{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T19:25:48Z","timestamp":1789068348000,"version":"build-2803163510"},"reference-count":71,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T00:00:00Z","timestamp":1748995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Circulating Extracellular Vesicles (cEVs) could represent new non-invasive biomarkers for diagnosis and prognosis in tumors. In the context of Non-Small Cell Lung Cancer (NSCLC) immunotherapy there\u2019s a great need for novel predictive and prognostic biomarkers. This study aims to analyze cEVs microRNAs in serum of advanced stage NSCLC patients with PD-L1 expression \u226550% at diagnosis, before first-line pembrolizumab, to evaluate their possible role as potential biomarkers for immunotherapy response prediction and outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>cEVs were isolated from serum of healthy subjects and NSCLC patients at diagnosis. All patients had tumor PD-L1\u226550% and cEVs were extracted before first-line pembrolizumab treatment. cEVs were then characterized for morphology, integrity, concentration, size and protein contaminants. Subsequently, microRNA content (miR-10a, miR-21, miR-22, miR-30a, miR-34a, miR-106b, miR-125b, miR-150, miR-155, miR-181a, miR-181b, miR-451a) was investigated by digital PCR. Additionally, miRNA-targets and their roles were evaluated. All data were associated with immunotherapy response, Progression Free Survival (PFS), Overall Survival (OS), Eastern Cooperative Oncology Group Performance Status (ECOG-PS) and metastases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Twelve NSCLC-related microRNAs have been found, for the first time, in serum cEVs from a specific cohort of metastatic advanced stage NSCLC patients. Through a functional analysis, these microRNAs are found to be connected to each other and involved in the pathology of NSCLC, particularly in IGF\/P53\/VEGF\/NOTCH\/PI3K pathways, in cytokine\/interleukin signaling and in the immune system. Specifically, we demonstrated that cEV miR-106b, miR-451a, miR-181 and miR-10a were significantly up-regulated in non-responder patients compared to responder ones (\n                      <jats:italic>p<\/jats:italic>\n                      -value=0.08-0.1) predicting with high accuracy, already at diagnosis, treatment response. Furthermore, a low level of all these microRNAs predicted improved PFS (\n                      <jats:italic>p<\/jats:italic>\n                      -value=0.009-0.02) and a low amount of miR-106b predicted longer OS (\n                      <jats:italic>p<\/jats:italic>\n                      =0.069). In addition, it was observed that high levels of miR-106b and miR-451a are indicative of a high number of metastases (\n                      <jats:italic>p<\/jats:italic>\n                      =0.05\/0.04, respectively) and of ECOG-PS=0.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>This is the first study that investigated specific potential serum cEV miRNAs to predict with high accuracy immunotherapy response and prognosis in specific metastatic NSCLC patients, already at diagnosis. Collectively, our cEV miRNA analysis identifies novel circulating biomarkers that are easily accessible and non-invasive, offering a potential blood-based tool to guide personalized medicine in NSCLC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2025.1540906","type":"journal-article","created":{"date-parts":[[2025,6,4]],"date-time":"2025-06-04T01:39:47Z","timestamp":1749001187000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Serum extracellular vesicle microRNAs as potential biomarkers to predict pembrolizumab response and prognosis in metastatic non-small cell lung cancer patients"],"prefix":"10.3389","volume":"16","author":[{"given":"Daniela","family":"Lamorte","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luciana","family":"De Luca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alfredo","family":"Tartarone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefania","family":"Trino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irene","family":"Giulivo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Angelo","family":"De Stradis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maddalena","family":"Maietti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonella","family":"Caivano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilaria","family":"Laurenzana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,4]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.3322\/CAAC.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J Clin"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000032899","article-title":"Non-small cell lung cancer (NSCLC): A review of risk factors, diagnosis, and treatment","volume":"102","author":"Alduais","year":"2023","journal-title":"Medicine"},{"key":"B3","doi-asserted-by":"publisher","first-page":"13323","DOI":"10.1038\/S41598-021-92725-8","article-title":"Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods","volume":"11","author":"Chen","year":"2021","journal-title":"Sci Rep"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3390\/JPM11111102","article-title":"Diagnostic, predictive, and prognostic biomarkers in non-small cell lung cancer (NSCLC) management","volume":"11","author":"\u0160uti\u0107","year":"2021","journal-title":"J Pers Med"},{"key":"B5","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1186\/S12935-023-02990-Y","article-title":"Recent advances in non-small cell lung cancer targeted therapy; 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