Medical Biology - Research Publications

Permanent URI for this collection

http://hdl.handle.net/11343/238

Filters

2020 - 2021 5
5
Reset filters

Settings
Statistics
Citations
Start date: 2020 × End date: 2022 × Author: Papenfuss, Anthony × Author: Mangiola, Stefano ×

Search Results

Now showing 1 - 5 of 5
  • Item
    Thumbnail Image
    Transcriptome sequencing and multi-plex imaging of prostate cancer microenvironment reveals a dominant role for monocytic cells in progression
    Mangiola, S ; McCoy, P ; Modrak, M ; Souza-Fonseca-Guimaraes, F ; Blashki, D ; Stuchbery, R ; Keam, SP ; Kerger, M ; Chow, K ; Nasa, C ; Le Page, M ; Lister, N ; Monard, S ; Peters, J ; Dundee, P ; Williams, SG ; Costello, AJ ; Neeson, PJ ; Pal, B ; Huntington, ND ; Corcoran, NM ; Papenfuss, AT ; Hovens, CM (BMC, 2021-07-22)
    BACKGROUND: Prostate cancer is caused by genomic aberrations in normal epithelial cells, however clinical translation of findings from analyses of cancer cells alone has been very limited. A deeper understanding of the tumour microenvironment is needed to identify the key drivers of disease progression and reveal novel therapeutic opportunities. RESULTS: In this study, the experimental enrichment of selected cell-types, the development of a Bayesian inference model for continuous differential transcript abundance, and multiplex immunohistochemistry permitted us to define the transcriptional landscape of the prostate cancer microenvironment along the disease progression axis. An important role of monocytes and macrophages in prostate cancer progression and disease recurrence was uncovered, supported by both transcriptional landscape findings and by differential tissue composition analyses. These findings were corroborated and validated by spatial analyses at the single-cell level using multiplex immunohistochemistry. CONCLUSIONS: This study advances our knowledge concerning the role of monocyte-derived recruitment in primary prostate cancer, and supports their key role in disease progression, patient survival and prostate microenvironment immune modulation.
  • Item
    Thumbnail Image
    The site of breast cancer metastases dictates their clonal composition and reversible transcriptomic profile
    Berthelet, J ; Wimmer, VC ; Whitfield, HJ ; Serrano, A ; Boudier, T ; Mangiola, S ; Merdas, M ; El-Saafin, F ; Baloyan, D ; Wilcox, J ; Wilcox, S ; Parslow, AC ; Papenfuss, AT ; Yeo, B ; Ernst, M ; Pal, B ; Anderson, RL ; Davis, MJ ; Rogers, KL ; Hollande, F ; Merino, D (AMER ASSOC ADVANCEMENT SCIENCE, 2021-07)
    Intratumoral heterogeneity is a driver of breast cancer progression, but the nature of the clonal interactive network involved in this process remains unclear. Here, we optimized the use of optical barcoding to visualize and characterize 31 cancer subclones in vivo. By mapping the clonal composition of thousands of metastases in two clinically relevant sites, the lungs and liver, we found that metastases were highly polyclonal in lungs but not in the liver. Furthermore, the transcriptome of the subclones varied according to their metastatic niche. We also identified a reversible niche-driven signature that was conserved in lung and liver metastases collected during patient autopsies. Among this signature, we found that the tumor necrosis factor-α pathway was up-regulated in lung compared to liver metastases, and inhibition of this pathway affected metastasis diversity. These results highlight that the cellular and molecular heterogeneity observed in metastases is largely dictated by the tumor microenvironment.
  • Item
    Thumbnail Image
    tidyHeatmap: an R package for modular heatmap production based on tidy principles
    Mangiola, S ; Papenfuss, A (The Open Journal, 2020-08-03)
  • Item
    Thumbnail Image
    Interfacing Seurat with the R tidy universe
    Mangiola, S ; Doyle, MA ; Papenfuss, AT ; Mathelier, A (OXFORD UNIV PRESS, 2021-11-15)
    MOTIVATION: Seurat is one of the most popular software suites for the analysis of single-cell RNA sequencing data. Considering the popularity of the tidyverse ecosystem, which offers a large set of data display, query, manipulation, integration and visualization utilities, a great opportunity exists to interface the Seurat object with the tidyverse. This interface gives the large data science community of tidyverse users the possibility to operate with familiar grammar. RESULTS: To provide Seurat with a tidyverse-oriented interface without compromising efficiency, we developed tidyseurat, a lightweight adapter to the tidyverse. Tidyseurat displays cell information as a tibble abstraction, allowing intuitively interfacing Seurat with dplyr, tidyr, ggplot2 and plotly packages powering efficient data manipulation, integration and visualization. Iterative analyses on data subsets are enabled by interfacing with the popular nest-map framework. AVAILABILITY AND IMPLEMENTATION: The software is freely available at cran.r-project.org/web/packages/tidyseurat and github.com/stemangiola/tidyseurat. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
  • Item
    Thumbnail Image
    tidybulk: an R tidy framework for modular transcriptomic data analysis
    Mangiola, S ; Molania, R ; Dong, R ; Doyle, MA ; Papenfuss, AT (BMC, 2021-01-22)
    Recently, efforts have been made toward the harmonization of transcriptomic data structures and workflows using the concept of data tidiness, to facilitate modularisation. We present tidybulk, a modular framework for bulk transcriptional analyses that introduces a tidy transcriptomic data structure paradigm and analysis grammar. Tidybulk covers a wide variety of analysis procedures and integrates a large ecosystem of publicly available analysis algorithms under a common framework. Tidybulk decreases coding burden, facilitates reproducibility, increases efficiency for expert users, lowers the learning curve for inexperienced users, and bridges transcriptional data analysis with the tidyverse. Tidybulk is available at R/Bioconductor bioconductor.org/packages/tidybulk .