ORCID Profile
0000-0003-4504-2901
Current Organisations
University of Technology Sydney
,
Universiteit Utrecht
,
Childrens Cancer Institute
,
University of Sydney
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Publisher: Wiley
Date: 05-09-2020
DOI: 10.1002/CYTO.A.24209
Abstract: In the past few years, the rapid development of single‐cell analysis techniques has allowed for increasingly in‐depth analysis of DNA, RNA, protein, and epigenetic states, at the level of the in idual cell. This unprecedented characterization ability has been enabled through the combination of cytometry, microfluidics, genomics, and informatics. Although traditionally discrete, when properly integrated, these fields create the synergistic field of Genomic Cytometry. In this review, we look at the in idual methods that together gave rise to the broad field of Genomic Cytometry. We further outline the basic concepts that drive the field and provide a framework to understand this increasingly complex, technology‐intensive space. Thus, we introduce Genomic Cytometry as an emerging field and propose that synergistic rationalization of disparate modalities of cytometry, microfluidics, genomics, and informatics under one banner will enable massive leaps forward in the understanding of complex biology. © 2020 International Society for Advancement of Cytometry
Publisher: Wiley
Date: 06-07-2017
DOI: 10.1002/HUP.2624
Publisher: Cold Spring Harbor Laboratory
Date: 03-05-2019
DOI: 10.1101/624890
Abstract: Both luminal and basal breast cancer subtypes originate in the mammary luminal progenitor cell compartment. Basal breast cancer is associated with younger age, early relapse, and high mortality rate. Here we used unbiased droplet-based single-cell RNAseq to elucidate the cellular basis of tumour progression during the specification of the basal breast cancer subtype from the luminal progenitor population. Basal–like cancer cells resembled the alveolar lineage that is specified upon pregnancy and showed molecular features indicative of an interaction with the tumour microenvironment (TME) including epithelial-to-mesenchymal transition (EMT), hypoxia, lactation and involution. Involution signatures in luminal breast cancer tumours with alveolar lineage features were associated with worse prognosis and features of basal breast cancer. Our high-resolution molecular characterisation of the tumour ecosystem also revealed a highly interactive cell-cell network reminiscent of an involution process. This involution mimicry involves malignant education of cancer-associated fibroblasts and myeloid cell recruitment to support tissue remodelling and sustained inflammation. Our study shows how luminal breast cancer acquires an aberrant post-lactation developmental program that involves both cancer cells and cells from the TME, to shift molecular subtype and promote tumour progression, with potential to explain the increased risk and poor prognosis of breast cancer associated to childbirth.
Publisher: Cold Spring Harbor Laboratory
Date: 04-04-2023
DOI: 10.1101/2023.04.04.535585
Abstract: Single-cell transcriptomics has emerged as the preferred tool to define cell identity through the analysis of gene expression signatures. However, there are limited studies that have comprehensively compared the performance of different scRNAseq systems in complex tissues. Here, we present a systematic comparison of three well-established high throughput 3’-scRNAseq platforms: Drop-seq, 10x Chromium and BD Rhapsody using tumours that present high cell ersity. Our experimental design includes both fresh and artificially damaged s les from the same tumours, which also provides a comparable dataset to examine their performance under challenging conditions. The performance metrics used in this study consist of gene sensitivity, mitochondrial content, reproducibility, clustering capabilities, cell type representation and ambient RNA contamination. These analyses showed that BD Rhapsody and 10x Chromium have similar but higher gene sensitivity than Drop-seq, while BD Rhapsody has the highest mitochondrial content. Interestingly, we found cell type detection biases between platforms, including a lower proportion of endothelial and myofibroblast cells in BD Rhapsody and lower gene sensitivity in granulocytes for 10x Chromium. Moreover, the source of the ambient noise was different between plate-based and droplet-based platforms. In conclusion, our reported platform differential performance should be considered for the selection of the scRNAseq method during the study experimental designs.
Publisher: MDPI AG
Date: 29-03-2023
DOI: 10.3390/MI14040751
Abstract: This paper describes, in detail, a method that uses flow cytometry to quantitatively characterise the performance of continuous-flow microfluidic devices designed to separate particles. Whilst simple, this approach overcomes many of the issues with the current commonly utilised methods (high-speed fluorescent imaging, or cell counting via either a hemocytometer or a cell counter), as it can accurately assess device performance even in complex, high concentration mixtures in a way that was previously not possible. Uniquely, this approach takes advantage of pulse processing in flow cytometry to allow quantitation of cell separation efficiencies and resulting s le purities on both single cells as well as cell clusters (such as circulating tumour cell (CTC) clusters). Furthermore, it can readily be combined with cell surface phenotyping to measure separation efficiencies and purities in complex cell mixtures. This method will facilitate the rapid development of a raft of continuous flow microfluidic devices, will be helpful in testing novel separation devices for biologically relevant clusters of cells such as CTC clusters, and will provide a quantitative assessment of device performance in complex s les, which was previously impossible.
Publisher: Wiley
Date: 16-04-2020
DOI: 10.1002/CYTO.A.24018
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C8LC01239C
Abstract: A step-by-step guide for droplet-based single cell RNAseq experiments, practical considerations and technical notes.
Publisher: Elsevier BV
Date: 04-2021
Publisher: Wiley
Date: 26-06-2022
DOI: 10.1002/CYTO.A.24477
No related grants have been discovered for Robert Salomon.