Thierry Pécot

Atypical E2F Repressors and Activators Coordinate Placental Development

The evolutionarily ancient arm of the E2f family of transcription factors consisting of the two atypical members E2f7 and E2f8 is essential for murine embryonic development. However, the critical tissues, cellular processes, and molecular pathways regulated by these two factors remain unknown. Using a series of fetal and placental lineage-specific cre mice, we show that E2F7/E2F8 functions in extraembryonic trophoblast lineages are both necessary and sufficient to carry fetuses to term. Expression profiling and biochemical approaches exposed the canonical E2F3a activator as a key family member that antagonizes E2F7/E2F8 functions. Remarkably, the concomitant loss of E2f3a normalized placental gene expression programs, corrected placental defects, and fostered the survival of E2f7/E2f8-deficient embryos to birth. In summary, we identified a placental transcriptional network tightly coordinated by activation and repression through two distinct arms of the E2F family that is essential for extraembryonic cell proliferation, placental development, and fetal viability.

Redeployment of Myc and E2f1-3 drives Rb-deficient cell cycles

Robust mechanisms to control cell proliferation have evolved to maintain the integrity of organ architecture. Here, we investigated how two critical proliferative pathways, Myc and E2f, are integrated to control cell cycles in normal and Rb-deficient cells using a murine intestinal model. We show that Myc and E2f1–3 have little impact on normal G1–S transitions. Instead, they synergistically control an S–G2 transcriptional program required for normal cell divisions and maintaining crypt–villus integrity. Surprisingly, Rb deficiency results in the Myc-dependent accumulation of E2f3 protein and chromatin repositioning of both Myc and E2f3, leading to the ‘super activation’ of a G1–S transcriptional program, ectopic S phase entry and rampant cell proliferation. These findings reveal that Rb-deficient cells hijack and redeploy Myc and E2f3 from an S–G2 program essential for normal cell cycles to a G1–S program that re-engages ectopic cell cycles, exposing an unanticipated addiction of Rb-null cells on Myc.

Identifying survival associated morphological features of triple negative breast cancer using multiple datasets

Background and objective Biomarkers for subtyping triple negative breast cancer (TNBC) are needed given the absence of responsive therapy and relatively poor prediction of survival. Morphology of cancer tissues is widely used in clinical practice for stratifying cancer patients, while genomic data are highly effective to classify cancer patients into subgroups. Thus integration of both morphological and genomic data is a promising approach in discovering new biomarkers for cancer outcome prediction. Here we propose a workflow for analyzing histopathological images and integrate them with genomic data for discovering biomarkers for TNBC. Materials and methods We developed an image analysis workflow for extracting a large collection of morphological features and deployed the same on histological images from The Cancer Genome Atlas (TCGA) TNBC samples during the discovery phase (n=44). Strong correlations between salient morphological features and gene expression profiles from the same patients were identified. We then evaluated the same morphological features in predicting survival using a local TNBC cohort (n=143). We further tested the predictive power on patient prognosis of correlated gene clusters using two other public gene expression datasets. Results and conclusion Using TCGA data, we identified 48 pairs of significantly correlated morphological features and gene clusters; four morphological features were able to separate the local cohort with significantly different survival outcomes. Gene clusters correlated with these four morphological features further proved to be effective in predicting patient survival using multiple public gene expression datasets. These results suggest the efficacy of our workflow and demonstrate that integrative analysis holds promise for discovering biomarkers of complex diseases.

Ets2 in tumor fibroblasts promotes angiogenesis in breast cancer.

Tumor fibroblasts are active partners in tumor progression, but the genes and pathways that mediate this collaboration are ill-defined. Previous work demonstrates that Ets2 function in stromal cells significantly contributes to breast tumor progression. Conditional mouse models were used to study the function of Ets2 in both mammary stromal fibroblasts and epithelial cells. Conditional inactivation of Ets2 in stromal fibroblasts in PyMT and ErbB2 driven tumors significantly reduced tumor growth, however deletion of Ets2 in epithelial cells in the PyMT model had no significant effect. Analysis of gene expression in fibroblasts revealed a tumor- and Ets2-dependent gene signature that was enriched in genes important for ECM remodeling, cell migration, and angiogenesis in both PyMT and ErbB2 driven-tumors. Consistent with these results, PyMT and ErbB2 tumors lacking Ets2 in fibroblasts had fewer functional blood vessels, and Ets2 in fibroblasts elicited changes in gene expression in tumor endothelial cells consistent with this phenotype. An in vivo angiogenesis assay revealed the ability of Ets2 in fibroblasts to promote blood vessel formation in the absence of tumor cells. Importantly, the Ets2-dependent gene expression signatures from both mouse models were able to distinguish human breast tumor stroma from normal stroma, and correlated with patient outcomes in two whole tumor breast cancer data sets. The data reveals a key function for Ets2 in tumor fibroblasts in signaling to endothelial cells to promote tumor angiogenesis. The results highlight the collaborative networks that orchestrate communication between stromal cells and tumor cells, and suggest that targeting tumor fibroblasts may be an effective strategy for developing novel anti-angiogenic therapies.

E2f3 in tumor macrophages promotes lung metastasis

The Rb-E2F axis is an important pathway involved in cell-cycle control that is deregulated in a number of cancers. E2f transcription factors have distinct roles in the control of cell proliferation, cell survival and differentiation in a variety of tissues. We have previously shown that E2fs are important downstream targets of a CSF-1 signaling cascade involved in myeloid development. In cancer, tumor-associated macrophages (TAMs) are recruited to the tumor stroma in response to cytokines secreted by tumor cells, and are believed to facilitate tumor cell invasion and metastasis. Using the MMTV-Polyoma Middle T antigen (PyMT) mouse model of human ductal carcinoma, we show that the specific ablation of E2f3 in TAMs, but not in tumor epithelial cells, attenuates lung metastasis without affecting primary tumor growth. Histological analysis and gene expression profiling suggest that E2f3 does not impact the proliferation or survival of TAMs, but rather controls a novel gene expression signature associated with cytoskeleton rearrangements, cell migration and adhesion. This E2f3 TAM gene expression signature was sufficient to predict cancer recurrence and overall survival of estrogen receptor (ER)-positive breast cancer patients. Interestingly, we find that E2f3b but not E2f3a levels are elevated in TAMs from PyMT mammary glands relative to controls, suggesting a differential role for these isoforms in metastasis. In summary, these findings identify E2f3 as a key transcription factor in TAMs, which influences the tumor microenvironment and tumor cell metastasis.

Noncatalytic PTEN missense mutation predisposes to organ-selective cancer development in vivo

Inactivation of phosphatase and tensin homology deleted on chromosome 10 (PTEN) is linked to increased PI3K-AKT signaling, enhanced organismal growth, and cancer development. Here we generated and analyzed Pten knock-in mice harboring a C2 domain missense mutation at phenylalanine 341 (Pten(FV)), found in human cancer. Despite having reduced levels of PTEN protein, homozygous Pten(FV/FV) embryos have intact AKT signaling, develop normally, and are carried to term. Heterozygous Pten(FV/+) mice develop carcinoma in the thymus, stomach, adrenal medulla, and mammary gland but not in other organs typically sensitive to Pten deficiency, including the thyroid, prostate, and uterus. Progression to carcinoma in sensitive organs ensues in the absence of overt AKT activation. Carcinoma in the uterus, a cancer-resistant organ, requires a second clonal event associated with the spontaneous activation of AKT and downstream signaling. In summary, this PTEN noncatalytic missense mutation exposes a core tumor suppressor function distinct from inhibition of canonical AKT signaling that predisposes to organ-selective cancer development in vivo.

Non parametric cell nuclei segmentation based on a tracking over depth from 3D fluorescence confocal images

3D cell nuclei segmentation from fluorescence microscopy images is a key application in many biological studies. We propose a new, fully automated and non parametric method that takes advantage of the resolution anisotropy in fluorescence microscopy. The cell nuclei are first detected in 2D at each image plane and then tracked over depth through a graph based decision to recover their 3D profiles. As the tracking fails to separate very close cell nuclei along depth, we also propose a corrective step based on an intensity projection criterion. Experimental results on real data demonstrate the efficacy of the proposed method.

Actin grips: Circular actin-rich cytoskeletal structures that mediate the wrapping of polymeric microfibers by endothelial cells

Interaction of endothelial-lineage cells with three-dimensional substrates was much less studied than that with flat culture surfaces. We investigated the in vitro attachment of both mature endothelial cells (ECs) and of less differentiated EC colony-forming cells to poly-e-capro-lactone (PCL) fibers with diameters in 5–20 μm range (‘scaffold microfibers’, SMFs). We found that notwithstanding the poor intrinsic adhesiveness to PCL, both cell types completely wrapped the SMFs after long-term cultivation, thus attaining a cylindrical morphology. In this system, both EC types grew vigorously for more than a week and became increasingly more differentiated, as shown by multiplexed gene expression. Three-dimensional reconstructions from multiphoton confocal microscopy images using custom software showed that the filamentous (F) actin bundles took a conspicuous ring-like organization around the SMFs. Unlike the classical F-actin-containing stress fibers, these rings were not associated with either focal adhesions or intermediate filaments. We also demonstrated that plasma membrane boundaries adjacent to these circular cytoskeletal structures were tightly yet dynamically apposed to the SMFs, for which reason we suggest to call them ‘actin grips’. In conclusion, we describe a particular form of F-actin assembly with relevance for cytoskeletal organization in response to biomaterials, for endothelial-specific cell behavior in vitro and in vivo, and for tissue engineering.

A signal processing approach for enriched region detection in RNA polymerase II ChIP-seq data

BackgroundRNA polymerase II (PolII) is essential in gene transcription and ChIP-seq experiments have been used to study PolII binding patterns over the entire genome. However, since PolII enriched regions in the genome can be very long, existing peak finding algorithms for ChIP-seq data are not adequate for identifying such long regions.MethodsHere we propose an enriched region detection method for ChIP-seq data to identify long enriched regions by combining a signal denoising algorithm with a false discovery rate (FDR) approach. The binned ChIP-seq data for PolII are first processed using a non-local means (NL-means) algorithm for purposes of denoising. Then, a FDR approach is developed to determine the threshold for marking enriched regions in the binned histogram.ResultsWe first test our method using a public PolII ChIP-seq dataset and compare our results with published results obtained using the published algorithm HPeak. Our results show a high consistency with the published results (80-100%). Then, we apply our proposed method on PolII ChIP-seq data generated in our own study on the effects of hormone on the breast cancer cell line MCF7. The results demonstrate that our method can effectively identify long enriched regions in ChIP-seq datasets. Specifically, pertaining to MCF7 control samples we identified 5,911 segments with length of at least 4 Kbp (maximum 233,000 bp); and in MCF7 treated with E2 samples, we identified 6,200 such segments (maximum 325,000 bp).ConclusionsWe demonstrated the effectiveness of this method in studying binding patterns of PolII in cancer cells which enables further deep analysis in transcription regulation and epigenetics. Our method complements existing peak detection algorithms for ChIP-seq experiments.

Non-parametric population analysis of cellular phenotypes

Methods to quantify cellular-level phenotypic differences between genetic groups are a key tool in genomics research. In disease processes such as cancer, phenotypic changes at the cellular level frequently manifest in the modification of cell population profiles. These changes are hard to detect due the ambiguity in identifying distinct cell phenotypes within a population. We present a methodology which enables the detection of such changes by generating a phenotypic signature of cell populations in a data-derived feature-space. Further, this signature is used to estimate a model for the redistribution of phenotypes that was induced by the genetic change. Results are presented on an experiment involving deletion of a tumor-suppressor gene dominant in breast cancer, where the methodology is used to detect changes in nuclear morphology between control and knockout groups.