Differential expression of immune-regulatory proteins C5AR1, CLEC4A and NLRP3 on peripheral blood mononuclear cells in early-stage non-small cell lung cancer patients

Differential gene expression in PBMCs: Insights into the mechanism how pulmonary tuberculosis increases lung cancer risk

Pre-existing of pulmonary tuberculosis (PTB) poses increased lung cancer risk, yet the molecular mechanisms remain inadequately understood. This study sought to elucidate the potential mechanisms by performing comprehensive analyses of differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMCs) from patients with PTB, lung adenocarcinoma (LUAD), and lung squamous cell carcinoma (LUSC). Microarray assays were employed to analyze the DEGs in PBMCs of these patients. The analyses revealed that, compared to healthy controls, the number of differentially expressed LncRNA in PBMCs from patients with PTB, LUAD, and LUSC were 801, 8,541, and 7,796, respectively. Similarly, the differentially expressed mRNA in PBMCs from patients with PTB, LUAD, and LUSC were 629, 4,865, and 4,438, respectively. These differentially expressed transcripts represent significant resources for the identifying diagnostic and differential diagnostic biomarkers for lung cancer and PTB. Pathways enriched by dysregulated mRNAs in patients with PTB, LUAD, and LUSC were identified through GO and KEGG pathway analyses. The results indicated that 9 pathways including the NOD-like receptor signaling pathway, pathways in cancer, and the MAPK signaling pathway were co-enriched across the PTB, LUAD, and LUSC groups, providing insights into the mechanisms by which PTB may increase the risk of cancer development and progression.

Validation of endoplasmic reticulum stress-related gene signature to predict prognosis and immune landscape of patients with non-small cell lung cancer

BACKGROUND

Lung cancer is one of the most common cancers worldwide, with the incidence increasing each year. It is crucial to improve the prognosis of patients who have lung cancer. Non-Small Cell Lung Cancer (NSCLC) accounts for the majority of lung cancer. Though its prognostic significance in NSCLC has not been often documented, Endoplasmic Reticulum (ER) stress has been identified to be implicated in tumour malignant behaviours and resistance to treatment.

OBJECTIVE

This work aimed to develop a gene profile linked to ER stress that could be applied to predictive and risk assessment for non-small cell lung cancer.

METHODS

Data from 1014 NSCLC patients were sourced from The Cancer Genome Atlas (TCGA) database, integrating clinical and Ribonucleic Acid (RNA) information. Diverse analytical techniques were utilized to identify ERS-associated genes associated with patients' prognoses. These techniques included Kaplan-Meier analysis, univariate Cox regression, Least Absolute Shrinkage and Selection Operator regression analysis (LASSO) regression, and Pearson correlation analysis. Using a risk score model obtained from multivariate Cox analysis, a nomogram was created and validated to classify patients into high- and low-risk groups. The study employed the CIBERSORT algorithm and Single-Sample Gene Set Eenrichment Analysis (ssGSEA) to investigate the tumour immune microenvironment. We used the Genomics of Drug Sensitivity in Cancer (GDSC) database and R tools to identify medicines that could be responsive.

RESULTS

Four genes - FABP5, C5AR1, CTSL, and LTA4H - were chosen to create the risk model. Overall Survival (OS) was considerably lower (P< 0.05) in the high-risk group. When it came to predictive accuracy, the risk model outperformed clinical considerations. Several medication types that are sensitive to high-risk groups were chosen.

CONCLUSION

Our study has produced a gene signature associated with ER stress that may be employed to forecast the prognosis and therapeutic response of non-small cell lung cancer patients.

Multi-site DNA methylation alterations of peripheral blood mononuclear cells serve as novel biomarkers for the diagnosis of AIS/stage I lung adenocarcinoma: A multi-center cohort study

BACKGROUND

Early diagnosis remains an obstacle for improving the outcome of lung adenocarcinoma (LUAD). DNA methylation changes in peripheral blood mononuclear cells (PBMCs) could reflect immune response to tumorigenesis, providing the theoretical basis for early cancer diagnosis based on immune cell profiling.

METHODS

This multi-center study evaluated the DNA methylation patterns based on PBMCs samples from 1115 individuals at nine medical centers. Genome-wide DNA methylation profiling of PBMCs in a discovery cohort (35 LUAD patients and 50 healthy controls) was performed using Illumina 850K microarray. Candidate differentially methylated CpG positions (DMPs) were selected and validated in a two-step DMPs screening cohort (65 LUAD patients and 80 healthy controls) by pyrosequencing and multiple target region methylation enrichment sequencing (MTRMES). Then, an early LUAD Diagnostic Panel (LDP score) based on multi-site methylation-specific chip-based digital PCR was constructed in a training set and then confirmed in a validation set from the LDP score development cohort (389 AIS/stage I LUAD patients and 293 healthy controls). Besides, we included 157 other cancer patients, including 52 gastric cancer (GC) patients, 50 breast cancer (BC) patients, and 55 colorectal cancer (CRC) patients to assess the specificity of LDP score. In addition, we also evaluated the early warning ability of LDP score for LUAD in a prospective cohort (46 people who were at high-risk of developing LC).

RESULTS

A total of 1415 LUAD-specific DMPs were identified. Then, six DMPs were selected for validation and three DMPs were finally verified. The LDP score was constructed by combining the three DMPs, age, and gender, and showed an AUC of 0.916, sensitivity of 88.17%, and specificity of 80.20% in combined set, outperforming traditional methods, such as CEA and CT (detection rate: 87.79% vs. 4.69%; 87.79% vs. 35.21%). This diagnostic performance was confirmed in sub-types of LUAD with clinical challenges, such as 6-20 mm LUAD (AUC: 0.914, 95%CI: 0.889-0.934) and ground-glass nodules (AUC: 0.916, 95%CI: 0.889-0.938). Importantly, our LDP score had significant improvement in terms of selecting high-risk individuals who should receive low-dose computed tomography (87.80% vs. 9.28%). Remarkably, LDP score could predict LUAD around two years before clinical diagnosis in our prospective cohort.

CONCLUSIONS

The novel developed LDP score represented a convenient and effective assay for the detection of AIS/stage I LUAD with high sensitivity and specificity, and had demonstrated unique advantages over traditional detection methods.

Causal relationships between immune cell phenotypes and lung adenocarcinoma: A bidirectional two-sample Mendelian randomization study

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and closely associated with the immune system. Emerging evidence suggests that blood immune cell phenotypes in patients with LUAD may undergo alterations. Nevertheless, the limited amount of relevant research makes it difficult to understand the causal links between LUAD and changes in the immune cells. This study aimed to reveal the potential causal relationships between 731 immune cell phenotypes and LUAD.

METHODS

A bidirectional two-sample Mendelian randomization (MR) analysis was used to clarify causal relationships. Four types of immune phenotypes, absolute cell counts, relative cell counts, median fluorescence intensities (MFIs) of surface antigens, and morphological parameters, were investigated in this study. Heterogeneity tests, horizontal pleiotropy tests, and leave-one-out analyses were performed to validate the reliability of our study.

RESULTS

A total of 26 immune cell characteristics were identified as contributing to the occurrence of LUAD. Memory B cells, IgD-CD38br cells, CD4+ regulatory T cells (Tregs), and plasmacytoid dendritic cells (DCs) may play a role in the development of LUAD. Through reverse MR, our study discovered that the presence of LUAD also induced changes in the expression levels of 16 immune cell traits involving specific surface markers and various types of immune cells, some of which pertain to antigen presentation and immune activation processes.

CONCLUSION

Our study demonstrated causal links between several immune cell phenotypes and LUAD, thereby providing indications of the potentially oncogenic physiological state and early screening biomarkers for future research.

TMErisk score: A tumor microenvironment-based model for predicting prognosis and immunotherapy in patients with head and neck squamous cell carcinoma

Tumor microenvironment (TME) is closely associated with the progression and prognosis of head and neck squamous cell carcinoma (HNSCC). To investigate potential biomarkers for predicting therapeutic outcomes in HNSCC, we analyzed the immune and stromal status of HNSCC based on the genes associated with TME using the ESTIMATE algorithm. Immune and stromal genes were identified with differential gene expression and weighted gene co-expression network analysis (WGCNA). From these genes, 118 were initially selected through Cox univariate regression and then further input into least absolute shrinkage and selection operator (LASSO) regression analysis. As a result, 11 genes were screened out for the TME-related risk (TMErisk) score model which presented promising overall survival predictive potential. The TMErisk score was negatively associated with immune and stromal scores but positively associated with tumor purity. Individuals with high TMErisk scores exhibited decreased expression of most immune checkpoints and all human leukocyte antigen family genes, and reduced abundance of infiltrating immune cells. Divergent genes were mutated in HNSCC. In both high and low TMErisk score groups, the tumor protein P53 exhibited the highest mutation frequency. A higher TMErisk score was found to be associated with reduced overall survival probability and worse outcomes of immunotherapy. Therefore, the TMErisk score could serve as a valuable model for the outcome prediction of HNSCC in clinic.

The high FKBP1A expression in WBCs as a potential screening biomarker for pancreatic cancer

Given the limitation of current routine approaches for pancreatic cancer screening and detection, the mortality rate of pancreatic cancer cases is still critical. The development of blood-based molecular biomarkers for pancreatic cancer screening and early detection which provide less-invasive, high-sensitivity, and cost-effective, is urgently needed. The goal of this study is to identify and validate the potential molecular biomarkers in white blood cells (WBCs) of pancreatic cancer patients. Gene expression profiles of pancreatic cancer patients from NCBI GEO database were analyzed by CU-DREAM. Then, mRNA expression levels of three candidate genes were determined by quantitative RT-PCR in WBCs of pancreatic cancer patients (N = 27) and healthy controls (N = 51). ROC analysis was performed to assess the performance of each candidate gene. A total of 29 upregulated genes were identified and three selected genes were performed gene expression analysis. Our results revealed high mRNA expression levels in WBCs of pancreatic cancer patients in all selected genes, including FKBP1A (p < 0.0001), PLD1 (p < 0.0001), and PSMA4 (p = 0.0002). Among candidate genes, FKBP1A mRNA expression level was remarkably increased in the pancreatic cancer samples and also in the early stage (p < 0.0001). Moreover, FKBP1A showed the greatest performance to discriminate patients with pancreatic cancer from healthy individuals than other genes with the 88.9% sensitivity, 84.3% specificity, and 90.1% accuracy. Our findings demonstrated that the alteration of FKBP1A gene in WBCs serves as a novel valuable biomarker for patients with pancreatic cancer. Detection of FKBP1A mRNA expression level in circulating WBCs, providing high-sensitive, less-invasive, and cost-effective, is simple and feasible for routine clinical setting that can be applied for pancreatic cancer screening and early detection.

Identification of biomarkers for the early detection of non-small cell lung cancer: a systematic review and meta-analysis

Lung cancer (LC) causes few symptoms in the earliest stages, leading to one of the highest mortality rates among cancers. Low-dose computerised tomography (LDCT) is used to screen high-risk individuals, reducing the mortality rate by 20%. However, LDCT results in a high number of false positives and is associated with unnecessary follow-up and cost. Biomarkers with high sensitivities and specificities could assist in the early detection of LC, especially in patients with high-risk features. Carcinoembryonic antigen (CEA), cytokeratin 19 fragments and cancer antigen 125 have been found to be highly expressed during the later stages of LC but have low sensitivity in the earliest stages. We determined the best biomarkers for the early diagnosis of LC, using a systematic review of eight databases. We identified 98 articles that focussed on the identification and assessment of diagnostic biomarkers and achieved a pooled area under curve of 0.85 (95% CI 0.82-0.088), indicating that the diagnostic performance of these biomarkers when combined was excellent. Of the studies, 30 focussed on single/antigen panels, 22 on autoantibodies, 31 on miRNA and RNA panels, and 15 suggested the use of circulating DNA combined with CEA or neuron-specific enolase (NSE) for early LC detection. Verification of blood biomarkers with high sensitivities (Ciz1, exoGCC2, ITGA2B), high specificities (CYFR21-1, antiHE4, OPNV) or both (HSP90α, CEA) along with miR-15b and miR-27b/miR-21 from sputum may improve early LC detection. Further assessment is needed using appropriate sample sizes, control groups that include patients with non-malignant conditions, and standardised cut-off levels for each biomarker.

Thymoquinone, a Novel Multi-Strike Inhibitor of Pro-Tumorigenic Breast Cancer (BC) Markers: CALR, NLRP3 Pathway and sPD-L1 in PBMCs of HR+ and TNBC Patients

Breast cancer (BC) is not only a mass of malignant cells but also a systemic inflammatory disease. BC pro-tumorigenic inflammation has been shown to promote immune evasion and provoke BC progression. The NOD-like receptor (NLR) family pyrin domain-containing protein 3 (NLRP3) inflammasome is activated when pattern recognition receptors (PRRs) sense danger signals such as calreticulin (CALR) from damaged/dying cells, leading to the secretion of interleukin-1β (IL-1β). CALR is a novel BC biological marker, and its high levels are associated with advanced tumors. NLRP3 expression is strongly correlated with an elevated proliferative index Ki67, BC progression, metastasis, and recurrence in patients with hormone receptor-positive (HR+) and triple-negative BC (TNBC). Tumor-associated macrophages (TAMs) secrete high levels of IL-1β promoting endocrine resistance in HR+ BC. Recently, an immunosuppressive soluble form of programmed death ligand 1 (sPD-L1) has been identified as a novel prognostic biomarker in triple-negative breast cancer (TNBC) patients. Interestingly, IL-1β induces sPD-L1 release. BC Patients with elevated IL-1β and sPD-L1 levels show significantly short progression-free survival. For the first time, this study aims to investigate the inhibitory impact of thymoquinone (TQ) on CALR, the NLRP3 pathway and sPD-L1 in HR+ and TNBC. Blood samples were collected from 45 patients with BC. The effect of differing TQ concentrations for different durations on the expression of CALR, NLRP3 complex components and IL-1β as well as the protein levels of sPD-L1 and IL-1β were investigated in the peripheral blood mononuclear cells (PBMCs) and TAMs of TNBC and HR+ BC patients, respectively. The findings showed that TQ significantly downregulated the expression of CALR, NLRP3 components and IL-1β together with the protein levels of secreted IL-1β and sPD-L1. The current findings demonstrated novel immunomodulatory effects of TQ, highlighting its potential role not only as an excellent adjuvant but also as a possible immunotherapeutic agent in HR+ and TNBC patients.

Identification of cell death-related biomarkers and immune infiltration in ischemic stroke between male and female patients

Background

Stroke is the second leading cause of death and the third leading cause of disability worldwide, with ischemic stroke (IS) being the most prevalent. A substantial number of irreversible brain cell death occur in the short term, leading to impairment or death in IS. Limiting the loss of brain cells is the primary therapy target and a significant clinical issue for IS therapy. Our study aims to establish the gender specificity pattern from immune cell infiltration and four kinds of cell-death perspectives to improve IS diagnosis and therapy.

Methods

Combining and standardizing two IS datasets (GSE16561 and GSE22255) from the GEO database, we used the CIBERSORT algorithm to investigate and compare the immune cell infiltration in different groups and genders. Then, ferroptosis-related differently expressed genes (FRDEGs), pyroptosis-related DEGs (PRDEGs), anoikis-related DEGs (ARDEGs), and cuproptosis-related DEGs (CRDEGs) between the IS patient group and the healthy control group were identified in men and women, respectively. Machine learning (ML) was finally used to generate the disease prediction model for cell death-related DEGs (CDRDEGs) and to screen biomarkers related to cell death involved in IS.

Results

Significant changes were observed in 4 types of immune cells in male IS patients and 10 types in female IS patients compared with healthy controls. In total, 10 FRDEGs, 11 PRDEGs, 3 ARDEGs, and 1 CRDEG were present in male IS patients, while 6 FRDEGs, 16 PRDEGs, 4 ARDEGs, and 1 CRDEG existed in female IS patients. ML techniques indicated that the best diagnostic model for both male and female patients was the support vector machine (SVM) for CDRDEG genes. SVM's feature importance analysis demonstrated that SLC2A3, MMP9, C5AR1, ACSL1, and NLRP3 were the top five feature-important CDRDEGs in male IS patients. Meanwhile, the PDK4, SCL40A1, FAR1, CD163, and CD96 displayed their overwhelming influence on female IS patients.

Conclusion

These findings contribute to a better knowledge of immune cell infiltration and their corresponding molecular mechanisms of cell death and offer distinct clinically relevant biological targets for IS patients of different genders.