Polymyalgia rheumatica and giant cell arteritis induced by immune checkpoint inhibitors: A systematic literature review highlighting differences from the idiopathic forms.

Introduction: An altered immune tolerance disturbed by immune checkpoint inhibitors (ICIs) may contribute to new-onset polymyalgia rheumatica (PMR) and giant cell arteritis (GCA). This systematic literature review (SLR) examines the characteristics of PMR and GCA-like syndromes following anticancer treatment with ICIs, summarizing their demographic, clinical and treatment-related features to provide insights whether they differ from the idiopathic forms.

Methods: The SLR was conducted in Medline and EMBASE databases from inception to July 2024, and in the EULAR/ACR abstract database (2021-2023).

Association between PD-1 single nucleotide gene variants and the risk of metastatic melanoma.

Previous studies showed an association between single nucleotide gene variants (SNVs) of PD-1 and cancer susceptibility. We analyzed PD1.5 C > T and PD1.

Combining germline, tissue and liquid biopsy analysis by comprehensive genomic profiling to improve the yield of actionable variants in a real-world cancer cohort.

Background: Comprehensive next-generation sequencing is widely used for precision oncology and precision prevention approaches. We aimed to determine the yield of actionable gene variants, the capacity to uncover hereditary predisposition and liquid biopsy appropriateness instead of, or in addition to, tumor tissue analysis, in a real-world cohort of cancer patients, who may benefit the most from comprehensive genomic profiling.

Methods: Seventy-eight matched germline/tumor tissue/liquid biopsy DNA and RNA samples were profiled using the Hereditary Cancer Panel (germline) and the TruSight Oncology 500 panel (tumor tissue/cfDNA) from 23 patients consecutively enrolled at our center according to at least one of the following criteria: no available therapeutic options; long responding patients potentially fit for other therapies; rare tumor; suspected hereditary cancer; primary cancer with high metastatic potential; tumor of unknown primary origin.

Machine Learning Methods for Gene Selection in Uveal Melanoma.

Uveal melanoma (UM) is the most common primary intraocular malignancy with a limited five-year survival for metastatic patients. Limited therapeutic treatments are currently available for metastatic disease, even if the genomics of this tumor has been deeply studied using next-generation sequencing (NGS) and functional experiments. The profound knowledge of the molecular features that characterize this tumor has not led to the development of efficacious therapies, and the survival of metastatic patients has not changed for decades.