Belzutifan is a new HIF-α inhibitor mainly used in two different indications: von Hippel–Lindau syndrome-associated renal cell carcinoma, haemangioblastomas and pancreatic neuroendocrine tumours, as well as sporadic advanced pre-treated renal cell carcinoma. Although efficacy has been demonstrated in phase II and III studies, belzutifan is still not approved in many countries. In addition, von Hippel–Lindau syndrome is a rare disease. Therefore, there is virtually no real-world experience data of belzutifan efficacy available. We aim to determine the real-world efficacy and tolerability of belzutifan in patients with von Hippel–Lindau syndrome-associated tumours and in patients with sporadic advanced tyrosine kinase- and immune checkpoint inhibitors pre-treated for renal cell carcinoma. A retrospective analysis of five patients treated with belzutifan between 2023 and 2024 at a Swiss cancer centre was conducted. In this case series, all patients consistently benefitted from belzutifan with response to treatment. This case series provides real-world evidence that belzutifan is an effective and well-tolerated treatment option for patients with von Hippel–Lindau syndrome-associated renal cell carcinoma, haemangioblastomas and sporadic advanced pre-treated renal cell carcinoma.

Background: Rare cancers combine low incidence with high biological heterogeneity and multi-institutional care trajectories. These features make single-center learning structurally incomplete and render pathway fragmentation a dominant driver of preventable harm, variability, and waste. In this context, care quality is best understood as a property of pathway integrity across routing, diagnostics (imaging/biopsy planning), multidisciplinary intent-setting, definitive treatment, and surveillance—rather than as a department-level attribute. Objective: To define a pragmatic, transferable operating blueprint for a rare-cancer Learning Health System (LHS) that turns routine care into continuous, auditable learning under explicit governance, while maintaining claims discipline and protecting measurement validity. Approach: We synthesize an implementation-oriented operating model using the Swiss Sarcoma Network (SSN) as an exemplar. The blueprint couples clinical governance (Integrated Practice Unit logic, hub-and-spoke routing, auditable multidisciplinary team decision systems) with an interoperable real-world-time data backbone designed for benchmarking, pathway mapping, and feedback. The operating logic is expressed as a closed-loop control cycle: capture → harmonize → benchmark → learn → implement → re-measure, with explicit owners, minimum requirements, and failure modes. Results/Blueprint: (i) The model specifies a minimal set of data primitives—time-stamped and traceable decision points covering baseline and tumor characteristics, pathway timing, treatment exposure, outcomes and complications, and feasible longitudinal PROMs and PREMs; (ii) a VBHC-ready, multi-domain measurement backbone spanning outcomes, harms, timeliness, function, process fidelity, and resource stewardship; and (iii) two non-negotiable validity guardrails: explicit applicability (“N/A”) rules and mandatory case-mix/complexity stratification. Implementation is treated as a governed step with defined workflow levers, fidelity criteria, balancing measures, and escalation thresholds to prevent “dashboard medicine” and surrogate-driven optimization. Conclusions: This perspective contributes an operating model—not a platform or single intervention—that enables credible improvement science and establishes prerequisites for downstream causal learning and minimum viable digital twins. By distinguishing enabling infrastructure from the governed clinical system as the primary intervention, the blueprint supports scalable, learnable excellence in rare-cancer care while protecting against gaming, inequity, and inference drift. Distinct from generic LHS or VBHC frameworks, this blueprint specifies validity gates required for rare-cancer benchmarking—explicit applicability (“N/A”) rules, denominator integrity/capture completeness disclosure, anti-gaming safeguards, and escalation governance. These elements are critical in rare cancers because small denominators, high heterogeneity, and multi-institutional pathways otherwise make benchmarking prone to artifacts and unsafe inferences.

Background: BRCA2 germline mutations are known to predispose carriers to various cancer types, including breast, ovarian, pancreatic and prostate cancer. An association with melanoma has also been reported. However, the full tumour spectrum associated with BRCA2 mutations, particularly in patients with other concurrent pathogenetic mutations, is unexplored. Case presentation: We present a 70-year-old female patient with a pathogenic BRCA2 c.5946del variant. Over a period of 15 years, she has developed two independent breast cancers, well-differentiated liposarcoma, clear cell renal cell carcinoma and myeloproliferative neoplasia. This unusual tumour spectrum and the staggered occurrence of these tumours required multiple rounds of genetic testing and led to a delayed diagnosis of the BRCA2-associated tumour predisposition. In addition to the BRCA2 mutation, extended germline testing revealed an APC c.3920T > A variant and variants of unknown significance in the BRIP1 and ATR genes. The molecular analysis of the tumours revealed distinct profiles with differences in HRD status and in copy number variations, indicating no common origin. Conclusions: Our case study revealed that the pathogenic BRCA2 c.5946del germline variant can be associated with an unusual tumour spectrum, which may lead to a delayed diagnosis of a hereditary tumour predisposition. Thus, upfront genetic testing using large multigene panels or whole-genome sequencing in encouraged, especially in cases with a prominent family history.