The Cancer Proteome Atlas (TCPA) Project based on Mass Spectrometry
Label-free mass spectrometry based on Data Independent Acquisition (DIA) is high-throughput and reproducible, opening up the opportunity for a multi-laboratory collaborative cancer proteome profiling effort
, a la TCGA, T
). This DIA-MS based TCPA is complementary to the on-going antibody-based TCPA developed by MD Anderson and the deep proteogenomics profiling of the Clinical Proteomic Tumor Analysis Consortium (CPTAC).
The global aims of TCPA based on Mass Spectrometry analysis are
- to better understand the molecular underpinnings of cancer.
- to identify core and cancer type enriched molecular therapeutic
targets and biomarkers.
As a first step, Guo and Jimenez recently described a mass spectrometric pipeline and spectral resource to support DIA-based biomarker studies and reported a comprehensive DIA pan-human library from 1,096 data dependent acquisition MS raw files, comprising 242,476 unique peptide sequences from 14,782 protein groups and 10,943 SwissProt-annotated proteins expressed in 16 types of cancer samples
Underscoring the high potential of DIA-MS for TCPA, a collaborative study led by Yue Xuan (Thermo Fisher) showed that harmonized MS instrument platforms and standardized data acquisition procedures demonstrated robust, sensitive, and reproducible data generation across eleven sites in nine countries on seven consecutive days in a 24/7 operation mode (submitted, preprint
We hope to present a first draft proteome of over 1000 tumors representing more than 20 cancer types in 2020 and distribute the data via existing queriable portals.
After this pilot phase, in the coming 3 years we aim to expand the dataset to 10,000 in a cancer proteomics community effort with more participating labs.