Background: Lung adenocarcinoma (LUAD) is the most frequent subtype of lung cancer. The prognostic signature could be reliable to stratify LUAD patients according to risk, which helps the management of the systematic treatments. In this study, a systematic and reliable immune signature was performed to estimate the prognostic stratification in LUAD. Methods: The profiles of immune-related genes for patients with LUAD were used as one TCGA training set: n = 494, other validation set 1: n = 226 and validation set 2: n = 398. Univariate Cox survival analysis was used to identify the candidate immune-related genes from each cohort. Then, the immune signature was developed and validated in the training and validation sets. Results: In this study, functional analysis showed that immune-related genes involved in immune regulation and MAPK signaling pathway. A prognostic signature based on 10 immune-related genes was established in the training set and patients were divided into high-risk and low-risk groups. Our 10 immune-related gene signature was significantly related to worse survival, especially during early-stage tumors. Further stratification analyses revealed that this 10 immune-related gene signature was still an effective tool for predicting prognosis in smoking or nonsmoking patients, patients with KRAS mutation or KRAS wild-type, and patients with EGFR mutation or EGFR wild-type. Our signature was negatively correlated with B cell, CD4+ T cell, CD8+ T cell, neutrophil, dendritic cell (DC), and macrophage immune infiltration, and immune checkpoint molecules PD-1 and CTLA-4 (P < 0.05). Conclusions: These findings suggested that our signature was a promising biomarker for prognosis prediction and can facilitate the management of immunotherapy in LUAD.
Background: DLEC1 is a tumor-suppressor gene which plays a role in carcinogenesis. The purpose of the current study was to help establish the diagnostic performance of DLEC1 methylation in lung cancer. Methods: PubMed, Embase, CNKI, and Wanfang databases were searched to obtain eligible studies. The pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to estimate the strength of the associations. The diagnostic value was assessed by the summary receiver operating characteristics test. Results: A total of 7 articles, with 8 studies that included 673 lung cancer and 581 control samples, were collected in this meta-analysis. Our results showed a significant association of DLEC1 hypermethylation with lung cancer (P < 0.00001, OR = 13.93, 95% CI = 9.44-20.55). The frequency of DLEC1 methylation was significantly higher in squamous cell carcinoma (SCC) than adenocarcinoma (AC). Moreover, DLEC1 was more frequently methylated in patients with lung cancer aged 60 years or over, patients with lymphatic metastasis, or patients with stage III/IV lung cancer. In addition, there was a sensitivity value of 0.90 (95% CI = 0.86-0.93) and a specificity value of 0.60 (95% CI = 0.56-0.63), a pooled positivelikelihood ratio (PLR) of 2.27 (95% CI = 2.08-2.48), a pooled negative-likelihood ratio (NLR) of 0.17 (95% CI = 0.12-0.23), a diagnostic odds ratio (DOR) of 14.72 (10.09-21) and an area under the curve (AUC) of 0.8146 using DLEC1 methylation in the prediction of lung cancer risk. Conclusion: This meta-analysis confirms that DLEC1 methylation is a promising biomarker for lung cancer.
Background:The study aimed to identify risk factors associated with overall survival (OS) of patients with lung adenocarcinoma (LACA) with brain metastasis and developed a prognostic tool (nomogram) for these patients.Methods: LACA patients with brain metastases between 2010 and 2013 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier analysis and a Cox regression model were used to assess the prognostic effect of variables on survival rate. A nomogram was developed to predict 3-, 6-and 9-month OS rates.Results: 2,631 LACA patients with brain metastases were studied. A nomogram was developed by using variables that affected OS and was validated by internal bootstrap resampling, which revealed that the nomogram had satisfactory discrimination. Conclusions:The nomogram was able to predict 3-, 6-and 9-month OS for patients with LACA and brain metastases.
Background: The correlation between vitamin D intake and lung cancer development is controversial. This meta-analysis aims to evaluate the relationship between vitamin D and the prognosis and incidence of lung cancer. Methods: A comprehensive database search on Pubmed, Web of Science, EBSCO, and Cochrane Library was carried out from the beginning to November 2020. Long-term survival and the incidence rate of patients with lung cancer were the primary outcomes of the study. Results: Ten eligible studies were selected for the meta-analysis following specific inclusion and exclusion criteria. Four included studies, covering 5007 patients, compared the overall survival (OS) and relapse-free survival (RFS) of lung cancer patients among total vitamin D users with non-users. Significantly, the estimated pooled hazard ratio (HR) revealed that vitamin D could improve OS and RFS of lung cancer patients [HR=0.83, 95% CI (0.72-0.95); HR=0.79, 95% CI (0.61-0.97), respectively]. Vitamin D intake was inversely associated with lung cancer incidence in six studies [OR=0.90, 95% CI (0.83-0.97)]. Conclusions: The present meta-analysis shows vitamin D not only improves the long-term survival of lung cancer patients but has a beneficial effect on the incidence of lung cancer. Notwithstanding, more studies are needed to confirm the study results.
Background Studying sex differences in the efficacy of immunotherapy may contribute to the practice of the precision medicine, especially in non-small cell lung cancer (NSCLC), a kind of cancer with sexual bimorphism. Methods Published randomized controlled trials (RCTs), published by PubMed, Medline, Embase, and Scopus, before 15 June 2022, testing immunotherapy (CTLA-4 or PD-1/L1 inhibitor alone, combination or with chemotherapy) versus non-immunotherapy (receiving chemotherapy or placebo only) were included to assess different efficacy between males and females. The primary endpoint was overall survival (OS). This meta-analysis was registered with PROSPERO (CRD42022298439). Results Sixteen RCTs, involving 10,155 patients with advanced NSCLC, was collected in this meta-analysis. The pooled HR comparing immunotherapy vs non-immunotherapy were 0.76 (95%CI 0.71–0.81) for males and 0.74 (95%CI 0.63–0.87) for females. The pooled HRs comparing immune-checkpoint inhibitors (ICIs) plus chemotherapy versus chemotherapy were 0.79 (95%CI 0.70–0.89) for males and 0.63 (95%CI 0.42–0.92) for females. The pooled HRs comparing ICIs versus chemotherapy were 0.74 (95%CI 0.67–0.81) for males and 0.83 (95%CI 0.73–0.95) for females. In squamous NSCLC, the pooled HRs comparing immunotherapy vs non-immunotherapy were 0.73 (95%CI 0.58–0.91) for males and 0.74 (95%CI 0.37–1.48) for females. In non-squamous NSCLC, the pooled HRs comparing immunotherapy versus non-immunotherapy were 0.62 (95%CI 0.71–0.94) for males and 0.59 (95%CI 0.39–0.89) for females. Conclusion Compared to chemotherapy, immunotherapy can improve the prognosis of patients with advanced NSCLC. Meanwhile, there are sex differences in the efficacy of immunotherapy. KEY MESSAGE Compared to chemotherapy, immunotherapy can improve the prognosis of patients with advanced NSCLC. The most interesting thing in this study is that immunotherapy showed significant sex differences in the treatment of squamous NSCLC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.