Three Ontologies to Define Phenotype Measurement Data

Background: There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol. Results: Three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository. Conclusion: An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies

Sessile Serrated Adenomas in the Proximal Colon are Likely to be Flat, Large and Occur in Smokers

Aim: To examine the epidemiology and the morphology of the proximal sessile serrated adenomas (SSAs). Methods: We conducted a retrospective study to identify patients with SSAs using a university-based hospital pathology database query from January 2007 to April 2011. Data collected included: age, gender, ethnicity, body mass index, diabetes, smoking, family history of colorectal cancer, aspirin, and statin use. We collected data on morphology of SSAs including site (proximal or distal), size, and endoscopic appearance (flat or protuberant). We also compared proximal SSAs to proximal tubular adenomas detected during same time period

Multi-omics analysis identifies therapeutic vulnerabilities in triple-negative breast cancer subtypes

Triple-negative breast cancer (TNBC) is a collection of biologically diverse cancers characterized by distinct transcriptional patterns, biology, and immune composition. TNBCs subtypes include two basal-like (BL1, BL2), a mesenchymal (M) and a luminal androgen receptor (LAR) subtype. Through a comprehensive analysis of mutation, copy number, transcriptomic, epigenetic, proteomic, and phospho-proteomic patterns we describe the genomic landscape of TNBC subtypes. Mesenchymal subtype tumors display high mutation loads, genomic instability, absence of immune cells, low PD-L1 expression, decreased global DNA methylation, and transcriptional repression of antigen presentation genes. We demonstrate that major histocompatibility complex I (MHC-I) is transcriptionally suppressed by H3K27me3 modifications by the polycomb repressor complex 2 (PRC2). Pharmacological inhibition of PRC2 subunits EZH2 or EED restores MHC-I expression and enhances chemotherapy efficacy in murine tumor models, providing a rationale for using PRC2 inhibitors in PD-L1 negative mesenchymal tumors. Subtype-specific differences in immune cell composition and differential genetic/pharmacological vulnerabilities suggest additional treatment strategies for TNBC

The brain microenvironment mediates resistance in luminal breast cancer to PI3K inhibition through HER3 activation

Although targeted therapies are often effective systemically, they fail to adequately control brain metastases. In preclinical models of breast cancer that faithfully recapitulate the disparate clinical responses in these microenvironments, we observed that brain metastases evade phosphatidylinositide 3-kinase (PI3K) inhibition despite drug accumulation in the brain lesions. In comparison to extracranial disease, we observed increased HER3 expression and phosphorylation in brain lesions. HER3 blockade overcame the resistance of HER2-amplified and/or PIK3CA-mutant breast cancer brain metastases to PI3K inhibitors, resulting in marked tumor growth delay and improvement in mouse survival. These data provide a mechanistic basis for therapeutic resistance in the brain microenvironment and identify translatable treatment strategies for HER2-amplified and/or PIK3CA-mutant breast cancer brain metastases

The molecular basis of breast cancer pathological phenotypes

The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or RPPA subtype. Marked nuclear pleomorphism, necrosis, inflammation and high mitotic count were associated with Basal-like subtype and have similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed using the METABRIC dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of epithelial tubule formation was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology and improve clinical management. This work is publicly accessible at www.dx.ai/tcga_breast

Lung Clearance Index to Track Acute Respiratory Events in School-Age Children with Cystic Fibrosis

Rationale: The lung clearance index (LCI) is responsive to acute respiratory events in preschool children with cystic fibrosis (CF), but its utility to identify and manage these events in school-age children with CF is not well defined. Objectives: To describe changes in LCI with acute respiratory events in school-age children with CF. Methods: In a multisite prospective observational study, the LCI and FEV1 were measured quarterly and during acute respiratory events. Linear regression was used to compare relative changes in LCI and FEV1% predicted at acute respiratory events. Logistic regression was used to compare the odds of a significant worsening in LCI and FEV1% predicted at acute respiratory events. Generalized estimating equation models were used to account for repeated events in the same subject. Measurements and Main Results: A total of 98 children with CF were followed for 2 years. There were 265 acute respiratory events. Relative to a stable baseline measure, LCI (+8.9%; 95% confidence interval, 6.5 to 11.3) and FEV1% predicted (−6.6%; 95% confidence interval, −8.3 to −5.0) worsened with acute respiratory events. A greater proportion of events had a worsening in LCI compared with a decline in FEV1% predicted (41.7% vs. 30.0%; P = 0.012); 53.9% of events were associated with worsening in LCI or FEV1. Neither LCI nor FEV1 recovered to baseline values at the next follow-up visit. Conclusions: In school-age children with CF, the LCI is a sensitive measure to assess lung function worsening with acute respiratory events and incomplete recovery at follow-up. In combination, the LCI and FEV1 capture a higher proportion of events with functional impairment

Determinants of lung disease progression measured by lung clearance index in children with cystic fibrosis

The lung clearance index (LCI) measured by the multiple breath washout (MBW) test is sensitive to early lung disease in children with cystic fibrosis. While LCI worsens during the preschool years in cystic fibrosis, there is limited evidence to clarify whether this continues during the early school age years, and whether the trajectory of disease progression as measured by LCI is modifiable. A cohort of children (healthy and cystic fibrosis) previously studied for 12 months as preschoolers were followed during school age (5–10 years). LCI was measured every 3 months for a period of 24 months using the Exhalyzer D MBW nitrogen washout device. Linear mixed effects regression was used to model changes in LCI over time. A total of 582 MBW measurements in 48 healthy subjects and 845 measurements in 64 cystic fibrosis subjects were available. The majority of children with cystic fibrosis had elevated LCI at the first preschool and first school age visits (57.8% (37 out of 64)), whereas all but six had normal forced expiratory volume in 1 s (FEV1) values at the first school age visit. During school age years, the course of disease was stable (−0.02 units·year−1 (95% CI −0.14–0.10). LCI measured during preschool years, as well as the rate of LCI change during this time period, were important determinants of LCI and FEV1, at school age. Preschool LCI was a major determinant of school age LCI; these findings further support that the preschool years are critical for early intervention strategies