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Biology subjects

Qosaj, F.

Publications and source records attributed to Qosaj, F..

3 recordsLinked to original sources

A three-dimensional imaging pipeline for the detection of vasculogenic mimicry in mouse tumor models

Vasculogenic mimicry (VM) describes the ability for tumor cells to mimic endothelial cells and form tumor-lined blood vessels. Although VM is associated with poor prognosis, resistance to therapeutics and metastasis, its presence, relevance and functionality have been debated, largely due to the techniques employed to determine its presence. Dual CD31 and periodic acid-Schiff (PAS) histological staining, the method widely used to detect VM within tumor tissue, is hampered by issues with artifacts of 2D sections and does not assess active blood flow through vessels and hence cannot confirm vessel functionality. Here, we present a 3D imaging pipeline to detect functionally perfused VM and host vessels within mouse tumor models. Mice tumor models are intravenously injected with fluorescently-labelled tomato lectin which binds to the lumen of functional blood vessels. These tumors are thickly sliced, optically-cleared, stained with endothelial markers and imaged using light-sheet microscopy. We apply this imaging modality to image tumors from six breast cancer patient-derived tissue xenograft models, an orthotopic mammary cancer model and two small cell lung cancer circulating-tumor cell explant models, where VM vessels, mosaic vessels and host-VM vessel junctions can be detected. To our knowledge, this is the largest collection of 3D VM vessel images to date, providing convincing evidence of the presence and functionality of VM within tumors and defining the level of evidence necessary to detect VM in vivo.

cancer biology↗

Exploration and analysis of molecularly annotated, 3D models of breast cancer at single-cell resolution using virtual reality

A set of increasingly powerful approaches are enabling spatially resolved measurements of growing numbers of molecular features in biological samples. While important insights can be derived from the two-dimensional data that many of these technologies generate, it is clear that extending these approaches into the third and fourth dimensions will magnify their impact. Realizing biological insights from datasets where thousands to millions of cells are annotated with tens to hundreds of parameters in space will require the development of new computational and visualization strategies. Here, we describe Theia, a virtual reality-based platform, which enables exploration and analysis of either volumetric or segmented, molecularly-annotated, three-dimensional datasets, with the option to extend the analysis to time-series data. We also describe our pipeline for generating annotated 3D models of breast cancer and supply several datasets to enable users to explore the utility of Theia for understanding cancer biology in three dimensions.

cancer biology↗

The Imaging and Molecular Annotation of Xenografts and Tumours (IMAXT) High Throughput Data and Analysis Infrastructure

With the aim of producing a 3D representation of tumours, IMAXT uses a large variety of modalities in order to acquire tumour samples and produce a map of every cell in the tumour and its host environment. With the large volume and variety of data produced in the project we develop automatic data workflows and analysis pipelines and introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located instead of bringing data to their local computers. Here we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumour models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT.

cancer biology↗