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Gene Expression Profiling of Muscle Stem Cells Identifies Novel Regulators of Postnatal Myogenesis

International audienceSkeletal muscle growth and regeneration require a population of muscle stem cells, the satellite cells, located in close contact to the myofiber. These cells are specified during fetal and early postnatal development in mice from a Pax3/7 population of embryonic progenitor cells. As little is known about the genetic control of their formation and maintenance, we performed a genome-wide chronological expression profile identifying the dynamic transcriptomic changes involved in establishment of muscle stem cells through life, and acquisition of muscle stem cell properties. We have identified multiple genes and pathways associated with satellite cell formation, including set of genes specifically induced (EphA1, EphA2, EfnA1, EphB1, Zbtb4, Zbtb20) or inhibited (EphA3, EphA4, EphA7, EfnA2, EfnA3, EfnA4, EfnA5, EphB2, EphB3, EphB4, EfnBs, Zfp354c, Zcchc5, Hmga2) in adult stem cells. Ephrin receptors and ephrins ligands have been implicated in cell migration and guidance in many tissues including skeletal muscle. Here we show that Ephrin receptors and ephrins ligands are also involved in regulating the adult myogenic program. Strikingly, impairment of EPHB1 function in satellite cells leads to increased differentiation at the expense of self-renewal in isolated myofiber cultures. In addition, we identified new transcription factors, including several zinc finger proteins. ZFP354C and ZCCHC5 decreased self-renewal capacity when overexpressed, whereas ZBTB4 increased it, and ZBTB20 induced myogenic progression. The architectural and transcriptional regulator HMGA2 was involved in satellite cell activation. Together, our study shows that transcriptome profiling coupled with myofiber culture analysis, provides an efficient system to identify and validate candidate genes implicated in establishment/maintenance of muscle stem cells. Furthermore, tour de force transcriptomic profiling provides a wealth of data to inform for future stem cell-based muscle therapies

Anaplastic oligodendrogliomas with 1p19q codeletion have a proneural gene expression profile

<p>Abstract</p> <p>Background</p> <p>In high grade gliomas, 1p19q codeletion and <it>EGFR </it>amplification are mutually exclusive and predictive of dramatically different outcomes. We performed a microarray gene expression study of four high grade gliomas with 1p19q codeletion and nine with <it>EGFR </it>amplification, identified by CGH-array.</p> <p>Results</p> <p>The two groups of gliomas exhibited very different gene expression profiles and were consistently distinguished by unsupervised clustering analysis. One of the most striking differences was the expression of normal brain genes by oligodendrogliomas with 1p19q codeletion. These gliomas harbored a gene expression profile that partially resembled the gene expression of normal brain samples, whereas gliomas with <it>EGFR </it>amplification expressed many genes in common with glioblastoma cancer stem cells. The differences between the two types of gliomas and the expression of neuronal genes in gliomas with 1p19q codeletion were both validated in an independent series of 16 gliomas using real-time RT-PCR with a set of 22 genes differentiating the two groups of gliomas (<it>AKR1C3</it>, <it>ATOH8</it>, <it>BMP2</it>, <it>C20orf42</it>, <it>CCNB1</it>, <it>CDK2</it>, <it>CHI3L1</it>, <it>CTTNBP2</it>, <it>DCX, EGFR, GALNT13, GBP1, IGFBP2, IQGAP1, L1CAM, NCAM1, NOG, OLIG2, PDPN, PLAT, POSTN, RNF135</it>). Immunohistochemical study of the most differentially expressed neuronal gene, alpha-internexin, clearly differentiated the two groups of gliomas, with 1p19q codeletion gliomas showing specific staining in tumor cells.</p> <p>Conclusion</p> <p>These findings provide evidence for neuronal differentiation in oligodendrogliomas with 1p19q codeletion and support the hypothesis that the cell of origin for gliomas with 1p19q codeletion could be a bi-potential progenitor cell, able to give rise to both neurons and oligodendrocytes.</p

Combined transcriptome studies identify AFF3 as a mediator of the oncogenic effects of β-catenin in adrenocortical carcinoma

International audienceAdrenocortical cancer (ACC) is a very aggressive tumor, and genomics studies demonstrate that the most frequent alterations of driver genes in these cancers activate the Wnt/β-catenin signaling pathway. However, the adrenal-specific targets of oncogenic β-catenin-mediating tumorigenesis have not being established. A combined transcriptomic analysis from two series of human tumors and the human ACC cell line H295R harboring a spontaneous β-catenin activating mutation was done to identify the Wnt/β-catenin targets. Seven genes were consistently identified in the three studies. Among these genes, we found that AFF3 mediates the oncogenic effects of β-catenin in ACC. The Wnt response element site located at nucleotide position − 1408 of the AFF3 transcriptional start sites (TSS) mediates the regulation by the Wnt/β-catenin signaling pathway. AFF3 silencing decreases cell proliferation and increases apoptosis in the ACC cell line H295R. AFF3 is located in nuclear speckles, which play an important role in RNA splicing. AFF3 overexpression in adrenocortical cells interferes with the organization and/or biogenesis of these nuclear speckles and alters the distribution of CDK9 and cyclin T1 such that they accumulate at the sites of AFF3/speckles. We demonstrate that AFF3 is a new target of Wnt/β-catenin pathway involved in ACC, acting on transcription and RNA splicing

DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification

Quantifcation of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specifcities. Bioinformatic tools to assess the diferent cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data

Data-driven analysis of immune infiltrate in a large cohort of breast cancer and its association with disease progression, ER activity, and genomic complexity.

The tumor microenvironment is now widely recognized for its role in tumor progression, treatment response, and clinical outcome. The intratumoral immunological landscape, in particular, has been shown to exert both pro-tumorigenic and anti-tumorigenic effects. Identifying immunologically active or silent tumors may be an important indication for administration of therapy, and detecting early infiltration patterns may uncover factors that contribute to early risk. Thus far, direct detailed studies of the cell composition of tumor infiltration have been limited; with some studies giving approximate quantifications using immunohistochemistry and other small studies obtaining detailed measurements by isolating cells from excised tumors and sorting them using flow cytometry. Herein we utilize a machine learning based approach to identify lymphocyte markers with which we can quantify the presence of B cells, cytotoxic T-lymphocytes, T-helper 1, and T-helper 2 cells in any gene expression data set and apply it to studies of breast tissue. By leveraging over 2,100 samples from existing large scale studies, we are able to find an inherent cell heterogeneity in clinically characterized immune infiltrates, a strong link between estrogen receptor activity and infiltration in normal and tumor tissues, changes with genomic complexity, and identify characteristic differences in lymphocyte expression among molecular groupings. With our extendable methodology for capturing cell type specific signal we systematically studied immune infiltration in breast cancer, finding an inverse correlation between beneficial lymphocyte infiltration and estrogen receptor activity in normal breast tissue and reduced infiltration in estrogen receptor negative tumors with high genomic complexity

Exquisite Sensitivity of TP53 Mutant and Basal Breast Cancers to a Dose-Dense Epirubicin−Cyclophosphamide Regimen

BACKGROUND: In breast cancers, only a minority of patients fully benefit from the different chemotherapy regimens currently in use. Identification of markers that could predict the response to a particular regimen would thus be critically important for patient care. In cell lines or animal models, tumor protein p53 (TP53) plays a critical role in modulating the response to genotoxic drugs. TP53 is activated in response to DNA damage and triggers either apoptosis or cell-cycle arrest, which have opposite effects on cell fate. Yet, studies linking TP53 status and chemotherapy response have so far failed to unambiguously establish this paradigm in patients. Breast cancers with a TP53 mutation were repeatedly shown to have a poor outcome, but whether this reflects poor response to treatment or greater intrinsic aggressiveness of the tumor is unknown. METHODS AND FINDINGS: In this study we analyzed 80 noninflammatory breast cancers treated by frontline (neoadjuvant) chemotherapy. Tumor diagnoses were performed on pretreatment biopsies, and the patients then received six cycles of a dose-dense regimen of 75 mg/m(2) epirubicin and 1,200 mg/m(2) cyclophosphamide, given every 14 days. After completion of chemotherapy, all patients underwent mastectomies, thus allowing for a reliable assessment of chemotherapy response. The pretreatment biopsy samples were used to determine the TP53 status through a highly efficient yeast functional assay and to perform RNA profiling. All 15 complete responses occurred among the 28 TP53-mutant tumors. Furthermore, among the TP53-mutant tumors, nine out of ten of the highly aggressive basal subtypes (defined by basal cytokeratin [KRT] immunohistochemical staining) experienced complete pathological responses, and only TP53 status and basal subtype were independent predictors of a complete response. Expression analysis identified many mutant TP53-associated genes, including CDC20, TTK, CDKN2A, and the stem cell gene PROM1, but failed to identify a transcriptional profile associated with complete responses among TP53 mutant tumors. In patients with unresponsive tumors, mutant TP53 status predicted significantly shorter overall survival. The 15 patients with responsive TP53-mutant tumors, however, had a favorable outcome, suggesting that this chemotherapy regimen can overcome the poor prognosis generally associated with mutant TP53 status. CONCLUSIONS: This study demonstrates that, in noninflammatory breast cancers, TP53 status is a key predictive factor for response to this dose-dense epirubicin–cyclophosphamide regimen and further suggests that the basal subtype is exquisitely sensitive to this association. Given the well-established predictive value of complete responses for long-term survival and the poor prognosis of basal and TP53-mutant tumors treated with other regimens, this chemotherapy could be particularly suited for breast cancer patients with a mutant TP53, particularly those with basal features

The consensus molecular subtypes of colorectal cancer

Colorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features: CMS1 (microsatellite instability immune, 14%), hypermutated, microsatellite unstable and strong immune activation; CMS2 (canonical, 37%), epithelial, marked WNT and MYC signaling activation; CMS3 (metabolic, 13%), epithelial and evident metabolic dysregulation; and CMS4 (mesenchymal, 23%), prominent transforming growth factor-beta activation, stromal invasion and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intratumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC-with clear biological interpretability-and the basis for future clinical stratification and subtype-based targeted interventions

Identity by Descent Mapping of Founder Mutations in Cancer Using High-Resolution Tumor SNP Data

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the “missing” heritability in cancer. This method is freely available and can be used online at the FounderTracker website