Mesenchymal-epithelial transition (MET) exon 14 (METex14) skipping mutation is a rare alteration in non-small-cell lung cancer (NSCLC), occurring in about 3%-4% of cases. Here we report disease and patient characteristics, and efficacy and tolerability of MET inhibitors among advanced METex14 NSCLC patients from the Italian real-world registry ATLAS. Clinical-pathological and molecular data, and treatment efficacy/tolerability outcomes were retrospectively collected from the ATLAS registry. From July 2020 to July 2023 a total of 146 METex14 advanced NSCLC patients were included across 27 Italian centers. Median age was 74 years, and most patients were male (52%), with an Eastern Cooperative Oncology Group performance status < 2 (72%) and adenocarcinoma subtype (83%). One hundred and twenty-five out of 146 (86%) patients received at least one line of systemic anticancer therapy. Fifty-six (38%) were treated with capmatinib and 34 (23%) with tepotinib. 29% and 52% of them received targeted treatment in the first and second line, respectively. In the cohort of patients treated with MET inhibitors, the response rate (RR) was 37% (33% in previously treated patients and 46% in treatment-naïve) with a disease control rate of 62%. With a median follow-up of 10.8 months, progression-free survival was 6.6 months [95% confidence interval (CI) 4.3-8.3 months] and overall survival was 10.7 months (95% CI 7.2-19.3 months). In patients with measurable brain metastases (17 cases), the intracranial RR was 41%. Grade ≥3 treatment-related adverse events (TRAEs) occurred in 12% of patients with grade 3 peripheral edema in 7% of cases. A fatal adverse reaction occurred in one patient due to pneumonitis. TRAEs-related dose reduction and discontinuation were reported in 6% and 8% of cases, respectively. Capmatinib and tepotinib represent an effective treatment option in NSCLC patients with METex14. Real-world efficacy outcomes are worse than those reported in prospective clinical trials. Their activity is more pronounced in the treatment-naïve population, suggesting that this is the right setting in the management of patients with METex14.

Purpose: This systematic review aims to analyze the literature on the application of AI in predicting patient outcomes and treatment-related toxicity in those undergoing SBRT or SRS across heterogeneous tumor sites. Materials and methods: Our review conformed to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. PubMed, EMBASE and Scopus were systematically searched for English-language human studies evaluating AI for outcome and toxicity prediction in patients undergoing SBRT or SRS for solid tumors. Search terms included (“Stereotactic Body Radiotherapy” OR “SBRT” OR “Stereotactic Radiosurgery” OR “SRS” OR “Stereotactic Ablative Radiotherapy” OR “SABR”) AND (“Artificial Intelligence” OR “AI” OR “Machine Learning” OR “Deep Learning” OR “Radiomics”) AND (“Response Prediction” OR “Response to Treatment” OR “Outcome Prediction”) AND (“Toxicity” OR “Side Effects” OR “Treatment Toxicities” OR “Adverse Events”). Results: The search yielded 29 eligible retrospective studies, published between 2020 and 2025. Eight studies addressed early-stage primary lung cancer, highlighting the potential of AI-based models in predicting radiation-induced pneumonitis, fibrosis and local control. Five studies investigated AI models for predicting hepatobiliary toxicity following SBRT for liver tumors. Sixteen studies involved SRS-treated patients with brain metastases or benign intracranial neoplasms (e.g., arteriovenous malformations, vestibular schwannomas, meningiomas), exploring AI algorithms for predicting treatment response and radiation-induced changes. In the results, AI might have been exploited to both reaffirm already known clinical predictors and to identify novel imaging, dosimetric or biological biomarkers. Examples include predicting radiation pneumonitis in lung cancer, residual liver function in hepatic tumors and local recurrence in brain metastases, thus supporting tailored treatment decisions. Conclusions: Combining AI with SBRT could greatly enhance personalized cancer care by predicting patient-specific outcomes and toxicity. AI models analyze complex datasets, including imaging and clinical data, to identify patterns that traditional methods may miss, thus enabling more accurate risk stratification and reducing variability in treatment planning. With further research and clinical validation, this integration could make radiotherapy safer, more effective and contribute to advancement in precision oncology.

Background: The landscape of systemic therapies for advanced non-melanoma skin cancers has been revolutionized by the advent of immunotherapy. Cemiplimab is the only immune checkpoint inhibitor (ICI) approved by the European Medicine Agency for recurrent/metastatic cutaneous squamous cell carcinoma (cSCC). Its excellent efficacy outcomes are achieved due to its good tolerability profile. The drug-related hypersensitivity reaction (HSR) is a well-known issue in oncology, but it is rarely reported in respect to immune checkpoint inhibitors. Cemiplimab is among the agents with the best infusion tolerability profiles. Clinical practice guidelines in this field are lacking. Results: We report on the successful management of a severe infusion reaction induced by Cemiplimab in a patient with cSCC based on a desensitization protocol, which led to adequate treatment delivery and prolonged clinical benefit. A review of the available literature on HSR rates and its management with ICIs, and on drug desensitization (DD) protocols and their efficacy, was conducted to highlight the limited knowledge on this topic and its importance. Conclusion: Our experience highlights the need for a DD protocol in order to improve the treatment of HSRs, particularly when elicited by an immunotherapy agent, preventing treatment discontinuation and preserving its efficacy.

The expression level of Programmed Death-Ligand 1 (PD-L1) determined by the immunohistochemical method is currently approved to test the potential efficacy of immune-checkpoint inhibitors and to candidate patients with Non-Small Cell Lung Cancer (NSCLC) for treatment with immunotherapeutic drugs. As part of the CORELAB (New prediCtivebiOmaRkers of activity and Efficacy of immune checkpoint inhibitors in advanced non-small cell Lung cArcinoma) project, aimed at identifying new predictive and prognostic biomarkers in NSCLC patients receiving immunotherapeutic drugs, we investigated the role of circulating tumor DNA (ctDNA) molecular characterization as an additional predictive biomarker. We analyzed plasma ctDNA by targeted Next Generation Sequencing in a subset of 50 patients at different time points. ctDNA content was inversely correlated with the clinical outcome both at a baseline and after 2 months of treatment. OS was significantly higher in patients with ≥50% ctDNA reduction. TP53 and KRAS were the most frequently mutated genes, and patients with KRAS and/or TP53 mutations showed worse outcomes than patients without detectable variants or with mutations in other genes. Fewer common variants were found in BRAF, EGFR, MAP2K1, MET, NRAS, and PIK3CA genes. Our data demonstrated that molecular characterization of ctDNA and also its quantitative evaluation could serve as a dynamic, real-time prognostic, and predictive biomarker, enabling regular molecular monitoring of therapy efficacy in support of other medical examinations.

Stereotactic body radiotherapy has been established as a viable treatment option for inoperable early-stage non-small cell lung cancer or secondary lesions mainly in oligoprogressive/oligometastatic scenarios. Treating lesions in the so-called “no flight zone” has always been challenging and conflicting data never cleared how to safely treat these lesions. This is truer considering ultra-central lesions, i.e., directly abutting or whose PTV is overlapping critical mediastinal organs. While historical retrospective data are abundant but mostly heterogenous in terms of the definition of ultra-central lesions, dosing regimens and outcomes, prospective data remain scarce, even though recently published studies have given new encouraging results for such delicate treatment scenarios. For this reason, we aimed to review and summarize current knowledge on stereotactic radiation treatment for ultra-central thoracic lesions, highlighting the most recent advances and the messages that can be taken from them. Lastly, we propose a workflow of the necessary steps to identify and treat such patients, therefore helping in elucidating the advantages and caveats of such treatment options.