Mapping the cellular and molecular heterogeneity of normal and malignant breast tissues and cultured cell lines

Introduction: Normal and neoplastic breast tissues are comprised of heterogeneous populations of epithelial cells exhibiting various degrees of maturation and differentiation. While cultured cell lines have been derived from both normal and malignant tissues, it remains unclear to what extent they retain similar levels of differentiation and heterogeneity as that found within breast tissues. Methods: We used 12 reduction mammoplasty tissues, 15 primary breast cancer tissues, and 20 human breast epithelial cell lines (16 cancer lines, 4 normal lines) to perform flow cytometry for CD44, CD24, epithelial cell adhesion molecule (EpCAM), and CD49f expression, as well as immunohistochemistry, and in vivo tumor xenograft formation studies to extensively analyze the molecular and cellular characteristics of breast epithelial cell lineages. Results: Human breast tissues contain four distinguishable epithelial differentiation states (two luminal phenotypes and two basal phenotypes) that differ on the basis of CD24, EpCAM and CD49f expression. Primary human breast cancer tissues also contain these four cellular states, but in altered proportions compared to normal tissues. In contrast, cultured cancer cell lines are enriched for rare basal and mesenchymal epithelial phenotypes, which are normally present in small numbers within human tissues. Similarly, cultured normal human mammary epithelial cell lines are enriched for rare basal and mesenchymal phenotypes that represent a minor fraction of cells within reduction mammoplasty tissues. Furthermore, although normal human mammary epithelial cell lines exhibit features of bi-potent progenitor cells they are unable to differentiate into mature luminal breast epithelial cells under standard culture conditions. Conclusions: As a group breast cancer cell lines represent the heterogeneity of human breast tumors, but individually they exhibit increased lineage-restricted profiles that fall short of truly representing the intratumoral heterogeneity of individual breast tumors. Additionally, normal human mammary epithelial cell lines fail to retain much of the cellular diversity found in human breast tissues and are enriched for differentiation states that are a minority in breast tissues, although they do exhibit features of bi-potent basal progenitor cells. These findings suggest that collections of cell lines representing multiple cell types can be used to model the cellular heterogeneity of tissues

Diabetes and risk of pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium

Diabetes is a suspected risk factor for pancreatic cancer, but questions remain about whether it is a risk factor or a result of the disease. This study prospectively examined the association between diabetes and the risk of pancreatic adenocarcinoma in pooled data from the NCI pancreatic cancer cohort consortium (PanScan). The pooled data included 1,621 pancreatic adenocarcinoma cases and 1,719 matched controls from twelve cohorts using a nested case-control study design. Subjects who were diagnosed with diabetes near the time (< 2 years) of pancreatic cancer diagnosis were excluded from all analyses. All analyses were adjusted for age, race, gender, study, alcohol use, smoking, BMI, and family history of pancreatic cancer. Self-reported diabetes was associated with a forty percent increased risk of pancreatic cancer (OR = 1.40, 95 % CI: 1.07, 1.84). The association differed by duration of diabetes; risk was highest for those with a duration of 2-8 years (OR = 1.79, 95 % CI: 1.25, 2.55); there was no association for those with 9+ years of diabetes (OR = 1.02, 95 % CI: 0.68, 1.52). These findings provide support for a relationship between diabetes and pancreatic cancer risk. The absence of association in those with the longest duration of diabetes may reflect hypoinsulinemia and warrants further investigation

DNA Polymerase Epsilon Deficiency Causes IMAGe Syndrome with Variable Immunodeficiency.

During genome replication, polymerase epsilon (Pol ε) acts as the major leading-strand DNA polymerase. Here we report the identification of biallelic mutations in POLE, encoding the Pol ε catalytic subunit POLE1, in 15 individuals from 12 families. Phenotypically, these individuals had clinical features closely resembling IMAGe syndrome (intrauterine growth restriction [IUGR], metaphyseal dysplasia, adrenal hypoplasia congenita, and genitourinary anomalies in males), a disorder previously associated with gain-of-function mutations in CDKN1C. POLE1-deficient individuals also exhibited distinctive facial features and variable immune dysfunction with evidence of lymphocyte deficiency. All subjects shared the same intronic variant (c.1686+32C>G) as part of a common haplotype, in combination with different loss-of-function variants in trans. The intronic variant alters splicing, and together the biallelic mutations lead to cellular deficiency of Pol ε and delayed S-phase progression. In summary, we establish POLE as a second gene in which mutations cause IMAGe syndrome. These findings add to a growing list of disorders due to mutations in DNA replication genes that manifest growth restriction alongside adrenal dysfunction and/or immunodeficiency, consolidating these as replisome phenotypes and highlighting a need for future studies to understand the tissue-specific development roles of the encoded proteins

De Novo Mutations in SLC1A2 and CACNA1A Are Important Causes of Epileptic Encephalopathies

Epileptic encephalopathies (EEs) are the most clinically important group of severe early-onset epilepsies. Next-generation sequencing has highlighted the crucial contribution of de novo mutations to the genetic architecture of EEs as well as to their underlying genetic heterogeneity. Our previous whole-exome sequencing study of 264 parent-child trios revealed more than 290 candidate genes in which only a single individual had a de novo variant. We sought to identify additional pathogenic variants in a subset (n = 27) of these genes via targeted sequencing in an unsolved cohort of 531 individuals with a diverse range of EEs. We report 17 individuals with pathogenic variants in seven of the 27 genes, defining a genetic etiology in 3.2% of this unsolved cohort. Our results provide definitive evidence that de novo mutations in SLC1A2 and CACNA1A cause specific EEs and expand the compendium of clinically relevant genotypes for GABRB3. We also identified EEs caused by genetic variants in ALG13, DNM1, and GNAO1 and report a mutation in IQSEC2. Notably, recurrent mutations accounted for 7/17 of the pathogenic variants identified. As a result of high-depth coverage, parental mosaicism was identified in two out of 14 cases tested with mutant allelic fractions of 5%–6% in the unaffected parents, carrying significant reproductive counseling implications. These results confirm that dysregulation in diverse cellular neuronal pathways causes EEs, and they will inform the diagnosis and management of individuals with these devastating disorders

Measurement of associated Z plus charm production in proton-proton collisions at root s=8TeV

A study of the associated production of a Z boson and a charm quark jet (Z + c), and a comparison to production with a b quark jet (Z + b), in pp collisions at a centre-of-mass energy of 8 TeV are presented. The analysis uses a data sample corresponding to an integrated luminosity of 19.7 fb(-1), collected with the CMS detector at the CERN LHC. The Z boson candidates are identified through their decays into pairs of electrons or muons. Jets originating from heavy flavour quarks are identified using semileptonic decays of c or b flavoured hadrons and hadronic decays of charm hadrons. The measurements are performed in the kinematic region with two leptons with pT(l) > 20 GeV, vertical bar eta(l)vertical bar 25 GeV and vertical bar eta(jet)vertical bar Z + c + X) B(Z -> l(+)l(-)) = 8.8 +/- 0.5 (stat)+/- 0.6 (syst) pb. The ratio of the Z+c and Z+b production cross sections is measured to be sigma(pp -> Z+c+X)/sigma (pp -> Z+b+X) = 2.0 +/- 0.2 (stat)+/- 0.2 (syst). The Z+c production cross section and the cross section ratio are also measured as a function of the transverse momentum of theZ boson and of the heavy flavour jet. The measurements are compared with theoretical predictions.Peer reviewe

Measurement of the underlying event activity in inclusive Z boson production in proton-proton collisions at root s=13 TeV

This paper presents a measurement of the underlying event activity in proton-proton collisions at a center-of-mass energy of 13TeV, performed using inclusive Z boson production events collected with the CMS experiment at the LHC. The analyzed data correspond to an integrated luminosity of 2.1 fb(-1). The underlying event activity is quantified in terms of the charged particle multiplicity, as well as of the scalar sum of the charged particles' transverse momenta in different topological regions defined with respect to the Z boson direction. The distributions are unfolded to the stable particle level and compared with predictions from various Monte Carlo event generators, as well as with similar CDF and CMS measurements at center-of-mass energies of 1.96 and 7TeV respectively.Peer reviewe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

DNA methylation-based measures of biological age:meta-analysis predicting time to death

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p ≤ 8.2 x 10-9), independent of chronological age, even after adjusting for additional risk factors (p < 5.4 x 10-4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p≤ 7.5 x 10-43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality