A hybrid DDA/DIA-PASEF based assay library for a deep proteotyping of triple-negative breast cancer

Petr Lapcik1, Klara Synkova1, Lucia Janacova1

  • 1Department of Biochemistry, Faculty of Science, Masaryk University, Brno, Czech Republic.

Scientific Data
|July 18, 2024
PubMed

Insights

Researchers developed a comprehensive mass spectrometry assay library for triple-negative breast cancer (TNBC), enabling deeper proteome coverage for this aggressive cancer subtype. This new TNBC proteome resource enhances protein identification in molecular characterization studies.

Area of Science:

  • Proteomics
  • Cancer Research
  • Mass Spectrometry

Background:

  • Triple-negative breast cancer (TNBC) is an aggressive subtype requiring advanced molecular characterization.
  • Existing proteomic coverage for TNBC is insufficient for comprehensive analysis.

Purpose of the Study:

  • To develop and validate a comprehensive targeted mass spectrometry assay library specific for TNBC.
  • To enhance the depth of proteome coverage for TNBC molecular studies.

Main Methods:

  • Proteins extracted from 105 TNBC tissues and analyzed using LC-MS/MS with data-dependent acquisition (DDA)-PASEF.
  • A hybrid library was generated using Spectronaut software, covering 244,464 precursors and 11,564 protein groups.
  • Pilot quantitative analysis of 16 tissues was performed using the developed library in Spectronaut and DIA-NN software.

Main Results:

  • The TNBC assay library provides the deepest proteome coverage to date for this cancer subtype.
  • Application of the library significantly increased protein identification numbers compared to library-free methods.
  • Spectronaut software achieved superior results, identifying 190,310 precursors and 10,463 protein groups.

Conclusions:

  • A novel assay library offers unprecedented proteome coverage for triple-negative breast cancer.
  • This resource facilitates improved molecular characterization and quantitative analysis of TNBC.
  • The TNBC library is publicly available via the PRIDE repository (PXD047793).

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