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  • Deciphering cancer stem cells regulatory circuits through an interactomeregulometranscriptome

    integrative approach

    Claire Rioualen, Rita El-Helou, Emmanuelle Charafe-Jauffret, Christophe Ginestier, Ghislain Bidaut

    Centre de Recherche en Cancrologie de Marseille, Inserm U10681, CNRS UMR72582, Aix-Marseille Universit3, Institut Paoli-Calmettes4, Marseille, 13009, France.

  • Breast Cancer

    Deadliest cancer in women worldwide 25% of cancers diagnosed in women More than 500,000 deaths per year Survival highly dependent on:

    Cancer subtype Cancer extension (early/late diagnosis) Patient (age, family background...)

    Breast cancer can be recurrent

  • Cancer Stem Cells (CSC)

    They could explain breast cancer recurrence after therapy

    Common characteristics with healthy stem cells: Self-renewal Differentiation

  • Design of the experiment

    Genome-wide miRNA sreening miR-600, a regulator of CSCs?

  • Design of the experiment

    miR-600SUM159 cancer cell line

  • Design of the experiment

    miR-600SUM159 cancer cell line

    LNA MIMIC

    xcontrol

    or or

  • Design of the experiment

    miR-600SUM159 cancer cell line

    LNA MIMIC

    xcontrol

    or or

    30hCancer stem cells (CSC) and mature cancer cells (MCC) are separated using Aldefluor*

    * ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome.Ginestier C et al., Cell Stem Cell. 2007 Nov;1(5):555-67. doi: 10.1016/j.stem.2007.08.014.

    CSC MCC

  • Network data

    Interactome: HPRD, MINT, INTAct, DIP, Proteinpedia,

    I2D, BioGrid 17k nodes 200k interactions

    Regulome: TRANSFAC, TRED, ITFP, PAZAR, OregAnno 2352 TFs 9k targets 70k regulations

  • Subnetworks detection

    1. Subnetwork seed detection

    Node * is called the seed. If the gene is differentially expressed in CSCs, it is kept and its neighbors are investigated next.

  • Subnetworks detection

    2. Neighbors exploration

    Nodes that increase the average score of the subnetwork are kept. Their neighbors are then investigated recursively too.

  • Subnetworks detection

    3. Subnetwork completion

    A node that is dismissed closes a path of expansion for the subnetwork. Once the score cannot be improved and all paths are closed, the subnetwork is complete.

  • Subnetworks detection

    4. Subnetworks statistical validation

    Every node is investigated as a seed. All kept subnetworks are statistically validated by randomizing interaction data, expression data and subnetworks interactions.

  • Detected Subnetworks

    4 sets of subnetworks are found: LNA-interactome LNA-regulome MIMIC-interactome MIMIC-regulome

  • Detected Subnetworks

    4 sets of subnetworks are found 42 subnetworks found in total

  • Detected Subnetworks

    4 sets of subnetworks are found 42 subnetworks found in total 35 switchers detected

    LNAMIMIC

  • Regulome-Interactome integration

    Genes switches can be integrated into pathways switches

  • Regulome-Interactome integration

    Pathways seem to have a mirror effect too Enrichment in GO terms related to cell proliferation

  • HTML report

  • HTML report

  • HTML report

  • HTML report

  • Conclusion A new multi-level integrative approach mixing interactome,

    regulome, transcriptome data and post-translational information with a candidate approach

    The integrative analysis confirmed the potential implication of miR-600 in CSC differenciation or self-renewal

    Using a pathway approach to explore the biology of cancer stem cells shows connections between identified switcher genes & can reveal more genes involved

    Ultimately, elaborating a new drug targeting CSC pathways could greatly improve breast cancer treatments & clinical outcome

  • Thank you Integrative Bioinformatics Platform

    Ghislain Bidaut

    Quentin Da Costa

    Samuel Granjeaud

    Samad El Kaoutari Molecular oncology breast stem cell group

    Christophe Ginestier

    Rita El Helou

    Slide 2Slide 5Slide 22Slide 23

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