Single-cell landscape in mammary epithelium reveals bipotent-like cells associated with breast cancer risk and outcome

Adult stem-cells may serve as the cell-of-origin for cancer, yet their unbiased identification in single cell RNA sequencing data is challenging due to the high dropout rate. In the case of breast, the existence of a bipotent stem-like state is also controversial. Here we apply a marker-free algorithm to scRNA-Seq data from the human mammary epithelium, revealing a high-potency cell-state enriched for an independent mammary stem-cell expression module. We validate this stem-like state in independent scRNA-Seq data. Our algorithm further predicts that the stem-like state is bipotent, a prediction we are able to validate using FACS sorted bulk expression data. The bipotent stem-like state correlates with clinical outcome in basal breast cancer and is characterized by overexpression of YBX1 and ENO1, two modulators of basal breast cancer risk. This study illustrates the power of a marker-free computational framework to identify a novel bipotent stem-like state in the mammary epithelium

Identification of Post-Transcriptional Modulators of Breast Cancer Transcription Factor Activity Using MINDy

We have recently identified transcription factors (TFs) that are key drivers of breast cancer risk. To better understand the pathways or sub-networks in which these TFs mediate their function we sought to identify upstream modulators of their activity. We applied the MINDy (Modulator Inference by Network Dynamics) algorithm to four TFs (ESR1, FOXA1, GATA3 and SPDEF) that are key drivers of estrogen receptor-positive (ER+) breast cancer risk, as well as cancer progression. Our computational analysis identified over 500 potential modulators. We assayed 189 of these and identified 55 genes with functional characteristics that were consistent with a role as TF modulators. In the future, the identified modulators may be tested as potential therapeutic targets, able to alter the activity of TFs that are critical in the development of breast cancer

An epidemiologic study of early biologic effects of benzene in Chinese workers.

Benzene is a recognized hematotoxin and leukemogen, but its mechanisms of action in humans are still uncertain. To provide insight into these processes, we carried out a cross-sectional study of 44 healthy workers currently exposed to benzene (median 8-hr time-weighted average; 31 ppm), and unexposed controls in Shanghai, China. Here we provide an overview of the study results on peripheral blood cells levels and somatic cell mutation frequency measured by the glycophorin A (GPA) gene loss assay and report on peripheral cytokine levels. All peripheral blood cells levels (i.e., total white blood cells, absolute lymphocyte count, platelets, red blood cells, and hemoglobin) were decreased among exposed workers compared to controls, with the exception of the red blood cell mean corpuscular volume, which was higher among exposed subjects. In contrast, peripheral cytokine levels (interleukin-3, interleukin-6, erythropoietin, granulocyte colony-stimulating factor, tissue necrosis factor-alpha) in a subset of the most highly exposed workers (n = 11) were similar to values in controls (n = 11), suggesting that benzene does not affect these growth factor levels in peripheral blood. The GPA assay measures stem cell or precursor erythroid cell mutations expressed in peripheral red blood cells of MN heterozygous subjects, identifying NN variants, which result from loss of the GPA M allele and duplication of the N allele, and N phi variants, which arise from gene inactivation. The NN (but not N phi) GPA variant cell frequency was elevated in the exposed workers compared with controls (mean +/- SD, 13.9 +/- 8.4 mutants per million cells versus 7.4 +/- 5.2 per million cells, (respectively; p = 0.0002), suggesting that benzene produces gene-duplicating but not gene-inactivating mutations at the GPA locus in bone marrow cells of exposed humans. These findings, combined with ongoing analyses of benzene macromolecular adducts and chromosomal aberrations, will provide an opportunity to comprehensively evaluate a wide range of early biologic effects associated with benzene exposure in humans

Statistical Gaussian Model of Image Regions in Stochastic Watershed Segmentation

International audienceStochastic watershed is an image segmentation technique based on mathematical morphology which produces a probability density function of image contours. Estimated probabilities depend mainly on local distances between pixels. This paper introduces a variant of stochastic watershed where the probabilities of contours are computed from a Gaussian model of image regions. In this framework, the basic ingredient is the distance between pairs of regions, hence a distance between normal distributions. Hence several alternatives of statistical distances for normal distributions are compared, namely Bhattacharyya distance, Hellinger metric distance and Wasserstein metric distance

Prenatal origin of childhood AML occurs less frequently than in childhood ALL

Background While there is enough convincing evidence in childhood acute lymphoblastic leukemia (ALL), the data on the pre-natal origin in childhood acute myeloid leukemia (AML) are less comprehensive. Our study aimed to screen Guthrie cards (neonatal blood spots) of non-infant childhood AML and ALL patients for the presence of their respective leukemic markers. Methods We analysed Guthrie cards of 12 ALL patients aged 2–6 years using immunoglobulin (Ig) and T-cell receptor (TCR) gene rearrangements (n = 15) and/or intronic breakpoints of TEL/AML1 fusion gene (n = 3). In AML patients (n = 13, age 1–14 years) PML/RARalpha (n = 4), CBFbeta/MYH11 (n = 3), AML1/ETO (n = 2), MLL/AF6 (n = 1), MLL/AF9 (n = 1) and MLL/AF10 (n = 1) fusion genes and/or internal tandem duplication of FLT3 gene (FLT3/ITD) (n = 2) were used as clonotypic markers. Assay sensitivity determined using serial dilutions of patient DNA into the DNA of a healthy donor allowed us to detect the pre-leukemic clone in Guthrie card providing 1–3 positive cells were present in the neonatal blood spot. Results In 3 patients with ALL (25%) we reproducibly detected their leukemic markers (Ig/TCR n = 2; TEL/AML1 n = 1) in the Guthrie card. We did not find patient-specific molecular markers in any patient with AML. Conclusion In the largest cohort examined so far we used identical approach for the backtracking of non-infant childhood ALL and AML. Our data suggest that either the prenatal origin of AML is less frequent or the load of pre-leukemic cells is significantly lower at birth in AML compared to ALL cases

Metabolic effects of diets differing in glycaemic index depend on age and endogenous GIP

Aims/hypothesis High- vs low-glycaemic index (GI) diets unfavourably affect body fat mass and metabolic markers in rodents. Different effects of these diets could be age-dependent, as well as mediated, in part, by carbohydrate-induced stimulation of glucose-dependent insulinotrophic polypeptide (GIP) signalling. Methods Young-adult (16 weeks) and aged (44 weeks) male wild-type (C57BL/6J) and GIP-receptor knockout (Gipr −/− ) mice were exposed to otherwise identical high-carbohydrate diets differing only in GI (20–26 weeks of intervention, n = 8–10 per group). Diet-induced changes in body fat distribution, liver fat, locomotor activity, markers of insulin sensitivity and substrate oxidation were investigated, as well as changes in the gene expression of anorexigenic and orexigenic hypothalamic factors related to food intake. Results Body weight significantly increased in young-adult high- vs low-GI fed mice (two-way ANOVA, p < 0.001), regardless of the Gipr genotype. The high-GI diet in young-adult mice also led to significantly increased fat mass and changes in metabolic markers that indicate reduced insulin sensitivity. Even though body fat mass also slightly increased in high- vs low-GI fed aged wild-type mice (p < 0.05), there were no significant changes in body weight and estimated insulin sensitivity in these animals. However, aged Gipr −/− vs wild-type mice on high-GI diet showed significantly lower cumulative net energy intake, increased locomotor activity and improved markers of insulin sensitivity. Conclusions/interpretation The metabolic benefits of a low-GI diet appear to be more pronounced in younger animals, regardless of the Gipr genotype. Inactivation of GIP signalling in aged animals on a high-GI diet, however, could be beneficial

BaalChIP: Bayesian analysis of allele-specific transcription factor binding in cancer genomes

Allele-specific measurements of transcription factor binding from ChIP-seq data are key to dissecting the allelic effects of non-coding variants and their contribution to phenotypic diversity. However, most methods of detecting an allelic imbalance assume diploid genomes. This assumption severely limits their applicability to cancer samples with frequent DNA copy-number changes. Here we present a Bayesian statistical approach called BaalChIP to correct for the effect of background allele frequency on the observed ChIP-seq read counts. BaalChIP allows the joint analysis of multiple ChIP-seq samples across a single variant and outperforms competing approaches in simulations. Using 548 ENCODE ChIP-seq and six targeted FAIRE-seq samples, we show that BaalChIP effectively corrects allele-specific analysis for copy-number variation and increases the power to detect putative cis-acting regulatory variants in cancer genomes.We would like to acknowledge the support of the University of Cambridge, Cancer Research UK (CRUK), and Hutchison Whampoa Limited. Parts of this work were funded by CRUK core grants C14303/A17197 and A19274 and the Breast Cancer Research Foundation

Correlation between nucleotide composition and folding energy of coding sequences with special attention to wobble bases

Background: The secondary structure and complexity of mRNA influences its accessibility to regulatory molecules (proteins, micro-RNAs), its stability and its level of expression. The mobile elements of the RNA sequence, the wobble bases, are expected to regulate the formation of structures encompassing coding sequences. Results: The sequence/folding energy (FE) relationship was studied by statistical, bioinformatic methods in 90 CDS containing 26,370 codons. I found that the FE (dG) associated with coding sequences is significant and negative (407 kcal/1000 bases, mean +/- S.E.M.) indicating that these sequences are able to form structures. However, the FE has only a small free component, less than 10% of the total. The contribution of the 1st and 3rd codon bases to the FE is larger than the contribution of the 2nd (central) bases. It is possible to achieve a ~ 4-fold change in FE by altering the wobble bases in synonymous codons. The sequence/FE relationship can be described with a simple algorithm, and the total FE can be predicted solely from the sequence composition of the nucleic acid. The contributions of different synonymous codons to the FE are additive and one codon cannot replace another. The accumulated contributions of synonymous codons of an amino acid to the total folding energy of an mRNA is strongly correlated to the relative amount of that amino acid in the translated protein. Conclusion: Synonymous codons are not interchangable with regard to their role in determining the mRNA FE and the relative amounts of amino acids in the translated protein, even if they are indistinguishable in respect of amino acid coding.Comment: 14 pages including 6 figures and 1 tabl

Using LASSO regression to detect predictive aggregate effects in genetic studies

We use least absolute shrinkage and selection operator (LASSO) regression to select genetic markers and phenotypic features that are most informative with respect to a trait of interest. We compare several strategies for applying LASSO methods in risk prediction models, using the Genetic Analysis Workshop 17 exome simulation data consisting of 697 individuals with information on genotypic and phenotypic features (smoking, age, sex) in 5-fold cross-validated fashion. The cross-validated averages of the area under the receiver operating curve range from 0.45 to 0.63 for different strategies using only genotypic markers. The same values are improved to 0.69–0.87 when both genotypic and phenotypic information are used. The ability of the LASSO method to find true causal markers is limited, but the method was able to discover several common variants (e.g., FLT1) under certain conditions