Extending Ripley's K-Function to Quantify Aggregation in 2-D Grayscale Images

A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer

Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists grade the microscopic appearance of breast tissue using the Nottingham criteria, which are qualitative and do not account for noncancerous elements within the tumor microenvironment. Here we present the Histomic Prognostic Signature (HiPS), a comprehensive, interpretable scoring of the survival risk incurred by breast tumor microenvironment morphology. HiPS uses deep learning to accurately map cellular and tissue structures to measure epithelial, stromal, immune, and spatial interaction features. It was developed using a population-level cohort from the Cancer Prevention Study-II and validated using data from three independent cohorts, including the Prostate, Lung, Colorectal, and Ovarian Cancer trial, Cancer Prevention Study-3, and The Cancer Genome Atlas. HiPS consistently outperformed pathologists in predicting survival outcomes, independent of tumor-node-metastasis stage and pertinent variables. This was largely driven by stromal and immune features. In conclusion, HiPS is a robustly validated biomarker to support pathologists and improve patient prognosis.

Five Inhibitory Receptors Display Distinct Vesicular Distributions in Murine T Cells

T cells can express multiple inhibitory receptors. Upon induction of T cell exhaustion in response to a persistent antigen, prominently in the anti-tumor immune response, many are expressed simultaneously. Key inhibitory receptors are CTLA-4, PD-1, LAG3, TIM3, and TIGIT, as investigated here. These receptors are important as central therapeutic targets in cancer immunotherapy. Inhibitory receptors are not constitutively expressed on the cell surface, but substantial fractions reside in intracellular vesicular structures. It remains unresolved to which extent the subcellular localization of different inhibitory receptors is distinct. Using quantitative imaging of subcellular distributions and plasma membrane insertion as complemented by proximity proteomics and biochemical analysis of the association of the inhibitory receptors with trafficking adaptors, the subcellular distributions of the five inhibitory receptors were discrete. The distribution of CTLA-4 was most distinct, with preferential association with lysosomal-derived vesicles and the sorting nexin 1/2/5/6 transport machinery. With a lack of evidence for the existence of specific vesicle subtypes to explain divergent inhibitory receptor distributions, we suggest that such distributions are driven by divergent trafficking through an overlapping joint set of vesicular structures. This extensive characterization of the subcellular localization of five inhibitory receptors in relation to each other lays the foundation for the molecular investigation of their trafficking and its therapeutic exploitation.

Modeling the effect of acquired resistance on cancer therapy outcomes

Adaptive therapy (AT) is an evolution-based treatment strategy that exploits cell-cell competition. Acquired resistance can change the competitive nature of cancer cells in a tumor, impacting AT outcomes. We aimed to determine if adaptive therapy can still be effective with cell's acquiring resistance. We developed an agent-based model for spatial tumor growth considering three different types of acquired resistance: random genetic mutations during cell division, drug-induced reversible (plastic) phenotypic changes, and drug-induced irreversible phenotypic changes. These three resistance mechanisms lead to different spatial distributions of resistant cells. To quantify the spatial distribution, we propose an extension of Ripley's K-function, Sampled Ripley's K-function (SRKF), which calculates the non-randomness of the resistance distribution over the tumor domain. Our model predicts that the emergent spatial distribution of resistance can determine the time to progression under both adaptive and continuous therapy (CT). Notably, a high rate of random genetic mutations leads to quicker progression under AT than CT due to the emergence of many small clumps of resistant cells. Drug-induced phenotypic changes accelerate tumor progression irrespective of the treatment strategy. Low-rate switching to a sensitive state reduces the benefits of AT compared to CT. Furthermore, we also demonstrated that drug-induced resistance necessitates aggressive treatment under CT, regardless of the presence of cancer-associated fibroblasts. However, there is an optimal dose that can most effectively delay tumor relapse under AT by suppressing resistance. In conclusion, this study demonstrates that diverse resistance mechanisms can shape the distribution of resistance and thus determine the efficacy of adaptive therapy.

Five inhibitory receptors display distinct vesicular distributions in T cells

T cells can express multiple inhibitory receptors. Upon induction of T cell exhaustion in response to persistent antigen, prominently in the anti-tumor immune response, many are expressed simultaneously. Key inhibitory receptors are CTLA-4, PD-1, LAG3, TIM3 and TIGIT, as investigated here. These receptors are important as central therapeutic targets in cancer immunotherapy. Inhibitory receptors are not constitutively expressed on the cell surface, but substantial fractions reside in intracellular vesicular structures. It remains unresolved to which extent the subcellular localization of different inhibitory receptors is distinct. Using quantitative imaging of subcellular distributions and plasma membrane insertion as complemented by proximity proteomics and a biochemical analysis of the association of the inhibitory receptors with trafficking adaptors, the subcellular distributions of the five inhibitory receptors were discrete. The distribution of CTLA-4 was most distinct with preferential association with lysosomal-derived vesicles and the sorting nexin 1/2/5/6 transport machinery. With a lack of evidence for the existence of specific vesicle subtypes to explain divergent inhibitory receptor distributions, we suggest that such distributions are driven by divergent trafficking through an overlapping joint set of vesicular structures. This extensive characterization of the subcellular localization of five inhibitory receptors in relation to each other lays the foundation for the molecular investigation of their trafficking and its therapeutic exploitation.

Identifying a spatial scale for the analysis of residential burglary: An empirical framework based on point pattern analysis

A key issue in the spatial and temporal analysis of residential burglary is the choice of scale: spatial patterns might differ appreciably for different time periods and vary across geographic units of analysis. Based on point pattern analysis of burglary incidents in Columbus, Ohio during a 9-year period, this study develops an empirical framework to identify a useful spatial scale and its dependence on temporal aggregation. Our analysis reveals that residential burglary in Columbus clusters at a characteristic scale of 2.2 km. An ANOVA test shows no significant impact of temporal aggregation on spatial scale of clustering. This study demonstrates the value of point pattern analysis in identifying a scale for the analysis of crime patterns. Furthermore, the characteristic scale of clustering determined using our method has great potential applications: (1) it can reflect the spatial environment of criminogenic processes and thus be used to define the spatial boundary for place-based policing; (2) it can serve as a candidate for the bandwidth (search radius) for hot spot policing; (3) its independence of temporal aggregation implies that police officials need not be concerned about the shifting sizes of risk-areas depending on the time of the year.

Detecting Differences of Fluorescent Markers Distribution in Single Cell Microscopy: Textural or Pointillist Feature Space?

We consider the detection of change in spatial distribution of fluorescent markers inside cells imaged by single cell microscopy. Such problems are important in bioimaging since the density of these markers can reflect the healthy or pathological state of cells, the spatial organization of DNA, or cell cycle stage. With the new super-resolved microscopes and associated microfluidic devices, bio-markers can be detected in single cells individually or collectively as a texture depending on the quality of the microscope impulse response. In this work, we propose, via numerical simulations, to address detection of changes in spatial density or in spatial clustering with an individual (pointillist) or collective (textural) approach by comparing their performances according to the size of the impulse response of the microscope. Pointillist approaches show good performances for small impulse response sizes only, while all textural approaches are found to overcome pointillist approaches with small as well as with large impulse response sizes. These results are validated with real fluorescence microscopy images with conventional resolution. This, a priori non-intuitive result in the perspective of the quest of super-resolution, demonstrates that, for difference detection tasks in single cell microscopy, super-resolved microscopes may not be mandatory and that lower cost, sub-resolved, microscopes can be sufficient.

In vivo nanoscale analysis of the dynamic synergistic interaction of Bacillus thuringiensis Cry11Aa and Cyt1Aa toxins in Aedes aegypti

The insecticidal Cry11Aa and Cyt1Aa proteins are produced by Bacillus thuringiensis as crystal inclusions. They work synergistically inducing high toxicity against mosquito larvae. It was proposed that these crystal inclusions are rapidly solubilized and activated in the gut lumen, followed by pore formation in midgut cells killing the larvae. In addition, Cyt1Aa functions as a Cry11Aa binding receptor, inducing Cry11Aa oligomerization and membrane insertion. Here, we used fluorescent labeled crystals, protoxins or activated toxins for in vivo localization at nano-scale resolution. We show that after larvae were fed solubilized proteins, these proteins were not accumulated inside the gut and larvae were not killed. In contrast, if larvae were fed soluble non-toxic mutant proteins, these proteins were found inside the gut bound to gut-microvilli. Only feeding with crystal inclusions resulted in high larval mortality, suggesting that they have a role for an optimal intoxication process. At the macroscopic level, Cry11Aa completely degraded the gastric caeca structure and, in the presence of Cyt1Aa, this effect was observed at lower toxin-concentrations and at shorter periods. The labeled Cry11Aa crystal protein, after midgut processing, binds to the gastric caeca and posterior midgut regions, and also to anterior and medium regions where it is internalized in ordered "net like" structures, leading finally to cell break down. During synergism both Cry11Aa and Cyt1Aa toxins showed a dynamic layered array at the surface of apical microvilli, where Cry11Aa is localized in the lower layer closer to the cell cytoplasm, and Cyt1Aa is layered over Cry11Aa. This array depends on the pore formation activity of Cry11Aa, since the non-toxic mutant Cry11Aa-E97A, which is unable to oligomerize, inverted this array. Internalization of Cry11Aa was also observed during synergism. These data indicate that the mechanism of action of Cry11Aa is more complex than previously anticipated, and may involve additional steps besides pore-formation activity.

The Accuracy of Determining Cluster Size by Analyzing Ripley’s K Function in Single Molecule Localization Microscopy

Ripley’s K function was developed to analyze the spatial distribution characteristics in point pattern analysis, including geography, economics and biomedical research. In biomedical applications, it is popularly used to analyze the clusters of proteins on the cell plasma membrane in single molecule localization microscopy (SMLM), such as photo activated localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), universal point accumulation imaging in nanoscale topography (uPAINT), etc. Here, by varying the parameters of the simulated clusters on a modeled SMLM image, the effects of cluster size, cluster separation and protein ratio inside/outside the cluster on the accuracy of cluster analysis by analyzing Ripley’s K function were studied. Although the predicted radius of clusters by analyzing Ripley’s K function did not exactly correspond to the actual radius, we suggest the cluster radius could be estimated within a factor of 1.3. Employing peak analysis methods to analyze the experimental epidermal growth factor receptor (EGFR) clusters at fibroblast-like cell lines derived from monkey kidney tissue - COS7 cell surface observed by uPAINT method, the cluster properties were characterized with errors. Our results present quantification of clusters and can be used to enhance the understanding of clusters in SMLM.

Localisation Microscopy of Breast Epithelial ErbB-2 Receptors and Gap Junctions: Trafficking after γ-Irradiation, Neuregulin-1β, and Trastuzumab Application

In cancer, vulnerable breast epithelium malignance tendency correlates with number and activation of ErbB receptor tyrosine kinases. In the presented work, we observe ErbB receptors activated by irradiation-induced DNA injury or neuregulin-1β application, or alternatively, attenuated by a therapeutic antibody using high resolution fluorescence localization microscopy. The gap junction turnover coinciding with ErbB receptor activation and co-transport is simultaneously recorded. DNA injury caused by 4 Gray of 6 MeV photon γ-irradiation or alternatively neuregulin-1β application mobilized ErbB receptors in a nucleograde fashion—a process attenuated by trastuzumab antibody application. This was accompanied by increased receptor density, indicating packing into transport units. Factors mobilizing ErbB receptors also mobilized plasma membrane resident gap junction channels. The time course of ErbB receptor activation and gap junction mobilization recapitulates the time course of non-homologous end-joining DNA repair. We explain our findings under terms of DNA injury-induced membrane receptor tyrosine kinase activation and retrograde trafficking. In addition, we interpret the phenomenon of retrograde co-trafficking of gap junction connexons stimulated by ErbB receptor activation.