Please use this identifier to cite or link to this item:
http://dx.doi.org/10.25673/120476
Title: | Case Report : Personalized peptide-based immunization in an advanced-stage prostate cancer patient with bone metastasis |
Author(s): | Thoennißen, Nils Heinrich![]() Martos-Contreras, Mari Carmen Manoochehri, Mehdi Nogueira, Mauro Oddo ![]() Bremm, Franziska Dörrie, Jan ![]() Christoph, Jan ![]() Kunz, Meik ![]() Schönharting, Wolfgang |
Issue Date: | 2025 |
Type: | Article |
Language: | English |
Abstract: | Neoantigens, which are recognized as non-self and trigger an immune response, are novel antigens generated by tumor cells. Here, we report a de novo metastatic hormone-sensitive prostate cancer (mHSPC) case, which benefited from our personalized peptide immunization named BioInformatic Tumor Address Peptides (BITAP) in a monotherapeutic setting. Our in-house bioinformatics pipeline involved identifying somatic variations, analyzing their expression, and computationally predicting novel epitopes from both metastatic and primary tumors, separately. As stand-alone therapy, the patient has been administered multiple injections of two peptide pools (BITAP-1 and BITAP-2). Several months following immunizations, a significant regression of both metastatic and primary tumor lesions was recorded along with low-level of prostate-specific antigen (PSA). Besides mild and short-lasting local and systemic reactions, no serious treatment-related adverse effects were reported by the patient. In conclusion, this case suggests that BITAP immunization is feasible and safe, and may present an immunotherapeutic approach inducing sustainable tumor regressions in mHSPC patients. |
URI: | https://opendata.uni-halle.de//handle/1981185920/122432 http://dx.doi.org/10.25673/120476 |
Open Access: | ![]() |
License: | ![]() |
Journal Title: | Frontiers in oncology |
Publisher: | Frontiers Media |
Publisher Place: | Lausanne |
Volume: | 15 |
Original Publication: | 10.3389/fonc.2025.1596315 |
Page Start: | 1 |
Page End: | 7 |
Appears in Collections: | Open Access Publikationen der MLU |
Files in This Item:
File | Description | Size | Format | |
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fonc-1-1596315.pdf | 2.14 MB | Adobe PDF | ![]() View/Open |