, Stefan Gröschel, Marina Ryzhova, Andrey Korshunov, Wenbiao Chen, Victor V. Chizhikov, Kathleen J. Millen, Vyacheslav Amstislavskiy, Hans Lehrach, Marie-Laure Yaspo, Roland Eils, Peter Lichter, Jan O. Korbel, Stefan Pfister, James E. Bradner, Paul A. Northcott. Medulloblastoma regulatory circuitries reveal subgroup-specific cellular origins. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-B23.

Ovarian cancer is the most lethal gynecological cancer and a leading cause of cancer deaths among women, with more than 15000 deaths per year in the United States (1). A majority of patients present with late-stage, high-grade disease, and the ability to distinguish biologically or clinically within this group is limited (2). Numerous efforts to develop molecular signatures that better stratify survival within this group of patients have generated an enormous archive of genomic discovery data; however, it remains difficult to assess which, if any, of these efforts have generated reproducible and clinically relevant prognostic models. Review papers have provided valuable summaries of proposed genomic prognostic models for ovarian cancer (3–7) but do not address the validity of published models when independently applied to new data. Independent validation can be addressed through meta-analysis by using archives of published data, but such efforts may be hindered by incomplete availability of original genomic and associated clinical data (8), diverse technologies and formats of published data (9), and lack of reproducibility of published models (10,11). However, sufficient archives of microarray data are now available to evaluate published prognostic models by meta-analysis. We therefore undertook a systematic validation of gene expression–based prognostic models for late-stage, high-grade serous ovarian cancer published between 2007 and 2012 (12–24) in a database of 10 clinically annotated microarray datasets totaling 1251 patients (12,14–18,20,23,25,26). This assessment addresses several important issues for the translation of genomics to clinical application: 1) the accuracy of published prognostic models when applied to new, independent datasets; 2) the impact of choice of validation datasets on apparent prognostic accuracy; 3) similarities between independently developed prognostic models; 4) the influence of popular datasets on the literature; and 5) the recent observation that random gene signatures may have prognostic ability (27). This study additionally addresses published controversies in the ovarian cancer prognostic signature literature by quantitatively placing these studies within their broader context. These controversies include the quality of a highly cited and frequently reused dataset associated with a now-retracted article (26) and the clinical relevance of a DNA damage repair-based prognostic model (19,28). Finally, evaluation of these prognostic models uncovered common pathways enriched for correlation with the most accurate prognostic models.

Summary Myeloid leukemia in Down syndrome (ML-DS) clonally evolves from transient abnormal myelopoiesis (TAM), a preleukemic condition in DS newborns. To define mechanisms of leukemic transformation, we combined exome and targeted resequencing of 111 TAM and 141 ML-DS samples with functional analyses. TAM requires trisomy 21 and truncating mutations in GATA1; additional TAM variants are usually not pathogenic. By contrast, in ML-DS, clonal and subclonal variants are functionally required. We identified a recurrent and oncogenic hotspot gain-of-function mutation in myeloid cytokine receptor CSF2RB. By a multiplex CRISPR/Cas9 screen in an in vivo murine TAM model, we tested loss-of-function of 22 recurrently mutated ML-DS genes. Loss of 18 different genes produced leukemias that phenotypically, genetically, and transcriptionally mirrored ML-DS.