The GATA3 X308_Splice breast cancer mutation is a hormone context-dependent oncogenic driver

As the catalog of oncogenic driver mutations is expanding, it becomes clear that alterations in a given gene might have different functions and should not be lumped into one class. The transcription factor GATA3 is a paradigm of this. We investigated the functions of the most common GATA3 mutation (X308_Splice) and five additional mutations, which converge into a neoprotein that we called “neoGATA3,” associated with excellent prognosis in patients. Analysis of available molecular data from >3000 breast cancer patients revealed a dysregulation of the ER-dependent transcriptional response in tumors carrying neoGATA3-generating mutations. Mechanistic studies in vitro showed that neoGATA3 interferes with the transcriptional programs controlled by estrogen and progesterone receptors, without fully abrogating them. ChIP-Seq analysis indicated that ER binding is reduced in neoGATA3-expressing cells, especially at distal regions, suggesting that neoGATA3 interferes with the fine tuning of ER-dependent gene expression. This has opposite outputs in distinct hormonal context, having pro- or anti-proliferative effects, depending on the estrogen/progesterone ratio. Our data call for functional analyses of putative cancer drivers to guide clinical application.Institute of Cancer Research of the Medical University Vienna and by the grant P27361-B23 from the Austrian Science Grant (FWF), FXR was supported by SAF2011-29530 and SAF2015-70553-R grants from Ministerio de Economía y Competitividad (Madrid, Spain) (co-funded by the ERDF-EU), Fundación Científica de la Asociación Española Contra el Cáncer. CNIO is supported by Ministerio de Ciencia, Innovación y Universidades as a Centro de Excelencia Severo Ochoa SEV-2015-051

Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies

High-throughput post-genomic studies are now routinely and promisingly investigated in biological and biomedical research. The main statistical approach to select genes differentially expressed between two groups is to apply a t-test, which is subject of criticism in the literature. Numerous alternatives have been developed based on different and innovative variance modeling strategies. However, a critical issue is that selecting a different test usually leads to a different gene list. In this context and given the current tendency to apply the t-test, identifying the most efficient approach in practice remains crucial. To provide elements to answer, we conduct a comparison of eight tests representative of variance modeling strategies in gene expression data: Welch's t-test, ANOVA [1], Wilcoxon's test, SAM [2], RVM [3], limma [4], VarMixt [5] and SMVar [6]. Our comparison process relies on four steps (gene list analysis, simulations, spike-in data and re-sampling) to formulate comprehensive and robust conclusions about test performance, in terms of statistical power, false-positive rate, execution time and ease of use. Our results raise concerns about the ability of some methods to control the expected number of false positives at a desirable level. Besides, two tests (limma and VarMixt) show significant improvement compared to the t-test, in particular to deal with small sample sizes. In addition limma presents several practical advantages, so we advocate its application to analyze gene expression data

Molecular apocrine differentiation is a common feature of breast cancer in patients with germline PTEN mutations

International audienceINTRODUCTION: Breast carcinoma is the main malignant tumor occurring in patients with Cowden disease, a cancer-prone syndrome caused by germline mutation of the tumor suppressor gene PTEN characterized by the occurrence throughout life of hyperplastic, hamartomatous and malignant growths affecting various organs. The absence of known histological features for breast cancer arising in a PTEN-mutant background prompted us to explore them for potential new markers. METHODS: We first performed a microarray study of three tumors from patients with Cowden disease in the context of a transcriptomic study of 74 familial breast cancers. A subsequent histological and immunohistochemical study including 12 additional cases of Cowden disease breast carcinomas was performed to confirm the microarray data. RESULTS: Unsupervised clustering of the 74 familial tumors followed the intrinsic gene classification of breast cancer except for a group of five tumors that included the three Cowden tumors. The gene expression profile of the Cowden tumors shows considerable overlap with that of a breast cancer subgroup known as molecular apocrine breast carcinoma, which is suspected to have increased androgenic signaling and shows frequent ERBB2 amplification in sporadic tumors. The histological and immunohistochemical study showed that several cases had apocrine histological features and expressed GGT1, which is a potential new marker for apocrine breast carcinoma. CONCLUSIONS: These data suggest that activation of the ERBB2-PI3K-AKT pathway by loss of PTEN at early stages of tumorigenesis promotes the formation of breast tumors with apocrine features

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression

International audienceQuantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases. While numerous methods can quantify immune or stromal cells in human tissue samples from transcriptomic data, few are available for mouse studies. We introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that accurately quantify 16 immune and stromal murine cell populations. We validated mMCP-counter with flow cytometry data and showed that mMCP-counter outperforms existing methods. We showed that mMCP-counter scores are predictive of response to immune checkpoint blockade in cancer mouse models and identify early immune impacts of Alzheimer's disease

The GATA3 X308_Splice breast cancer mutation is a hormone context-dependent oncogenic driver

Funder: Spanish Ministry of Science, Innovation, and University. BFU2016-80570-RFunder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289Funder: Fundación Científica Asociación Española Contra el Cáncer (Scientific Foundation, Spanish Association Against Cancer); doi: https://doi.org/10.13039/501100002704Abstract: As the catalog of oncogenic driver mutations is expanding, it becomes clear that alterations in a given gene might have different functions and should not be lumped into one class. The transcription factor GATA3 is a paradigm of this. We investigated the functions of the most common GATA3 mutation (X308_Splice) and five additional mutations, which converge into a neoprotein that we called “neoGATA3,” associated with excellent prognosis in patients. Analysis of available molecular data from >3000 breast cancer patients revealed a dysregulation of the ER-dependent transcriptional response in tumors carrying neoGATA3-generating mutations. Mechanistic studies in vitro showed that neoGATA3 interferes with the transcriptional programs controlled by estrogen and progesterone receptors, without fully abrogating them. ChIP-Seq analysis indicated that ER binding is reduced in neoGATA3-expressing cells, especially at distal regions, suggesting that neoGATA3 interferes with the fine tuning of ER-dependent gene expression. This has opposite outputs in distinct hormonal context, having pro- or anti-proliferative effects, depending on the estrogen/progesterone ratio. Our data call for functional analyses of putative cancer drivers to guide clinical application

Prognostic value of circulating tumour DNA in metastatic pancreatic cancer patients: post-hoc analyses of two clinical trials

International audienceObjective: The prognostication of metastatic pancreatic adenocarcinoma (mPDAC) patients remains uncertain, mainly based on carbohydrate antigen 19-9 (CA19-9), with limited utility. Circulating tumour DNA (ctDNA) has been suggested as a prognostic factor, but its added value has been poorly explored. The objective was to determine whether ctDNA is an independent factor for the prognostication of mPDAC.Design: Translational study based on two prospective collections of plasma samples of mPDAC patients naïve for chemotherapy. One used as a test series and the other as validation series coming from two randomised trials (Prodige 35 and Prodige 37). CtDNA was assessed by digital droplet PCR targeting two methylated markers (HOXD8 and POU4F1) according to a newly developed and validated method. Univariate and multivariate analyses were performed according to ctDNA status.Results: Of 372 plasma samples available, 354 patients were analyzed for survival. In the validation series, 145 of 255 patients were found ctDNA positive (56.8%), Median PFS and OS were 5.3 and 8.2 months in ctDNA-positive and 6.2 and 12.6 months in ctDNA-negative patients, respectively. ctDNA positivity was more often associated with young age, high CA19-9 level and neutrophils lymphocytes ratio. In multivariate analysis including these previous markers, ctDNA was confirmed as an independent prognostic marker for PFS (adjusted hazard ratio (HR) 1.5, CI 95% [1.03-2.18], p = 0.034) and OS (HR 1.62, CI 95% [1.05-2.5], p = 0.029).Conclusions: In this first ctDNA assessment in a large series of mPDAC derived from clinical trials, ctDNA was detectable in 56.8% of patients and confirmed as an independent prognostic marker