Lung adenocarcinoma (LUAD) is a non-small-cell lung cancer and is the leading cause of cancer-related deaths worldwide. Immunotherapy is a promising candidate for LUAD, and tumor mutation burden (TMB) could be a new biomarker to monitor the response of cancer patients to immunotherapy. It is known that the mucin 16 (MUC16) mutation is the most common and affects the progression and prognosis of several cancers. However, whether MUC16 mutations are associated with TMB and tumor-infiltrating immune cells in LUAD is not fully elucidated. All the data were obtained from the cancer genome atlas database to assess the prognostic value and potential mechanism of MUC16 in LUAD. An immune prognostic model (IPM) was developed based on immune-related genes that could be differentially expressed between MUC16MUT and MUC16WT LUAD patients. Later, the IPM effect on the prognosis and immunotherapy of LUAD was comprehensively evaluated. MUC16 was frequently mutated in LUAD, with a mutational frequency of 43.4%, significantly associated with higher TMB and better clinical prognosis. Based on 436 patients with LUAD, an IPM was established and validated to differentiate patients with a low or high risk of poor survival. The univariate and multivariate Cox regression analyses demonstrated that the IPM was an independent prognostic indicator for LUAD patients. Elevated expressions of PD-L1, LAG3, PDCD1, and SIGLEC15, and most of the T-effector and interferon-γ gene signatures, were depicted in the high-risk group. Moreover, the nomogram using the IPM and clinical prognostic factors also predicted the overall survival and clinical utility. Our project developed a robust risk signature depending on the MUC16 status and provided novel insights for individualized treatment options for LUAD patients.
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http://dx.doi.org/10.1097/MD.0000000000035481 | DOI Listing |
Sci Rep
January 2025
Department of Clinical Laboratory, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China.
Our aim was to investigate the potential value of immune-related miRNA signaling in predicting clinical prognosis and immunotherapy. We first identified immune-related miRNAs in lung adenocarcinoma (LUAD), and then constructed a miRNA-based risk model by lasso regression modeling. Finally, we validated our findings using RT-qPCR in serum from LUAD patients and normal patients.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Thoracic Surgery, Affiliated Hospital of Chengde Medical College, Chengde, 067000, Hebei, China.
DCUN1D5 is up-regulated and promotes tumor progression in many cancers such as laryngeal squamous cell carcinoma and breast cancer, but the expression of DCUN1D5 in lung adenocarcinoma and its molecular mechanism are not clear. The differences of DCUN1D5 expression between lung adenocarcinoma and normal tissues were compared by TCGA, GEO and UALCAN databases, and the relationship between DCUN1D5 expression and clinicopathological features of patients was analyzed. The diagnostic and prognostic value of DCUN1D5 in patients with LUAD was analyzed by TCGA, GEPIA and Kaplan-Meier Plotter database.
View Article and Find Full Text PDFFront Med (Lausanne)
December 2024
Department of Rheumatology and Immunology, The Affiliated Huai'an Hospital of Xuzhou Medical University, The Second People's Hospital of Huai'an, Huai'an, China.
The risk of lung cancer is significantly increased in patients with systemic sclerosis (SSc), yet the specific genes underlying this association remain unexplored. Our study aims to identify genes shared by SSc and lung cancer. We identified differentially expressed genes (DEGs) from SSc and lung adenocarcinoma (LUAD) datasets (SSc: GSE95065, LUAD: GSE136043) in the GEO database.
View Article and Find Full Text PDFOncol Res
December 2024
Department of Respiratory Medicine, Shandong Provincial Third Hospital, Jinan, 250010, China.
Background: To investigate SCL/TAL 1 interrupting locus ()'s role and prognostic significance in lung adenocarcinoma (LUAD) progression, we examined and E2 promoter binding factor 1 (E2F1) expression and their impacts on LUAD prognosis using Gene Expression Profiling Interactive Analysis (GEPIA).
Methods: Functional assays including CCK-8, wound-healing, 5-ethynyl-2-deoxyuridine (EdU), Transwell assays, and flow cytometry, elucidated and E2F1's effects on cell viability, proliferation, apoptosis, and migration. Gene set enrichment analysis (GSEA) identified potential pathways, while metabolic assays assessed glucose metabolism.
Front Oncol
December 2024
Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Background: The aim of this study is to develop deep learning models based on F-fluorodeoxyglucose positron emission tomography/computed tomographic (F-FDG PET/CT) images for predicting individual epidermal growth factor receptor () mutation status in lung adenocarcinoma (LUAD).
Methods: We enrolled 430 patients with non-small-cell lung cancer from two institutions in this study. The advanced Inception V3 model to predict EGFR mutations based on PET/CT images and developed CT, PET, and PET + CT models was used.
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