David Gacquer

Principles Governing A-to-I RNA Editing in the Breast Cancer Transcriptome.

Summary Little is known about how RNA editing operates in cancer. Transcriptome analysis of 68 normal and cancerous breast tissues revealed that the editing enzyme ADAR acts uniformly, on the same loci, across tissues. In controlled ADAR expression experiments, the editing frequency increased at all loci with ADAR expression levels according to the logistic model. Loci-specific “editabilities,” i.e., propensities to be edited by ADAR, were quantifiable by fitting the logistic function to dose-response data. The editing frequency was increased in tumor cells in comparison to normal controls. Type I interferon response and ADAR DNA copy number together explained 53% of ADAR expression variance in breast cancers. ADAR silencing using small hairpin RNA lentivirus transduction in breast cancer cell lines led to less cell proliferation and more apoptosis. A-to-I editing is a pervasive, yet reproducible, source of variation that is globally controlled by 1q amplification and inflammation, both of which are highly prevalent among human cancers.

Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology

BackgroundMicroarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC’s subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated.Results16,097 genes common to the two platforms were retained for downstream analysis. Gene-wise comparison of microarray and RNA-Seq data revealed that 52% had a Spearman’s correlation coefficient greater than 0.7 with highly correlated genes displaying significantly higher expression levels. We found excellent correlation between microarray and RNA-Seq for the estrogen receptor (ER; rs = 0.973; 95% CI: 0.971-0.975), progesterone receptor (PgR; rs = 0.95; 0.947-0.954), and human epidermal growth factor receptor 2 (HER2; rs = 0.918; 0.912-0.923), while a few discordances between ER and PgR quantified by immunohistochemistry and RNA-Seq/microarray were observed. All the subtype classifiers evaluated agreed well (Cohen’s kappa coefficients >0.8) and all the proliferation-based GES showed excellent Spearman correlations between microarray and RNA-Seq (all rs >0.965). Immune-, stroma- and pathway-based GES showed a lower correlation relative to prognostic signatures (all rs >0.6).ConclusionsTo our knowledge, this is the first study to report a systematic comparison of RNA-Seq to microarray for the evaluation of single genes and GES clinically relevant to BC. According to our results, the vast majority of single gene biomarkers and well-established GES can be reliably evaluated using the RNA-Seq technology.

A general method to derive robust organ-specific gene expression-based differentiation indices: application to thyroid cancer diagnostic

Differentiation is central to development, while dedifferentiation is central to cancer progression. Hence, a quantitative assessment of differentiation would be most useful. We propose an unbiased method to derive organ-specific differentiation indices from gene expression data and demonstrate its usefulness in thyroid cancer diagnosis. We derived a list of thyroid-specific genes by selecting automatically those genes that are expressed at higher level in the thyroid than in any other organ in a normal tissues genome-wide gene expression compendium. The thyroid index of a tissue was defined as the median expression of these thyroid-specific genes in that tissue. As expected, the thyroid index was inversely correlated with meta-PCNA, a proliferation metagene, across a wide range of thyroid tumors. By contrast, the two indices were positively correlated in a time course of thyroid-stimulating hormone (TSH) activation of primary thyrocytes. Thus, the thyroid index captures biological information not integrated by proliferation rates. The differential diagnostic of follicular thyroid adenomas and follicular thyroid carcinoma is a notorious challenge for pathologists. The thyroid index discriminated them as accurately as did machine-learning classifiers trained on the genome-wide cancer data. Hence, although it was established exclusively from normal tissue data, the thyroid index integrates the relevant diagnostic information contained in tumoral transcriptomes. Similar results were obtained for the classification of the follicular vs classical variants of papillary thyroid cancers, that is, tumors dedifferentiating along a different route. The automated procedures demonstrated in the thyroid are applicable to other organs.

New global analysis of the microRNA transcriptome of primary tumors and lymph node metastases of papillary thyroid cancer

BackgroundPapillary Thyroid Cancer (PTC) is the most prevalent type of endocrine cancer. Its incidence has rapidly increased in recent decades but little is known regarding its complete microRNA transcriptome (miRNome). In addition, there is a need for molecular biomarkers allowing improved PTC diagnosis.MethodsWe performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deepsequencing of 59 normal samples, 495 PTC, and 8 LNM).ResultsWe performed small RNA deep-sequencing of 3 PTC, their matching normal tissues and lymph node metastases (LNM). We designed a new bioinformatics framework to handle each aspect of the miRNome: whole expression profiles, isomiRs distribution, non-templated additions distributions, RNA-editing or mutation. Results were validated experimentally by qRT-PCR on normal samples, tumors and LNM from 14 independent patients and in silico using the dataset from The Cancer Genome Atlas (small RNA deep-sequencing of 59 normal samples, 495 PTC, and 8 LNM). We confirmed already described up-regulations of microRNAs in PTC, such as miR-146b-5p or miR-222-3p, but we also identified down-regulated microRNAs, such as miR-7-5p or miR-30c-2-3p. We showed that these down-regulations are linked to the tumorigenesis process of thyrocytes. We selected the 14 most down-regulated microRNAs in PTC and we showed that they are potential biomarkers of PTC samples. Nevertheless, they can distinguish histological classical variants and follicular variants of PTC in the TCGA dataset. In addition, 12 of the 14 down-regulated microRNAs are significantly less expressed in aggressive PTC compared to non-aggressive PTC. We showed that the associated aggressive expression profile is mainly due to the presence of the BRAF V600E mutation. In general, primary tumors and LNM presented similar microRNA expression profiles but specific variations like the down-regulation of miR-7-2-3p and miR-30c-2-3p in LNM were observed. Investigations of the 5p-to-3p arm expression ratios, non-templated additions or isomiRs distributions revealed no major implication in PTC tumorigenesis process or LNM appearance.ConclusionsOur results showed that down-regulated microRNAs can be used as new potential common biomarkers of PTC and to distinguish main subtypes of PTC. MicroRNA expressions can be linked to the development of LNM of PTC. The bioinformatics framework that we have developed can be used as a starting point for the global analysis of any microRNA deep-sequencing data in an unbiased way.

No significant viral transcription detected in whole breast cancer transcriptomes

BackgroundStudies evaluating the presence of viral sequences in breast cancer (BC), including various strains of human papillomavirus and human herpes virus, have yielded conflicting results. Most were based on RT-PCR and in situ hybridization.MethodsIn this report we searched for expressed viral sequences in 58 BC transcriptomes using five distinct in silico methods. In addition, we complemented our RNA sequencing results with exome sequencing, PCR and immunohistochemistry (IHC) analyses. A control sample was used to test our in silico methods.ResultsAll of the computational methods correctly detected viral sequences in the control sample. We identified a small number of viral sequences belonging to human herpesvirus 4 and 6 and Merkel cell polyomavirus. The extremely low expression levels—two orders of magnitude lower than in a typical hepatitis B virus infection in hepatocellular carcinoma—did not suggest active infections. The presence of viral elements was confirmed in sample-matched exome sequences, but could not be confirmed by PCR or IHC.ConclusionsOur results show that no viral sequences are expressed in significant amounts in the BC investigated. The presence of non-transcribed viral DNA cannot be excluded.

Intratumor heterogeneity and clonal evolution in an aggressive papillary thyroid cancer and matched metastases

The contribution of intratumor heterogeneity to thyroid metastatic cancers is still unknown. The clonal relationships between the primary thyroid tumors and lymph nodes (LN) or distant metastases are also poorly understood. The objective of this study was to determine the phylogenetic relationships between matched primary thyroid tumors and metastases. We searched for non-synonymous single-nucleotide variants (nsSNVs), gene fusions, alternative transcripts, and loss of heterozygosity (LOH) by paired-end massively parallel sequencing of cDNA (RNA-Seq) in a patient diagnosed with an aggressive papillary thyroid cancer (PTC). Seven tumor samples from a stage IVc PTC patient were analyzed by RNA-Seq: two areas from the primary tumor, four areas from two LN metastases, and one area from a pleural metastasis (PLM). A large panel of other thyroid tumors was used for Sanger sequencing screening. We identified seven new nsSNVs. Some of these were early events clonally present in both the primary PTC and the three matched metastases. Other nsSNVs were private to the primary tumor, the LN metastases and/or the PLM. Three new gene fusions were identified. A novel cancer-specific KAZN alternative transcript was detected in this aggressive PTC and in dozens of additional thyroid tumors. The PLM harbored an exclusive whole-chromosome 19 LOH. We have presented the first, to our knowledge, deep sequencing study comparing the mutational spectra in a PTC and both LN and distant metastases. This study has yielded novel findings concerning intra-tumor heterogeneity, clonal evolution and metastases dissemination in thyroid cancer.

Human-Specific NOTCH2NL Genes Expand Cortical Neurogenesis through Delta/Notch Regulation

Summary The cerebral cortex underwent rapid expansion and increased complexity during recent hominid evolution. Gene duplications constitute a major evolutionary force, but their impact on human brain development remains unclear. Using tailored RNA sequencing (RNA-seq), we profiled the spatial and temporal expression of hominid-specific duplicated (HS) genes in the human fetal cortex and identified a repertoire of 35 HS genes displaying robust and dynamic patterns during cortical neurogenesis. Among them NOTCH2NL, human-specific paralogs of the NOTCH2 receptor, stood out for their ability to promote cortical progenitor maintenance. NOTCH2NL promote the clonal expansion of human cortical progenitors, ultimately leading to higher neuronal output. At the molecular level, NOTCH2NL function by activating the Notch pathway through inhibition of cis Delta/Notch interactions. Our study uncovers a large repertoire of recently evolved genes active during human corticogenesis and reveals how human-specific NOTCH paralogs may have contributed to the expansion of the human cortex.

Hominin-specific NOTCH2 paralogs expand human cortical neurogenesis through regulation of Delta/Notch interactions.

The human cerebral cortex has undergone rapid expansion and increased complexity during recent evolution. Hominid-specific gene duplications represent a major driving force of evolution, but their impact on human brain evolution remains unclear. Using tailored RNA sequencing (RNAseq), we profiled the spatial and temporal expression of Hominid-specific duplicated (HS) genes in the human fetal cortex, leading to the identification of a repertoire of 36 HS genes displaying robust and dynamic patterns during cortical neurogenesis. Among these we focused on NOTCH2NL, previously uncharacterized HS paralogs of NOTCH2. NOTCH2NL promote the clonal expansion of human cortical progenitors by increasing self-renewal, ultimately leading to higher neuronal output. NOTCH2NL function by activating the Notch pathway, through inhibition of Delta/Notch interactions. Our study uncovers a large repertoire of recently evolved genes linking genomic evolution to human brain development, and reveals how hominin-specific NOTCH paralogs may have contributed to the expansion of the human cortex.

Distinctive desmoplastic 3D morphology associated with BRAFV600E in papillary thyroid cancers.

Context Although 60% of papillary thyroid carcinomas are BRAFV600E mutant (PTCV600E), the increased aggressiveness of these cancers is still debated. Objective For PTCV600E we aimed to further characterize the extent of the stroma and its activation, the three-dimensional (3D) tumor-stroma interface, and the proliferation rates of tumor and stromal fibroblasts. Design We analyzed exomes, transcriptomes, and images of 364 papillary thyroid carcinoma (PTCs) from The Cancer Genome Atlas (TCGA), including 211 PTCV600E; stained 22 independent PTCs for BRAFV600E and Ki67; sequenced the exomes and stained BRAFV600E in 5 primary tumor blocks and 4 nodal metastases from one patient with PTCV600E; and reconstructed the 3D volumes of one tumor and one metastatic block at histological resolution. Results In TCGA, BRAFV600E was associated with higher expression of proliferation markers and lower expression of thyroid differentiation markers, independently of tumor purity. Moreover, PTCV600E, in line with their overall lower purity, also had higher expression of fibroblast- and T cell-associated genes and presented more fibrosis. Tumor cells that appeared disconnected on two-dimensional histological slices were revealed to be part of a unique tumor component in the 3D reconstructed microvolumes, and they formed a surprisingly complex connected space, infiltrating a proliferative stroma. Finally, in our PTC set, both stromal fibroblasts and tumor cells presented higher proliferation rates in PTCV600E. Conclusions Our results support the increased aggressiveness associated with BRAFV600E in PTC and shed light on the important role of the stroma in tumor expansion. The greater and more active fibrotic component predicts better efficiency of combined targeted treatments, as previously proposed for melanomaV600E.

Genomic hotspots but few recurrent fusion genes in breast cancer.

The advent of next generation sequencing technologies has boosted the interest in exploring the role of fusion genes in the development and progression of solid tumors. In breast cancer, most of the detected gene fusions seem to be “passenger” events while the presence of recurrent and driver fusions is still under study. We performed RNA sequencing in 55 well‐characterized breast cancer samples and 10 adjacent normal breast tissues, complemented by an analysis of SNP array data. We explored the presence of fusion genes and defined their association with breast cancer subtypes, clinical‐pathologic characteristics and copy number aberrations. Overall, 370 fusions were detected across the majority of the samples. HER2+ samples had significantly more fusions than triple negative and luminal subtypes. The number of fusions was correlated with histological grade, Ki67 and tumor size. Clusters of fusion genes were observed across the genome and a significant correlation of fusions with copy number aberrations and more specifically amplifications was also revealed. Despite the large number of fusion events, only a few were recurrent, while recurrent individual genes forming fusions with different partners were also detected including the estrogen receptor 1 gene in the previously detected ESR1—CCDC170 fusion. Overall we detected novel gene fusion events while we confirmed previously reported fusions. Genomic hotspots of fusion genes, differences between subtypes and small number of recurrent fusions are the most relevant characteristics of these events in breast cancer. Further investigation is necessary to comprehend the biological significance of these fusions.