MET exon 14 skipping mutations in non-small-cell lung cancer: real-world data from the Italian biomarker ATLAS database.

BACKGROUND: 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. MATERIALS AND METHODS: Clinical-pathological and molecular data, and treatment efficacy/tolerability outcomes were retrospectively collected from the ATLAS registry. RESULTS: 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. CONCLUSION: 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.

Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project.

BACKGROUND: Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. PATIENTS AND METHODS: Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. RESULTS: The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. CONCLUSIONS: This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.