SEPT9: From pan-cancer to lung squamous cell carcinoma
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ABSTRACT:
SUBMITTER: Wang W
PROVIDER: S-EPMC11375884 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:CUGBP Elav-like family member 2(CELF2) plays crucial roles in the development and activation of T cell. However, the impacts of CELF2 on tumour-infiltrating immune cells (TIICs) and clinical outcomes of tumours remain unclear. In this study, we found that elevated CELF2 expression was markedly correlated with prolonged survival in multiple tumours, particularly in breast and lung cancers. Notably, CELF2 only impacted the prognosis of triple-negative breast cancer (TNBC) with lymph node metastasis. Further investigation showed CELF2 expression was positively correlated with the infiltration abundance of dendritic cells (DCs), CD8+ T cells and neutrophils in breast invasive carcinoma (BRCA) and DCs in lung squamous cell carcinoma (LUSC). CELF2 also had strong correlations with markers of diverse TIICs such as T cells, tumour-associated macrophages and DCs in BRCA and LUSC. Importantly, CELF2 was significantly associated with plenty of immune checkpoint molecules (ICMs) and outperformed five prevalent biomarkers including PD-1, PD-L1, CTLA-4, CD8 and tumour mutation burden in predicting immunotherapeutic responses. Immunohistochemistry also revealed lower protein levels of CELF2 in TNBC and LUSC compared to normal tissues, and patients with high expression showed significantly prolonged prognosis. In conclusion, we demonstrated that increased CELF2 expression was closely related to better prognosis and superior TIIC infiltration and ICM expression, particularly in BRCA and LUSC. CELF2 also performed well in evaluating the immunotherapeutic efficacy, suggesting CELF2 might be a promising biomarker.
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Project description:The following fictional case is intended as a learning tool within the Pathology Competencies for Medical Education (PCME), a set of national standards for teaching pathology. These are divided into three basic competencies: Disease Mechanisms and Processes, Organ System Pathology, and Diagnostic Medicine and Therapeutic Pathology. For additional information, and a full list of learning objectives for all three competencies, see http://journals.sagepub.com/doi/10.1177/2374289517715040.
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Project description:Two subclasses of lung squamous cell carcinoma with different gene expression profiles and prognosis identified by hierarchical clustering and validated by non-negative matrix factorization . BACKGROUND: Current clinical and histopathological criteria used to define lung squamous cell carcinomas (SCCs) are insufficient to predict clinical outcome. We attempted to make a clinically-useful classification based on gene expression profiling. METHODS: We used cDNA microarrays with 40386 elements to analyze the gene expression profiles of 48 surgically resected samples of lung SCC. 9 samples of lung adenocarcinoma and 30 of normal lung were also included to give a total of 87 samples analyzed. After gene filtering, the data were subjected to hierarchical clustering and consensus clustering with the non-negative matrix factorization (NMF) approach. FINDINGS: Initial analysis by hierarchical clustering allowed division of SCCs into two distinct subclasses. An additional independent round of hierarchical clustering and consensus clustering with the NMF approach provided a validation for the classification. Kaplan-Meier analysis with the log rank test pointed to a non-significant difference in survival (p=0.071) but the likelihood of survival to 6 years was significantly different between the two groups (40.5% vs 81.8%, p=0.014, Z-test). Biological process categories characteristic for each subclass were identified statistically and up-regulation of cell-proliferation related genes was evident in the subclass with a poor prognosis. In the subclass with the better survival, genes involved in differentiated intracellular functions, such as the MAPKKK cascade, ceramide metabolism, or regulation of transcription, were up-regulated. Keywords: repeat sample
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Project description:As an innate feature of human beings, gender differences have an influence on various biological phenotypes, yet it does not attract enough attention in genomics studies. The prognosis of multiple carcinomas usually exhibits a favorable ending for female patients, but the neglect of gender differences can cause serious bias in survival analysis. Enhancer RNAs (eRNAs) are mostly downstream of androgens or estrogen. The present study was aimed to screen eRNAs in patients with non-small-cell lung cancer. The findings revealed that eRNA TBX5-AS1 was expressed differently between female and male patients. Meanwhile, its prognostic significance appeared only in male patients with squamous cell carcinoma (SCC) type. The Gene Set Enrichment Analysis proved that the expression level of TBX5-AS1 increased following the activation of the androgen signaling pathway. In pan-cancer analysis, the prognostic prediction based on gender grouping obtained more meaningful results, and the synergy between TBX5-AS1 and its homologous target was more consistent. Furthermore, immunity variations between sexes prompted us to explore the role that TBX5-AS1 played in tumor microenvironment and immunotherapy. The robust evidence proved that male patients with high expression of TBX5-AS1 possessed a malignant immune microenvironment and urgently needed immune checkpoint inhibitor treatment. In conclusion, TBX5-AS1 may be one of the strongest candidates to predict prognosis for male patients with SCC and provide a reference for immunotherapy.
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Project description:Lung squamous cell carcinoma gene expression (LSCC) is highly variable. This study discovered and validated LSCC gene expression subtypes. RNA from tumors and a common reference were hybridized to Agilent two color microarrays
| S-ECPF-GEOD-17710 | biostudies-other
Project description:BackgroundThe roles and clinical values of synaptojanin 2 (SYNJ2) in lung squamous cell carcinoma (LUSC) remain unclear.MethodsA total of 2824 samples from multi-center were collected to identify the expression of SYNJ2 in LUSC by using Wilcoxon rank-sum test, t-test, and standardized mean difference (SMD), and 194 in-house samples were also included to validate SYNJ2 expression in LUSC. The clinical roles of SYNJ2 were investigated via receiver operating characteristic (ROC) curves, univariate Cox regression analysis, and Kaplan-Meier plots. The underlying mechanisms of SYNJ2 in LUSC were explored by gene set enrichment analysis and immune correlation analysis. Further, a pan-cancer analysis based on 10,238 sapiens was performed to promote the understating of the expression and clinical significance of SYNJ2 in multiple human cancers.ResultsSYNJ2 was found to be significantly upregulated in LUSC at both mRNA and protein levels (p < 0.05, SMD = 0.89 [95% CI 0.34-1.45]) via public and in-house samples. Overexpressed SYNJ2 predicted poor prognosis for LUSC patients (hazard ratio = 2.38 [95% CI 1.42-3.98]). The cancer-promoting effect of SYNJ2 may be related to protein digestion and absorption and extracellular matrix-receptor interaction. SYNJ2 expression was closely related to immune cell infiltration, indicating its role in the immune response. Moreover, the distinct expression levels and essential clinical relevance of SYNJ2 in a series of cancers were initially revealed in this study.ConclusionsThis study disclosed the clinical significance of SYNJ2 in LUSC and multiple cancers, demonstrating the novel and potential biomarker for predicting and treating cancers.
| S-EPMC9112447 | biostudies-literature
Project description:Oral squamous cell carcinomas unusually show distant metastasis to the lung after primary treatment, which can be difficult to differentiate from primary squamous cell carcinoma of the lung. While the location and number of tumor nodules is helpful in diagnosing cases, differential diagnosis may be difficult even with histopathological examination. Therefore, we attempted to identify molecules that can facilitate accurate differential diagnosis. First, we performed a comprehensive gene expression analysis using microarray data for OSCC-LM and LSCC, and searched for genes showing significantly different expression levels. We then identified KRT13, UPK1B, and nuclear receptor subfamily 0, group B, member 1 (NR0B1) as genes that were significantly upregulated in LSCC and quantified the expression levels of these genes by real-time quantitative RT-PCR. The expression of KRT13 and UPK1B proteins were then examined by immunohistochemical staining. While OSCC-LM showed no KRT13 and UPK1B expression, some tumor cells of LSCC showed KRT13 and UPK1B expression in 10 of 12 cases (83.3%). All LSCC cases were positive for at least one of these markers. Thus, KRT13 and UPK1B might contribute in differentiating OSCC-LM from LSCC.
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Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Experiment Overall Design: The NSCLC patient collective was composed of the histological subtype adenocarcinoma (n=40) and squamous cell carcinoma (n=18). We subjected gene expression profiles of 40 AC and 18 SCC samples into further analysis. Unsupervised hierarchical clustering of all 58 NSCLC tumors using the 500 most variably expressed transcripts revealed two different clusters, which were strongly associated with the histological subtypes AC and SCC of NSCLC. Our result indicated that the major impact on global transcriptional changes was due to the NSCLC histology.
| S-ECPF-GEOD-10245 | biostudies-other
Project description:BackgroundTo explore the molecular mechanisms of the anti-cancer effect of curcumin in human lung squamous cell carcinoma (LSQCC) SK-MES-1 cells.MethodsCell viability was determined using MTT assay. Ribonucleic acid sequencing was performed to measure expression levels of transcripts in LSQCC cells treated with 15 μmol/L curcumin (treatment groups) or an equal amount of dimethylsulfoxide (control). Cuffdiff software was used to identify differentially expressed genes (DEGs) in treatment groups, followed by enrichment analysis of DEGs using the Database for Annotation, Visualization and Integration Discovery. The protein-protein interaction (PPI) networks for up and downregulated DEGs were constructed by Cytoscape software using Search Tool for the Retrieval of Interacting Genes data to identify hub nodes.ResultsCurcumin significantly reduced cell viability in LSQCC cells. In total, 380 DEGs including 154 upregulated and 126 downregulated genes were found in the treatment groups. The upregulated genes were enriched in base excision repair (BER, such as PCNA, POLL, and MUTYH) and Janus kinase-signal transducer and activator of transcription (JAT-STAT) signaling pathways (such as AKT1 and STAT5A), while the downregulated genes were enriched in nine pathways, including the vascular endothelial growth factor (VEGF) signaling pathway (such as PTK2, VEGFA, MAPK1, and MAPK14) and mitogen-activated protein kinase (MAPK) signaling pathway (ARRB2, MAPK1, MAPK14, and NFKB1). PCNA and AKT1 were the hub nodes in the PPI network of upregulated genes while MAPK1, MAPK14, VEGFA, and NFKB1 were the hub nodes in the PPI network of downregulated genes.ConclusionsCurcumin might exert anti-cancer effects on LSQCC via regulating BER, JAT-STAT, VEGF, and MAPK signaling pathways.
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Project description:BackgroundTumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.MethodsRNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.ResultsLUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein-protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.ConclusionmRNAsi-related hub genes could be a potential biomarker of LUSC.
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