The introduction of immunotherapy revolutionized the treatment landscape in metastatic melanoma. Despite the impressive results associated with immune checkpoint inhibitors (ICIs), only a portion of patients obtain a response to this treatment. In this scenario, the research of predictive factors is fundamental to identify patients who may have a response and to exclude patients with a low possibility to respond. These factors can be host-associated, immune system activation-related, and tumor-related. Patient-related factors can vary from data obtained by medical history (performance status, age, sex, body mass index, concomitant medications, and comorbidities) to analysis of the gut microbiome from fecal samples. Tumor-related factors can reflect tumor burden (metastatic sites, lactate dehydrogenase, C-reactive protein, and circulating tumor DNA) or can derive from the analysis of tumor samples (driver mutations, tumor-infiltrating lymphocytes, and myeloid cells). Biomarkers evaluating the immune system activation, such as IFN-gamma gene expression profile and analysis of circulating immune cell subsets, have emerged in recent years as significantly correlated with response to ICIs. In this manuscript, we critically reviewed the most updated literature data on the landscape of predictive factors in metastatic melanoma treated with ICIs. We focus on the principal limits and potentiality of different methods, shedding light on the more promising biomarkers.

Background: The timing of immune checkpoint inhibitor (ICI) administration may influence clinical outcomes, incidence, and severity of immune-related adverse events (irAEs), but evidence remains limited. Methods: We conducted a retrospective analysis of 41 patients with advanced melanoma treated with combined ipilimumab and nivolumab at the Istituto Oncologico della Svizzera Italiana between 2018 and 2024. Infusions completed before 2:00 p.m. were classified as morning (AM). Patients receiving ≥50% of doses in the morning were assigned to the AM group; the remaining patients comprised the afternoon (PM) group. Results: Twenty-one patients were included in the AM group and twenty in the PM group. Median progression-free survival (PFS) was not reached in the AM group, compared with 7.8 months in the PM group (univariate HR 0.29, 95% CI 0.12–0.70; p = 0.006). Overall survival (OS) was also significantly improved in the AM group (univariate HR 0.25, 95% CI 0.08–0.80; p = 0.019). The overall incidence of irAEs was similar between groups. However, systemic immunosuppression for grade ≥ 2 toxicities was more frequently required in the PM group (80% vs. 52%, p = 0.06). Conclusions: In this retrospective cohort, morning administration of ICIs was associated with improved PFS and OS in patients with advanced melanoma. While irAE incidence was comparable between groups, patients treated in the afternoon more often required systemic immunosuppression.

Emerging liquid biopsy platforms are expanding frontiers in lung cancer care, facilitating real-time molecular insights and addressing some of the limitations of tissue biopsy. While standardization and sensitivity improvements are undergoing continuous refinement in those liquid biopsy techniques that are now established, several advancements are expanding the panorama of its potential future applications. This review offers an overview of the emerging uses of liquid biopsy in the field of lung cancer, with a specific focus on emerging technologies. We comprehensively reviewed the literature through PubMed and Embase, combining keywords and Medical Subject Headings (MeSH) related to small-cell (SCLC) and non-small-cell lung cancer (NSCLC) and liquid biopsy using Boolean operators. The search was limited to publications from 2017 up to 2026. Titles and abstracts underwent manual scrutiny for relevance. We critically analyzed a body of evidence assessing the potential role of liquid biopsy in common and uncommon applications, such as its combination with machine learning and AI and its integration in multiomics approaches or its usage in next-generation technologies—including label-free CTC isolation, DNA fragmentomics and end-motif profiling, four-dimensional proteomics, and unconventional biospecimens—that remain largely unaddressed in prior narrative reviews on this topic.