Statistical methods for automated drug susceptibility testing: Bayesian minimum inhibitory concentration prediction from growth curves

Determination of the minimum inhibitory concentration (MIC) of a drug that prevents microbial growth is an important step for managing patients with infections. In this paper we present a novel probabilistic approach that accurately estimates MICs based on a panel of multiple curves reflecting features of bacterial growth. We develop a probabilistic model for determining whether a given dilution of an antimicrobial agent is the MIC given features of the growth curves over time. Because of the potentially large collection of features, we utilize Bayesian model selection to narrow the collection of predictors to the most important variables. In addition to point estimates of MICs, we are able to provide posterior probabilities that each dilution is the MIC based on the observed growth curves. The methods are easily automated and have been incorporated into the Becton--Dickinson PHOENIX automated susceptibility system that rapidly and accurately classifies the resistance of a large number of microorganisms in clinical samples. Over seventy-five studies to date have shown this new method provides improved estimation of MICs over existing approaches.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS217 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Clinical relevance of Neutral Endopeptidase (NEP/CD10) in melanoma

BACKGROUND: Overexpression of Neutral Endopeptidase (NEP) has been reported in metastatic carcinomas, implicating NEP in tumor progression and suggesting a role for NEP inhibitors in its treatment. We investigated the role of NEP expression in the clinical progression of cutaneous melanoma. METHODS: We screened 7 melanoma cell lines for NEP protein expression. NEP-specific siRNA was transfected into the lines to examine the role of gene transcription in NEP expression. Immunohistochemistry was done for 93 specimens and correlated with clinicopathologic parameters. Thirty-seven metastatic melanoma specimens were examined for NEP transcript expression using Affymetrix GeneChips. In a subset of 25 specimens for which both transcript and protein expression was available, expression ratios were used to identify genes that co-express with NEP in GeneChip analysis. RESULTS: NEP was overexpressed in 4/7 human melanoma cell lines, and siRNA knock-down of NEP transcripts led to downregulation of its protein expression. NEP protein overexpression was significantly more common in metastatic versus primary tumors (P = 0.002). Twelve of 37 (32%) metastatic tumors had increased NEP transcript expression, and an association was observed between NEP transcript upregulation and protein overexpression (P < 0.0001). Thirty-eight genes were found to significantly co-express with NEP (p < 0.005). Thirty-three genes positively correlated with NEP, including genes involved in the MAP kinase pathway, antigen processing and presentation, apoptosis, and WNT signaling pathway, and 5 genes negatively correlated with NEP, including genes of focal adhesion and the notch signaling pathways. CONCLUSION: NEP overexpression, which seems to be largely driven by increased transcription, is rare in primary melanoma and occurs late in melanoma progression. Functional studies are needed to better understand the mechanisms of NEP regulation in melanoma

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Biologic Phenotyping of the Human Small Airway Epithelial Response to Cigarette Smoking

BACKGROUND: The first changes associated with smoking are in the small airway epithelium (SAE). Given that smoking alters SAE gene expression, but only a fraction of smokers develop chronic obstructive pulmonary disease (COPD), we hypothesized that assessment of SAE genome-wide gene expression would permit biologic phenotyping of the smoking response, and that a subset of healthy smokers would have a "COPD-like" SAE transcriptome. METHODOLOGY/PRINCIPAL FINDINGS: SAE (10th-12th generation) was obtained via bronchoscopy of healthy nonsmokers, healthy smokers and COPD smokers and microarray analysis was used to identify differentially expressed genes. Individual responsiveness to smoking was quantified with an index representing the % of smoking-responsive genes abnormally expressed (I(SAE)), with healthy smokers grouped into "high" and "low" responders based on the proportion of smoking-responsive genes up- or down-regulated in each smoker. Smokers demonstrated significant variability in SAE transcriptome with I(SAE) ranging from 2.9 to 51.5%. While the SAE transcriptome of "low" responder healthy smokers differed from both "high" responders and smokers with COPD, the transcriptome of the "high" responder healthy smokers was indistinguishable from COPD smokers. CONCLUSION/SIGNIFICANCE: The SAE transcriptome can be used to classify clinically healthy smokers into subgroups with lesser and greater responses to cigarette smoking, even though these subgroups are indistinguishable by clinical criteria. This identifies a group of smokers with a "COPD-like" SAE transcriptome

Activation Status of Wnt/ß-Catenin Signaling in Normal and Neoplastic Breast Tissues: Relationship to HER2/neu Expression in Human and Mouse

Wnt/ß-catenin signaling is strongly implicated in neoplasia, but the role of this pathway in human breast cancer has been controversial. Here, we examined Wnt/ß-catenin pathway activation as a function of breast cancer progression, and tested for a relationship with HER2/neu expression, using a human tissue microarray comprising benign breast tissues, ductal carcinoma in situ (DCIS), and invasive carcinomas. Cores were scored for membranous ß-catenin, a key functional component of adherens junctions, and for nucleocytoplasmic ß-catenin, a hallmark of Wnt/ß-catenin pathway activation. Only 82% of benign samples exhibited membrane-associated ß-catenin, indicating a finite frequency of false-negative staining. The frequency of membrane positivity was similar in DCIS samples, but was significantly reduced in carcinomas (45%, P<0.001), consistent with loss of adherens junctions during acquisition of invasiveness. Negative membrane status in cancers correlated with higher grade (P = 0.04) and estrogen receptor-negative status (P = 0.03), both indices of poor prognosis. Unexpectedly, a substantial frequency of nucleocytoplasmic ß-catenin was observed in benign breast tissues (36%), similar to that in carcinomas (35%). Positive-staining basal nuclei observed in benign breast may identify putative stem cells. An increased frequency of nucleocytoplasmic ß-catenin was observed in DCIS tumors (56%), suggesting that pathway activation may be an early event in human breast neoplasia. A correlation was observed between HER2/neu expression and nucleocytoplasmic ß-catenin in node-positive carcinomas (P = 0.02). Furthermore, cytoplasmic ß-catenin was detected in HER2/neu-induced mouse mammary tumors. The Axin2NLSlacZ mouse strain, a previously validated reporter of mammary Wnt/ß-catenin signaling, was utilized to define in vivo transcriptional consequences of HER2/neu-induced ß-catenin accumulation. Discrete hyperplastic foci observed in mammary glands from bigenic MMTV/neu, Axin2NLSlacZ mice, highlighted by robust ß-catenin/TCF signaling, likely represent the earliest stage of mammary intraepithelial neoplasia in MMTV/neu mice. Our study thus provides provocative evidence for Wnt/ß-catenin signaling as an early, HER2/neu-inducible event in breast neoplasia

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements