Because cancer has unique plasticity and diversity in its metabolic state, systematic interpretation using multiple omics data is important. Metabolomics requires analytical tools that can accurately and comprehensively capture quantitative changes in metabolites inside and outside of cancer cells. However, most critical metabolites, such as amino acids and organic acids, are difficult to quantify by LC-MS using common reversed-phase analytical columns owing to their polarity and sensitivity limitations. To address this issue, we developed a system for the simultaneous absolute determination of amino acids, ATP, and NAD using a column packed with polymer particles featuring mixed amino group modifications. Furthermore, we adapted an organic acid measurement system using the 2-picolylamine derivatization method, and an adamantylethyl group column was used to establish a system for the absolute quantification of major cancer metabolomes using an isotope dilution method. Application of this method to three prostate cancer cell lines, combined with data-independent acquisition (DIA) proteomic data, revealed cell line-specific metabolic transitions. These methods introduced in this report are expected to be an important analytical platform for cancer metabolomics.

We present our recent works on vibrational circular dichroism spectroscopy (VCD). VCD is a chiro-optical method detecting molecular chirality in the infrared region. A main attention has been focused on the asymmetric structures (called “supramolecular chirality”) that appear when many molecules are linked together, such as seen in gels and molecular crystals. Recently, we have developed a multi-dimensional infrared circular dichroism spectroscopy (named the multi-dimensional VCD method) with a microscopic function by adding time and space axes to the conventional wavenumber axis. Spatial resolution of 100 μm was achieved by using a quantum cascade laser as a highly brilliant infrared light source. Here, we describe the application of the solid-state VCD method to amino acids and peptides. Next, we introduce the application of the microscopy technique to insect wings as an example of biological samples. It is revealed that a wing comprises the heterogenous distribution of protein domains in various secondary structures.

Multiomics/proteogenomics was developed through the integration of deep sequencing technology and mass spectrometry technology, which has expanded the search space for mass spectrometry data. Expanded landscapes for peptide searches work well with the enlarged data size acquired by state-of-the-art MS instruments. To accommodate this landscape, researchers have synergistically developed supporting algorithms to perform efficient peptide searches with machine learning, further advancing the multidisciplinary field of MS-associated omics. The utility of immunopeptidomics in the field of cancer immunology has been acknowledged in recent years, and this analytical field has benefited the most from innovations in MS technology. Along with the technological innovations of MS described above, fractionation techniques based on ion mobility have been developed to analyze delicate analytes, such as immunopeptides; in addition, clinical immunopeptidomics is being advanced to improve the efficacy of precision cancer immunotherapy.

In this review, we first outline the background and current status of immunopeptidomics research. Then, by introducing the differential ion mobility system in our laboratory, we explain why ion mobility is advantageous for immunopeptidomics analysis. For researchers that are new to this field or interested in immunopeptidomics, we also discuss frequently asked questions regarding sample preparation, MS parameters for immunopeptidomics (including differential ion mobility), and validation of the identified peptides as immunopeptides.