Lung Squamous Cell Carcinoma Cohort Research Articles

Characterization of prognostic signature related with twelve types of programmed cell death in lung squamous cell carcinoma

ObjectiveThis study aimed to develop a prognostic cell death index (CDI) based on the expression of genes related with various types of programmed cell death (PCD), and to assess its clinical relevance in lung squamous cell carcinoma (LUSC).MethodsPCD-related genes were gathered and analyzed in silico using the transcriptomic data from the LUSC cohorts of The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Differentially expressed PCD genes were analyzed, and a prognostic model was subsequently constructed. CDI scores were calculated for each patient, and their correlations with clinical features, survival outcomes, tumor mutation burden, gene clusters, and tumor microenvironment were investigated. Unsupervised consensus clustering was performed based on CDI model genes. Furthermore, the correlation of CDI for sensitivity of targeted drugs, chemotherapy efficacy, and immunotherapy responses was assessed.ResultsBased on 351 differentially expressed PCD genes in LUSC, a CDI signature comprising FGA, GAB2, JUN, and CDKN2A was identified. High CDI scores were significantly associated with poor survival outcomes (p < 0.05). Unsupervised clustering revealed three distinct patient subsets with varying survival rates. CDKN2A exhibited significantly different mutation patterns between patients with high and low CDI scores (p < 0.01). High CDI scores were also linked to increased immune cell infiltration of specific subsets and altered expression of immune-related genes. Patients with high-CDI showed reduced sensitivity to several chemotherapeutic drugs and a higher Tumor Immune Dysfunction and Exclusion (TIDE) score, indicating potential resistance to immunotherapy.ConclusionThe CDI signature based on PCD genes offers valuable prognostic insights into LUSC, reflecting molecular heterogeneity, immune microenvironment associations, and potential therapeutic challenges. The CDI holds potential clinical utility in predicting treatment responses and guiding the selection of appropriate therapies for patients with LUSC. Future studies are warranted to further validate the prognostic value of CDI in combination with clinical factors and to explore its application across diverse patient cohorts.

Pyroptosis-related long-noncoding RNA signature predicting survival and immunotherapy efficacy in patients with lung squamous cell carcinoma

Pyroptosis-related long-noncoding RNAs (PRlncRNAs) play an important role in cancer progression. However, their role in lung squamous cell carcinoma (LUSC) is unclear. A risk model was constructed using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis based on RNA sequencing data from The Cancer Genome Atlas database. The LUSC cohort was divided into high- and low-risk groups based on the median risk score. For the prognostic value of the model, the Kaplan–Meier analysis, log-rank test, and Cox regression analysis were performed. A nomogram was constructed to predict the prognosis of patients, using a risk score and clinical parameters such as age, sex, clinical stage, and tumor node metastasis classification (TNM) stage. Afterwards, six common algorithms were employed to assess the invasion of immune cells. The Gene Set Enrichment Analysis (GSEA) was conducted to identify differences between patients at high and low risk. Furthermore, the pRRophetic package was employed to forecast the half-maximal inhibitory doses of prevalent chemotherapeutic drugs, while the tumor immune dysfunction and exclusion score was computed to anticipate the response to immunotherapy. The expression levels of the seven PRlncRNAs were examined in both LUSC and normal lung epithelial cell lines using RT-qPCR. Proliferation, migration, and invasion assays were also carried out to investigate the role of MIR193BHG in LUSC cells. Patients in the low-risk group showed prolonged survival in the total cohort or subgroup analysis. The Cox regression analysis showed that the risk model could act as an independent prognostic factor for patients with LUSC. The results of GSEA analysis revealed that the high-risk group showed enrichment of cytokine pathways, Janus tyrosine kinase/signal transducer and activator of the transcription signalling pathway, and Toll-like receptor pathway. Conversely, the low-risk group showed enrichment of several gene repair pathways. Furthermore, the risk score was positively correlated with immune cell infiltration. Moreover, patients in the high-risk category showed reduced responsiveness to conventional chemotherapeutic medications and immunotherapy. The majority of the long noncoding RNAs in the risk model were confirmed to be overexpressed in LUSC cell lines compared to normal lung epithelial cell lines by in vitro tests. Further studies have shown that downregulating the expression of MIR193BHG may inhibit the growth, movement, and infiltration capabilities of LUSC cells, whereas increasing the expression of MIR193BHG could enhance these malignant tendencies. This study found that PRlncRNAs were linked to the prognosis of LUSC patients. The risk model, evaluated across various clinical parameters and treatment modalities, shows potential as a future reference for clinical applications.

Ensartinib in the treatment of anaplastic lymphoma kinase-positive locally advanced or metastatic patients with lung squamous or adenosquamous carcinoma: A real-world, retrospective study.

To report the efficacy and safety of ensartinib, an anaplastic lymphoma kinase (ALK) inhibitor, in treating patients with ALK-positive advanced lung squamous cell carcinoma (LUSC) or lung adenosquamous carcinoma (LASC) in China. This retrospective study analyzed data for 36 advanced-stage patients with ALK-positive LUSC (cohort A) and 13 patients with ALK-positive LASC (cohort B) between December 16, 2020 and December 16, 2021. All patients received once-daily ensartinib 225mg. Outcome analysis included the demographic characteristics, tumor response, progression-free survival (PFS), and treatment-related adverse events (TRAE). Among the 49 patients, the majority were under 65 years old (73.5%), non-smokers (85.7%), had an Eastern Cooperative Oncology Group Performance Status of 0-1 (77.6%), and were at stage IV (71.4%). All patients were included in the efficacy and safety analysis. Seven PFS events were reported in cohort A while no patients experienced PFS events in cohort B. The median PFS was not estimable for both cohorts. In cohort A, the objective response rate (ORR) was 63.9%, and the disease control rate (DCR) was 83.3%. In the cohort B, the ORR was 76.9% and the DCR was 100.0%. Rash was the only TRAE reported in the cohort A (8.3%) and cohort B (23.1%). No patients had grade 3 or higher TRAE. Ensartinib has been tentatively proven favorable efficacy and tolerability in the treatment of patients with ALK-positive advanced LUSC or LASC in the real-world. However, confirmatory studies are still needed in larger sample sizes.

Identification of SLC2A1 as a predictive biomarker for survival and response to immunotherapy in lung squamous cell carcinoma

BackgroundAs one of the common subtypes of non-small lung cancer, lung squamous cell carcinoma (LUSC) patients with advanced stage have few choices of treatment strategies. Therefore, it is urgent to discover genes that are associated with the survival and efficacy of immunotherapies. MethodDifferential gene expression analyses were conducted using TCGA LUSC bulk-sequencing and single-cell RNA-sequencing data. Prognostic genes were identified from the TCGA LUSC cohort. Protein expression validation and survival analyses were performed. Experiments were conducted to explore the underlying mechanisms. In addition, the correlation between gene expression and pathological response to adjuvant immunochemotherapy was also investigated. ResultsAfter a series of bioinformatic analyses, solute carrier family 2 member 1(SLC2A1), encoding glucose transporter-1 (GLUT1), was found to be differentially expressed between tumor and normal tissues. GLUT1 was subsequently identified as an independent prognostic factor for LUSC. GSEA analysis revealed the glycolysis metabolism pathway of KEGG enriched in SLC2A1high tumor tissues. LASSO analyses revealed that tumor tissues with high expression of SLC2A1 were associated with high levels of protein lactylation. We found that SLC2A1 was preferentially expressed by SPP1+ macrophages in the tumor microenvironment, and the expression of SLC2A1 was associated with the abundance of SPP1+ macrophages. Immunofluorescence demonstrated GLUT1 and HIF1α colocalization in tumor-infiltrating macrophages. In vitro experiments showed HIF-1α-induced macrophage polarization under hypoxia, and GLUT1 inhibition blocked this polarization. In addition, SLC2A1 was negatively associated with the common immune checkpoint molecules, such as programmed cell death 1(PD-1), T cell immunoreceptor with Ig and ITIM domains (TIGIT), cytotoxic T-lymphocyte associated protein 4 (CTLA4) and lymphocyte activating 3 (LAG3), while showed a positive association with CD44. Finally, we observed that there was a significant correlation between pre-adjuvant-treatment GLUT1 expression and the pathological response. ConclusionSLC2A1 expression was differentially upregulated in tumor tissues, and elevated GLUT1 expression was associated with worse survival and poor pathological response to adjuvant immunochemotherapy. Upregulation of GLUT1 promoted macrophage polarization into the M2 phenotype. The findings will contribute to guiding the treatment selection for LUSC patients and providing personalized immunotherapy strategies.

High FLT3 expression increases immune-cell infiltration in the tumor microenvironment and correlates with prolonged disease-free survival in patients with non-small cell lung cancer.

Most of the currently used cancer immunotherapies inhibit the programmed cell death protein 1 (PD1)-programmed cell death 1 ligand 1 (PDL1) axis of T-cells. However, dendritic cells (DCs) controlled by natural killer (NK) cells via the FMS-related tyrosine kinase 3 (FLT3) axis are necessary for activation of T-cells. The aim of the study was to evaluate FLT3 as a prognostic factor and determine its role in immune infiltration (with emphasis on NK cells and DCs). Using The Cancer Genome Atlas (TCGA) database, we performed bioinformatic analysis of the gene expression datasets of 501 lung squamous cell carcinoma (LUSC) and 515 lung adenocarcinoma (LUAD) patient who had corresponding clinical data [analysis was performed in R (version 4.2.0)]. Disease-free survival (DFS) differed between the FLT3-low and FLT3-high expression groups, respectively, in LUSC (61.0 vs 71.3 months P = 0.075) and LUAD (32.7 vs 47.5 months P = 0.045). A tumor microenvironment (TME) with high immune infiltration and rich in T-cell exhaustion markers was observed in the FLT3-high group. We showed overexpression of NK cell and DC gene signatures in the FLT3-high expression group as well as overexpression of key effector genes of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes protein (STING) pathway, which is crucial in response to radiotherapy. High expression of FLT3 in the TME was associated with immune cell infiltration (especially of NK cells and DCs), increased expression of T-cell exhaustion markers and expression of effector genes of the cGAS-STING pathway, which may consequently increase susceptibility to immunotherapy and radiotherapy. High FLT3 expression correlated with prolonged DFS in the LUSC and LUAD cohorts.

Tumor-derived KLK8 predicts inferior survival and promotes an immune-suppressive tumor microenvironment in lung squamous cell carcinoma

Lung squamous cell carcinoma (LUSC) is the second most common lung cancer worldwide, leading to millions of deaths annually. Although immunotherapy has expanded the therapeutic choices for LUSC and achieved considerable efficacy in a subset of patients, many patients could not benefit, and resistance was pervasive. Therefore, it is significant to investigate the mechanisms leading to patients’ poor response to immunotherapies and explore novel therapeutic targets. Using multiple public LUSC datasets, we found that Kallikrein-8 (KLK8) expression was higher in tumor samples and was correlated with inferior survival. Using a LUSC cohort (n = 190) from our center, we validated the bioinformatic findings about KLK8 and identified high KLK8 expression as an independent risk factor for LUSC. Function enrichment showed that several immune signaling pathways were upregulated in the KLK8 low-expression group and downregulated in the KLK8 high-expression group. For patients with low KLK8 expression, they were with a more active TME, which was both observed in the TCGA database and immune marker immunohistochemistry, and they had extensive positive relations with immune cells with tumor-eliminating functions. This study identified KLK8 as a risk factor in LUSC and illustrated the associations between KLK8 and cancer immunity, suggesting the potentiality of KLK8 as a novel immune target in LUSC.

Prediction of Tumor Microenvironment Characteristics and Treatment Response in Lung Squamous Cell Carcinoma by Pseudogene OR7E47P-related Immune Genes.

Pseudogenes are initially regarded as nonfunctional genomic sequences, but some pseudogenes regulate tumor initiation and progression by interacting with other genes to modulate their transcriptional activities. Olfactory receptor family 7 subfamily E member 47 pseudogene (OR7E47P) is expressed broadly in lung tissues and has been identified as a positive regulator in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD). This study aimed to elucidate the correlation between OR7E47P and tumor immunity in lung squamous cell carcinoma (LUSC). Clinical and molecular information from The Cancer Genome Atlas (TCGA) LUSC cohort was used to identify OR7E47P-related immune genes (ORIGs) by weighted gene correlation network analysis (WGCNA). Based on the ORIGs, 2 OR7E47P clusters were identified using non-negative matrix factorization (NMF) clustering, and the stability of the clustering was tested by an extreme gradient boosting classifier (XGBoost). LASSO-Cox and stepwise regressions were applied to further select prognostic ORIGs and to construct a predictive model (ORPScore) for immunotherapy. The Botling cohorts and 8 immunotherapy cohorts (the Samstein, Braun, Jung, Gide, IMvigor210, Lauss, Van Allen, and Cho cohorts) were included as independent validation cohorts. OR7E47P expression was positively correlated with immune cell infiltration and enrichment of immune-related pathways in LUSC. A total of 57 ORIGs were identified to classify the patients into 2 OR7E47P clusters (Cluster 1 and Cluster 2) with distinct immune, mutation, and stromal programs. Compared to Cluster 1, Cluster 2 had more infiltration by immune and stromal cells, lower mutation rates of driver genes, and higher expression of immune-related proteins. The clustering performed well in the internal and 5 external validation cohorts. Based on the 7 ORIGs (HOPX, STX2, WFS, DUSP22, SLFN13, GGCT, and CCSER2), the ORPScore was constructed to predict the prognosis and the treatment response. In addition, the ORPScore was a better prognostic factor and correlated positively with the immunotherapeutic response in cancer patients. The area under the curve values ranged from 0.584 to 0.805 in the 6 independent immunotherapy cohorts. Our study suggests a significant correlation between OR7E47P and TME modulation in LUSC. ORIGs can be applied to molecularly stratify patients, and the ORPScore may serve as a biomarker for clinical decision-making regarding individualized prognostication and immunotherapy.

Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma

Molecular subtyping of lung squamous cell carcinoma (LUSC) has been performed at the genomic, transcriptomic, and proteomic level. However, LUSC stratification based on tissue metabolomics is still lacking. Combining high-mass-resolution imaging mass spectrometry with consensus clustering, four tumor- and four stroma-specific subtypes with distinct metabolite patterns were identified in 330 LUSC patients. The first tumor subtype T1 negatively correlated with DNA damage and immunological features including CD3, CD8, and PD-L1. The same features positively correlated with the tumor subtype T2. Tumor subtype T4 was associated with high PD-L1 expression. Compared with the status of subtypes T1 and T4, patients with subtype T3 had improved prognosis, and T3 was an independent prognostic factor with regard to UICC stage. Similarly, stroma subtypes were linked to distinct immunological features and metabolic pathways. Stroma subtype S4 had a better prognosis than S2. Subsequently, analyses based on an independent LUSC cohort treated by neoadjuvant therapy revealed that the S2 stroma subtype was associated with chemotherapy resistance. Clinically relevant patient subtypes as determined by tissue-based spatial metabolomics are a valuable addition to existing molecular classification systems. Metabolic differences among the subtypes and their associations with immunological features may contribute to the improvement of personalized therapy.

Carbonic Anhydrase 4 Serves as A Novel Prognostic Biomarker and Therapeutic Target for Non-Small Cell Lung Cancer: A Study Based on TCGA Samples.

Carbonic anhydrase 4 (CA4) is a member of a large family of zinc metalloenzymes that catalyze the reversible hydration of carbon dioxide and was found to have low expression in non-small cell lung cancer (NSCLC). However, the specific role of CA4 in NSCLC and the underlying mechanisms remain unknown. The bioinformatic analysis on lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) datasets downloaded from The Cancer Genome Atlas (TCGA) database was performed. We found that CA4 expression was lower in tumors than that in normal tissues, which were verified by Real-time PCR. Lower CA4 levels were significantly associated with higher T stages in LUAD and LUSC cohorts. Multivariate analysis showed that CA4 is an independent prognostic factor for NSCLC. Furthermore, the expression of CA4 also correlated with immune infiltration and drug sensitivity. Ectopic expression of CA4 decreased NSCLC cell proliferation in vitro by CCK-8 assay. CA4 caused G0/G1 cell cycle arrest by cell experiments. Mechanistic studies found that CA affects the cell cycle and inhibits cell proliferation by downregulating the expression of CDK2. The present findings highlight the role of CA4 in NSCLC and identify CA4 as a potential novel diagnostic and prognostic biomarker for the treatment of NSCLC.

Integrative multiomics and weighted network approach reveals the prognostic role of RPS7 in lung squamous cell carcinoma pathogenesis.

Lung cancer is one of the most commonly occurring malignant cancers with the highest rate of mortality globally. Difference between lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) and their treatment strategies according to genetic markers may be helpful in reducing the cancer progression and increasing the overall survival (OS) in patients. LUSC is known for comparatively less typical onco-drivers, target therapy resistance, marked genomic complexity, and a reasonably higher mutation rate. The mRNA-seq data and clinical information of LUAD and LUSC cohorts from UCSC Xena comprising 437 and 379 patient samples were extracted. Differential expression and weighted network analyses revealed 47 and 18 hub differentially expressed genes (DEGs) corresponding to LUAD and LUSC cohorts. These hub DEGs were further subjected to protein-protein interaction network (PPIN) and OS analyses. Lower mRNA expression levels of both RPS15A and RPS7 worsened the OS of LUSC patients. Additionally, both these prognostic biomarkers were validated via external sources such as UALCAN, cBioPortal, TIMER, and HPA. RPS7 had higher mutation frequency compared to RPS15A and showed significant negative correlations with infiltrating levels of CD4+ T cells, CD8+ T cells, neutrophils, and macrophages. Our findings provided novel insights into biomarker discovery and the critical role of ribosomal biogenesis especially smaller ribosomal subunit in pathogenesis of LUSC.

Five-hub genes identify potential mechanisms for the progression of asthma to lung cancer.

Previous studies have shown that asthma is a risk factor for lung cancer, while the mechanisms involved remain unclear. We attempted to further explore the association between asthma and non-small cell lung cancer (NSCLC) via bioinformatics analysis. We obtained GSE143303 and GSE18842 from the GEO database. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) groups were downloaded from the TCGA database. Based on the results of differentially expressed genes (DEGs) between asthma and NSCLC, we determined common DEGs by constructing a Venn diagram. Enrichment analysis was used to explore the common pathways of asthma and NSCLC. A protein-protein interaction (PPI) network was constructed to screen hub genes. KM survival analysis was performed to screen prognostic genes in the LUAD and LUSC groups. A Cox model was constructed based on hub genes and validated internally and externally. Tumor Immune Estimation Resource (TIMER) was used to evaluate the association of prognostic gene models with the tumor microenvironment (TME) and immune cell infiltration. Nomogram model was constructed by combining prognostic genes and clinical features. 114 common DEGs were obtained based on asthma and NSCLC data, and enrichment analysis showed that significant enrichment pathways mainly focused on inflammatory pathways. Screening of 5 hub genes as a key prognostic gene model for asthma progression to LUAD, and internal and external validation led to consistent conclusions. In addition, the risk score of the 5 hub genes could be used as a tool to assess the TME and immune cell infiltration. The nomogram model constructed by combining the 5 hub genes with clinical features was accurate for LUAD. Five-hub genes enrich our understanding of the potential mechanisms by which asthma contributes to the increased risk of lung cancer.

Transcriptomic FHITlow/pHER2high signature as a predictive factor of outcome and immunotherapy response in non-small cell lung cancer.

In recent decades, the development of immunotherapy and targeted therapies has considerably improved the outcome of non-small cell lung cancer (NSCLC) patients. Despite these impressive clinical benefits, new biomarkers are needed for an accurate stratification of NSCLC patients and a more personalized management. We recently showed that the tumor suppressor fragile histidine triad (FHIT), frequently lost in NSCLC, controls HER2 receptor activity in lung tumor cells and that tumor cells from NSCLC patients harboring a FHITlow/pHER2high phenotype are sensitive to anti-HER2 drugs. Here, we sought to identify the transcriptomic signature of this phenotype and evaluate its clinical significance. We performed RNA sequencing analysis on tumor cells isolated from NSCLC (n=12) according to FHIT/pHER2 status and a functional analysis of differentially regulated genes. We also investigated the FHITlow/pHER2high signature in The Cancer Genome Atlas (TCGA) lung adenocarcinoma (LUAD) (n=489) and lung squamous cell carcinoma (LUSC) (n=493) cohorts and used the tumor immune dysfunction and exclusion (TIDE) model to test the ability of this signature to predict response to immune checkpoint inhibitors (ICI). We showed that up-regulated genes in FHITlow/pHER2high tumors were associated with cell proliferation, metabolism and metastasis, whereas down-regulated genes were related to immune response. The FHITlow/pHER2high signature was associated with the higher size of tumors, lymph node involvement, and late TNM stages in LUAD and LUSC cohorts. It was identified as an independent predictor of overall survival (OS) in LUAD cohort. FHITlow/pHER2high tumors were also predictive of poor response to ICI in both LUAD and LUSC cohorts. These data suggest that ICI might not be a relevant option for NSCLC patients with FHITlow/pHER2high tumors and that anti-HER2 targeted therapy could be a good therapeutic alternative for this molecular subclass with poorer prognosis.

Prediction of lung squamous cell carcinoma immune microenvironment and immunotherapy efficiency with pyroptosis-derived genes.

Lung squamous cell carcinoma (LUSC) is a common subtype of lung cancer that exhibits diverse pyroptosis regulatory patterns. Studies have highlighted the significance of pyroptosis in cancer invasion and immune responses. We aimed to explore the signatures of pyroptosis-related genes and their immune relevance in LUSC. Using The Cancer Genome Atlas (TCGA)-LUSC cohort and 5 gene expression omnibus (GEO) datasets, we performed consensus clustering based on 41 pyroptosis-related genes, and single sample gene set enrichment analysis (ssGSEA) was employed to calculate the infiltration levels of distinct clusters. A pyroptosis scoring scheme using the principal component analysis (PCA) method was used to quantify pyroptosis regulation in patients with LUSC and predict their prognosis. Four pyroptosis clusters were identified among 833 LUSC samples, which were associated with different Kyoto encyclopedia of genes and genome (KEGG) signaling pathways and tumor microenvironment infiltration features, and were highly consistent with 4 reported immune phenotypes: immune-responsive, immune-non-functional, immune-exclusion, and immune-ignorance. We then divided the patients into high- and low-pyroptosis score subgroups, and patients with higher scores were characterized by prolonged survival and attenuated immune infiltration. Moreover, higher scores were correlated with male patients, higher microsatellite instability, lower immune checkpoint inhibitor expression (such as CTLA-4 and GAL-9), and high mutation rates of typical mutated genes (e.g., TP53 and TTN). In particular, patients with lower pyroptosis scores showed better immune response to immune checkpoint inhibitor treatment. Pyroptosis regulatory patterns in the immune microenvironment can predict the clinical outcomes of patients with LUSC. Accurately quantifying the pyroptosis of individual patients will strengthen the understanding of heterogeneity within the LUSC tumor microenvironment infiltration areas.

Transcriptome Analysis of Human Endogenous Retroviruses at Locus-Specific Resolution in Non-Small Cell Lung Cancer.

Simple SummaryLung cancer is the leading cause of cancer deaths worldwide. Most lung cancer patients are diagnosed with locally advanced or metastatic diseases, and their prognosis is relatively poor, with 5-year survival rates ranging from 4 to 17%. Consequently, the identification of novel diagnostic lung cancer biomarkers remains crucial. Recently, human endogenous retroviruses (HERVs) have been found to be implicated in cancer development and later employed as novel diagnostic and prognostic cancer biomarkers. In this study, we present the first-ever locus-specific analysis of HERV expression in 515 lung adenocarcinoma (LUAD) and 497 lung squamous cell carcinoma (LUSC) patients’ samples from the TCGA repository. In our study, we identified the differentially expressed HERVs in both TCGA-LUAD and TCGA-LUSC cohorts, we examined their impact on signaling pathways using in silico models, and we described HERVs’ association with overall survival (OS) and relapse-free survival (RFS).Lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer deaths worldwide. Among its subtypes, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the most common, accounting for more than 85% of lung cancer diagnoses. Despite the incredible efforts and recent advances in lung cancer treatments, patients affected by this condition still have a poor prognosis. Therefore, novel diagnostic biomarkers are needed. Recently, a class of transposable elements called human endogenous retroviruses (HERVs) has been found to be implicated in cancer development and later employed as novel biomarkers for several tumor types. In this study, we first ever characterized the expression of HERVs at genomic locus-specific resolution in both LUAD and LUSC cohorts available in The Cancer Genome Atlas (TCGA). Precisely, (i) we profiled the expression of HERVs in TCGA-LUAD and TCGA-LUSC cohorts; (ii) we identified the dysregulated HERVs in both lung cancer subtypes; (iii) we evaluated the impact of the dysregulated HERVs on signaling pathways using neural network-based predictions; and (iv) we assessed their association with overall survival (OS) and relapse-free survival (RFS). In conclusion, we believe this study may help elucidate another layer of dysregulation that occurs in lung cancer involving HERVs, paving the way for identifying novel lung cancer biomarkers.

Construction of a predictive model for immunotherapy efficacy in lung squamous cell carcinoma based on the degree of tumor-infiltrating immune cells and molecular typing

BackgroundTo construct a predictive model of immunotherapy efficacy for patients with lung squamous cell carcinoma (LUSC) based on the degree of tumor-infiltrating immune cells (TIIC) in the tumor microenvironment (TME).MethodsThe data of 501 patients with LUSC in the TCGA database were used as a training set, and grouped using non-negative matrix factorization (NMF) based on the degree of TIIC assessed by single-sample gene set enrichment analysis (GSEA). Two data sets (GSE126044 and GSE135222) were used as validation sets. Genes screened for modeling by least absolute shrinkage and selection operator (LASSO) regression and used to construct a model based on immunophenotyping score (IPTS). RNA extraction and qPCR were performed to validate the prognostic value of IPTS in our independent LUSC cohort. The receiver operating characteristic (ROC) curve was constructed to determine the predictive value of the immune efficacy. Kaplan–Meier survival curve analysis was performed to evaluate the prognostic predictive ability. Correlation analysis and enrichment analysis were used to explore the potential mechanism of IPTS molecular typing involved in predicting the immunotherapy efficacy for patients with LUSC.ResultsThe training set was divided into a low immune cell infiltration type (C1) and a high immune cell infiltration type (C2) by NMF typing, and the IPTS molecular typing based on the 17-gene model could replace the results of the NMF typing. The area under the ROC curve (AUC) was 0.82. In both validation sets, the IPTS of patients who responded to immunotherapy were significantly higher than those who did not respond to immunotherapy (P = 0.0032 and P = 0.0451), whereas the AUC was 0.95 (95% CI = 1.00–0.84) and 0.77 (95% CI = 0.58–0.96), respectively. In our independent cohort, we validated its ability to predict the response to cancer immunotherapy, for the AUC was 0.88 (95% CI = 1.00–0.66). GSEA suggested that the high IPTS group was mainly involved in immune-related signaling pathways.ConclusionsIPTS molecular typing based on the degree of TIIC in the TME could well predict the efficacy of immunotherapy in patients with LUSC with a certain prognostic value.

Comprehensive analysis of molecular features, prognostic values, and immune landscape association of m6A-regulated immune-related lncRNAs in smoking-associated lung squamous cell carcinoma.

Lung squamous cell carcinoma (LUSC) is the second most common histopathological subtype of lung cancer, and smoking is the leading cause of this type of cancer. However, the critical factors that directly affect the survival rate and sensitivity to immunotherapy of smoking LUSC patients are still unknown. Previous studies have highlighted the role of N6-methyladenosine (m6A) RNA modification, the most common epigenetic modification in eukaryotic species, together with immune-related long non-coding RNAs (lncRNAs) in promoting the development and progression of tumors. Thus, elucidating m6A-modified immune lncRNAs in LUSC patients with smoking history is vital. In this study, we described the expression and mutation features of the 24 m6A-related regulators in the smoking-associated LUSC cohort from The Cancer Genome Atlas (TCGA) database. Then, two distinct subtypes based on the expression levels of the prognostic m6A-regulated immune lncRNAs were defined, and differentially expressed genes (DEGs) between the subtypes were identified. The distributions of clinical characteristics and the tumor microenvironment (TME) between clusters were analyzed. Finally, we established a lncRNA-associated risk model and exhaustively clarified the clinical features, prognosis, immune landscape, and drug sensitivity on the basis of this scoring system. Our findings give insight into potential mechanisms of LUSC tumorigenesis and development and provide new ideas in offering LUSC patients with individual and effective immunotherapies.

TP53 and LRP1B Co-Wild Predicts Improved Survival for Patients with LUSC Receiving Anti-PD-L1 Immunotherapy.

Simple SummaryImmune checkpoint inhibitors (ICIs) changed the standard care of patients with lung squamous cell carcinoma (LUSC). It is an urgent need to precisely predict the population’s response to ICIs. The aim of the study was to explore novel biomarkers for LUSC immunotherapy and the potential mechanism. Five hundred and twenty-five Chinese patients with LUSC who underwent targeted sequencing were involved, and TP53 and LRP1B were the genes most frequently correlated to tumor mutational burden (TMB). Further analysis demonstrated that TP53/LRP1B co-wild was associated with improved survival of immunotherapy. Compared with those with TP53/LRP1B mutant, patients with TP53/LRP1B co-wild had lower TMB and chromosome instability, while stronger cytotoxic immune cell infiltrations, which might be the reason for the better clinical outcomes of immunotherapy. These results indicated that TP53/LRP1B co-wild might be regarded as a potential biomarker for guiding anti-PD-L1 immunotherapy in LUSC.Immunotherapy brought long-term benefits for partial patients with lung squamous cell carcinoma (LUSC). The predictor of anti-PD-L1 therapy was controversial and limited in LUSC. We aimed to explore novel biomarker for LUSC immunotherapy and the potential mechanism. Five hundred and twenty-five Chinese patients (Geneplus cohort) with LUSC underwent targeted sequencing and were involved to explore the genomic profiling. TP53 and LRP1B were the most frequently recurrent genes and correlated to higher tumor mutational burden (TMB). We observed that LUSC patients with TP53 and LRP1B co-wild (co-wild type) were associated with better survival of anti-PD-L1 therapy compared with TP53 mutant or LRP1B mutant (mutant type) in POPAR/OAK cohort. Copy-number variation (CNV) and whole genome doubling (WGD) data from TCGA LUSC cohort were obtained to assess the CNV events. There were fewer CNV alterations and lower chromosome instability in patients with TP53/LRP1B co-wild compared with those with TP53/LRP1B mutant. RNA expression data from the TCGA LUSC cohort were collected to explore the differences in RNA expression and tumor immune microenvironment (TIME) between mutant and co-wild groups. The TP53/LRP1B co-wild type had a significantly increased proportion of multiple tumor-infiltrating lymphocytes (TILs), including activated CD8 T cell, activated dendritic cell (DC), and effector memory CD8 T cell. Immune-related gene sets including checkpoint, chemokine, immunostimulatory, MHC and receptors were enriched in the co-wild type. In conclusion, TP53/LRP1B co-wild LUSC conferred an elevated response rate in anti-PD-L1 therapy and improved survival, which was associated with a chromosome-stable phenotype and an activated immune microenvironment.

RAB11A Expression Is Associated With Cancer Aggressiveness Through Regulation of FGFR-Signaling in Lung Squamous Cell Carcinoma.

Fibroblast growth factor receptor (FGFR)-signaling in lung squamous cell carcinoma (LSCC) is associated with cancer aggressiveness and poor prognosis. Small GTPase RAB11A regulates the recycling of membrane proteins such as FGFR. This study evaluated the potential of RAB11A as a new therapeutic target for LSCC through its regulation of FGFR-signaling. Immunohistochemical analysis of 84 LSCC samples was performed to determine the correlation between RAB11A expression, clinicopathologic features, and prognosis. Alterations in FGFR-signaling were assessed in RAB11A-suppressed and RAB11A-overexpressed LSCC cells both in vitro and in vivo. The study identified RAB11A as a strong predictor of poor prognosis in the LSCC cohort. Cell proliferation and invasion were promoted and inhibited respectively in RAB11A-overexpressed and RAB11A -suppressed LSCC cells. In RAB11A-overexpressed and RAB11A-suppressed LSCC cells, FGFR-signaling was respectively up- and downregulated. The viability of the cells treated with nintedanib and lenvatinib was greater in RAB11A-overexpressing cells than in control cells. The in vivo tumor growth and micro-vessel density of RAB11A-overexpressing tumors were significantly higher than in the control cells. As a potentially valuable prognostic marker, RAB11A is a promising therapeutic target for LSCC. Evaluation of RAB11A may be useful for identification of LSCC in patients whose cancer is refractory to FGFR inhibitors.

TIGIT/CD47 dual high expression predicts prognosis and is associated with immunotherapy response in lung squamous cell carcinoma.

BackgroundRecent studies indicated that T cell immunoreceptor with immunoglobulin and ITIM domains (TIGIT) and cluster of differentiation 47 (CD47) have emerged as new potential immunotherapy targets. However, the roles of TIGIT and CD47 in lung squamous cell carcinoma (LUSC) have not been fully illustrated.MethodsThe specimens and clinicopathological information from 190 LUSC patients who underwent surgeries in our center were retrospectively collected. Immunohistochemical staining for TIGIT and CD47 was conducted. Transcriptional and clinical data of 479 LUSC were downloaded from The Cancer Genome Atlas (TCGA).ResultsIn the TCGA LUSC cohort, 142 (29.6%) cases were TIGIT/CD47 dual high expression at RNA level. The expression levels of TIGIT and CD47 were significantly correlated (p < 0.001). The proportions of patients with high TIGIT expression (p = 0.001) and high TIGIT/CD47 dual high expression (p = 0.049) were both higher in female cases. Advanced TNM stage (p = 0.006) and TIGIT/CD47 dual high expression (p = 0.047) were independent prognostic factors for LUSC. In the 190 LUSC cohort of our center, 75 (39.5%) cases were TIGIT/CD47 dual high expression at protein level. Cross‐table analysis showed a correlation between TIGIT and CD47 expression. Older age (p = 0.001), advanced TNM stage (p < 0.001) and TIGIT/CD47 dual high expression (p = 0.046) were independent prognostic factors in our cohort.ConclusionWe found that TIGIT and CD47 dual high expression was associated with poor prognosis in LUSC. We speculated that patients with dual high expression of CD47/TIGIT might be suitable for new target immunotherapy in the future.

Vasohibin 2 promotes lymphangiogenesis of lung squamous cell carcinoma through snail-dependent vascular endothelial growth factor-D (VEGF-D) signaling pathway.

BackgroundTumor lymphatic metastasis is mostly dependent on lymphangiogenesis, which was less studied compared to angiogenesis and the molecular mechanisms involved remained unclear.MethodsWe analyzed the mRNA expression profiles of 937 primary lung squamous cell carcinoma (LUSC) samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the genes related to lymphatic metastasis in LUSC. We focused on vasohibin 2 (VASH2) and investigated its biological functions in LUSC proliferation, apoptosis, migration, invasion, as well as lymphangiogenesis capacity by forced over-expressing VASH2 in LUSC cell line H520 in vitro and in vivo. We also evaluated the anti-tumor efficacy of specific anti-VASH2 antibody in LUSC xenograft-bearing mice models.ResultsVasohibin2 (VASH2) was filtered out as a significant predictive factor of poor prognosis and lymphatic metastasis in LUSC patients both in public datasets and an independent Chinese LUSC cohort. VASH2 promoted the proliferation and invasion of LUSC cells in vitro and vivo. Forced over-expression of VASH2 in LUSC cells promoted the amplification and tube formation capacity of human umbilical vein endothelial cells (HUVECs) and human lymphatic endothelial cells (HLECs) via up-regulating vascular endothelial growth factor-D (VEGF-D), which could be reversed via Snail inhibition. Furthermore, blocking VASH2/VEGF-D signaling using specific antibodies dramatically inhibited tumor growth in mice by interfering with the proliferation of cancer cells and lymphangiogenesis in tumor tissues.ConclusionsIn conclusion, VASH2 facilitated lymphangiogenesis and tumor growth in a Snail-dependent manner and might serve as a novel biomarker for early diagnosis and prognosis prediction, as well as a potential therapeutic target in LUSC.