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The prognosis of extensive-stage small cell lung cancer is usually poor. In this study, a combined model based on pre-treatment CT radiomics and clinical features was constructed to predict the OS of extensive-stage small cell lung cancer after chemotherapy with immunotherapy.Clinical data of 111 patients with extensive stage small-cell lung cancer who received first-line immunotherapy combined with chemotherapy in our hospital from December 2019 to December 2021 were retrospectively collected. Finally, 93 patients were selected for inclusion in the study, and CT images were obtained through PACS system before treatment. All patients were randomly divided into a training set (n = 66) and a validation set (n = 27). Images were imported into ITK-SNAP to outline areas of interest, and Python software was used to extract radiomics features. A total of 1781 radiomics features were extracted from each patient’s images. The feature dimensions were reduced by MRMR and LASSO methods, and the radiomics features with the greatest predictive value were screened. The weight coefficient of radiomics features was calculated, and the linear combination of the feature parameters and the weight coefficient was used to calculate Radscore. Univariate cox regression analysis was used to screen out the factors significantly associated with prognosis from the radiomics and clinical features, and multivariate cox regression analysis was performed to establish the prognosis prediction model of extensive stage small cell lung cancer. The degree of metastases was selected as a significant clinical prognostic factor by univariate cox regression analysis. Seven radiomics features with significance were selected by LASSO-COX regression analysis, and the Radscore was calculated according to the coefficient of the radiomics features. An alignment diagram survival prediction model was constructed by combining Radscore with the number of metastatic lesions. The study population was stratified into those who survived less than 11 months, and those with a greater than 11 month survival. The C-index was 0.722 (se = 0.044) and 0.68(se = 0.074) in the training and the validation sets, respectively. The Log_rank test results of the combination model were as follows: training set: p < 0.0001, validation set: p = 0.00042. In this study, a combined model based on radiomics and clinical features could predict OS in patients with extensive stage small cell lung cancer after chemotherapy with immunotherapy, which could help guide clinical treatment strategies. [ABSTRACT FROM AUTHOR]

Secondary BRAF variations have been identified as a mechanism of resistance to tyrosine kinase inhibitors (TKIs) in patients with driver gene-positive NSCLC. Nevertheless, there is still a lack of consensus regarding the characteristics and subsequent treatment strategies for these patients. We retrospectively reviewed the medical records of patients with driver gene-positive NSCLC who received TKIs therapy at Zhejiang Cancer Hospital between May 2016 and December 2023. The clinical and genetic characteristics of these patients were assessed, along with the impact of various treatment strategies on survival. This study enrolled 27 patients with advanced NSCLC, in whom BRAF variations occurred at a median time of 28 months after the initiation of targeted therapy. The multivariate accelerated failure time (AFT) model revealed that, compared to chemotherapy-based regimens group, the combined targeted therapy group (p < 0.001) and the combined local treatment group for oligo-progression (p < 0.001) significantly extended patient survival. In contrast, continuing the original signaling pathway's targeted monotherapy was associated with shorter survival (p = 0.034). The median global OS for each treatment group was as follows: chemotherapy-based regimens group, 45 months; combined targeted therapy group, 59 months; combined local treatment group for patients with oligo-progression, 46 months; and targeted monotherapy group, 36 months. Study results indicate that the combination targeted therapy group (including TKIs, BRAF inhibitors, and/or MEK inhibitors) and the localized treatment group are more effective than traditional chemotherapy-based regimens in improving survival. Additionally, continuing targeted monotherapy along the original signaling pathway proves less effective than chemotherapy-based regimens. [ABSTRACT FROM AUTHOR]

Worldwide, Lung cancer is the leading cause of cancer-related death and poses a direct health threat, non-small cell lung cancer (NSCLC) is the most common type. In this study, we demonstrated that centrosomal protein 20 (CEP20) is upregulated in NSCLC tissues and associated with cancer invasion metastasis. Notably, CEP20 depletion inhibited NSCLC cell proliferation, migration, and microtubule polymerization. Mechanistically, we discovered that CEP20 is critical in the development of NSCLC by regulating microtubule dynamics and cell adhesion-related signaling pathways. Furthermore, the knockdown or overexpression of CEP20 affects microtubule polymerization in A549 cell lines. Our research provides a promising therapeutic target for the diagnosis and treatment of lung cancer, as well as a theoretical and experimental basis for clinical application. [ABSTRACT FROM AUTHOR]

Anaprazole, a new proton pump inhibitor (PPI), is designed for the treatment of acid-related diseases, such as gastric ulcers and gastroesophageal reflux. This study explored the in vitro metabolic transformation of anaprazole. The metabolic stabilities of anaprazole in human plasma and human liver microsomes (HLM) were analyzed by liquid chromatography-tandem mass spectrometry (LC–MS/MS). Then, the contribution (%) of non-enzymatic and cytochrome P450s (CYPs) enzyme-mediated anaprazole metabolism was assessed. To obtain the metabolic pathways of anaprazole, the metabolites generated in HLM, thermal deactivated HLM, and cDNA-expressed recombinant CYPs incubation systems were identified by ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF–MS). Results showed that anaprazole was very stable in human plasma and unstable in HLM. The contribution (%) of non-enzymatic vs. CYPs enzyme-mediated metabolism was 49% vs. 51%. CYP3A4 was the major enzyme (48.3%), followed by CYP2C9 (17.7%) and CYP2C8 (12.3%), in responsible for the metabolism of anaprazole. Specific chemical inhibitors targeting CYP enzymes notably blocked the metabolic transformation of anaprazole. Six metabolites of anaprazole were identified in the non-enzymatic system, whereas 17 metabolites were generated in HLM. The biotransformation reactions mainly included sulfoxide reduction to thioether, sulfoxide oxidation to sulfone, deoxidation, dehydrogenation, O-dealkylation or O-demethylation of thioether, O-demethylation and dehydrogenation of thioether, O-dealkylation and dehydrogenation of thioether, thioether O-dealkylation and dehydrogenation of thioether, and O-dealkylation of sulfone. Both enzymatic and non-enzymatic metabolisms contribute to the clearance of anaprazole in human. Anaprazole is less likely to develop drug-drug interactions in clinical use compared to other PPIs. [ABSTRACT FROM AUTHOR]

Immunotherapy has greatly changed the status of cancer treatment, and many patients do not respond or develop acquired resistance. The related research is blocked by lacking of comprehensive resources for researchers to discovery and analysis signatures, then further exploring the mechanisms. Here, we first offered a benchmarking dataset of experimentally supported signatures of cancer immunotherapy by manually curated from published literature works and provided an overview. We then developed CiTSA (http://bio-bigdata.hrbmu.edu.cn/CiTSA/) which stores 878 entries of experimentally supported associations between 412 signatures such as genes, cells, and immunotherapy across 30 cancer types. CiTSA also provides flexible online tools to identify and visualize molecular/cell feature and interaction, to perform function, correlation, and survival analysis, and to execute cell clustering, cluster activity, and cell–cell communication analysis based on single cell and bulk datasets of cancer immunotherapy. In summary, we provided an overview of experimentally supported cancer immunotherapy signatures and developed CiTSA which is a comprehensive and high-quality resource and is helpful for understanding the mechanism of cancer immunity and immunotherapy, developing novel therapeutic targets and promoting precision immunotherapy for cancer. [ABSTRACT FROM AUTHOR]

The incidence of laryngeal carcinoma accounts for 1 to 5% of systemic malignancies and ranks second among head and neck malignancies. Screening more effective targets are meaningful for the treatment of laryngeal carcinoma. The purpose was to research the action of miR-21-5p in the occurrence of laryngeal carcinoma. Genecards combined with g:profiler was used for cluster analysis to predict gene-related miRNAs. Q-PCR assay was performed for measuring the level of miR-21-5p and Kruppel-like factor 6 (KLF6). miR-21-5p-mimic, miR-21-5p-inhibitor and sh-KLF6 were transfected using LipofectamineTM 2000. Both CCK-8 and EdU experiments were undertaken to detect cell proliferation ability. Western blot was used to detect apoptosis and epithelial–mesenchymal transition (EMT) related proteins. Wound healing assay and transwell assay were undertaken for migration and invasion, respectively. Three online software (ENCORI, miRWalk, and miRDB) were applied to screen the downstream of miR-21-5p. At the same time, a dual-luciferase reporter experiment was processed to verify the binding. Finally, a rescue experiment was applied to reveal the mediating role of miR-21-5p and KLF6. MiR-21-5p expressed highly in laryngeal carcinoma tissues and cell lines. Knockdown of miR-21-5p reduced the EMT, while enhancing apoptosis of laryngeal carcinoma cell lines. MiR-21-5p targeted KLF6 with negative relationships. The rescue assay results confirmed that sh-KLF6 rescued the action of miR-21-5p knockdown in developing laryngeal carcinoma cells. MiR-21-5p promotes the occurrence and development of laryngeal cancer by targeting KLF6. This finding may provide new insights into miRNA as a biomarker for diagnosing and treating laryngeal carcinoma in the future. [ABSTRACT FROM AUTHOR]