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Updated: Jun 23, 2026

A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
PCI-DB: a novel primary tissue immunopeptidome database to guide next-generation peptide-based immunotherapy
Steffen Lemke1,2,3,4,5, Marissa L Dubbelaar1,2,3, Patrick Zimmermann1,2,6
1Department of Peptide-based Immunotherapy, Institute of Immunology, University and University Hospital Tübingen, Tübingen, BW, Germany.
Background:
Various cancer immunotherapies rely on the T cell-mediated recognition of peptide antigens presented on human leukocyte antigens (HLA). However, the identification and selection of naturally presented peptide targets for the development of personalized as well as off-the-shelf immunotherapy approaches remain challenging.
Methods:
Over 10,000 raw mass spectrometry (MS) files from over 3,000 tissue samples were analyzed, summing to approximately seven terabytes of data. The raw MS data were processed using the standardized and open-source nf-core pipelines MHCquant2 and epitopeprediction, providing a uniform procedure for data handling. A global false discovery rate was applied to minimize false-positive identifications.
Results:
Here, we introduce the open-access Peptides for Cancer Immunotherapy Database (PCI-DB, https://pci-db.org/), a comprehensive resource of immunopeptidome data originating from various malignant and benign primary tissues that provides the research community with a convenient tool to facilitate the identification of peptide targets for immunotherapy development. The PCI-DB includes >6.6 million HLA class I and >3.4 million HLA class II peptides from over 40 tissue types and cancer entities. First application of the database provided insights into the representation of cancer-testis antigens across malignant and benign tissues, enabling the identification and characterization of cross-tumor entity and entity-specific tumor-associated antigens (TAAs) as well as naturally presented neoepitopes from frequent cancer mutations. Further, we used the PCI-DB to design personalized peptide vaccines for two patients suffering from metastatic cancer. In a retrospective analysis, PCI-DB enabled the composition of both a multi-peptide vaccine comprising non-mutated, highly frequent TAAs matching the immunopeptidome of the individual patient's tumor and a neoepitope-based vaccine matching the mutational profile of a patient with cancer. Both vaccine approaches induced potent and long-lasting T-cell responses, accompanied by long-term survival of these patients with advanced cancer.
Conclusion:
The PCI-DB provides a highly versatile tool to broaden the understanding of cancer-related antigen presentation and, ultimately, supports the development of novel immunotherapies.
Insights
A new database, Peptides for Cancer Immunotherapy Database (PCI-DB), aids in identifying cancer-specific peptide targets for immunotherapy. This resource supports the development of personalized and off-the-shelf cancer immunotherapies by analyzing millions of peptides.
Area of Science:
- Immunology
- Oncology
- Bioinformatics
Background:
- Cancer immunotherapies depend on T cell recognition of peptide antigens presented by human leukocyte antigens (HLA).
- Identifying naturally presented peptide targets for personalized and off-the-shelf immunotherapies is challenging.
Purpose of the Study:
- To introduce the Peptides for Cancer Immunotherapy Database (PCI-DB) as an open-access resource for identifying peptide targets for cancer immunotherapy development.
- To facilitate the identification and characterization of tumor-associated antigens (TAAs) and neoepitopes.
Main Methods:
- Analysis of over 10,000 mass spectrometry (MS) files from 3,000+ tissue samples.
- Standardized data processing using nf-core pipelines MHCquant2 and epitopeprediction.
- Application of a global false discovery rate to minimize false positives.
Main Results:
- The PCI-DB contains over 6.6 million HLA class I and 3.4 million HLA class II peptides from 40+ tissue types.
- Insights into cancer-testis antigen representation and identification of cross-tumor and entity-specific TAAs and neoepitopes.
- Successful design of personalized peptide vaccines for two metastatic cancer patients, inducing potent T-cell responses and long-term survival.
Conclusions:
- PCI-DB is a versatile tool for understanding cancer antigen presentation.
- PCI-DB supports the development of novel immunotherapies.

