Annual Report 2023
Department of Proteomics
Shungo Adachi, Mari Masuda, Hideo Kusano, Masae Homoto, Tatsuki Yokoseki, Yuka Teratoko
Introduction
Our division aims to elucidate the core vulnerabilities of cancer at the functional proteome level through the development of protein analysis technologies leveraging mass spectrometry and through large-scale sample analysis, ultimately contributing to the development of new therapeutic approaches. In addition to advancing various proteomic analysis techniques, we are also focusing on automating the experimental workflows and data analysis methods required for high-throughput proteomic studies.
The Team and What We Do
1) Development of techniques for the comprehensive analysis of dynamic changes in protein activity
2) Development of proteomic analysis technologies for cancer clinical specimens to identify potential biomarkers
3) Accumulation of protein analysis data and development of technologies for utilizing this data
4) Development of automated technologies for sample preparation in proteomic analysis
Research Activities
In FY 2023, the Department of Proteomics was newly launched, with two core staff members and four project researchers. We successfully established an analytical environment centered on mass spectrometry. Specifically, we relocated a mass spectrometer from an external facility and installed a new high-end mass spectrometer. To support proteomic analysis of tissue specimens and other biological samples requested by both internal and external cancer research centers, we developed protocols for sample processing, measurement, and operational conditions. These advancements have enabled the routine identification and quantification of over 8,000 proteins, and up to 10,000 phosphorylated peptides during phosphoproteomics analysis. Additionally, we conducted proteomic analyses of cancer tissues in which the efficacy of specific drugs had been demonstrated, leading to the identification of candidate biomarkers associated with drug response, underscoring the utility of proteomics in cancer research. Furthermore, we established a collaborative platform to integrate protein quantification results obtained via mass spectrometry with reverse-phase protein array (RPPA) technology for cross-validation.
Future Prospects
In FY 2023, we successfully implemented a new proteomic analysis infrastructure, and by the end of the year, introduced a state-of-the-art high-throughput mass spectrometer capable of analyzing over 50 samples and more than 10,000 proteins per day. Leveraging this new instrument, we aim to digitize the protein expression profiles of cancer tissue samples stored in biobanks, enabling comprehensive integration with clinical and other omics data. This is expected to further enhance our understanding of cancer initiation and progression at the proteomic level. Furthermore, since analysis of blood samples is crucial for cancer diagnostics in addition to tissue analysis, we plan to expand our efforts to develop blood-based proteomic analysis technologies. Although improvements in the throughput of mass spectrometry, previously a major bottleneck, represent a significant step forward, the efficiency of sample preparation and data analysis will need to be addressed to prevent new bottlenecks from emerging. Thus, we will prioritize the automation of both sample preparation and data analysis workflows moving forward.
List of papers published in 2023
Journal
1. Masuda M, Nakagawa R, Kondo T. Harnessing the potential of reverse-phase protein array technology: Advancing precision oncology strategies. Cancer science, 115:1378-1387, 2024
2. Maru Y, Kohno M, Suzuka K, Odaka A, Masuda M, Araki A, Itami M, Tanaka N, Hippo Y. Establishment and characterization of multiple patient-derived organoids from a case of advanced endometrial cancer . Human cell, 37:840-853 , 2024
3. Hirukawa K, Yagi H, Kuroda K, Watanabe M, Nishi K, Nagata S, Abe Y, Kitago M, Adachi S, Sudo R, Kitagawa Y. Novel approach for reconstruction of the three-dimensional biliary system in decellularized liver scaffold using hepatocyte progenitors . PloS one, 19:e0297285 , 2024
4. Akiyama T, Yasuda T, Uchihara T, Yasuda-Yoshihara N, Tan BJY, Yonemura A, Semba T, Yamasaki J, Komohara Y, Ohnishi K, Wei F, Fu L, Zhang J, Kitamura F, Yamashita K, Eto K, Iwagami S, Tsukamoto H, Umemoto T, Masuda M, Nagano O, Satou Y, Saya H, Tan P, Baba H, Ishimoto T. Stromal Reprogramming through Dual PDGFRα/β Blockade Boosts the Efficacy of Anti-PD-1 Immunotherapy in Fibrotic Tumors . Cancer research, 83:753-770 , 2023
5. Maeda F, Adachi S, Natsume T. Non-destructive and efficient method for obtaining miRNA information in cells by artificial extracellular vesicles . Scientific reports, 13:22231 , 2023
6. Takakuwa H, Yamazaki T, Souquere S, Adachi S, Yoshino H, Fujiwara N, Yamamoto T, Natsume T, Nakagawa S, Pierron G, Hirose T. Shell protein composition specified by the lncRNA NEAT1 domains dictates the formation of paraspeckles as distinct membraneless organelles . Nature cell biology, 25:1664-1675 , 2023
7. Takayama KI, Matsuoka S, Adachi S, Honma T, Yoshida M, Doi T, Shin-Ya K, Yoshida M, Osada H, Inoue S. Identification of small-molecule inhibitors against the interaction of RNA-binding protein PSF and its target RNA for cancer treatment . PNAS nexus, 2:pgad203 , 2023
8. Hata S, Saito H, Kakiuchi T, Fukumoto D, Yamamoto S, Kasuga K, Kimura A, Moteki K, Abe R, Adachi S, Kinoshita S, Yoshizawa-Kumagaye K, Nishio H, Saito T, Saido TC, Yamamoto T, Nishimura M, Taru H, Sobu Y, Ohba H, Nishiyama S, Harada N, Ikeuchi T, Tsukada H, Ouchi Y, Suzuki T. Brain p3-Alcβ peptide restores neuronal viability impaired by Alzheimer's amyloid β-peptide . EMBO molecular medicine, 15:e17052 , 2023