Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features

BACKGROUND: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. RESULTS: Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile). In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO) terms and the Conserved Domain Database (CDD) protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occured consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists contained groups of genes with the functional properties of membrane receptor biology/signal transduction and nucleic acid binding/transcription. A subset of the luminal markers was associated with metabolic and oxidoreductase activities, whereas a subset of myoepithelial markers was associated with protein hydrolase activity. CONCLUSION: Given a set of genes and/or proteins associated with a phenomenon, process or system of interest, ensemble attribute profile clustering provides a simple method for collating and sythesizing the annotation data pertaining to them that are present in text-based, gene-centered corpora. The results provide information about properties common and unique to subsets of the list and hence insights into the biology of the problem under investigation

3D culture reveals a signaling network

The behavior of a cell is significantly influenced by its context. Epithelial cells derived from glandular organs such as the breast recreate their glandular organization when grown under 3D culture conditions. While traditional monolayer cultures are powerful tools to understand how cells proliferate, grow and respond to stress, they do not recreate the 3D property observed in vivo. Multiple studies demonstrate that 3D organization can reveal novel and unexpected insights into the mechanisms by which normal and tumorderived epithelial cells function. In the present article we comment on a study that reports identification of a RasV12-induced IL-6 signaling network in mammary epithelial cells in 3D cultures

Does the immune reaction cause malignant transformation by disrupting cell-to-cell or cell-to-matrix communications?

Tumor progression: In many (perhaps in all) tumor systems, a malignant cancer is preceded by a benign lesion. Most benign lesions do not transform to malignancy and many regress. The final transformative step to malignancy differs from the preceding steps in, among other things, that it often occurs in the absence of the original carcinogenic stimulus. Mechanism of immunostimulation: Relatively low titers of specific immune reactants are known to stimulate, but cell-to-cell or cell-to-matrix interactions appear to be major inhibitors of tumor-growth. Therefore, it seems reasonable to hypothesize that the mechanism of immunostimulation may be an interference with cell-to-cell or cell-to-matrix communication by a sub-lethal immune-reaction. Discussion: While the above hypothesis remains unproven, some evidence suggests that immunity may have a major facilitating effect on tumor growth especially at the time of malignant transformation. There is even some evidence suggesting that transformation in vivo may seldom occur in the absence of immunostimulation of the premalignant lesion. Positive selection by the immune reaction may be the reason that tumors are immunogenic

Beyond Bernoulli: Improving the Accuracy and Precision of Noninvasive Estimation of Peak Pressure Drops

Background: Transvalvular peak pressure drops are routinely assessed noninvasively by echocardiography using the Bernoulli principle. However, the Bernoulli principle relies on several approximations that may not be appropriate, including that the majority of the pressure drop is because of the spatial acceleration of the blood flow, and the ejection jet is a single streamline (single peak velocity value). Methods and Results: We assessed the accuracy of the Bernoulli principle to estimate the peak pressure drop at the aortic valve using 3-dimensional cardiovascular magnetic resonance flow data in 32 subjects. Reference pressure drops were computed from the flow field, accounting for the principles of physics (ie, the Navier–Stokes equations). Analysis of the pressure components confirmed that the spatial acceleration of the blood jet through the valve is most significant (accounting for 99% of the total drop in stenotic subjects). However, the Bernoulli formulation demonstrated a consistent overestimation of the transvalvular pressure (average of 54%, range 5%–136%) resulting from the use of a single peak velocity value, which neglects the velocity distribution across the aortic valve plane. This assumption was a source of uncontrolled variability. Conclusions: The application of the Bernoulli formulation results in a clinically significant overestimation of peak pressure drops because of approximation of blood flow as a single streamline. A corrected formulation that accounts for the cross-sectional profile of the blood flow is proposed and adapted to both cardiovascular magnetic resonance and echocardiographic data

Prognostic Breast Cancer Signature Identified from 3D Culture Model Accurately Predicts Clinical Outcome across Independent Datasets

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasets having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds prognostic value for both ER-positive and ER-negative breast cancer. The signature was selected using a novel biological approach and hence holds promise to represent the key biological processes of breast cancer

Curriculum, intellectual property rights and open educational resources in British universities — and beyond

Is the curriculum in British universities being influenced by decisions about ownership of intellectual property rights (IPR) in ‘open educational resources’ (OERs) that are available online under Creative Commons licenses, free of charge? This paper provides the context for, describes and analyses three significant examples in British higher education where OERs are being created for use by academics and learners on campus or at a distance. OpenLearn and iTunes U, two of the British examples, are drawn from the Open University of the United Kingdom, which teaches over 200,000 undergraduate and graduate students almost entirely at a distance. The third example, OTTER, is at the University of Leicester, a campus university in England with about 7,000 distance learners. Both universities depend on government funding, student fees, research and entrepreneurial income. All three examples are funded indirectly by the British government, though OpenLearn has received substantial US foundation support as well. In presenting these examples, the questions arise of whether the projects are supply- or demand-driven, and of whether they are altruistic or not. Debate over intellectual property rights has influenced creation of the OERs and vice versa, but from these three examples it seems doubtful whether, as yet, OERs and IPR have significantly influenced British universities’ curriculum. The paper ends with discussion of how OERs created in British universities are influencing teaching and learning in other countries, as globalisation advances