Inverted U-Shaped relationship Between Systemic Immune-Inflammation Index and Pulmonary Function: A Large Population-Based Study in US Adults.

Background: Systemic immune-inflammation index (SII) is a novel comprehensive inflammatory marker. Inflammation is associated with impaired lung function. We aimed to explore the possible relationship between SII and lung function to examine the potential of SII in predicting lung function decline. Methods: A cross-sectional survey was conducted using the data of the NHANES from 2007 to 2012. Multiple linear regression models were used to analyze the linear relationship between SII and pulmonary functions. Sensitivity analyses, subgroup analyses, and interaction tests were used to examine the robustness of this relationship across populations. Fitted smooth curves and threshold effect analysis were used to describe the nonlinear relationships. Results: A total of 10,125 patients were included in this study. After adjusting for all covariates, multiple linear regression model analysis showed that high Log2-SII level was significantly associated with decreased FVC(ß, -23.4061; 95% CI, -42.2805- -4.5317), FEV1(ß, -46.7730; 95% CI, -63.3371- -30.2089), FEV1%(ß, -0.7923; 95% CI, -1.1635- -0.4211), FEV1/FVC(ß, -0.6366; 95% CI, -0.8328- -0.4404) and PEF(ß, -121.4468; 95% CI,-164.1939- -78.6998). The negative correlation between Log2-SII and pulmonary function indexes remained stable in trend test and stratified analysis. Inverted U-shaped relationships between Log2-SII and FVC, FEV1, FEV1%, and PEF were observed, while a negative linear correlation existed between FEV1/FVC and Log2-SII. The cutoff values of the nonlinear relationship between Log2-SII and FVC, FEV1, FEV1%, PEF were 8.3736, 8.0688, 8.3745, and 8.5255, respectively. When SII exceeded the critical value, the lung function decreased significantly. Conclusion: This study found a close correlation between SII and pulmonary function indicators. This study investigated the SII threshold when lung functions began to decline in the overall population. SII may become a promising serological indicator for predicting lung function decline. However, prospective studies were needed further to establish the causal relationship between these two factors.

STAS: New explorations and challenges for thoracic surgeons.

Spread through air spaces (STAS) represents a relatively novel concept in the pathology of lung cancer, and it specifically refers to the dissemination of tumour cells into the parenchymal air spaces adjacent to the primary tumour. In 2015, the World Health Organization (WHO) classified STAS as a new invasive form of lung adenocarcinoma (LUAD). Many studies investigated the role of STAS and revealed its association with the prognosis of LUAD and its influence on the outcomes of other malignant pulmonary neoplasms. Additionally, the underlying mechanisms and predictive models of STAS have received considerable attention in recent years. This paper provides a comprehensive overview of the research advancements and prospects of STAS by examining it from multiple perspectives.

Epidemiological and transcriptome data identify shared gene signatures and immune cell infiltration in type 2 diabetes and non-small cell lung cancer.

BACKGROUND: Numerous previous studies have reported an association between type 2 diabetes mellitus (T2DM) and lung cancer risk, but the underlying mechanism of the interaction remains unclear. This study aimed to investigate the shared genetic features and immune infiltration processes between lung cancer and T2DM. METHODS: Epidemiological data from the National Health and Nutrition Examination Survey (NHANES) 2000-2018 was used to explore the relationship between lung cancer and diabetes systematically. In addition, we also used bioinformatics methods to analyze the transcriptome data from the Gene Expression Omnibus (GEO) to explore the potential functional mechanisms from the perspective of genes and immune infiltration. RESULTS: Logistic regression analysis showed that prediabetes (OR = 3.289,95%CI 1.231, 8.788, p = 0.01760, model 3)and type 2 diabetes (OR = 3.032 95%CI,1.015, 9.054, p = 0.04689) were significantly associated with an increased risk of lung cancer after adjusting for multiple covariates. Data from NHANES showed an inverted U-shaped relationship between fasting blood glucose and glycosylated haemoglobin and the risk of lung cancer (P for non-linear < 0.001). Transcriptome data showed that we screened 57 co-DEGs, of which 25 were up-regulated co-DEGs and 32 were down-regulated. Ten core DEGs were identified by bioinformatics analysis, which were SMC6, CDC27, CDC7, RACGAP1, SMC4, NCF4, NCF1, NCF2, SELPLG and CFP. Correlation analysis showed that some core DEGs were significantly associated with simultaneous dysregulation of immune cells. CONCLUSION: The identified core genes of NSCLC and T2DM are associated with dysregulated immune cells, which provides a potential research avenue for diagnosing and treating lung cancer combined with diabetes.