Integrative Analysis Constructs an Extracellular Matrix-Associated Gene Signature for the Prediction of Survival and Tumor Immunity in Lung Adenocarcinoma

Single-cell transcriptomics reveal metastatic CLDN4+ cancer cells underlying the recurrence of malignant pleural effusion in patients with advanced non-small-cell lung cancer

BACKGROUND

Recurrent malignant pleural effusion (MPE) resulting from non-small-cell lung cancer (NSCLC) is easily refractory to conventional therapeutics and lacks predictive markers. The cellular or genetic signatures of recurrent MPE still remain largely uncertain.

METHODS

16 NSCLC patients with pleural effusions were recruited, followed by corresponding treatments based on primary tumours. Non-recurrent or recurrent MPE was determined after 3-6 weeks of treatments. The status of MPE was verified by computer tomography (CT) and cytopathology, and the baseline pleural fluids were collected for single-cell RNA sequencing (scRNA-seq). Samples were then integrated and profiled. Cellular communications and trajectories were inferred by bioinformatic algorithms. Comparative analysis was conducted and the results were further validated by quantitative polymerase chain reaction (qPCR) in a larger MPE cohort from the authors' centre (n = 64).

RESULTS

The scRNA-seq revealed that 33 590 cells were annotated as 7 major cell types and further characterized into 14 cell clusters precisely. The cell cluster C1, classified as Epithelial Cell Adhesion Molecule (EpCAM)+ metastatic cancer cell and correlated with activation of tight junction and adherence junction, was significantly enriched in the recurrent MPE group, in which Claudin-4 (CLDN4) was identified. The subset cell cluster C3 of C1, which was enriched in recurrent MPE and demonstrated a phenotype of ameboidal-type cell migration, also showed a markedly higher expression of CLDN4. Meanwhile, the expression of CLDN4 was positively correlated with E74 Like ETS Transcription Factor 3 (ELF3), EpCAM and Tumour Associated Calcium Signal Transducer 2 (TACSTD2), independent of driver-gene status. CLDN4 was also found to be associated with the expression of Hypoxia Inducible Factor 1 Subunit Alpha (HIF1A) and Vascular Endothelial Growth Factor A (VEGFA), and the cell cluster C1 was the major mediator in cellular communication of VEGFA signalling. In the extensive MPE cohort, a notably increased expression of CLDN4 in cells from pleural effusion among patients diagnosed with recurrent MPE was observed, compared with the non-recurrent group, which was also associated with a trend towards worse overall survival (OS).

CONCLUSIONS

CLDN4 could be considered as a predictive marker of recurrent MPE among patients with advanced NSCLC. Further validation for its clinical value in cohorts with larger sample size and in-depth mechanism studies on its biological function are warranted.

TRIAL REGISTRATION

Not applicable.

Six-Gene Signature for Differential Diagnosis and Therapeutic Decisions in Non-Small-Cell Lung Cancer-A Validation Study

Non-small-cell lung cancer (NSCLC) poses a challenge due to its heterogeneity, necessitating precise histopathological subtyping and prognostication for optimal treatment decision-making. Molecular markers emerge as a potential solution, overcoming the limitations of conventional methods and supporting the diagnostic-therapeutic interventions. In this study, we validated the expression of six genes (MIR205HG, KRT5, KRT6A, KRT6C, SERPINB5, and DSG3), previously identified within a 53-gene signature developed by our team, utilizing gene expression microarray technology. Real-time PCR on 140 thoroughly characterized early-stage NSCLC samples revealed substantial upregulation of all six genes in squamous cell carcinoma (SCC) compared to adenocarcinoma (ADC), regardless of clinical factors. The decision boundaries of the logistic regression model demonstrated effective separation of the relative expression levels between SCC and ADC for most genes, excluding KRT6C. Logistic regression and gradient boosting decision tree classifiers, incorporating all six validated genes, exhibited notable performance (AUC: 0.8930 and 0.8909, respectively) in distinguishing NSCLC subtypes. Nevertheless, our investigation revealed that the gene expression profiles failed to yield predictive value regarding the progression of early-stage NSCLC. Our molecular diagnostic models manifest the potential for an exhaustive molecular characterization of NSCLC, subsequently informing personalized treatment decisions and elevating the standards of clinical management and prognosis for patients.

Revealing a Novel Methylated Integrin Alpha-8 Related to Extracellular Matrix and Anoikis Resistance Using Proteomic Analysis in the Immune Microenvironment of Lung Adenocarcinoma

Genomic epigenetics of extracellular matrix (ECM) play an important role in lung adenocarcinoma (LUAD). Our study identified a signature of potential prognostic genes associated with ECM and constructed immune risk-related prognosis model in LUAD. We downloaded mRNAs transcriptome data, miRNAs expression data, and clinical patient information for LUAD based on The Cancer Genome Atlas. "Limma, clusterProfiler, ggplot2" R packages and GSEA were used to analyze meaningful genes and explore potential biological function. A competing endogenous RNA network was constructed to reveal the mechanism of ECM-related genes. Combined with clinical LUAD patients' characteristics, univariate and multivariate Cox regression analyses were used to build prognostic immune risk model. Next, we calculated AUC value of ROC curve, and explored survival probability of different risk groups. A total of 2966 mRNAs were differently expressed in LUAD samples and normal samples. Function enrichment analyses proved mRNAs were associated with many tumor pathways, such as cell adhesion, vascular smooth muscle contraction, and cell cycle. There were 18 mRNAs related to ECM receptor signaling pathway, and 7 mRNAs expressions were correlated with EGFR expression, but only 5mRNAs were associated with the long-term prognosis. Based on Integrin alpha-8 (ITGA8) molecule, we identified potential 3 miRNAs from several databases. The promoter of ITGA8 was higher-methylated and lower-expressed in LUAD. And lower-expressed group has poor prognosis for patients. 66 immunomodulators related to ITGA8 were performed to construct immune correlation prediction model (p < 0.05). Comprehensive analyses of ITGA8 revealed it combined focal adhesion kinase to activate PI3K/AKT signaling pathway to influence the occurrence and development of LUAD. A novel immune prognostic model about ITGA8 was constructed and verified in LUAD patients. Combined with non-coding genes and genomic epigenetics, identification of potential biomarkers provided new light on therapeutic strategy for clinical patients.

Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma

Background

The extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response.

Methods

Gene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD.

Results

A risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity.

Conclusion

A novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.

BTG2 and SerpinB5, a novel gene pair to evaluate the prognosis of lung adenocarcinoma

Introduction

Lung adenocarcinoma (LUAD), as the most frequent pathological subtype of non−small cell lung cancer, is often characterized by poor prognosis and low 5-year survival rate. Exploriton of new biomarkers and accurate molecular mechanisms for effectively predicting the prognosis of LUAD patients is still necessary. Presently, BTG2 and SerpinB5, which play important roles in tumors, are studied as a gene pair for the first time with the aim of exploring whether they can be used as potential prognostic markers.

Methods

Using the bioinformatics method to explore whether BTG2 and SerpinB5 can become independent prognostic factors, and explore their clinical application value and whether they can be used as immunotherapeutic markers. In addition, we also verify the conclusions obtained from external datasets, molecular docking, and SqRT-PCR.

Results

The results show that compared with normal lung tissue, BTG2 expression level was down-regulated and SerpinB5 was up-regulated in LUAD. Additionally, Kaplan–Meier survival analysis demonstrate that the prognosis of low expression level of BTG2 was poor, and that of high expression level of SerpinB5 was poor, suggesting that both of them can be used as independent prognostic factors. Moreover, the prognosis models of the two genes were constructed respectively in this study, and their prediction effect was verified by external data. Besides, ESTIMATE algorithm reveals the relationship between this gene pair and the immune microenvironment. Furthermore, patients with a high expression level of BTG2 and a low expression level of SerpinB5 have higher immunophenoscore for CTLA-4 and PD-1 inhibitors than patients with a low expression level of BTG2 and a high expression level of SerpinB5, indicating that such patients have a more obvious effect of immunotherapy.

Discussion

Collectively, all the results demonstrate that BTG2 and SerpinB5 might serve as potential prognostic biomarkers and novel therapeutic targets for LUAD.