Protein characterization of cancer proteins is vital for advancing cancer research, serving as foundational resources in integrative multi-omics studies. Recently, significant progress has been made in expanding the mass spectrometry-based proteomics and detecting cancer proteins with a particular focus on addressing gaps in protein identification and enhancing data accessibility. However, the accessibility of cancer proteins is limited. In this study, we report advancements in the development of integrated datasets of mass spectrometric detected cancer proteins database (MSCPDIDMSCP) from recent proteomics characterization of major cohorts of human tumor tissues, normal adjacent to tumors (NATs), Patient-Derived Xenograft (PDX) models, and human cancer cell lines. We also compare this cancer proteomic database with previously reported human proteomic databases, such as UniProt Knowledgebase (UniProtKB) and the neXtProt knowledgebase (neXtProt), for complementary analysis. Enhanced database analysis and statistical validation of protein sources have contributed to the detection of 15,737 cancer proteins in the human proteome. These advancements are supported by robust platforms for mass spectrometry, data mining, annotation, and validation, ensuring high-confidence discoveries that contributed by the diversity of cancer cohorts. The MSCPD provides the first public accessible database for cancer proteins identified from different cancer tissues and cells, serving as resource for cancer research.