Targeted diagnosis and therapy enable precise tumor detection and treatment. Successful examples for precise tumor targeting are diagnostic and therapeutic radioligands. However, patients with tumors expressing low levels of the relevant molecular targets are deemed ineligible for such targeted approaches. Methods: We performed a screen for drugs that upregulate the somatostatin receptor subtype 2 (sstr 2 ). Then, we characterized the effects of these drugs on transcriptional, translational, and functional levels in vitro and in vivo. Results: We identified 9 drugs that act as epigenetic modifiers, including the inhibitor of DNA methyltransferase decitabine as well as the inhibitors of histone deacetylase tacedinaline and romidepsin. In vitro, these drugs upregulated sstr 2 on transcriptional, translational, and functional levels in a time-and dose-dependent manner. Thereby, their combinations revealed synergistic effects. In vivo, drug-based sstr 2 upregulation improved the tumor-to-background and tumor-tokidney ratios, which are the key determinants of successful sstr 2 -targeted imaging and radiopeptide therapy. Conclusion: We present an approach that uses epigenetic modifiers to improve sstr 2 targeting in vitro and in vivo. Translation of this method into the clinic may potentially convert patients ineligible for targeted imaging and therapy to eligible candidates.

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Prostate cancer is the fourth most common cancer worldwide with definitive diagnosis reliant on biopsy and human-graded histopathology. As with other pathologies, grading based on classical haematoxylin and eosin (H&E) staining of formalin fixed paraffin-embedded material can be prone to variation between pathologists, prompting investigation of biomolecular markers. Comprising around 50% of cellular mass, and with known metabolic variations in cancer, lipids provide a promising target for molecular pathology. Here we apply isomer-resolved lipidomics in combination with imaging mass spectrometry to interrogate tissue sections from radical prostatectomy specimens. Guided by the histopathological assessment of adjacent tissue sections, regions of interest are investigated for molecular signatures associated with lipid metabolism, especially desaturation and elongation pathways. Monitoring one of the most abundant cellular membrane lipids within these tissues, phosphatidylcholine (PC) 34:1, high positive correlation was observed between the n-9 isomer (site of unsaturation 9-carbons from the methyl terminus) and epithelial cells from potential pre-malignant lesions, while the n-7 isomer abundance was observed to correlate with immune cell infiltration and inflammation. The correlation of lipid isomer signatures with human disease states in tissue suggests a future role for isomer-resolved mass spectrometry imaging in assisting pathologists with prostate cancer diagnoses and patient stratification.

Precision medicine is entering a new era of digital diagnostics; the availability of integrated digital pathology (DP) and structured clinical datasets has the potential to become a key catalyst for biomedical research, education and business development. In Europe, national programs for sharing of this data will be crucial for the development, testing, and validation of machine learning–enabled tools supporting clinical decision-making. Here, the Swiss Digital Pathology Consortium (SDiPath) discusses the creation of a Swiss Digital Pathology Infrastructure (SDPI), which aims to develop a unified national DP network bringing together the Swiss Personalized Health Network (SPHN) with Swiss university hospitals and subsequent inclusion of cantonal and private institutions. This effort builds on existing developments for the national implementation of structured pathology reporting. Opening this national infrastructure and data to international researchers in a sequential rollout phase can enable the large-scale integration of health data and pooling of resources for research purposes and clinical trials. Therefore, the concept of a SDPI directly synergizes with the priorities of the European Commission communication on the digital transformation of healthcare on an international level, and with the aims of the Swiss State Secretariat for Economic Affairs (SECO) for advancing research and innovation in the digitalization domain. SDPI directly addresses the needs of existing national and international research programs in neoplastic and non-neoplastic diseases by providing unprecedented access to well-curated clinicopathological datasets for the development and implementation of novel integrative methods for analysis of clinical outcomes and treatment response. In conclusion, a SDPI would facilitate and strengthen inter-institutional collaboration in technology, clinical development, business and research at a national and international scale, promoting improved patient care via precision medicine.