Cargando…

Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework

BACKGROUND: Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hinder...

Descripción completa

Detalles Bibliográficos
Autores principales: Föll, Melanie Christine, Volkmann, Veronika, Enderle-Ammour, Kathrin, Timme, Sylvia, Wilhelm, Konrad, Guo, Dan, Vitek, Olga, Bronsert, Peter, Schilling, Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016955/
https://www.ncbi.nlm.nih.gov/pubmed/35439943
http://dx.doi.org/10.1186/s12014-022-09347-z
_version_ 1784688668074573824
author Föll, Melanie Christine
Volkmann, Veronika
Enderle-Ammour, Kathrin
Timme, Sylvia
Wilhelm, Konrad
Guo, Dan
Vitek, Olga
Bronsert, Peter
Schilling, Oliver
author_facet Föll, Melanie Christine
Volkmann, Veronika
Enderle-Ammour, Kathrin
Timme, Sylvia
Wilhelm, Konrad
Guo, Dan
Vitek, Olga
Bronsert, Peter
Schilling, Oliver
author_sort Föll, Melanie Christine
collection PubMed
description BACKGROUND: Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of a urothelial carcinoma dataset. METHODS: Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle infiltrating urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. RESULTS: Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle infiltrating urothelial tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: stromal tissue was characterized by collagen peptides and tumor tissue by histone peptides. Immunohistochemistry confirmed an increased histone H2A abundance in the tumor compared to the stroma tissues. The muscle-infiltration status was distinguished via MSI by peptides from intermediate filaments such as cytokeratin 7 in non-muscle infiltrating carcinomas and vimentin in muscle-infiltrating urothelial carcinomas, which was confirmed by immunohistochemistry. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. CONCLUSION: Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts.
format Online
Article
Text
id pubmed-9016955
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-90169552022-04-20 Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework Föll, Melanie Christine Volkmann, Veronika Enderle-Ammour, Kathrin Timme, Sylvia Wilhelm, Konrad Guo, Dan Vitek, Olga Bronsert, Peter Schilling, Oliver Clin Proteomics Research BACKGROUND: Mass spectrometry imaging (MSI) derives spatial molecular distribution maps directly from clinical tissue specimens and thus bears great potential for assisting pathologists with diagnostic decisions or personalized treatments. Unfortunately, progress in translational MSI is often hindered by insufficient quality control and lack of reproducible data analysis. Raw data and analysis scripts are rarely publicly shared. Here, we demonstrate the application of the Galaxy MSI tool set for the reproducible analysis of a urothelial carcinoma dataset. METHODS: Tryptic peptides were imaged in a cohort of 39 formalin-fixed, paraffin-embedded human urothelial cancer tissue cores with a MALDI-TOF/TOF device. The complete data analysis was performed in a fully transparent and reproducible manner on the European Galaxy Server. Annotations of tumor and stroma were performed by a pathologist and transferred to the MSI data to allow for supervised classifications of tumor vs. stroma tissue areas as well as for muscle-infiltrating and non-muscle infiltrating urothelial carcinomas. For putative peptide identifications, m/z features were matched to the MSiMass list. RESULTS: Rigorous quality control in combination with careful pre-processing enabled reduction of m/z shifts and intensity batch effects. High classification accuracy was found for both, tumor vs. stroma and muscle-infiltrating vs. non-muscle infiltrating urothelial tumors. Some of the most discriminative m/z features for each condition could be assigned a putative identity: stromal tissue was characterized by collagen peptides and tumor tissue by histone peptides. Immunohistochemistry confirmed an increased histone H2A abundance in the tumor compared to the stroma tissues. The muscle-infiltration status was distinguished via MSI by peptides from intermediate filaments such as cytokeratin 7 in non-muscle infiltrating carcinomas and vimentin in muscle-infiltrating urothelial carcinomas, which was confirmed by immunohistochemistry. To make the study fully reproducible and to advocate the criteria of FAIR (findability, accessibility, interoperability, and reusability) research data, we share the raw data, spectra annotations as well as all Galaxy histories and workflows. Data are available via ProteomeXchange with identifier PXD026459 and Galaxy results via https://github.com/foellmelanie/Bladder_MSI_Manuscript_Galaxy_links. CONCLUSION: Here, we show that translational MSI data analysis in a fully transparent and reproducible manner is possible and we would like to encourage the community to join our efforts. BioMed Central 2022-04-19 /pmc/articles/PMC9016955/ /pubmed/35439943 http://dx.doi.org/10.1186/s12014-022-09347-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Föll, Melanie Christine
Volkmann, Veronika
Enderle-Ammour, Kathrin
Timme, Sylvia
Wilhelm, Konrad
Guo, Dan
Vitek, Olga
Bronsert, Peter
Schilling, Oliver
Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework
title Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework
title_full Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework
title_fullStr Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework
title_full_unstemmed Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework
title_short Moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the Galaxy framework
title_sort moving translational mass spectrometry imaging towards transparent and reproducible data analyses: a case study of an urothelial cancer cohort analyzed in the galaxy framework
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9016955/
https://www.ncbi.nlm.nih.gov/pubmed/35439943
http://dx.doi.org/10.1186/s12014-022-09347-z
work_keys_str_mv AT follmelaniechristine movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT volkmannveronika movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT enderleammourkathrin movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT timmesylvia movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT wilhelmkonrad movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT guodan movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT vitekolga movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT bronsertpeter movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework
AT schillingoliver movingtranslationalmassspectrometryimagingtowardstransparentandreproducibledataanalysesacasestudyofanurothelialcancercohortanalyzedinthegalaxyframework