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Background: The lung has a sophisticated microbiome, and respiratory illnesses are greatly influenced by the lung microbiota. Despite the fact that numerous studies have shown that lung cancer patients have a dysbiosis as compared to healthy people, more research is needed to explore the association between the microbiota dysbiosis and immune profile within the tumor microenvironment (TME). Methods: In this study, we performed metagenomic sequencing of tumor and normal tissues from 61 non‐small cell lung cancer (NSCLC) patients and six patients with other lung diseases. In order to characterize the impact of the microbes in TME, the cytokine concentrations of 24 lung tumor and normal tissues were detected using a multiple cytokine panel. Results: Our results showed that tumors had lower microbiota diversity than the paired normal tissues, and the microbiota of NSCLC was enriched in Proteobacteria, Firmicutes, and Actinobacteria. In addition, proinflammatory cytokines such as IL‐8, MIF, TNF‐ α, and so on, were significantly upregulated in tumor tissues. Conclusion: We discovered a subset of bacteria linked to host inflammatory signaling pathways and, more precisely, to particular immune cells. We determined that lower airway microbiome dysbiosis may be linked to the disruption of the equilibrium of the immune system causing lung inflammation. The spread of lung cancer may be linked to specific bacteria. [ABSTRACT FROM AUTHOR]

Background: Detection of lung cancer at earlier stage can greatly improve patient survival. We aim to develop, validate, and implement a cost-effective ctDNA-methylation-based plasma test to aid lung cancer early detection. Methods: Case-control studies were designed to select the most relevant markers to lung cancer. Patients with lung cancer or benign lung disease and healthy individuals were recruited from different clinical centers. A multi-locus qPCR assay, LunaCAM, was developed for lung cancer alertness by ctDNA methylation. Two LunaCAM models were built for screening (-S) or diagnostic aid (-D) to favor sensitivity or specificity, respectively. The performance of the models was validated for different intended uses in clinics. Results: Profiling DNA methylation on 429 plasma samples including 209 lung cancer, 123 benign diseases and 97 healthy participants identified the top markers that detected lung cancer from benign diseases and healthy with an AUC of 0.85 and 0.95, respectively. The most effective methylation markers were verified individually in 40 tissues and 169 plasma samples to develop LunaCAM assay. Two models corresponding to different intended uses were trained with 513 plasma samples, and validated with an independent collection of 172 plasma samples. In validation, LunaCAM-S model achieved an AUC of 0.90 (95% CI: 0.88–0.94) between lung cancer and healthy individuals, whereas LunaCAM-D model stratified lung cancer from benign pulmonary diseases with an AUC of 0.81 (95% CI: 0.78–0.86). When implemented sequentially in the validation set, LunaCAM-S enables to identify 58 patients of lung cancer (90.6% sensitivity), followed by LunaCAM-D to remove 20 patients with no evidence of cancer (83.3% specificity). LunaCAM-D significantly outperformed the blood test of carcinoembryonic antigen (CEA), and the combined model can further improve the predictive power for lung cancer to an overall AUC of 0.86. Conclusions: We developed two different models by ctDNA methylation assay to sensitively detect early-stage lung cancer or specifically classify lung benign diseases. Implemented at different clinical settings, LunaCAM models has a potential to provide a facile and inexpensive avenue for early screening and diagnostic aids for lung cancer. [ABSTRACT FROM AUTHOR]

Background: The incidence rate of lung cancer in women has significantly increased over the past decade, and previous evidence has indicated a significant relationship between the elevated levels of sex hormones and the risk of lung cancer. Therefore, we hypothesized that female hormone-related cancer (FHRC) patients, including breast, endometrial, cervical, and ovarian cancer patients, may experience a higher risk of developing subsequent lung cancer. This meta-analysis aimed to identify the risk of lung cancer among FHRC patients compared to the general population., Methods: The PubMed, Web of Science, EMBASE, Cochrane Library, and CNKI databases were searched up to May 11, 2022. Standardized incidence ratios (SIRs) with 95% confidence intervals (CIs) were used to identify the risk of subsequent lung cancer after FHRC. Subgroup analyses based on the follow-up time and tumor type were also conducted., Results: A total of 58 retrospective cohort studies involving 4,360,723 FHRC participants were included. The pooled results demonstrated that FHRC patients had a significantly increased risk of developing subsequent primary lung cancer (SIR = 1.61, 95% CI: 1.48-1.76, P <0.001). Subgroup analysis revealed an obvious trend of increasing lung cancer risk over time (SIRs for <5 years, ≥5 years, ≥10 years, ≥20 years, and ≥30 years after FHRC: 1.32, 1.59, 1.57, 1.68, and 1.95, respectively). In addition, subgroup analysis stratified by tumor type indicated an increased risk of developing subsequent lung cancer after breast (SIR = 1.25, P <0.001), endometrial (SIR = 1.40, P = 0.019), cervical (SIR = 2.56, P <0.001), and ovarian cancer (SIR = 1.50, P = 0.010)., Conclusion: FHRC patients are more likely to develop lung cancer than the general population. Furthermore, the increased risk of subsequent primary lung cancer is more obvious with a longer survival time and is observed in all types of hormone-related cancer., Registration: International Platform of Registered Systematic Review and Meta-analysis Protocols: No. INPLASY202270044; https://inplasy.com/., (Copyright © 2024 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.)