Amino acid (AA) substitutions play a critical role in regulating cellular activities, including complex signaling and cell cycle processes. Recent research on AA substitutions has primarily relied on genomic and transcriptomic data. The identification at the proteomic scale remains underexplored, despite evidence suggesting that DNA and RNA biosynthesis are not the sole sources of these substitutions. This gap persists due to challenges in analyzing large-scale proteomic data. In this study, we address this limitation by analyzing multiple independent datasets across five cancer types using PIPI-C, a novel mass spectrometry data analysis tool. And we propose AA substitutomics, a pipeline for characterizing AA substitutions arising after protein translation and dissecting the regulatory functions of key proteins with AA substitutions. Among our identified AA substitutions, 87% are novel findings and not recorded in genomic/transcriptomic databases, which indicates that the post-translational AA substitutions are prevalent. Our findings reveal biologically significant AA substitutions linked to cancer, such as F43S and E91D in hemoglobin subunit beta, P584T in filamin A, and A175N in fructose-bisphosphate aldolase B. Furthermore, our pipeline enables direct investigation of drug resistance and immune escape. By capturing functional protein-level alterations beyond genomic and transcriptomic profiling, it establishes a robust framework to advance cancer research.

Background: Amino acid (AA) substitutions in Alzheimer’s disease (AD) have been studied almost exclusively at the DNA and RNA levels, and the proteome-level substitution landscape remains largely uncharacterized. Methods: We applied an open-search substitutomics pipeline (PIPI-C with Comet re-scoring, 1% PSM-level FDR) to two independent AD brain proteomic datasets, the AMP-AD superior temporal gyrus cohort (244 individuals) and PXD013753, excluding substitutions whose mass shifts coincide with common post-translational modifications. Results: We quantified 789 substitution-bearing peptidoforms from 185 proteins, corresponding to 784 protein-level substitution events. N > M was the most frequent N > X substitution in both datasets. In an institution-stratified case–control meta-analysis, 138 peptidoforms were more and 142 less abundant in AD than in neuropathological controls. Of 774 genome-mappable events, 710 (91.7%) were recorded in neither UniProt nor gnomAD, and only five matched a population variant with allele frequency ≥ 0.1%. The unrestricted search recovered six literature-reported sites in GFAP, ACTG1, and HBB. Conclusions: Proteome-level profiling reveals substitution events in AD brains that catalogued germline variation does not explain; their molecular origin requires orthogonal validation.