Scientific Data (Apr 2021)

An integrated landscape of protein expression in human cancer

  • Andrew F. Jarnuczak,
  • Hanna Najgebauer,
  • Mitra Barzine,
  • Deepti J. Kundu,
  • Fatemeh Ghavidel,
  • Yasset Perez-Riverol,
  • Irene Papatheodorou,
  • Alvis Brazma,
  • Juan Antonio Vizcaíno

DOI
https://doi.org/10.1038/s41597-021-00890-2
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 14

Abstract

Read online

Abstract Using 11 proteomics datasets, mostly available through the PRIDE database, we assembled a reference expression map for 191 cancer cell lines and 246 clinical tumour samples, across 13 lineages. We found unique peptides identified only in tumour samples despite a much higher coverage in cell lines. These were mainly mapped to proteins related to regulation of signalling receptor activity. Correlations between baseline expression in cell lines and tumours were calculated. We found these to be highly similar across all samples with most similarity found within a given sample type. Integration of proteomics and transcriptomics data showed median correlation across cell lines to be 0.58 (range between 0.43 and 0.66). Additionally, in agreement with previous studies, variation in mRNA levels was often a poor predictor of changes in protein abundance. To our knowledge, this work constitutes the first meta-analysis focusing on cancer-related public proteomics datasets. We therefore also highlight shortcomings and limitations of such studies. All data is available through PRIDE dataset identifier PXD013455 and in Expression Atlas.