Dataset Information

Lymph node metastasis in lung squamous cell carcinoma and identification of metastasis-related genes based on the Cancer Genome Atlas.

ABSTRACT: Squamous cell carcinoma (SCC) is a unique clinical and histological category that accounts for about 30% of total lung cancer. To identify risk factors for lymph node metastasis and analyze the molecular features of these metastases in lung SCC, a retrospective study was performed for 170 lung SCC patients who underwent surgical treatment. The overall survival of these patients with or without lymph node metastasis (LM/NLM) was analyzed using the Kaplan-Meier method. We also used the TCGA database to compare the differentially expressed genes (DEGs) in patients with stage T1-2 and T3-4 lung SCC. Data from both our retrospective study and the TCGA database demonstrated a correlation between age and stage T1-T2 LM (P = .002). There were significant differences between the LM and NLM groups in both mean survival time and median survival time for different T-stages (P = .031). There were 176 upregulated and 177 downregulated DEGs between the LM and NLM groups in the stage T1-2 group and 93 upregulated and 34 downregulated DEGs in the stage T3-T4 group. These differentially expressed genes were predicted to participate in five cellular components, five molecular functions, and five biological processes. There were 20 genes, including GCG, CASR, NPY, CGA, TAC1, ALB, APOA1, CRH, CHRH, TRH, and GHSR, located at the core of the protein-protein interaction network in the stage T1-2 group and 11 genes, including F2, CASR, GRM1, GNRHR, GRPR, NTSR1, PROKR2, UTS2D, PTH, ALB, and FGA, in the stage T3-4 group. Overall, LM plays a key role in the treatment response and prognosis of SCC patients. Several risk factors, including age and stage, were identified for LM. There was a previously undiscovered enrichment of significant novel genes in lung SCC between the LM and NLM groups, which may have the potential for predicting prognosis and targeting.

SUBMITTER: Dong M

PROVIDER: S-EPMC6797670 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Lymph node metastasis in lung squamous cell carcinoma and identification of metastasis-related genes based on the Cancer Genome Atlas.

Dong Ming M Gong Hao H Li Tong T Li Xin X Liu Jinghao J Zhang Hongbing H Liu Minghui M Chen Gang G Liu Hongyu H Chen Jun J

Cancer medicine 20190903 14

Squamous cell carcinoma (SCC) is a unique clinical and histological category that accounts for about 30% of total lung cancer. To identify risk factors for lymph node metastasis and analyze the molecular features of these metastases in lung SCC, a retrospective study was performed for 170 lung SCC patients who underwent surgical treatment. The overall survival of these patients with or without lymph node metastasis (LM/NLM) was analyzed using the Kaplan-Meier method. We also used the TCGA databa ...[more]

PMID: 31482686

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Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most serious diseases affecting populations worldwide and lymph node metastasis is a key pathological feature of HNSCC which predicts poor survival. However, the molecular mechanisms associated with the development of lymph node metastasis in HNSCC have not been fully elucidated.MethodsDifferentially expressed genes (DEGs) were identified in two HNSCC datasets (GES6631 and GES58911). Functional annotation analysis was constructed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Meanwhile, the protein-protein interaction (PPI) network and module analysis using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape were carried out to identify the hub genes. The expression differences, overall survival (OS), and disease-free survival (DFS) of hub genes were analyzed by Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and verified by immunohistochemistry (IHC) from Human Protein Atlas (HPA). Moreover, receiver operating characteristic (ROC) curve analysis was conducted to judge whether those hub genes had good diagnostic and prognostic ability, and the web tool Tumor Immune Estimation Resource (TIMER) was used to analyze the correlation of hub genes' expression and immune infiltration.ResultsIn total, 913 DEGs including 476 upregulated and 437 downregulated genes were identified. The genes Aurora kinase A (AURKA), CyclinB1 (CCNB1), Cyclin-dependent kinase regulatory subunit 1B (CKS1B), Serpin Family H Member 1(SERPINH1), and Transforming growth factor-beta-induced protein (TGFBI) were screened out as hub genes and were associated with lymph node metastasis, showing notably abnormal expression in HNSCC samples, and the high expression of all the hub genes in HNSCC patients was related to worse overall survival.ConclusionsThe genes AURKA, CCNB1, CKS1B, SERPINH1, and TGFBI may be involved in the lymph node metastasis of HNSCC and reveal the potential to serve as molecular biomarkers in the diagnosis of HNSCC. This study may help to elucidate the molecular mechanisms of the development of lymph node metastasis and facilitate the selection of targets for the treatment and diagnosis of HNSCC.

Project description:BackgroundmiRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis.MethodsR software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network.ResultsA combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that CXCL12, IGF1, PTPRC CDH5, RAD51B, REV3L, and WDHD1 are key genes that significantly correlate with cervical cancer lymph node metastasis.ConclusionsThis study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (PTPRC and CDH5) were first reported to be potential novel biomarkers for cervical cancer. The current study further characterizes the progression of lymph node metastasis and mechanism of cervical tumors; therefore, it provides a novel diagnostic indicator and therapeutic targets for future clinical treatments.

Dataset Information

Lymph node metastasis in lung squamous cell carcinoma and identification of metastasis-related genes based on the Cancer Genome Atlas.

Publications

Lymph node metastasis in lung squamous cell carcinoma and identification of metastasis-related genes based on the Cancer Genome Atlas.

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