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Subject: Non-Small Cell Lung Cancer

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    Article
    ACPA Prevents Lung Fibroblast-to Transformation by Reprogramming the Tumor Microenvironment through NSCLC-Derived Exosomes
    (Nature Portfolio, 2025) Boyacioglu, Ozge; Kalali, Berfin Deniz; Recber, Tuba; Gelen-Gungor, Dilek; Nemutlu, Emirhan; Eroglu, Ipek; Korkusuz, Petek; Kilic, Nedret
    Non-small cell lung cancer (NSCLC) accounts for most lung cancer cases. Current treatments often cause systemic side effects or lead to drug resistance, prompting the development of new therapies targeting tumors and related cells simultaneously. Cancer-associated fibroblasts (CAFs) are crucial stromal cells within the tumor microenvironment (TME), making them potential targets for therapy. Previously, we found that the CB1 receptor agonist ACPA has anti-tumor effects on NSCLC, inhibiting pathways such as Akt/PI3K, JNK, glycolysis, the citric acid cycle, and the urea cycle both in vitro and in vivo. We hypothesize that ACPA could enhance therapy by inhibiting the transformation of lung fibroblasts into CAFs via exosomes. Control and ACPA-treated NSCLC cell exosomes exhibited similar size, PDI, ZP, and high expression of CD9, CD63, and CD81. ACPA-treated exosomes showed reduced levels of miR-21 and miR-23. These exosomes decreased fibroblast viability within 12 h by disrupting pentose phosphate, lipid, and amino acid metabolism, and by lowering PDPN, alpha-SMA, and FAP expressions. This research highlights ACPA as a promising chemotherapeutic agent, capable of improving NSCLC treatment and reprogramming the TME with more targeted therapies.
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    Article
    The Prognostic Impact of 18F-FDG PET SUVmax in Patients with Non-Small Cell Lung Cancer
    (Bayrakol Medical Publisher, 2026) Gulcek, Ilham; Agar, Mehmet; Kalkan, Muhammed; Celik, Muhammet Reha; Ulutas, Hakki
    Aim: The maximum standardized uptake value (SUVmax) of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) enhances clinical prediction in non-small cell lung cancers (NSCLC). This study aimed to investigate whether SUVmax could serve as a prognostic factor and improve clinical prognostication. Methods: This retrospective study included 86 patients with NSCLC who underwent surgical resection. Using receiver operating characteristic (ROC) analysis, the SUVmax cut-off value was 12.3. Patients with SUVmax values below 12.3 were classified as Group A, while those with values above 12.3 were designated as Group B. Survival analyses were performed using the Kaplan-Meier method. Overall survival was defined as the time from diagnosis to death. Confidence intervals were reported at 95%, and a p-value of <0.05 was considered statistically significant. The variables analyzed for survival included gender, age, surgical approach, histopathological subtype of lung cancer, cancer stage, T score, and N score. Results: Survival analyses revealed statistically significant associations between SUVmax and age (p=0.043), gender (p=0.060), surgical approach (p=0.037), and histopathological subtype (p=0.026). Due to insufficient sample size within subgroups, separate p-values were calculated for each stage, T score, and N score. Based on the obtained p-values, no statistically significant correlation was found between SUVmax and overall survival across different stages, T scores, or N scores, except for stage 1A and T1b. Conclusion: SUVmax contributes to determining appropriate diagnostic and treatment protocols and aids in predicting the prognosis of the disease.