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State of the Art Modelling of the Breast Cancer Metastatic Microenvironment: Where Are We?
J Mammary Gland Biol Neoplasia
July 2024
Breast Biology Group, Manchester Breast Centre, Division of Cancer Sciences, Oglesby Cancer Research Building, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M20 4GJ, UK.
Metastatic spread of tumour cells to tissues and organs around the body is the most frequent cause of death from breast cancer. This has been modelled mainly using mouse models such as syngeneic mammary cancer or human in mouse xenograft models. These have limitations for modelling human disease progression and cannot easily be used for investigation of drug resistance and novel therapy screening.
View Article and Find Full Text PDFTopPICR: A Companion R Package for Top-Down Proteomics Data Analysis.
J Proteome Res
February 2023
Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States.
Top-down proteomics is the analysis of proteins in their intact form without proteolysis, thus preserving valuable information about post-translational modifications, isoforms, and proteolytic processing. However, it is still a developing field due to limitations in the instrumentation, difficulties with the interpretation of complex mass spectra, and a lack of well-established quantification approaches. TopPIC is one of the popular tools for proteoform identification.
View Article and Find Full Text PDFDeep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features.
J Mammary Gland Biol Neoplasia
June 2021
Biomedical Imaging Group, School of Engineering, Ecole Polytechnique Fédéralé de Lausanne (EPFL), Lausanne, Switzerland.
Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminate between xenografted and host cells in histological sections prior to performing immunostainings.
View Article and Find Full Text PDFQuality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.
J Proteome Res
December 2017
Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.
Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes.
View Article and Find Full Text PDFTowards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS.
J Am Soc Mass Spectrom
May 2018
Department of Chemistry and Biochemistry, Florida International University, Miami, FL, 33199, USA.
In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow.
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