Shape Characterization of Extracted and Simulated Tumor Samples using Topological and Geometric Measures

The prognosis of cancer patients suffering from solid tumors significantly depends on the developmental stage of the tumor. For cervix carcinoma the prognosis is better for compact shapes than for diffusive shapes since the latter may already indicate invasion, the stage in tumor progression that precedes the formation of metastases. In this paper, we present methods for describing and evaluating tumor objects and their surfaces based on topological and geometric properties. For geometry, statistics of the binary object's distance transform are used to evaluate the tumor's invasion front. In addition, a simple compactness measure is adapted to 3D images and presented to compare different types of tumor samples. As a topological measure, the Betti numbers are calculated of voxelized tumor objects based on a medial axis transform. We further illustrate how these geometric and topological properties can be used for a quantitative comparison of histological material and single-cell-based tumor growth simulations

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

<p>Abstract</p> <p>Background</p> <p>Three-dimensional <it>in vitro </it>culture of cancer cells are used to predict the effects of prospective anti-cancer drugs <it>in vivo</it>. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images.</p> <p>Methods</p> <p>Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using <it>k</it>-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system.</p> <p>Results</p> <p>Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images.</p> <p>Conclusion</p> <p>Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development.</p

Head and Neck Cancer Invasion: Contributions of Actin Regulatory Proteins and the Microenvironment

Metastasis of primary tumor lesions is the leading cause of cancer-related death. In head and neck cancer, a local-regional disease, metastasis is achieved mainly through invasion into surrounding tissue and spreads to cervical lymph nodes. Movement from the initial tumor site requires dynamic reorganization of the actin cytoskeleton, which utilizes the coordinated action of many actin regulatory proteins. However, there is increasing evidence that the tumor microenvironment is also a driver of invasion. This work aims to determine the contributions of proteins which regulate the actin cytoskeleton during head and neck cancer invasion both in vitro and in vivo, and provide details on how the HNSCC tumor microenvironment influences progression. This was accomplished, by the following Studies. In Study one, the actin binding protein coronin 1B is found to be amplified and overexpressed in invasive HNSCC patient samples, and a novel function in the regulation of protrusive membrane structures called invadopodia is described. Study two defines an in vivo role for the actin regulatory protein cortactin, which has been previously associated with more aggressive cancers in vitro and in patients. This work finds that cortactin expression is dispensable for tongue tumor invasion in a transgenic model of oral cancer, implicating the tumor microenvironment as being the major contributor to driving oral cancer invasion. Study three describes a technique for monitoring and biopsying cervical lymph nodes of mice using high frequency ultrasound. By using this technique, alterations in cervical lymph node size and blood flow were discovered in mice given the carcinogen 4-NQO to induce oral carcinogenesis. Collectively, these studies shed light on the importance of choosing comprehensive model systems for studying roles of actin binding proteins in cancer invasion

Comparative Analysis of Tissue Reconstruction Algorithms for 3D Histology

Motivation: Digital pathology enables new approaches that expand beyond storage, visualization or analysis of histological samples in digital format. One novel opportunity is 3D histology, where a three-dimensional reconstruction of the sample is formed computationally based on serial tissue sections. This allows examining tissue architecture in 3D, for example, for diagnostic purposes. Importantly, 3D histology enables joint mapping of cellular morphology with spatially resolved omics data in the true 3D context of the tissue at microscopic resolution. Several algorithms have been proposed for the reconstruction task, but a quantitative comparison of their accuracy is lacking. Results: We developed a benchmarking framework to evaluate the accuracy of several free and commercial 3D reconstruction methods using two whole slide image datasets. The results provide a solid basis for further development and application of 3D histology algorithms and indicate that methods capable of compensating for local tissue deformation are superior to simpler approaches.publishedVersionPeer reviewe

Cortactin Phosphorylation by Casein Kinase 2 Regulates Actin Related Protein 2/3 Complex Activity and Invadopodia Function

Malregulation of the actin cytoskeleton enhances tumor cell motility and invasion. The actin-binding protein cortactin facilitates branched actin network formation through activation of the actin-related protein (Arp) 2/3 complex. Arp2/3 complex activation is responsible for driving increased migration and extracellular matrix (ECM) degradation by governing invadopodia formation and activity. While cortactin-mediated activation of Arp2/3 complex and invadopodia regulation has been well established, signaling pathways responsible for governing cortactin binding to Arp2/3 are unknown. In this dissertation we identify casein kinase (CK) 2α phosphorylation of cortactin as a negative regulator of Arp2/3 binding. CK2α directly phosphorylates cortactin at a conserved threonine (T24) adjacent to the canonical Arp2/3 binding motif. Phosphorylation of cortactin T24 by CK2α impairs the ability of cortactin to bind Arp2/3 and activate actin nucleation. Decreased invadopodia activity is observed in HNSCC cells with expression of CK2α phosphorylation-null cortactin mutants, shRNA-mediated CK2α knockdown, and with the CK2α inhibitor Silmitasertib. Silmitasertib inhibits HNSCC collective invasion in tumor spheroids and orthotopic tongue tumors in mice. Although overall cancer incidence rates are declining across the United States, the incidence of head and neck squamous cell carcinoma (HNSCC) continues to increase within the Appalachian region. To better understand the underlying factors leading to disproportionate outcomes, our group has established an Appalachian-specific HNSCC patient tissue cohort from surgically-resected tumors. This cohort represents all HNSCC stages, lesion types and morphologies, as well as cases that contain human papillomavirus (HPV) and/or tobacco and alcohol use. Moreover, we have generated several patient derived xenografts (PDXs) from these tissues, allowing further cellular, biochemical and preclinical therapeutic evaluation. Utilization of PDX tumors from this cohort will allow examination of critical steps in the development and potential treatment of invasive, metastatic, and recurrent Appalachian-associated disease. Matched patient and PDX sample availability enables personalized medicine and co-clinical trials aimed at reversing this Appalachian cancer health disparity and ultimately improving regional HNSCC patient care

Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

BACKGROUND: Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. METHODS: This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. RESULTS: Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. CONCLUSION: These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest information gathered from the whole section images will guide the excision of tissue for constructing tissue microarrays and for high throughput profiling of global gene expression

Phenotypic heterogeneity of breast tumors

Breast tumors are typically heterogeneous and contain diverse subpopulations of tumor cells with differing phenotypic properties. In order to identify potential biomarkers of relapse in breast cancer, we have analyzed relapse related microarray data from five different laboratories and identified a list of significantly altered genes for each dataset. KEGG pathways for MAPK signaling, focal adhesion and cytokine-mediated signaling have been enriched for relapse in breast cancer in four out of the five microarray databases. We found that a set of genes coding for extracellular proteins are consistently upregulated in breast cancer patients with relapse in a multitude of microarray databases. A significant subset of these genes code for proteins found in the serum and as such could be potential candidates for relapse biomarkers. In addition, our work presents an in vitro coculture-based three-dimensional heterogeneous breast tumor model that can be used in drug resistance and drug delivery investigations. Breast cancer cell lines of different phenotypes (MDAMB231, MCF7 and ZR751) were cocultured in a rotating wall vessel (RWV) bioreactor to form a large number of heterogeneous tumoroids in a single cell culture experiment. In vitro tumoroids developed in this study recapture important features of the temporal-spatial organization of solid tumors, including the presence of necrotic areas at the center and higher levels of cell division at the tumor periphery. E-cad positive MCF7 cells form larger tumoroids than E-cad negative MDAMB231 cells. In addition, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images. Histologic cross sections of breast tumoroids developed in coculture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development.Ph.D., Biomedical Engineering -- Drexel University, 200