Lung Squamous Cell Carcinoma is characterised by significant alterations in RNA expression patterns, and a lack of early symptoms and diagnosis results in poor survival rates. Our study aimed to identify the hub genes involved in LUSC by differential expression analysis and their influence on overall survival rates in patients. Thus, identifying genes with the potential to serve as biomarkers and therapeutic targets. RNA sequence data for LUSC was obtained from TCGA and analysed using R Studio. Survival analysis was performed on DE genes. PPI network and hub gene analysis was performed on survival-relevant genes. Enrichment analysis was conducted on the PPI network to elucidate the functional roles of hub genes. Our analysis identified 2774 DEGs in LUSC patient datasets. Survival analysis revealed 511 genes with a significant impact on patient survival. Among these, 20 hub genes-FN1, ACTB, HGF, PDGFRB, PTEN, SNAI1, TGFBR1, ESR1, SERPINE1, THBS1, PDGFRA, VWF, BMP2, LEP, VTN, PXN, ABL1, ITGA3 and ANXA5-were found to have lower expression levels associated with better patient survival, whereas high expression of SOX2 correlated with longer survival. Enrichment analysis indicated that these hub genes are involved in critical cellular and cancer-related pathways. Our study has identified six key hub genes that are differentially expressed and exhibit significant influence over LUSC patient survival outcomes. Further, in vitro and in vivo studies must be conducted on the key genes for their utilisation as therapeutic targets and biomarkers in LUSC.

OBJECTIVE: Twenty to thirty percent of non-small cell lung cancers (NSCLC) are caused by lung squamous cell carcinoma (LUSC), especially in smokers and there has been limited study previously evaluating the situation in terms of the genome and gene expression profile, which demonstrates the relationship among DEL-1, leucocyte recruitment, and pro-inflammatory cytokines in LUSC.
METHODS: In the current study, the m-RNA expression patterns and mutation profiles of our target genes, such as, pro-inflammatory cytokines, chemoattractant molecules, and DEL-1 genes, in 511 LUSC patients. To find the harmful mutations, the PolyPhen-2 and SNAP programs were employed. Not only gene expression was detected, but also survival analysis and correlation between DEL-1 and other target genes\' expression levels were explored too.
RESULTS: Target genes such as, DEL-1, TNF, IL-18, IL-1, CXCL8, CXCL13, and IL-6 were found to have a total genetic anomaly carrying rate of 16.4%. Seven mutations were found, and two of those mutations have a pathogenic aspect. Deep deletion and gene amplification of the genetic anomalies were also observed. According to gene expression analysis results in the LUSC patient group; DEL-1 and IL-6 levels were significantly lower than those of the control group, whereas the CXCL13 level was found to be higher.
CONCLUSIONS: Findings of the current study revealed that, there is a significant role of DEL-1 in LUSC pathogenesis. Since present study is an in silico-centered study, this approach can give more insight on experimental studies. These events may support that one of the cancer improvement mechanisms depending on DEL-1 gene at the molecular level.

OBJECTIVE: To identify biomarkers that can discriminated small cell lung cancer (SCLC) from non-SCLC (NSCLC), and explore their association with the prognosis of SCLC under chemoradiotherapy.
METHODS: The GSE40275 dataset was used to identify potential targets in SCLC. There were 196 patients of lung cancer (LC) in cohort 1 of this study. MTHFD1 levels in tissues were determined by immunohistochemistry assay in cohort 1. Lung cancer patients who were all underwent local chemoradiotherapy (CRT) were included in cohort 2, and the association of MTHFD1 levels with CRT treatment outcome were determined in cohort 2. Cell experiments were used to determine the function of MTHFD1 on the radio-sensitivity of SCLC and NSCLC cells.
RESULTS: The MTHFD1 levels in LC tissues were increased, and could discriminate SCLC from both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). Small cell lung cancer patients with MTHFD1 high phenotype had a poorer prognosis after CRT treatment, whereas no significant correlation was found between MTHFD1 levels and prognosis in LUSC and LUAD group. Cell experiments demonstrated that overexpression of MTHFD1 increases radio-resistance in both SCLC and NSCLC in vitro.
CONCLUSIONS: MTHFD1 expressions might be a novel specifically prognostic biomarker for SCLC and the CRT treatment outcome.

BACKGROUND: Dysregulation of RNA guanine-7 methyltransferase (RNMT) plays a crucial role in the tumor progression and immune responses. However, the detailed role of RNMT in pan-cancer is still unknown.
METHODS: Bulk transcriptomic data of pan-cancer were obtained from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases. Single-cell transcriptomic and proteomics data of lung squamous cell carcinoma (LUSC) were analyzed in the Tumor Immune Single-cell Hub 2 (TISCH2) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, respectively. The correlation between RNMT expression and cancer prognosis was analyzed by Cox proportional hazards regression and Kaplan-Meier analyses. The correlation of RNMT expression with common immunoregulators, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), and DNA methyltransferase (DNMT) was analyzed. Additionally, the correlation between RNMT expression and immune infiltration level was evaluated. A total of 1287 machine learning combinations were used to construct prognostic models for LUSC. qRT-PCR and Western blot were used to validate the bioinformatics findings of RNMT upregulation in LUSC.
RESULTS: RNMT was widely expressed across different cancers, with significant correlation to prognosis in cancers such as kidney chromophobe (KICH) (p = 0.0033, HR = 7.12), liver hepatocellular carcinoma (LIHC) (p = 0.01, HR = 1.41), and others. Notably, RNMT participates in the regulation of the tumor microenvironment. RNMT expression positively correlated with immune cell expression (Spearman\'s rank correlation, p < 0.05). Moreover, RNMT expression was strongly associated with immunoregulators, TMB, MSI, MMR, and DNMT in most cancer types. Notably, RNMT expression displayed excellent prognostic and immunological performance in LUSC. The expression of RNMT was mainly enriched in B cells of LUSC tissues. qRT-PCR and Western blot verified the high expression of RNMT in LUSC.
CONCLUSIONS: RNMT expression widely correlated with prognosis and immune infiltration in various tumors, especially LUSC. The RNMT detection may provide a new idea for future tumor immune studies and treatment strategies.

UNASSIGNED: Lung squamous cell carcinoma (LUSC) ranks among the carcinomas with the highest incidence and dismal survival rates, suffering from a lack of effective therapeutic strategies. Consequently, biomarkers facilitating early diagnosis of LUSC could significantly enhance patient survival. This study aims to identify novel biomarkers for LUSC.
UNASSIGNED: Utilizing the TCGA, GTEx, and CGGA databases, we focused on the gene encoding Family with Sequence Similarity 20, Member A (FAM20A) across various cancers. We then corroborated these bioinformatic predictions with clinical samples. A range of analytical tools, including Kaplan-Meier, MethSurv database, Wilcoxon rank-sum, Kruskal-Wallis tests, Gene Set Enrichment Analysis, and TIMER database, were employed to assess the diagnostic and prognostic value of FAM20A in LUSC. These tools also helped evaluate immune cell infiltration, immune checkpoint genes, DNA repair-related genes, DNA methylation, and tumor-related pathways.
UNASSIGNED: FAM20A expression was found to be significantly reduced in LUSC, correlating with lower survival rates. It exhibited a negative correlation with key proteins in DNA repair signaling pathways, potentially contributing to LUSC\'s radiotherapy resistance. Additionally, FAM20A showed a positive correlation with immune checkpoints like CTLA-4, indicating potential heightened sensitivity to immunotherapies targeting these checkpoints.
UNASSIGNED: FAM20A emerges as a promising diagnostic and prognostic biomarker for LUSC, offering potential clinical applications.

Chronic obstructive pulmonary disease (COPD) is often associated with lung squamous cell carcinoma (LUSC), which has the same etiology (smoking, inflammation, oxidative stress, microenvironmental changes, and genetics). Smoking, inflammation, and airway remodeling are the most important and classical mechanisms of COPD comorbidity in LUSC patients. Cancer can occur during repeated airway damage and repair (airway remodeling). Changes in the inflammatory and immune microenvironments, which can cause malignant transformation of some cells, are currently being revealed in both LUSC and COPD patients. We obtained the GSE76925 dataset from the Gene Expression Omnibus database. Screening for possible COPD biomarkers was performed using the LASSO regression model and a random forest classifier. The compositional patterns of the immune cell fraction in COPD patients were determined using CIBERSORT. HTR2B expression was analyzed using validation datasets (GSE47460, GSE106986, and GSE1650). HTR2B expression in COPD cell models was determined via real-time quantitative PCR. Epithelial-mesenchymal transition (EMT) marker expression levels were determined after knocking down or overexpressing HTR2B. HTR2B function and mechanism in LUSC were analyzed with the Kaplan‒Meier plotter database. HTR2B expression was inhibited to detect changes in LUSC cell proliferation. A total of 1082 differentially expressed genes (DEGs) were identified in the GSE76925 dataset (371 genes were significantly upregulated, and 711 genes were significantly downregulated). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were mainly enriched in the p53 signaling and β-alanine metabolism pathways. Gene Ontology enrichment analysis indicated that the DEGs were largely related to transcription initiation from the RNA polymerase I promoter and to the regulation of mononuclear cell proliferation. The LASSO regression model and random forest classifier results revealed that HTR2B, DPYS, FRY, and CD19 were key COPD genes. Immune cell infiltration analysis indicated that these genes were closely associated with immune cells. Analysis of the validation sets suggested that HTR2B was upregulated in COPD patients. HTR2B was significantly upregulated in COPD cell models, and its upregulation was associated with increased EMT marker expression. Compared with that in bronchial epithelial cells, HTR2B expression was upregulated in LUSC cells, and inhibiting HTR2B expression led to the inhibition of LUSC cell proliferation. In conclusions, HTR2B might be a new biomarker and therapeutic target in COPD patients with LUSC.

Although the p21-activated kinase 2 (PAK2) is an essential serine/threonine protein kinase, its role in lung squamous cell carcinoma (LUSC) progression has yet to be fully understood. We analyzed PAK2 mRNA levels and DNA copy numbers as well as protein levels by quantitative real-time PCR and immunohistochemical staining, respectively, in human LUSC tissues and adjacent normal tissues. Then, we used colony formation assays, cell counting kit-8 assays, matrigel invasion assays, wound healing assays and xenograft models in nude mice to investigate the functions of PAK2 in LUSC progression. We demonstrated that the mRNA levels, DNA copy numbers, and protein levels of PAK2 were up-regulated in human LUSC tissues than in adjacent normal tissues. In addition, a higher PAK2 expression was correlated with a poorer prognosis in LUSC patients. In the in vitro study, we found that PAK2 promoted cell growth, migration, invasion, EMT process, and cell morphology regulation in LUSC cells. Furthermore, PAK2 enhanced tumor cell proliferation, migration, and invasion by regulating actin dynamics through the LIMK1/cofilin signaling. Our findings implicated that the PAK2/LIMK1/cofilin signaling pathway is likely a potential clinical marker and therapeutic target for LUSC.

Thymus cell antigen 1 (THY1) has been proven to play pivotal roles in many diseases. However, we do not fully understand its functional mechanism, especially in lung squamous cell carcinoma (LUSC). Here, we aimed to perform a comprehensive analysis to explore the expression and prognostic values of THY1 in LUSC using bioinformatic technology. Some online public databases (e.g., ONCOMINE, PrognoScan, TIMER, Kaplan-Meier plotter, STRING, LinkedOmics, and GEPIA) were used to explore the expression, prognostic significance, and potential molecular mechanism of THY1. The analysis indicated that THY1 was significantly up-regulated and closely correlated with poor prognosis in many malignant tumors, including LUSC. Further analysis revealed that over-expression of THY1 was significantly correlated with clinicopathological parameters (e.g., individual cancer stage, age, smoking habits, nodal metastasis status, and TP53 mutation status) in LUSC. The CpG islands methylation of THY1 was negatively correlated with THY1 mRNA expression in The Cancer Genome Atlas Program (TCGA). Further enrichment analysis of THY1 correlated genes revealed that they were mainly correlated with the formation of extracellular matrix (ECM), and got involved in the pathway of epithelial mesenchymal transition (EMT). Furthermore, differentially expressed THY1 was significantly correlated with immune cell infiltrations and poor prognosis in LUSC. In summary, bioinformatic analysis demonstrated that THY1 was significantly over-expressed and closely correlated with unfavorable prognosis in LUSC, which may apply as a promising diagnostic and therapeutic biomarker for LUSC in the future.

Lung squamous cell carcinoma (LUSC) kills more than four million people yearly. Creating more trustworthy tumor molecular markers for LUSC early detection, diagnosis, prognosis, and customized treatment is essential. Cuproptosis, a novel form of cell death, opened up a new field of study for searching for trustworthy tumor indicators. Our goal was to build a risk model to assess drug sensitivity, monitor immune function, and predict prognosis in LUSC patients. The 19 cuproptosis-related genes were found in the literature, and patient genomic and clinical information was collected using the Cancer Genomic Atlas (TCGA) database. The LUSC patients were grouped using unsupervised clustering techniques, and 7626 differentially expressed genes were identified. Using univariate COX analysis, LASSO regression analysis, and multivariate COX analysis, a prognostic model for LUSC patients was developed. The tumor immune escape was evaluated using the Tumor Immune Dysfunction and Exclusion (TIDE) method. The R packages \'pRRophetic,\' \'ggpubr,\' and \'ggplot2\' were utilized to examine drug sensitivity. For modeling, a 6-cuproptosis-based gene signature was found. Patients with high-risk LUSC had significantly worse survival rates than those with low-risk conditions. The possibility of tumor immunological escape was increased in patients with higher risk scores due to more immune cell inactivation. For patients with high-risk LUSC, we discovered seven potent potential drugs (AZD6482, CHIR.99021, CMK, Embelin, FTI.277, Imatinib, and Pazopanib). In conclusion, the cuproptosis-based genes predictive risk model can be utilized to predict outcomes, track immune function, and evaluate medication sensitivity in LUSC patients.

BACKGROUND: Lung squamous cell carcinoma (LUSC) is associated with high mortality and has limited therapeutic treatment options. Plasminogen activator urokinase (PLAU) plays important roles in tumor cell malignancy. However, the oncogenic role of PLAU in the progression of LUSC remains unknown. GATA-binding factor 6 (GATA6), a key regulator of lung development, inhibits LUSC cell proliferation and migration, but the underlying regulatory mechanism remains to be further explored. Moreover, the regulatory effect of GATA6 on PLAU expression has not been reported. The aim of this study was to identify the role of PLAU and the transcriptional inhibition mechanism of GATA6 on PLAU expression in LUSC.
METHODS: To identify the potential target genes regulated by GATA6, differentially expressed genes (DEGs) obtained from GEO datasets analysis and RNA-seq experiment were subjected to Venn analysis and correlation heatmap analysis. The transcriptional regulatory effects of GATA6 on PLAU expression were detected by real-time PCR, immunoblotting, and dual-luciferase reporter assays. The oncogenic effects of PLAU on LUSC cell proliferation and migration were evaluated by EdU incorporation, Matrigel 3D culture and Transwell assays. PLAU expression was detected in tissue microarray of LUSC via immunohistochemistry (IHC) assay. To determine prognostic factors for prognosis of LUSC patients, the clinicopathological characteristics and PLAU expression were subjected to univariate Cox regression analysis.
RESULTS: PLAU overexpression promoted LUSC cell proliferation and migration. PLAU is overexpressed in LUSC tissues compared with normal tissues. Consistently, high PLAU expression, which acts as an independent risk factor, is associated with poor prognosis of LUSC patients. Furthermore, the expression of PLAU is transcriptionally regulated by GATA6.
CONCLUSIONS: In this work, it was revealed that PLAU is a novel oncogene for LUSC and a new molecular regulatory mechanism of GATA6 in LUSC was unveiled. Targeting the GATA6/PLAU pathway might help in the development of novel therapeutic treatment strategies for LUSC.