Lipid metabolism disorder, a new hallmark of cancer initiation, has been involved in lung adenocarcinoma (LUAD). However, few biomarkers about lipid metabolism-related genes (LMRGs) have been developed for prognosis prediction and clinical treatment of LUAD patients. In this study, we constructed and validated an effective prognostic prediction model for LUAD patients depending on LMRGs. Subsequently, we investigated the prediction model from immune microenvironment, genomic changes, and immunotherapy. Then, eleven LMRGs were identified and applied to LUAD subtyping. In comparison with the high-risk group, the low-risk group exhibited a remarkably favorable prognosis, along with a higher immune score and lower tumor purity. Moreover, the low-risk group presented higher levels of immune checkpoint molecules, lower tumor immune dysfunction and exclusion (TIDE) score and tumor mutation burden (TMB), and higher likelihood of benefiting from immunotherapy. Furthermore, the genomic changes of six LMRGs (CD79A, HACD1, CYP17A1, SLCO1B3, ANGPTL4, and LDHA) were responsible for the difference in susceptibility to LUAD by greatly influencing B-cell activation. Generally speaking, the LMRG model is a reliable independent biomarker for predicting adverse outcomes in LUAD patients and has the potential to facilitate risk-stratified immunotherapy.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918775 | PMC |
http://dx.doi.org/10.3389/fcell.2022.730132 | DOI Listing |
Front Immunol
December 2024
Department of Respiratory and Critical Care Medicine, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China.
Background: APOE gene polym orphisms have been linked to Alzheimer's disease and coronary heart diseases. However, their relationship with lung adenocarcinoma (LUAD) remains uncertain.
Methods: This study analyzed a cohort of 600 individuals comprising 200 LUAD patients in the lung cancer group and 400 healthy individuals as controls.
Sci Rep
January 2025
1Nantong University, Nantong, 226007, People's Republic of China.
Estrogen sulfotransferase (SULT1E1), a member of the sulfotransferase family (SULTs), is the enzyme with the strongest affinity for estrogen. Despite significant associations between SULT1E1 and the progression and prognosis of a range of diseases, its functional role and potential mechanisms in lung adenocarcinoma (LUAD) remain unclear. The objective of this study was to examine the potential of SULT1E1 as a biomarker for LUAD.
View Article and Find Full Text PDFCancer Control
January 2025
School of Basic Medical Sciences, Anhui Medical University, Hefei, China.
Introduction: and mutations are frequently detected in lung adenocarcinoma (LUAD). Tumor mutational signature (TMS) determination is an approach to identify somatic mutational patterns associated with pathogenic factors. In this study, through the analysis of TMS, the underlying pathogenic factors of LUAD with and mutations were traced.
View Article and Find Full Text PDFFront Oncol
December 2024
Central Laboratory, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Hospital of Traditional Chinese Medicine), Qingdao, Shandong, China.
Introduction: Lung adenocarcinoma (LUAD) poses a significant therapeutic challenge, primarily due to delayed diagnosis and the limited efficacy of existing treatments.
Methods: To understand the pathogenesis and identify diagnostic biomarkers for LUAD in the early stage, we investigated differential miRNA expression in 33 stage I LUAD patients between tumor and matched paracancerous tissues by Illumina Sequencing. Target genes of differentially expressed miRNAs were predicted using TargetScan and miRDB databases and further analyzed by GO and KEGG pathway enrichment analysis.
J Cardiothorac Surg
January 2025
Department of Oncology Radiotherapy, Ruian People's Hospital, Wenzhou Medical University, Affiliated Hospital 3, Wenzhou, Zhejiang, 35200, China.
Background: Lung adenocarcinoma (LUAD) is a high-risk malignancy. Telomeres- (TRGs) and aging-related genes (ARGs) play an important role in cancer progression and prognosis. This study aimed to develop a novel prognostic model combined TRGs and ARGs signatures to predict the prognosis of patients with LUAD.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!