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Heiser, L. M.

Publications and source records attributed to Heiser, L. M..

21 records · Page 2Linked to original sources

Transformation and Integration of Microenvironment Microarray Data Improves Discovery of Latent Effects

The immediate physical and bio-chemical surroundings of a cell, the cellular microenvironment, is an important component of many fundamental cell and tissue level processes and is implicated in many diseases and dysfunctions. Thus understanding the interaction of cells with their microenvironment can further both basic research and aid the discovery of therapeutic agents. To study perturbations of cellular microenvironments a novel image-based cell-profiling technology called the microenvironment microarray (MEMA) has been recently employed. In this paper we explore the effect of preprocessing transformations for MEMA data on the discovery of biological and technical latent effects. We find that Gaussianizing the data and carefully removing outliers can enhance discovery of important biological effects. In particular, these transformations help reveal a relationship between cell morphological features and the extra-cellular-matrix protein THBS1 in MCF10A breast tissue. More broadly, MEMAs are part of a recent and wide-spread adoption of image-based cell-profiling technologies in the quantification of phenotypic differences among cell populations (Caicedo et al., 2017). Thus we anticipate that the advantages of the proposed preprocessing transformations will likely also be realized in the analysis of data from other highly-multiplexed technologies like Cyclic Immunofluorescence. All code and supplementary analysis for this paper is available at gjhunt.github.io/rr.

bioinformatics↗

Accurate transmission of IGF-I into AKT signaling activity in individual cells

Cells sense and respond to their environment by activating distinct intracellular signaling pathways, however an individual cells ability to faithfully transmit and discriminate environmental signals is thought to be limited. To assess the fidelity of signal transmission in the PI3K-AKT signaling pathway, we first developed an optimized genetically encoded sensor that had an increased dynamic range and reduced variation under basal conditions. We then used this reporter to track responses to varying doses of IGF-I in live cells and found that signaling responses from individual cells overlapped across a wide range of IGF-I doses, suggesting limited transmission accuracy. However, further analysis of individual cell traces revealed that responses were constant over time without stochastic fluctuations. We devised a new information theoretic approach to calculate the channel capacity using variance of the single cell time course data--rather than population-level variance as has been previously used--and predicted that cells were capable of discriminating multiple growth factor doses. We validated these predictions by tracking individual cell responses to multiple IGF-I doses and found that cells can accurately distinguish at least four different IGF-I concentrations, as demonstrated by their distinct responses. Furthermore, we found a similar discriminatory ability to pathway inhibition, as assessed by responses to the PI3K inhibitor alpelisib. Our studies indicate that cells can faithfully transmit an IGF-I input into a down-stream signaling response and that heterogeneous responses result from variation in the input-output relation across the population. These observations reveal the importance of viewing each cell as having its own communication channel and underscore the importance of understanding responses at the single cell level.

cell biology↗

A multi-center study on factors influencing the reproducibility of in vitro drug-response studies

Evidence that some influential biomedical results cannot be repeated has increased interest in practices that generate data meeting findable, accessible, interoperable and reproducible (FAIR) standards. Multiple papers have identified examples of irreproducibility, but practical steps for increasing reproducibility have not been widely studied. Here, seven research centers in the NIH LINCS Program Consortium investigate the reproducibility of a prototypical perturbational assay: quantifying the responsiveness of cultured cells to anti-cancer drugs. Such assays are important for drug development, studying cell biology, and patient stratification. While many experimental and computational factors have an impact on intra- and inter-center reproducibility, the factors most difficult to identify and correct are those with a strong dependency on biological context. These factors often vary in magnitude with the drug being analyzed and with growth conditions. We provide ways of identifying such context-sensitive factors, thereby advancing the conceptual and practical basis for greater experimental reproducibility.

cancer biology↗