610
Proteogenomics-based identifying neoantigens in refractory cancers using xenograft mice
Yuko Nakamura1, Susumu Iizumi2, Hiroki Ueda3, Shogo Yamamoto3, Kenji Tatsuno3, Aya Nakayama1, Kazuki
Yamamoto1, Taku Koro4, Kyoko Hasegawa2, Norihiro Nakamura2, Hiroyuki Aburatani3, Tetsuro Sasada4, Takeshi
Kawamura1, 3
1. Isotope Science Center, The University of Tokyo, Bunkyo-Ku, Tokyo, Japan
2. BrightPath Biotherapeutics Co., Ltd., Kawasaki, Kanagawa, Japan
3. Research Center for Advanced Science and Technology, The University of Tokyo, Meguro-ku, Tokyo, Japan
4. Kanagawa Cancer Center Research Institute, Yokohama, Kanagawa, Japan
Background
Recently, neoantigens have been paid great attention among cancer-specific antigens. Neoantigens are self-peptides that are
displayed on major histocompatibility complexes (MHC) with cancer specific mutations that are never seen in normal tissues. We
performed combined searching by the next generation sequencing (NGS) and mass spectrometry for MHC-associatedneoantigens in the refractory cancers.
Methodologies
DNAs and RNAs are extracted and sequenced from cultured colon cancer cell lines and patient tissues (total 9 samples) frompancreatic and biliary cancers. Among the samples, 4 tissues are transplanted to mice to prepare xenograft mice. Proteins areextracted from the xenograft models, immunoprecipitated with anti-MHC antibody, and measured by a mass spectrometer.
Peptide sequences are searched against database obtained from the exome and transcriptome from the identical tissue.
Findings
After a systematic examination of experimental conditions using the cultured cells, we have established a workflow that can detect
above 1,000 MHC-associated peptides from 3 mg of protein lysates from xenograft mice. We have also identified several
neoantigen candidates by DNA and RNA sequencing followed by peptide sequencing with mass spectrometric analysis.
Concluding
In identifying neoantigens, we have found that peptidomics have been added the detection confidence of the identified
neoantigens. We are further improving sensitivity to the level to detect directly from patient tissues without xenograft formation.
The identified neoantigen candidates are tested for immunogenicity in vitro.

611
Promotion of proteomic data sharing through a specialized data journal
Shin Kawano1, 2, Shujiro Okuda3, Masaki Matsumoto4, Yasushi Ishihama5
1. Research Organization of Information and Systems, Kashiwa, Japan
2. Toyama University of International Studies, Toyama, Japan
3. Niigata University, Niigata, Japan
4. Kyushu University, Fukuoka, Japan
5. Kyoto University, Kyoto, Japan
BackgroundProteomics is a rapidly growing research area that produces large amounts of data, which has led to complex challenges arounddata management. Proteomics data and datasets need to become more Findable, Accessible, Interoperable, and Re-usable(FAIR1) to promote data sharing. To address these challenges and facilitate better proteome data management, the field needs
to develop formal structures and procedures. To this end, the Japanese Proteomics Society decided to launch a new data journal– the Journal of Proteome Data and Methods (JPDM).
Preparations
In order to launch JPDM, we prepared the following documents: Publishing plan, Instruction to authors, Guide to reviewers, Ethics
policies, License to publish form, and Frequently asked questions. All documents are available at https://www.jhupo.org/jpdm/.
We also prepared a submission system (https://mc.manuscriptcentral.com/jpdm/) using the ScholarOne platform.
Features of JPDM
JPDM is a peer-reviewed and fully open access journal provided via the J-stage platform. JPDM publishes four article types: Datadescriptors, Protocols, Data processing notes, and Reviews. The main content of the journal is Data descriptors, which isdescribed detailed metadata of mass-based proteomics datasets. JPDM collaborates with ProteomeXchange 2 (PX), which is aconsortium of proteome data repositories including jPOST3, PRIDE4, MassIVE, etc. When data producers register their datasetsin a PX repository then post detailed metadata in JPDM, the journal sends a feedback to the PX repository. JPDM contributes toadd a value for proteome datasets by providing detailed metadata.
Conclusion
We launched the new data journal for proteomics community named JPDM. The journal is peer-reviewed and fully open access,and the website is https://www.jhupo.org/jpdm/. JPDM realizes the FAIR principal in the proteomics field by providing richinformation. JPDM welcomes lots of submission from community members.
1.
2.
3.

Wilkinson MD et al., The FAIR Guiding Principles for scientific data management and stewardship, Sci Data. 3:160018(2016).
Deutsch EW et al., The ProteomeXchange consortium in 2017: supporting the cultural change in proteomics public datadeposition. Nucleic Acids Res. 45:D1100-D1106 (2017).
Moriya Y et al., The jPOST environment: an integrated proteomics data repository and database. Nucleic Acids Res.
47:D1218-D1224 (2019).