Interleukin polymorphisms and protein levels associated with lung cancer susceptibility and phenotypes

Impact of IL-6 and IL-1β Gene Variants on Non-small-cell Lung Cancer Risk in Egyptian Patients

Lung cancer is a serious health and life issue, with the fastest-growing incidence and fatality rates worldwide. It is now clear that inflammation is a key factor involved in all aspects of carcinogenesis, notably lung cancer development. Genetic changes, including polymorphisms in inflammatory genes, are supposed to be a significant cause of increased lung cancer risk. The main idea of this research was to disclose the linkage between both IL-6 rs1800795 and IL-1β rs16944 variants and susceptibility to non-small-cell lung cancer (NSCLC) in Egyptians. This case-control design was composed of 127 cases and 138 controls, which were genotyped using the ARMS-PCR technique. To examine the NSCLC susceptibility under various genetic models, the odds ratio (OR) and 95% confidence intervals (CIs) were determined by logistic regression. Rs1800795 of the IL-6 gene was linked to higher odds of NSCLC under the allele model (adjusted, OR 2.28; 95% CI 1.2-4.33; p = 0.011). In the genetic models, IL-6 rs1800795 elevated the odds of NSCLC, while IL-1β rs16944 decreased the odds of NSCLC. Stratification analysis showed that IL-6 rs1800795 greatly increased the NSCLC risk in females and adenocarcinoma subtypes, whereas IL-1β rs16944 largely decreased the NSCLC risk for males, patients aged < 55, and nonsmokers. Regarding clinical data, the IL-6 variant was remarkably correlated with tumor size. This work primarily established that IL-6 and IL-1β variants have a great impact on NSCLC development in the Egyptian population; thus, it may be a supportive guide for earlier NSCLC prevention.

Identification and validation of a novel prognostic model of inflammation-related gene signature of lung adenocarcinoma

Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Time-dependent receiver operating characteristic (ROC) curve indicated the AUC of 1-, 3- and 5-years of the risk signature was 0.715, 0.719, 0.699 respectively. A prognostic nomogram was constructed by integrating risk group and clinical features. The independent dataset GSE30219 of Gene Expression Omnibus (GEO) was used for verification. We further explored the differences among risk groups in Gene set enrichment analysis (GSEA), tumor mutation and tumor microenvironment. Furthermore, Single Sample Gene Set Enrichment Analysis (ssGSEA) and the results of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) suggested the status of immune cell infiltration was highly associated with risk groups. We demonstrated the prediction effect of CTLA-4 and PD-1/PD-L1 inhibitors in the low-risk group was better than that in the high-risk group using two methods of immune score include immunophenoscore from The Cancer Immunome Atlas (TCIA) and TIDE score from Tumor Immune Dysfunction and Exclusion (TIDE). In addition, partial targeted drugs and chemotherapy drugs for lung cancer had higher drug sensitivity in the high-risk group. Our findings provide a foundation for future research targeting inflammation-related genes to predictive prognosis and some reference significance for the selection of immunotherapy and drug regimen for lung adenocarcinoma.

Prognosis value of IL-6, IL-8, and IL-1β in serum of patients with lung cancer: A fresh look at interleukins as a biomarker

Interleukins are assumed to be closely related to the occurrence and development of human malignant tumors, while a few of them were commonly used as diagnostic markers in clinical cancer, including lung cancer. This study aimed to explore the value of serum interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-8 (IL-8) combined with carcinoembryonic antigen (CEA) as biomarker panel for the diagnosis and metastasis prediction of lung cancer. IL-1β, IL-6, IL-8, and CEA in serum were determined using electrochemiluminescence immunoassay (ECLIA) and flow cytometry, and the diagnostic value of each marker was analyzed using receiver operating characteristic (ROC) curves and logistic fitting regression. We found that the levels of serum IL-1β, IL-6, and IL-8 showed no significant difference among squamous cell carcinoma, adenocarcinoma, and small cell carcinoma, while they were significantly higher in the lung cancer group or benign group than those in the healthy group. The levels of IL-8 and CEA were positively correlated with clinical stages respectively. Importantly, the panel of CEA + IL-6 + IL-8 has the highest efficacy for the diagnosis of lung cancer (AUC = 0.883) among all the detected panels, while the panel of IL-8 + CEA showed the most promising predictive value for the lymph node metastasis (AUC = 0.686) and distant metastasis of lung cancer (AUC = 0.793). In conclusion, IL-6 and IL-8 could be used as promising molecular biomarkers to diagnose and predict the metastasis of lung cancer independent of pathological types, improving the specificity and sensitivity of diagnosis for lung cancer when they were combined with CEA.

Efficacy comparison of immune treating strategies for NSCLC patients with negative PD-L1 expression

BACKGROUND

We intended to compare and grade the proposed immune treating strategies for non-small cell lung cancer (NSCLC) with negative Programmed Cell Death Ligand 1(PD-L1).

METHODS

We compared the efficacy of single immune checkpoint inhibitor (ICI), single ICI plus chemotherapy, and doublet ICIs with chemotherapy alone, as well as single ICI plus radiotherapy with single ICI for negative PD-L1 (<1%) NSCLC patients. Hazard Ratio (HR) and 95% confidence interval (CI) of progression-free survival (PFS) and overall survival (OS) were used as outcomes.

RESULTS

We included 23 randomized control trials with 4665 patients. Compared with chemotherapy alone, single ICI, single ICI plus chemotherapy and doublet ICIs all showed a better OS (0.84 [0.71, 0.99] ; 0.77 [0.69, 0.85] ; 0.64 [0.53, 0.77])), while single ICI plus chemotherapy and doublet ICIs showed a better PFS (0.68 [0.61, 0.75] ; 0.69 [0.56, 0.85]). Additionally, single ICI plus radiotherapy obtained a greater pooled PFS (0.49 [0.28-0.87]) than single ICI.

CONCLUSIONS

Both single ICI plus chemotherapy and doublet ICIs were probably better treatment decisions than chemotherapy alone for negative PD-L1 NSCLC patients. Also, single ICI plus radiotherapy carved out a new strategy.

Variants of candidate genes associated with the risk of obstructive sleep apnea

BACKGROUND

The researches on the associations between different candidate genes and obstructive sleep apnea (OSA) are inconsistent. Here, we performed a comprehensive qualitative and quantitative analysis to estimate the contribution of variants from candidate genes to the risk of OSA.

METHODS

Qualitative analysis was conducted to find the relationships for all included genes. Then, quantitative analysis of both allele models and genotype models was applied to evaluate the risk variants for OSA. Furthermore, a similar analysis was performed in different ethnic groups.

RESULTS

We included 152 publications containing 75 genes for qualitative analysis. Among them, we included 93 articles containing 28 variants from 16 genes for quantitative analysis. Through allele models, we found 10 risk variants for OSA (rs1801133 of MTHFR, ɛ4 of ApoE, -1438G/A of 5-HT2A, -308G/A of TNF-α, Pro1019Pro of LEPR, rs1130864 and rs2794521 of CRP, D/I of ACE, LPR and VNTR of 5-HTT) with the ORs of 1.21-2.07 in global population. We found that the variant of ɛ2 of ApoE could uniquely decrease the risk of OSA in the East Asian subgroup, while the other 6 variants, including ɛ4 in ApoE, -308G/A in TNF-α, Pro1019Pro in LEPR, D/I in ACE, LPR and VNTR in 5-HTT, could increase the risk of OSA. As for the European subpopulation, we only found that -308G/A in TNF-α could increase the risk for OSA.

CONCLUSIONS

Eleven variants from the candidate genes are associated with the risk of OSA, which also show ethnicity differences in East Asian and European subgroups.

High diagnostic value of miRNAs for NSCLC: quantitative analysis for both single and combined miRNAs in lung cancer

BACKGROUND

MicroRNAs (miRNAs) are good candidates as biomarkers for Lung cancer (LC). The aim of this article is to figure out the diagnostic value of both single and combined miRNAs in LC.

METHODS

Normative meta-analysis was conducted based on PRISMA. We assessed the diagnostic value by calculating the combined sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) and the area under the curve (AUC) of single and combined miRNAs for LC and specific subgroups.

RESULTS

A total of 80 qualified studies with a total of 8971 patients and 10758 controls were included. In non-small cell lung carcinoma (NSCLC), we involved 20 single-miRNAs and found their Sen, Spe and AUC ranged from 0.52-0.81, 0.66-0.88, and 0.68-0.90, respectively, specially, miR-19 with the maximum Sen, miR-20 and miR-10 with the highest Spe as well as miR-17 with the maximum AUC. Additionally, we detected miR-21 with the maximum Sen of 0.74 [95%CI: 0.62-0.83], miR-146 with the maximum Spe and AUC of 0.93 [95%CI: 0.79-0.98] and 0.89 [95%CI: 0.86-0.92] for early-stage NSCLC. We also identified the diagnostic power of available panel (miR-210, miR-31 and miR-21) for NSCLC with satisfying Sen, Spe and AUC of 0.82 [95%CI: 0.78-0.84], 0.87 [95%CI: 0.84-0.89] and 0.91 [95%CI: 0.88-0.93], and furtherly constructed 2 models for better diagnosis.

CONCLUSIONS

We identified several single miRNAs and combined groups with high diagnostic power for NSCLC through pooled quantitative analysis, which shows that specific miRNAs are good biomarker candidates for NSCLC and further researches needed.