Dataset Information

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling.

ABSTRACT: Tumor-associated macrophages (TAMs) are regarded as the most abundantly infiltrating immune cells around the tumor microenvironment (TME) in head and neck squamous cell carcinoma (HNSCC), which plays an essential role in immunosuppression and tumorigenesis. In the TCGA HNSCC cohort, 500 patients with clinical-pathological information and RNA sequence expression were randomly assigned to training for lasso regression and validation for verification, respectively. A TAM-based ten-gene signature (TBGs) was constructed, which divided the patients into high-risk and low-risk groups, could predict overall survival (OS) of HNSCC patients in the training dataset (p = 3.527e^-05) and validation dataset (p = 3.785e^-02). The result of Cox univariate and multivariate regression analyses showed that the risk score of TBGs could be an independent prognostic factor in HNSCC. ROC curve confirmed that the risk score of TBGs has good sensitivity and specificity for prognosis prediction (AUC = 0.659) and was also verified by the validation dataset (AUC = 0.621). We obtained key risk transcription factors (TFs)-EHF and SNAI2-by correlation analysis with TBGs. Moreover, we ran a gene set enrichment analysis (GSEA) to speculate that TBGs act on interstitial remodeling, tumor killing, metabolic reprogramming, and tumor immune-related pathways. Finally, we combined clinical-pathological features and risk score of TBGs to establish clinical nomograms, and calibration curves verified the accuracy of long-term clinical prognosis in the two datasets (C-index of 5-year OS = 0.721 and 0.716). In general, the TBGs we obtained may accurately predict the prognosis of HNSCC patients to provide personalized treatment.

SUBMITTER: Lu Z

PROVIDER: S-EPMC7708322 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling.

Lu Zhaoyi Z Deng Xiaoli X Li Hui H

Frontiers in oncology 20201118

Tumor-associated macrophages (TAMs) are regarded as the most abundantly infiltrating immune cells around the tumor microenvironment (TME) in head and neck squamous cell carcinoma (HNSCC), which plays an essential role in immunosuppression and tumorigenesis. In the TCGA HNSCC cohort, 500 patients with clinical-pathological information and RNA sequence expression were randomly assigned to training for lasso regression and validation for verification, respectively. A TAM-based ten-gene signature (T ...[more]

PMID: 33312950

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Project description:Background: Uveal melanoma (UM) is the most common primary intraocular cancer in adults. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of UM that may lead to novel therapeutic strategies. Methods: Dataset TCGA-UVM, download from TCGA portal, were taken as the training cohort, and dataset GSE22138, obtained from GEO database, was set as the validation cohort. In training cohort, Kaplan-Meier analysis and univariate Cox regression model were applied to preliminary screen prognostic genes. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in the validation cohorts through Kaplan-Meier, Cox, and ROC analyses. In addition, the correlation between copy number aberrations and risk score was evaluated by Spearman test. GSEA and immune infiltrating analyses were conducted for understanding function annotation and the role of the signature in the tumor microenvironment. Results: A ten-gene signature was built, and it was examined by Kaplan-Meier analysis revealing that significantly overall survival, progression-free survival, and metastasis-free survival difference was seen. The ten-gene signature was further proven to be an independent risk factor compared to other clinic-pathological parameters via the Cox regression analysis. Moreover, the receiver operating characteristic curve (ROC) analysis results demonstrated a better predictive power of the UM prognosis that our signature owned. The ten-gene signature was significantly correlated with copy numbers of chromosome 3, 8q, 6q, and 6p. Furthermore, GSEA and immune infiltrating analyses showed that the signature had close interactions with immune-related pathways and the tumor environment. Conclusions: Identifying the ten-gene signature (SIRT3, HMCES, SLC44A3, TCTN1, STPG1, POMGNT2, RNF208, ANXA2P2, ULBP1, and CA12) could accurately identify patients' prognosis and had close interactions with the immunodominant tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.

Project description:Breast cancer (BC) is the most common type of malignancy among females worldwide. Histone modifications, which are the major post-translational modifications, have a significant role in cancer development and prognosis. However, whether histone family genes may serve as potential prognostic biomarkers for BC patients has remained elusive. In the present study, RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed genes were identified and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway functional enrichment analysis was performed. As histone family genes have been reported to be associated with cervical cancer, the present study hypothesized that histone family genes are associated with gynecological tumors. Histone family genes, including histone cluster 1 H1A family member B (HIST1H1B), HIST1H2AJ, HIST1H2AM, HIST1H2BI, HIST1H2BO, HIST1H3B, HIST1H3F, HIST1H3H, HIST1H4C and HIST1H4D, were upregulated and identified as hub genes in the protein-protein interaction network. In addition, Oncomine and the Human Protein Atlas were used to further verify the expression levels of histone gene sets. The PrognoScan database was then used to investigate the association between expression and prognostic value regarding cancer patient survival. The present results indicated that higher expression of histone gene sets was associated with poor overall survival, relapse-free survival and distant metastasis-free survival of BC patients. The differential expression of histone family genes between BC and normal samples was validated by reverse transcription-quantitative PCR. Finally, to determine the clinical role of histone family genes in BC, the correlations between histone family genes expression and clinical characteristics were investigated through data collected from TCGA. Therefore, the present study indicates that histone gene sets may be used as prognostic factors for survival prediction for BC patients.

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Dataset Information

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling.

Publications

Prognostic Value of a Ten-Gene Signature in HNSCC Patients Based on Tumor-Associated Macrophages Expression Profiling.

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