According to these authors, RPPA is better than MS:
A few citations from the article:
“Reverse Phase Protein Arrays (RPPA) represent a very promising sensitive and precise high-throughput technology for the quantitative measurement of hundreds of signaling proteins in biological and clinical samples. This array format allows quantification of one protein or phosphoprotein in multiple samples under the same experimental conditions at the same time”.
“Mass spectrometry (MS)-based technologies have rapidly advanced in recent years. Beside other advantages mentioned in Table 1, MS-based methods enable the identification of new biomarker candidates by comparing protein signals obtained from cancer and healthy tissues (de novo discovery platform) [7–10]. However, in author opinion, MS-based technologies are not suitable for the use in clinical routine at the moment. First, due to the complex sample preparation and secondly due to the insufficient profiling of low-abundance signaling proteins.”
Below people discuss TCGA and CPTAC:
"The Cancer Genome Atlas (TCGA) has become a focal point for a lot of genomics and bioinformatics research. DNA and RNA level data on different tumor types are now used in countless papers to test computational methods and to learn more about hallmarks of different types of cancer.
Perhaps, though, there aren’t as many people who are using the quantitative proteomics data hosted by Clinical Proteomic Tumor Analysis Consortium (CPTAC). There are mass spectrometry based expression measurements for many different types of tumor available at their Data Portal."
The CPTAC Data Portal from above:
Below there is more general discussion and there are more disease types:
It's difficult to say what is more important: one approach works with data submitted by another one.
"Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens.
The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples."
So the TCGA provide samples. CPTAC study them and insert the information into the database.