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Mass spectrometry-based proteomic characterization of pre-treatment esophageal adenocarcinoma biopsies

Grothey, Bastian; Quaas, Alexander

Abstract

This repository contains preprocessed mass spectrometry-based proteomic data from pre-treatment biopsies of esophageal adenocarcinoma patients, along with corresponding clinicopathological annotations and R scripts for data analysis and visualization.This project was funded by the Manfred Stolte Stiftung, Bayreuth, Germany.

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● ● ● ● ● ● ● ● ● ● ● ● ● Contents Data Files: ms_data.xlsx - Preprocessed mass spectrometry protein expression data annotation.xlsx - Clinicopathological annotations including therapy response, tumor grading, and histological subtype Analysis Code: main.R - Primary analysis script functions.R - Supporting functions for analysis and visualization Additional Requirements: matrisomedb.tsv - Matrisome database file (not included; must be downloaded from https://matrisomedb.org). This file is required for matrisome-related analyses and must contain at least two columns: Species and UniProt ID. Mass Spectrometry Data Structure The mass spectrometry data were preprocessed according to methods described in the corresponding publication (DOI: [to be added upon publication]). Data exported from Perseus (v1.6.15.0) and are provided as multiple tables representing different preprocessing stages: Dataset N1U (Cohort 1): N1U-uf - Unfiltered data (matrix8) N1U-f30 - Outliers removed, filtered for >30% data completeness (matrix12) N1U-f30imp - Imputed data based on N1U-f30 (matrix13) Dataset N2U (Cohort 2): N2U-uf - Unfiltered data (matrix24) N2U-f30 - Outliers removed, filtered for >30% data completeness (matrix26) N2U-f30imp - Imputed data based on N2U-f30 (matrix27) Important Notes The mass spectrometry dataset includes additional samples of esophageal squamous cell carcinoma and normal esophageal tissue that are not included in the annotation file and are not used in the provided R scripts. Only esophageal adenocarcinoma samples with clinical annotations are utilized in the analysis scripts. Usage The R scripts are designed to work with the annotated EAC samples for downstream analysis and visualization. Users interested in the additional nonEAC samples should refer to the corresponding author.