Stéphane Wenric

Circulating microRNA-based screening tool for breast cancer

Circulating microRNAs (miRNAs) are increasingly recognized as powerful biomarkers in several pathologies, including breast cancer. Here, their plasmatic levels were measured to be used as an alternative screening procedure to mammography for breast cancer diagnosis. A plasma miRNA profile was determined by RT-qPCR in a cohort of 378 women. A diagnostic model was designed based on the expression of 8 miRNAs measured first in a profiling cohort composed of 41 primary breast cancers and 45 controls, and further validated in diverse cohorts composed of 108 primary breast cancers, 88 controls, 35 breast cancers in remission, 31 metastatic breast cancers and 30 gynecologic tumors. A receiver operating characteristic curve derived from the 8-miRNA random forest based diagnostic tool exhibited an area under the curve of 0.81. The accuracy of the diagnostic tool remained unchanged considering age and tumor stage. The miRNA signature correctly identified patients with metastatic breast cancer. The use of the classification model on cohorts of patients with breast cancers in remission and with gynecologic cancers yielded prediction distributions similar to that of the control group. Using a multivariate supervised learning method and a set of 8 circulating miRNAs, we designed an accurate, minimally invasive screening tool for breast cancer.

Evaluation of BRCA1-related molecular features and microRNAs as prognostic factors for triple negative breast cancers.

BackgroundThe BRCA1 gene plays a key role in triple negative breast cancers (TNBCs), in which its expression can be lost by multiple mechanisms: germinal mutation followed by deletion of the second allele; negative regulation by promoter methylation; or miRNA-mediated silencing. This study aimed to establish a correlation among the BRCA1-related molecular parameters, tumor characteristics and clinical follow-up of patients to find new prognostic factors.MethodsBRCA1 protein and mRNA expression was quantified in situ in the TNBCs of 69 patients. BRCA1 promoter methylation status was checked, as well as cytokeratin 5/6 expression. Maintenance of expressed BRCA1 protein interaction with BARD1 was quantified, as a marker of BRCA1 functionality, and the tumor expression profiles of 27 microRNAs were determined.ResultsmiR-548c-5p was emphasized as a new independent prognostic factor in TNBC. A combination of the tumoral expression of miR-548c and three other known prognostic parameters (tumor size, lymph node invasion and CK 5/6 expression status) allowed for relapse prediction by logistic regression with an area under the curve (AUC) = 0.96.BRCA1 mRNA and protein in situ expression, as well as the amount of BRCA1 ligated to BARD1 in the tumor, lacked any associations with patient outcomes, likely due to high intratumoral heterogeneity, and thus could not be used for clinical purposes.ConclusionsIn situ BRCA1-related expression parameters could be used for clinical purposes at the time of diagnosis. In contrast, miR-548c-5p showed a promising potential as a prognostic factor in TNBC.

Transcriptome-wide analysis of natural antisense transcripts shows their potential role in breast cancer.

Non-coding RNAs (ncRNA) represent 1/5 of the mammalian transcript number, and 90% of the genome length is transcribed. Many ncRNAs play a role in cancer. Among them, non-coding natural antisense transcripts (ncNAT) are RNA sequences that are complementary and overlapping to those of either protein-coding (PCT) or non-coding transcripts. Several ncNATs were described as regulating protein coding gene expression on the same loci, and they are expected to act more frequently in cis compared to other ncRNAs that commonly function in trans. In this work, 22 breast cancers expressing estrogen receptors and their paired adjacent non-malignant tissues were analyzed by strand-specific RNA sequencing. To highlight ncNATs potentially playing a role in protein coding gene regulations that occur in breast cancer, three different data analysis methods were used: differential expression analysis of ncNATs between tumor and non-malignant tissues, differential correlation analysis of paired ncNAT/PCT between tumor and non-malignant tissues, and ncNAT/PCT read count ratio variation between tumor and non-malignant tissues. Each of these methods yielded lists of ncNAT/PCT pairs that were enriched in survival-associated genes. This work highlights ncNAT lists that display potential to affect the expression of protein-coding genes involved in breast cancer pathology.

Variations of circulating cardiac biomarkers during and after anthracycline-containing chemotherapy in breast cancer patients

BackgroundOver time, the chance of cure after the diagnosis of breast cancer has been increasing, as a consequence of earlier diagnosis, improved diagnostic procedures and more effective treatment options. However, oncologists are concerned by the risk of long term treatment side effects, including congestive heart failure (CHF).MethodsIn this study, we evaluated innovative circulating cardiac biomarkers during and after anthracycline-based neoadjuvant chemotherapy (NAC) in breast cancer patients. Levels of cardiac-specific troponins T (cTnT), N-terminal natriuretic peptides (NT-proBNP), soluble ST2 (sST2) and 10 circulating microRNAs (miRNAs) were measured.ResultsUnder chemotherapy, we observed an elevation of cTnT and NT-proBNP levels, but also the upregulation of sST2 and of 4 CHF-related miRNAs (miR-126-3p, miR-199a-3p, miR-423-5p, miR-34a-5p). The elevations of cTnT, NT-proBNP, sST2 and CHF-related miRNAs were poorly correlated, suggesting that these molecules could provide different information.ConclusionsCirculating miRNA and sST2 are potential biomarkers of the chemotherapy-related cardiac dysfunction (CRCD). Nevertheless, further studies and long-term follow-up are needed in order to evaluate if these new markers may help to predict CRCD and to identify the patients at risk to later develop CHF.

Genomic Studies of Multiple Myeloma Reveal an Association between X Chromosome Alterations and Genomic Profile Complexity.

The genomic profile of multiple myeloma (MM) has prognostic value by dividing patients into a good prognosis hyperdiploid group and a bad prognosis nonhyperdiploid group with a higher incidence of IGH translocations. This classification, however, is inadequate and many other parameters like mutations, epigenetic modifications, and genomic heterogeneity may influence the prognosis. We performed a genomic study by array‐based comparative genomic hybridization on a cohort of 162 patients to evaluate the frequency of genomic gains and losses. We identified a high frequency of X chromosome alterations leading to partial Xq duplication, often associated with inactive X (Xi) deletion in female patients. This partial X duplication could be a cytogenetic marker of aneuploidy as it is correlated with a high number of chromosomal breakages. Patient with high level of chromosomal breakage had reduced survival regardless the region implicated. A higher transcriptional level was shown for genes with potential implication in cancer and located in this altered region. Among these genes, IKBKG and IRAK1 are members of the NFKB pathway which plays an important role in MM and is a target for specific treatments.

Exome copy number variation detection: Use of a pool of unrelated healthy tissue as reference sample

An increasing number of bioinformatic tools designed to detect CNVs (copy number variants) in tumor samples based on paired exome data where a matched healthy tissue constitutes the reference have been published in the recent years. The idea of using a pool of unrelated healthy DNA as reference has previously been formulated but not thoroughly validated. As of today, the gold standard for CNV calling is still aCGH but there is an increasing interest in detecting CNVs by exome sequencing. We propose to design a metric allowing the comparison of two CNV profiles, independently of the technique used and assessed the validity of using a pool of unrelated healthy DNA instead of a matched healthy tissue as reference in exome‐based CNV detection. We compared the CNV profiles obtained with three different approaches (aCGH, exome sequencing with a matched healthy tissue as reference, exome sequencing with a pool of eight unrelated healthy tissue as reference) on three multiple myeloma samples. We show that the usual analyses performed to compare CNV profiles (deletion/amplification ratios and CNV size distribution) lack in precision when confronted with low LRR values, as they only consider the binary status of each CNV. We show that the metric‐based distance constitutes a more accurate comparison of two CNV profiles. Based on these analyses, we conclude that a reliable picture of CNV alterations in multiple myeloma samples can be obtained from whole‐exome sequencing in the absence of a matched healthy sample.