deciphering cancer stem cells regulatory circuits through an interactome–regulome–transcriptome...

Deciphering cancer stem cells regulatory circuits through an interactome–regulome–transcriptome

integrative approach

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

Centre de Recherche en Cancérologie de Marseille, Inserm U10681, CNRS UMR72582, Aix-Marseille Université3, 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?


miR-600SUM159 cancer cell line



LNA MIMIC

xcontrol

or or



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.


2. Neighbors exploration

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


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.


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


● 4 sets of subnetworks are found● 42 subnetworks found in total


● 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

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

deciphering cancer stem cells regulatory circuits through an interactome–regulome–transcriptome...

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