Guillem Rigaill

Frequent PTEN genomic alterations and activated phosphatidylinositol 3-kinase pathway in basal-like breast cancer cells

IntroductionBasal-like carcinomas (BLCs) and human epidermal growth factor receptor 2 overexpressing (HER2+) carcinomas are the subgroups of breast cancers that have the most aggressive clinical behaviour. In contrast to HER2+ carcinomas, no targeted therapy is currently available for the treatment of patients with BLCs. In order to discover potential therapeutic targets, we aimed to discover deregulated signalling pathways in human BLCs.MethodsIn this study, we focused on the oncogenic phosphatidylinositol 3-kinase (PI3K) pathway in 13 BLCs, and compared it with a control series of 11 hormonal receptor negative- and grade III-matched HER2+ carcinomas. The two tumour populations were first characterised by immunohistochemistry and gene expression. The PI3K pathway was then investigated by gene copy-number analysis, gene expression profiling and at a proteomic level using reverse-phase protein array technology and tissue microarray. The effects of the PI3K inhibition pathway on proliferation and apoptosis was further analysed in three human basal-like cell lines.ResultsThe PI3K pathway was found to be activated in BLCs and up-regulated compared with HER2+ tumours as shown by a significantly increased activation of the downstream targets Akt and mTOR (mammalian target of rapamycin). BLCs expressed significantly lower levels of the tumour suppressor PTEN and PTEN levels were significantly negatively correlated with Akt activity within that population. PTEN protein expression correlated significantly with PTEN DNA copy number and more importantly, reduced PTEN DNA copy numbers were observed specifically in BLCs. Similar to human samples, basal-like cell lines exhibited an activation of PI3K/Akt pathway and low/lack PTEN expression. Both PI3K and mTOR inhibitors led to basal-like cell growth arrest. However, apoptosis was specifically observed after PI3K inhibition.ConclusionsThese data provide insight into the molecular pathogenesis of BLCs and implicate the PTEN-dependent activated Akt signalling pathway as a potential therapeutic target for the management of patients with poor prognosis BLCs.

Genome Alteration Print (GAP): a tool to visualize and mine complex cancer genomic profiles obtained by SNP arrays

We describe a method for automatic detection of absolute segmental copy numbers and genotype status in complex cancer genome profiles measured with single-nucleotide polymorphism (SNP) arrays. The method is based on pattern recognition of segmented and smoothed copy number and allelic imbalance profiles. Assignments were verified by DNA indexes of primary tumors and karyotypes of cell lines. The method performs well even for poor-quality data, low tumor content, and highly rearranged tumor genomes.

Oxidative stress promotes myofibroblast differentiation and tumour spreading

JunD regulates genes involved in antioxidant defence. We took advantage of the chronic oxidative stress resulting from junD deletion to examine the role of reactive oxygen species (ROS) in tumour development. In a model of mammary carcinogenesis, junD inactivation increased tumour incidence and revealed an associated reactive stroma. junD‐inactivation in the stroma was sufficient to shorten tumour‐free survival rate and enhance metastatic spread. ROS promoted conversion of fibroblasts into highly migrating myofibroblasts through accumulation of the hypoxia‐inducible factor (HIF)‐1α transcription factor and the CXCL12 chemokine. Accordingly, treatment with an antioxidant reduced the levels of HIF and CXCL12 and numerous myofibroblast features. CXCL12 accumulated in the stroma of HER2‐human breast adenocarcinomas. Moreover, HER2 tumours exhibited a high proportion of myofibroblasts, which was significantly correlated to nodal metastases. Interestingly, this subset of tumours exhibited a significant nuclear exclusion of JunD and revealed an associated oxido‐reduction signature, further demonstrating the relevance of our findings in human cancers. Collectively, our data uncover a new mechanism by which oxidative stress increases the migratory properties of stromal fibroblasts, which in turn potentiate tumour dissemination.

Diaphanous-Related Formins Are Required for Invadopodia Formation and Invasion of Breast Tumor Cells

Proteolytic degradation of the extracellular matrix by metastatic tumor cells is initiated by the formation of invadopodia, i.e., actin-driven filopodia-like membrane protrusions endowed with matrix-degradative activity. A signaling cascade involving neural Wiskott-Aldrich syndrome protein and the Arp2/3 actin nucleating complex is involved in actin assembly at invadopodia. Yet, the mechanism of invadopodia formation is poorly understood. Based on their role as actin nucleators in cytoskeletal rearrangements, including filopodia formation, we examined the function of Diaphanous-related formins (DRF) in invadopodia formation and invasion by breast tumor cells. Using small interfering RNA silencing of protein expression in highly invasive MDA-MB-231 breast adenocarcinoma cells, we show that three members of the DRF family (DRF1-DRF3) are required for invadopodia formation and two-dimensional matrix proteolysis. We also report that invasion of a three-dimensional Matrigel matrix involves filopodia-like protrusions enriched for invadopodial proteins, including membrane type 1 matrix metalloproteinase, which depend on DRFs for their formation. These data identify DRFs as critical components of the invasive apparatus of tumor cells in two-dimensional and three-dimensional matrices and suggest that different types of actin nucleators cooperate during the formation of invadopodia.

Polo-like Kinase 1: A Potential Therapeutic Option in Combination with Conventional Chemotherapy for the Management of Patients with Triple-Negative Breast Cancer

Breast cancers are composed of molecularly distinct subtypes with different clinical outcomes and responses to therapy. To discover potential therapeutic targets for the poor prognosis-associated triple-negative breast cancer (TNBC), gene expression profiling was carried out on a cohort of 130 breast cancer samples. Polo-like kinase 1 (PLK1) was found to be significantly overexpressed in TNBC compared with the other breast cancer subtypes. High PLK1 expression was confirmed by reverse phase protein and tissue microarrays. In triple-negative cell lines, RNAi-mediated PLK1 depletion or inhibition of PLK1 activity with a small molecule (BI-2536) induced an increase in phosphorylated H2AX, G(2)-M arrest, and apoptosis. A soft-agar colony assay showed that PLK1 silencing impaired clonogenic potential of TNBC cell lines. When cells were grown in extracellular matrix gels (Matrigel), and exposed to BI-2536, apoptosis was observed specifically in TNBC cancerous cells, and not in a normal cell line. When administrated as a single agent, the PLK1 inhibitor significantly impaired tumor growth in vivo in two xenografts models established from biopsies of patients with TNBC. Most importantly, the administration of BI-2536, in combination with doxorubicin + cyclophosphamide chemotherapy, led to a faster complete response compared with the chemotherapy treatment alone and prevented relapse, which is the major risk associated with TNBC. Altogether, our observations suggest PLK1 inhibition as an attractive therapeutic approach, in association with conventional chemotherapy, for the management of patients with TNBC.

TTK/hMPS1 is an attractive therapeutic target for triple-negative breast cancer.

Triple-negative breast cancer (TNBC) represents a subgroup of breast cancers (BC) associated with the most aggressive clinical behavior. No targeted therapy is currently available for the treatment of patients with TNBC. In order to discover potential therapeutic targets, we searched for protein kinases that are overexpressed in human TNBC biopsies and whose silencing in TNBC cell lines causes cell death. A cohort including human BC biopsies obtained at Institut Curie as well as normal tissues has been analyzed at a gene-expression level. The data revealed that the human protein kinase monopolar spindle 1 (hMPS1), also known as TTK and involved in mitotic checkpoint, is specifically overexpressed in TNBC, compared to the other BC subgroups and healthy tissues. We confirmed by immunohistochemistry and reverse phase protein array that TNBC expressed higher levels of TTK protein compared to the other BC subgroups. We then determined the biological effects of TTK depletion by RNA interference, through analyses of tumorigenic capacity and cell viability in different human TNBC cell lines. We found that RNAi-mediated depletion of TTK in various TNBC cell lines severely compromised their viability and their ability to form colonies in an anchorage-independent manner. Moreover, we observed that TTK silencing led to an increase in H2AX phosphorylation, activation of caspases 3/7, sub-G1 cell population accumulation and high annexin V staining, as well as to a decrease in G1 phase cell population and an increased aneuploidy. Altogether, these data indicate that TTK depletion in TNBC cells induces apoptosis. These results point out TTK as a protein kinase overexpressed in TNBC that may represent an attractive therapeutic target specifically for this poor prognosis associated subgroup of breast cancer.

Exact posterior distributions and model selection criteria for multiple change-point detection problems

In segmentation problems, inference on change-point position and model selection are two difficult issues due to the discrete nature of change-points. In a Bayesian context, we derive exact, explicit and tractable formulae for the posterior distribution of variables such as the number of change-points or their positions. We also demonstrate that several classical Bayesian model selection criteria can be computed exactly. All these results are based on an efficient strategy to explore the whole segmentation space, which is very large. We illustrate our methodology on both simulated data and a comparative genomic hybridization profile.

On optimal multiple changepoint algorithms for large data

Many common approaches to detecting changepoints, for example based on statistical criteria such as penalised likelihood or minimum description length, can be formulated in terms of minimising a cost over segmentations. We focus on a class of dynamic programming algorithms that can solve the resulting minimisation problem exactly, and thus find the optimal segmentation under the given statistical criteria. The standard implementation of these dynamic programming methods have a computational cost that scales at least quadratically in the length of the time-series. Recently pruning ideas have been suggested that can speed up the dynamic programming algorithms, whilst still being guaranteed to be optimal, in that they find the true minimum of the cost function. Here we extend these pruning methods, and introduce two new algorithms for segmenting data: FPOP and SNIP. Empirical results show that FPOP is substantially faster than existing dynamic programming methods, and unlike the existing methods its computational efficiency is robust to the number of changepoints in the data. We evaluate the method for detecting copy number variations and observe that FPOP has a computational cost that is even competitive with that of binary segmentation, but can give much more accurate segmentations.

Segmentor3IsBack: an R package for the fast and exact segmentation of Seq-data

BackgroundChange point problems arise in many genomic analyses such as the detection of copy number variations or the detection of transcribed regions. The expanding Next Generation Sequencing technologies now allow to locate change points at the nucleotide resolution.ResultsBecause of its complexity which is almost linear in the sequence length when the maximal number of segments is constant, and as its performance had been acknowledged for microarrays, we propose to use the Pruned Dynamic Programming algorithm for Seq-experiment outputs. This requires the adaptation of the algorithm to the negative binomial distribution with which we model the data. We show that if the dispersion in the signal is known, the PDP algorithm can be used, and we provide an estimator for this dispersion. We describe a compression framework which reduces the time complexity without modifying the accuracy of the segmentation. We propose to estimate the number of segments via a penalized likelihood criterion. We illustrate the performance of the proposed methodology on RNA-Seq data.ConclusionsWe illustrate the results of our approach on a real dataset and show its good performance. Our algorithm is available as an R package on the CRAN repository.

Genomic Instability: A Stronger Prognostic Marker Than Proliferation for Early Stage Luminal Breast Carcinomas

Background The accurate prognosis definition to tailor treatment for early luminal invasive breast carcinoma patients remains challenging. Materials and Methods Two hundred fourteen early luminal breast carcinomas were genotyped with single nucleotide polymorphisms (SNPs) array to determine the number of chromosomal breakpoints as a marker of genomic instability. Proliferation was assessed by KI67 (immunohistochemistry) and genomic grade index (transcriptomic analysis). IHC3 (IHC4 score for HER2 negative tumors) was also determined. Results In the training set (109 cases), the optimal cut-off was 34 breakpoints with a specificity of 0.94 and a sensitivity of 0.57 (Area under the curve (AUC): 0.81[0.71; 0.91]). In the validation set (105 cases), the outcome of patients with > 34 breakpoints (11 events / 22 patients) was poorer (logrank test p < 0.001; Relative Risk (RR): 3.7 [1.73; 7.92]), than that of patients with < 34 breakpoints (19 events / 83 patients).Whereas genomic grade and KI67 had a significant prognostic value in univariate analysis in contrast to IHC3 that failed to have a statistical significant prognostic value in this series, the number of breakpoints remained the only significant parameter predictive of outcome (RR: 3.47, Confidence Interval (CI [1.29; 9.31], p = 0.014)) in multivariate analysis . Conclusion Genomic instability, defined herein as a high number of chromosomal breakpoints, in early stage luminal breast carcinoma is a stronger prognostic marker than proliferation.