Histone posttranslational modifications (hPTMs) generate a complex combinatorial code that plays a critical role in the regulation of gene activity and nuclear architecture during physiological and pathological processes. Mass spectrometry (MS) offers an unbiased, comprehensive, and quantitative view on hPTM patterns, and has emerged as a powerful tool in epigenetic research. Stable isotope labeling by amino acid in cell culture (SILAC) is a MS-based quantitative method that relies on the metabolic labeling of cell populations, which has been widely applied in global proteomic studies and can also be exploited for the accurate quantitation of hPTM changes among distinct functional states. However, the classical SILAC strategy has two main limits: it cannot be applied to more than three cell populations at the time and excludes samples that cannot be metabolically labeled, such as clinical samples. These limitations can be overcome by using a super-SILAC strategy, where a mix of heavy-labeled cell lines is used as a spike-in to analyze any types of samples with high accuracy and high multiplexing capabilities. In this chapter, we will provide a detailed description of a protocol to set up a histone-focused super-SILAC strategy and exploit it to accurately profile hPTMs across multiple samples. As a case study, we will describe a breast cancer-focused super-SILAC approach, which we used in a recent publication to profile hPTMs in frozen and formalin-fixed paraffin-embedded human samples, revealing previously unknown marks that differentiate breast cancer subtypes.