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Kiesel, B.

Publications and source records attributed to Kiesel, B..

2 recordsLinked to original sources

Mutanome-guided immunopeptidomics of blood plasma for neoepitope detection in solid tumors is constrained by cfDNA variant calling sensitivity and MS detection limits

Introduction: Neoepitopes form the basis of tumor-specific immune responses. Tissue biopsy, the primary source for neoepitope detection, is limited and invasive. Therefore, we aimed to identify neoepitopes by mutanome-guided immunopeptidomics from plasma of cancer patients. Methods: Mass spectrometry (MS) data analysis of HLA ligands from plasma (n = 4) was guided by patient-specific mutanomes of cell-free DNA (cfDNA) from plasma or tumor genomic DNA (tgDNA) from tissue. Matched tumor tissue and healthy donor plasma served as controls. Neoepitopes were validated with synthetic peptides, and immunogenicity was assessed using IFN-gamma ELISpot and intracellular cytokine staining. Results: Wild-type immunopeptidomes from tissue and plasma overlapped by 58%, with 91% of plasma HLA ligands rediscovered in tissue. 13 out of 15 tumor-associated HLA ligands detected in plasma were rediscovered in the matching tissue. However, no neoepitopes in plasma were identified by immunopeptidomics guided by cfDNA mutanomes, likely reflecting the limited overlap between cfDNA and tgDNA mutanomes (15%). Using the tgDNA mutanome as a complementary reference, two neoepitopes were detected in one patient's plasma, albeit at the MS detection limit. Both neoepitopes were also discovered in tissue, along with three tissue-exclusive neoepitopes. Two tissue-exclusive neoepitopes induced antigen-specific T cell responses in healthy donor PBMCs. Conclusion: In summary, plasma immunopeptidomics enables profiling of HLA ligands from wild-type proteins, including TAAs. In principle, neoepitope detection from plasma at the peptide level is feasible, but tissue remains the gold standard for variant calling and neoepitope identification. Improved detection methods may enable minimally invasive approaches in the future.

immunology↗

The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of the DNA methylation dynamics in matched primary and recurring glioblastoma tumors, based on a national population registry and a comprehensively annotated clinical cohort. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected formalin-fixed paraffin-embedded (FFPE) samples, and we validate bisulfite sequencing as a multi-purpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional tumor characteristics. Based on these data, we identified characteristic differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study provides a resource for dissecting DNA methylation heterogeneity in genetically diverse and heterogeneous tumors, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology in a representative national cohort, leveraging samples and data collected as part of routine clinical practice.

cancer biology↗