scholarly journals Interferon-lambda (IFNL) germline variations and their significance for HCC and PDAC progression: an analysis of The Cancer Genome Atlas (TCGA) data

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Henriette Huschka ◽  
Sabine Mihm
Keyword(s):  
Disease Progression ◽  
Cox Regression ◽  
Genetic Variations ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Disease Outcome ◽  
Ductal Adenocarcinoma ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Background Hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC) are malignancies with a leading lethality. With reference to interferons (IFNs) known to mediate antitumor activities, this study investigated the relationship between germline genetic variations in type III IFN genes and cancer disease progression from The Cancer Genome Atlas (TCGA) data. The genetic variations under study tag a gain-or-loss-of-function dinucleotide polymorphism within the IFNL4 gene, rs368234815 [TT/ΔG]. Methods The entirety of the TCGA sequencing data was used to assess genotypes of 187 patients with HCC and of 162 patients with PDAC matched for ethnicity. Stratified for IFNL genotypes, both cohorts were subjected to time-to-event analyses according to Kaplan-Meier with regard to the length of the specific progression free interval (PFI) and the overall survival (OS) time as two clinical endpoints for disease progression. Results Logrank analysis revealed a significant relationship between IFNL genotypes and disease outcome for PDAC. This relationship was not found for HCC. A multiple Cox regression analysis employing patients’ age, tumor grade and tumor stage as further covariates proved IFNL genotypes to be independent predictors for PDAC disease outcome. Conclusion This repository-based approach unveiled clinical evidence suggestive for an impact of IFNL germline variations for PDAC progression with an IFNL haplotype predisposing for IFNL4 expression being favorable.

Eight-gene prognostic signature associated with hypoxia and ferroptosis for gastric cancer with general applicability

Epigenomics ◽  
2021 ◽  
Author(s):  
Junyu Huo ◽  
Liqun Wu ◽  
Yunjin Zang
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aims: To investigate the prognostic significance of hypoxia- and ferroptosis-related genes for gastric cancer (GC). Materials & methods: We extracted data on 259 hypoxia- and ferroptosis-related genes from The Cancer Genome Atlas and identified the differentially expressed genes between normal (n = 32) and tumor (n = 375) tissues. A risk score was established by univariate Cox regression analysis and LASSO penalized Cox regression analysis. Results: The risk score contained eight genes showed good performance in predicting overall survival and relapse-free survival in GC patients in both the training cohort (The Cancer Genome Atlas, n = 350) and the testing cohorts (GSE84437, n = 431; GSE62254, n = 300; GSE15459, n = 191; GSE26253, n = 432). Conclusion: The eight-gene signature may help to the improve the prognostic risk classification of GC.

scholarly journals Downregulation of SPINK13 Promotes Metastasis by Regulating uPA in Ovarian Cancer Cells

2018 ◽  
Vol 45 (3) ◽  
pp. 1061-1071 ◽  
Author(s):  
Shengyun Cai ◽  
Pei Zhang ◽  
Suhe Dong ◽  
Li Li ◽  
Jianming Cai ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Regression Analysis ◽  
Cellular Proliferation ◽  
Cox Regression ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background/Aims: Ovarian cancer (OC) is the fifth leading cause of cancer-related death in women, and it is difficult to diagnose at an early stage. The purpose of this study was to explore the prognostic biological markers of OC. Methods: Univariate Cox regression analysis was used to identify genes related to OC prognosis from the Cancer Genome Atlas(TCGA) database. Immunohistochemistry was used to analyse the level of SPINK13 in OC and normal tissues. Cell proliferation, apoptosis and invasion were performed using MTT assay, flow cytometric analysis and Transwell assay, respectively. Results: We identified the Kazal-type serine protease inhibitor-13 (SPINK13) gene related to OC prognosis from the Cancer Genome Atlas (TCGA) database by univariate Cox regression analysis. Overexpression of SPINK13 was associated with higher overall survival rate in OC patients. Immunohistochemistry showed that the level of SPINK13 protein was significantly lower in OC tissues than in normal tissues (P < 0.05).In vitro experiments showed that the overexpression of SPINK13 inhibited cellular proliferation and promoted apoptosis. Moreover, SPINK13 inhibited cell migration and epithelial to mesenchymal transition (EMT). SPINK13 was found to inhibit the expression of urokinase-type plasminogen activator (uPA), while recombinant uPA protein could reverse the inhibitory effect of SPINK13 on OC metastasis. Conclusion: These results indicate that SPINK13 functions as a tumour suppressor. The role of SPINK13 in cellular proliferation, apoptosis and migration is uPA dependent, and SPINK13 may be used as a potential biomarker for diagnosis and targeted therapy in OC.

scholarly journals Screening and Identifying m6A Regulators as an Independent Prognostic Biomarker in Pancreatic Cancer Based on The Cancer Genome Atlas Database

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Bi Lin ◽  
Yangyang Pan ◽  
Dinglai Yu ◽  
Shengjie Dai ◽  
Hongwei Sun ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Tumor Therapy ◽  
Disease Free Survival ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background. Pancreatic cancer is one of the most malignant tumors of the digestive system, and its treatment has rarely progressed for the last two decades. Studies on m6A regulators for the past few years have seemingly provided a novel approach for malignant tumor therapy. m6A-related factors may be potential biomarkers and therapeutic targets. This research is focused on the gene characteristics and clinical values of m6A regulators in predicting prognosis in pancreatic cancer. Methods. In our study, we obtained gene expression profiles with copy number variation (CNV) data and clinical characteristic data of 186 patients with pancreatic cancer from The Cancer Genome Atlas (TCGA) portal. Then, we determined the alteration of m6a regulators and their correlation with clinicopathological features using the log-rank tests, Cox regression model, and chi-square test. Additionally, we validated the prognostic value of m6A regulators in the International Cancer Genome Consortium (ICGC). Results. The results suggested that pancreatic cancer patients with ALKBH5 CNV were associated with worse overall survival and disease-free survival than those with diploid genes. Additionally, upregulation of the writer gene ALKBH5 had a positive correlation with the activation of AKT pathways in the TCGA database. Conclusion. Our study not only demonstrated genetic characteristic changes of m6A-related genes in pancreatic cancer and found a strong relationship between the changes of ALKBH5 and poor prognosis but also provided a novel therapeutic target for pancreatic cancer therapy.

scholarly journals Molecular Profiling of Core Immune-Escape Genes Highlights LCK Has Potential to Reshape TME in Melanoma

2021 ◽  
Author(s):  
Duoli Zhang ◽  
Zhuo Zhang ◽  
Shixin Xiang ◽  
Mintao Xiao ◽  
Yao Zhang ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Immune System ◽  
Tumor Microenvironment ◽  
Immune Escape ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Tumor Environment ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Background: The game between the immune system of the organism and the tumor is a dynamic course of events. Once the escape phase is reached, the tumor will overcome the limitations of the immune system and the tumor will progress. Objective: This study aimed to determine the potential tumor environment-based prognostic biomarkers related to immunotherapy in melanoma. Methods: 471 tumor samples and 398 normal samples were extracted from The Cancer Genome Atlas and The Genotype-Tissue Expression. Furthermore, a core set of immune-escape genes were collected from previous studies and a set of immune-related genes were obtained from IMMPORT database. Through overlapping these two sets of genes, a set of core immune-escape related genes were identified. In the next place, we conducted a systematic analysis of core immune-escape related genes through The Cancer Genome Atlas cohort and identified independent prognostic factors in melanoma. Through CIBERSORT, ssGSEA algorithm and TIMER database, we explored the potential of independent prognostic factors to reshape the tumor microenvironment.Results: Through Kaplan-Meier as well as univariate cox regression analysis of expression profiles and clinical information obtained from the TCGA cohort, we found that high LCK expression was associated with prolonged overall survival. In addition, the expression level of LCK was significantly correlated with the dysregulation of the infiltration level of immune cells in the tumor microenvironment. Conclusions: In this study, we determined LCK as a biomarker that is significantly associated with tumor environment and has significant prognostic significance. Meanwhile, immunotherapeutic approaches targeting LCK in tumor cells may provide a new perspective for the treatment of melanoma.

scholarly journals Screening and Identifying m6A Regulators in Pancreatic Cancer Based on The Cancer Genome Atlas Database

2020 ◽  
Author(s):  
Bi Lin ◽  
Hongwei Sun ◽  
Dinglai Yu ◽  
Yukai Xiang ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Tumor Therapy ◽  
Disease Free Survival ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Background: Pancreatic cancer is one of the most malignant tumors of the digestive system and its treatment has rarely progressed for the last two decades. Studies on m6A regulators for the past few years have seemingly provided a novel approach for malignant tumor therapy. m6A-related factors may be potential biomarkers and therapeutic targets. This research is focused on the gene characteristics and clinical values of m6A regulators in predicting prognosis in pancreatic cancer. Methods: In our study, we obtained gene expression profiles with copy number variation (CNV) data and clinical characteristic data of 186 patients with pancreatic cancer from The Cancer Genome Atlas portal (TCGA). Then, we determined the alteration of m6a regulators and their correlation with clinicopathological features using the log-rank tests, Cox regression model, and chi-square test. Results: The results suggested that pancreatic cancer patients with ALKBH5 CNV were associated with worse overall survival and disease-free survival than those with diploid genes. Additionally, upregulation of the writer gene ALKBH5 had a positive correlation with the activation of AKT pathways. Conclusion: Our study not only demonstrated genetic characteristic changes of m6A-related genes in pancreatic cancer and found a strong relationship between the changes of ALKBH5 and poor prognosis but also provided a novel therapeutic target for pancreatic cancer therapy.

scholarly journals Identification of an Individualized Immune-Related Prognostic Risk Score in Lung Squamous Cell Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Yuan Zhuang ◽  
Sihan Li ◽  
Chang Liu ◽  
Guang Li
Keyword(s):  
Risk Score ◽  
Squamous Cell ◽  
Cell Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Gene ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: Lung squamous cell carcinoma (LUSC) is one of the most common histological subtypes of non-small cell lung cancer (NSCLC), and its morbidity and mortality are steadily increasing. The purpose of this study was to study the relationship between the immune-related gene (IRGs) profile and the outcome of LUSC in patients by analyzing datasets from The Cancer Genome Atlas (TCGA).Methods: We obtained publicly available LUSC RNA expression data and clinical survival data from The Cancer Genome Atlas (TCGA), and filtered IRGs based on The ImmPort database. Then, we identified risk immune-related genes (r-IRGs) for model construction using Cox regression analysis and defined the risk score in this model as the immune gene risk index (IRI). Multivariate analysis was used to verify the independent prognostic value of IRI and its association with other clinicopathological features. Pearson correlation analysis was used to explore the molecular mechanism affecting the expression of IRGs and the correlation between IRI and immune cell infiltration.Results: We screened 15 r-IRGs for constructing the risk model. The median value of IRI stratified the patients and there were significant survival differences between the two groups (p = 4.271E-06). IRI was confirmed to be an independent prognostic factor (p &lt; 0.001) and had a close correlation with the patients' age (p &lt; 0.05). Interestingly, the infiltration of neutrophils or dendritic cells was strongly upregulated in the high-IRI groups (p &lt; 0.05). Furthermore, by investigating differential transcription factors (TFs) and functional enrichment analysis, we explored potential mechanisms that may affect IRGs expression in tumor cells.Conclusion: In short, this study used 15 IRGs to build an effective risk prediction model, and demonstrated the significance of IRGs-based personalized immune scores in LUSC prognosis.

scholarly journals Development and validation of an immune gene set-based prognostic signature in cutaneous melanoma

2021 ◽  
Author(s):  
Qi Tian ◽  
Huan Gao ◽  
Wen Zhao ◽  
Yan Zhou ◽  
Jin Yang
Keyword(s):  
Cutaneous Melanoma ◽  
Prognostic Model ◽  
Expression Profiles ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Immune Gene ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Genome Atlas

We aimed to fully understand the landscape of the skin cutaneous melanoma (SKCM) microenvironment and develop an immune prognostic signature that can predict the prognosis for SKCM patients. RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas and Gene Expression Omnibus databases. The immune-prognostic signature was constructed by LASSO Cox regression analysis. We calculated the relative abundance of 29 immune-related gene sets based on the mRNA expression profiles of 314 SKCM patients in the Cancer Genome Atlas training set. Hierarchical clustering was performed to classify SKCM patients into three clusters: immunity-high, -medium and -low. The values of our prognostic model in predicting disease progression, metastasis and immunotherapeutic responses were also validated. In conclusion, the prognostic model demonstrated a powerful ability to distinguish and predict SKCM patients’ prognosis.

scholarly journals Systematic analysis and prediction model construction of alternative splicing events in hepatocellular carcinoma: a study on the basis of large-scale spliceseq data from The Cancer Genome Atlas

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8245 ◽  
Author(s):  
Lingpeng Yang ◽  
Yang He ◽  
Zifei Zhang ◽  
Wentao Wang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Prediction Model ◽  
Gene Network ◽  
Cox Regression ◽  
The Cancer Genome Atlas ◽  
Systematic Analysis ◽  
Cox Regression Analysis ◽  
Regulation Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Growing evidence showed that alternative splicing (AS) event is significantly related to tumor occurrence and progress. This study was performed to make a systematic analysis of AS events and constructed a robust prediction model of hepatocellular carcinoma (HCC). The clinical information and the genes expression profile data of 335 HCC patients were collected from The Cancer Genome Atlas (TCGA). Information of seven types AS events were collected from the TCGA SpliceSeq database. Overall survival (OS) related AS events and splicing factors (SFs) were identified using univariate Cox regression analysis. The corresponding genes of OS-related AS events were sent for gene network analysis and functional enrichment analysis. Optimal OS-related AS events were selected by LASSO regression to construct prediction model using multivariate Cox regression analysis. Prognostic value of the prediction models were assessed by receiver operating characteristic (ROC) curve and KaplanMeir survival analysis. The relationship between the Percent Spliced In (PSI) value of OS-related AS events and SFs expression were analyzed using Spearman correlation analysis. And the regulation network was generated by Cytoscape. A total of 34,163 AS events were identified, which consist of 3,482 OS-related AS events. UBB, UBE2D3, SF3A1 were the hub genes in the gene network of the top 800 OS-related AS events. The area under the curve (AUC) of the final prediction model based on seven types OS-related AS events was 0.878, 0.843, 0.821 in 1, 3, 5 years, respectively. Upon multivariate analysis, risk score (All) served as the risk factor to independently predict OS for HCC patients. SFs HNRNPH3 and HNRNPL were overexpressed in tumor samples and were signifcantly associated with the OS of HCC patients. The regulation network showed prominent correlation between the expression of SFs and OS-related AS events in HCC patients. The final prediction model performs well in predicting the prognosis of HCC patients. And the findings in this study improve our understanding of the association between AS events and HCC.

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