scholarly journals Prognostic and Predictive Value of Transcription Factors Panel for Digestive System Carcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Guoxu Fang ◽  
Jianhui Fan ◽  
Zongren Ding ◽  
Rong Li ◽  
Kongying Lin ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Digestive System ◽  
Cox Regression ◽  
Predictive Performance ◽  
Clinicopathological Parameters ◽  
Cox Regression Analysis ◽  
External Data ◽  
Carcinoma Patient ◽  
Prognosis Model ◽  
Prognostic Prediction

PurposeDigestive system carcinoma is one of the most devastating diseases worldwide. Lack of valid clinicopathological parameters as prognostic factors needs more accurate and effective biomarkers for high-confidence prognosis that guide decision-making for optimal treatment of digestive system carcinoma. The aim of the present study was to establish a novel model to improve prognosis prediction of digestive system carcinoma, with a particular interest in transcription factors (TFs).Materials and MethodsA TF-related prognosis model of digestive system carcinoma with data from TCGA database successively were processed by univariate and multivariate Cox regression analyses. Then, for evaluating the prognostic prediction value of the model, ROC curve and survival analysis were performed by external data from GEO database. Furthermore, we verified the expression of TFs expression by qPCR in digestive system carcinoma tissue. Finally, we constructed a TF clinical characteristics nomogram to furtherly predict digestive system carcinoma patient survival probability with TCGA database.ResultsBy Cox regression analysis, a panel of 17 TFs (NFIC, YBX2, ZBTB47, ZNF367, CREB3L3, HEYL, FOXD1, TIGD1, SNAI1, HSF4, CENPA, ETS2, FOXM1, ETV4, MYBL2, FOXQ1, ZNF589) was identified to present with powerful predictive performance for overall survival of digestive system carcinoma patients based on TCGA database. A nomogram that integrates TFs was established, allowing efficient prediction of survival probabilities and displaying higher clinical utility.ConclusionThe 17-TF panel is an independent prognostic factor for digestive system carcinoma, and 17 TFs based nomogram might provide implication an effective approach for digestive system carcinoma patient management and treatment.

scholarly journals Immune-Related lncRNA Correlated with Transcription Factors Provide Strong Prognostic Prediction in Gliomas

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yixin Tian ◽  
Yi-Quan Ke ◽  
Yanxia Ma
Keyword(s):  
Patient Outcome ◽  
Central Nervous System ◽  
Transcription Factors ◽  
Cox Regression ◽  
Noncoding Rnas ◽  
Immune Microenvironment ◽  
Cox Regression Analysis ◽  
New Strategy ◽  
Prognostic Prediction ◽  
Significant Factors

Glioma is the most common and deadly tumor in central nervous system. According to previous studies, long noncoding RNAs (lncRNA) and transcription factors were significant factors of gliomas progression by regulating gliomas immune microenvironment. In our study, we built two independent cohorts from CGGA and TCGA. And we extracted 253 immune-related lncRNA correlated with prognosis. After LASSO analysis and multivariate Cox regression analysis, 8 immune-related lncRNA were used to construct classifier. The effectiveness of classifier was confirmed in both CGGA (AUC = 0.869) and TCGA (AUC = 0.902) cohorts. The correlation between transcription factors and immune-related lncRNA was calculated by WCGNA. Eventually, we built a network between 8 lncRNA and transcription factors. The function of core immune-related lncRNA in gliomas immune microenvironment was also investigated by CIBERTSORT. Our research provided a strong classifier of immune-related lncRNA to predict gliomas patient outcome. We also found the correlation between core immune-related lncRNA and transcription factors. These results may stimulate new strategy of immunotherapy in gliomas patients.

scholarly journals Identification and Validation of a Glycolysis Related Metabolic Reprogramming Gene Signature for Predicting Survival in Colon Cancer Patients

2021 ◽  
Author(s):  
Gang Liu ◽  
Xiaowang WU ◽  
Jian Chen
Keyword(s):  
Colon Cancer ◽  
Prediction Model ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Gene Signature ◽  
Metabolic Reprogramming ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Prognosis Model ◽  
The Relationship

Abstract Background Colon cancer (CC) is one of the most common gastrointestinal malignant tumors with high mortality rate. Because of malignancy and easily metastasis feather, and limited treatments, the prognosis of CC remains poor. Glycolysis is a metabolic process of glucose in anoxic environments which is an important way to provide energy for tumor. The role of glycolysis in CC largely remains unknown and is necessary to be explored. Method In our study, we analyzed glycolysis related genes expression in CC, patients gene expression and corresponding clinical data were downloaded from GEO dataset, glycolysis related genes sets were collected from Msigdb. Through COX regression analysis, prognosis model based on glycolysis-related genes was established. The efficacy of gene model was tested by Survival analysis, ROC analysis and PCA analysis. Furthermore, the relationship between risk scores and clinical characteristic was researched. Results Our findings identified 13 glycolysis related genes (NUP107, SEC13, ALDH7A1, ALG1, CHPF, FAM162A, FBP2, GALK1, IDH1, TGFA, VLDLR, XYLT2 and OGDHL) consisted prognostic prediction model with relative high accuracy. The relationship between prediction model and clinical feathers were specifically studied, results showed age > 65years, TNM III-IV, T3-4, N1-3, M1 and high-risk score were independent prognostic risk factors with poorer prognosis. Finally, model genes were significantly expressed and EMT were activated in CC patients. Conclusion This study provided a new aspect to advance our understanding in the potential mechanism of glycolysis in CC.

Aberrant β-Catenin and Lef1 Expression May Predict the Clinical Outcome for Patients with Oropharyngeal Cancer

2012 ◽  
Vol 25 (1) ◽  
pp. 135-146 ◽  
Author(s):  
P. Papagerakis ◽  
G. Pannone ◽  
A-H. Shabana ◽  
J. Depondt ◽  
A. Santoro ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Intracellular Signaling ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Wnt Signaling Pathway ◽  
Clinicopathological Parameters ◽  
Cox Regression Analysis ◽  
Local Recurrences ◽  
Long Term Follow Up ◽  
Epithelial Cell Surface

β-catenin, normally expressed on the epithelial cell surface, plays a crucial role in cadherin-mediated cell adhesion. Recent evidence suggests that β-catenin is also involved in other functions such as intracellular signaling via the Wnt pathway by creating a nuclear complex with members of the Lymphoid-Enhancer-Factor/T-Cell-Factor (LEF/TCF) family of transcription factors, and gene regulation that it is implicated in the development of several tumors. Little information is available on β-catenin expression and its main partner in the Wnt signaling pathway, LEF1, in oropharyngeal squamous cell carcinomas (OP-SCCs). The aim of this study is to investigate the expression of β-catenin and LEF1 expression in human primary OP-SCCs and to evaluate their clinical and prognostic significance. OP-SCCs and normal peritumoral areas were analyzed by immunohistochemistry, Western-blot and RT-PCR. β-catenin was overexpressed in tumors in comparison to normal peritumoral areas and displayed predominantly intracellular (cytosolic/nuclear) localization in 62% of the tumors. Immunoreactivity was correlated with clinicopathological parameters and long-term follow-up, and a significant association was found between protein expression and development of local recurrences (P =0.03). The OP-SCCs with poor clinical outcome, which displayed intracellular β-catenin expression, were also strongly positive for LEF1, with their co-expression statistically significant (P = 0.040). All (100%) advanced (stages 3+4) SCCs, 66.7% of the SCCs with positive lymph nodes and 80% of the SSCs that developed local recurrences were LEF1 positive. Cox regression analysis confirmed a poorer overall survival in cases with high expression of β-catenin and LEF1. Our results suggest that assessing intracellular β-catenin and LEF1 expression might help in patient risk stratification and outcome prediction, and serve as novel therapeutic targets in advanced OP-SCC.

scholarly journals Increased RCAS1 Expression Is Associated with Advanced Histopathological Stage and Poor Prognosis in Patients with Gastric Adenocarcinoma

2013 ◽  
Vol 35 ◽  
pp. 213-219 ◽  
Author(s):  
Constantinos Giaginis ◽  
Themistoclis Efkarpidis ◽  
Paraskevi Alexandrou ◽  
Efstratios Patsouris ◽  
Gregory Kouraklis ◽  
...  
Keyword(s):  
Gastric Adenocarcinoma ◽  
Cox Regression ◽  
Human Tumor ◽  
Clinicopathological Parameters ◽  
Rank Test ◽  
Survival Times ◽  
Biological Behaviour ◽  
Tissue Samples ◽  
Cox Regression Analysis ◽  
Expression Levels

Background. The receptor-binding cancer antigen expressed on SiSo cells (RCAS1) is a human tumor-associated antigen that has been considered to play a crucial role in tumor progression by enabling cancer cells to evade immune surveillance. The present study aimed to evaluate the clinical significance of the RCAS1 expression in gastric adenocarcinoma.Material and Methods. RCAS1 protein expression was assessed immunohistochemically on 54 gastric adenocarcinoma tissue samples and was analyzed in relation to clinicopathological parameters, tumor proliferative capacity, and patients’ survival.Results. Enhanced RCAS1 expression levels were significantly associated with advanced histopathological stage and presence of organ metastasis (P=0.0084andP=0.0327). Gastric cancer patients with elevated RCAS1 expression levels showed significantly shorter survival times compared to those with low RCAS1 expression (log-rank test,P=0.0168). In multivariate analysis, histopathological stage and grade of differentiation as well as the RCAS1 expression were identified as independent prognostic factors (Cox regression analysis,P=0.0204,P=0.0035, andP=0.0081).Conclusions. Our data support the evidence that RCAS1 upregulation may contribute to gastric malignant progression, representing a useful biomarker to predict the biological behaviour and prognosis in gastric neoplasia.

scholarly journals Clinical Implications and Prognostic Values ofProstate Cancer Susceptibility CandidateMethylation in Primary Nonmuscle Invasive Bladder Cancer

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Young-Won Kim ◽  
Hyung-Yoon Yoon ◽  
Sung Pil Seo ◽  
Sang Keun Lee ◽  
Ho Won Kang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Cox Regression ◽  
Cancer Susceptibility ◽  
Methylation Status ◽  
High Rate ◽  
Invasive Bladder Cancer ◽  
Clinicopathological Parameters ◽  
Cox Regression Analysis ◽  
Significant Difference ◽  
Nonmuscle Invasive Bladder Cancer

DNA methylation is the most common and well-characterized epigenetic change in human cancer. Recently, an association betweenprostate cancer susceptibility candidate(PRAC) methylation and genitourinary cancer was proposed. The aim of the present study was to evaluate the association betweenPRACmethylation status and clinicopathological parameters and prognosis in long-term follow-up primary nonmuscle invasive bladder cancer (NMIBC). The clinical relevance ofPRACmethylation was determined in 136 human bladder specimens (eight normal controls [NCs] and 128 primary NMIBCs) using quantitative pyrosequencing analysis.PRACmethylation was significantly higher in NMIBC patients than in NCs and was significantly associated with higher grade and more advanced stage of cancer. Kaplan-Meier estimates revealed significant difference in tumor recurrence and progression according toPRACmethylation status (bothp< 0.05). Multivariate Cox regression analysis revealed that thePRACmethylation status was a strong predictor of recurrence (hazard ratio [HR], 2.652;p= 0.012) and progression (HR, 9.531;p= 0.035) of NMIBC. Enhanced methylation status ofPRACwas positively associated with a high rate of recurrence and progression in NMIBC patients, suggesting thatPRACmethylation may be a promising prognostic marker of NMIBC.

scholarly journals A Novel Autophagy-Related IncRNAs Signature for Prognostic Prediction and Clinical Value in Patients With Pancreatic Cancer

2020 ◽  
Vol 8 ◽  
Author(s):  
Zhengdong Deng ◽  
Xiangyu Li ◽  
Yuanxin Shi ◽  
Yun Lu ◽  
Wei Yao ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Risk Scores ◽  
Migration And Invasion ◽  
Characteristic Analysis ◽  
Cox Regression Analysis ◽  
Validation Set ◽  
Prognostic Prediction

Autophagy is an important bioprocess throughout the occurrence and development of cancer. However, the role of autophagy-related lncRNAs in pancreatic cancer (PC) remains obscure. In the study, we identified the autophagy-related lncRNAs (ARlncRNAs) and divided the PC patients from The Cancer Genome Atlas into training and validation set. Firstly, we constructed a signature in the training set by the least absolute shrinkage and selection operator penalized cox regression analysis and the multivariate cox regression analysis. Then, we validated the independent prognostic role of the risk signature in both training and validation set with survival analysis, receiver operating characteristic analysis, and Cox regression. The nomogram was established to demonstrate the predictive power of the signature. Moreover, high risk scores were significantly correlated to worse outcomes and severe clinical characteristics. The Pearson’s analysis between risk scores with immune cells infiltration, tumor mutation burden, and the expression level of chemotherapy target molecules indicated that the signature could predict efficacy of immunotherapy and targeted therapy. Next, we constructed an lncRNA–miRNA–mRNA regulatory network and identified several potential small molecule drugs in the Connectivity Map (CMap). What’s more, quantitative real-time PCR (qRT-PCR) analysis showed that serum LINC01559 could serve as a diagnostic biomarker. In vitro analysis showed inhibition of LINC01559 suppressed PC cell proliferation, migration, and invasion. Additionally, silencing LINC01559 suppressed gemcitabine-induced autophagy and promoted the sensitivity of PC cells to gemcitabine. In conclusion, we identified a novel ARlncRNAs signature with valuable clinical utility for reliable prognostic prediction and personalized treatment of PC patients. And inhibition of LINC01559 might be a novel strategy to overcome chemoresistance.

scholarly journals A novel ferroptosis-related genes model for prognosis prediction of lung adenocarcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Fei Li ◽  
Dongcen Ge ◽  
Shu-lan Sun
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Prediction Model ◽  
Cox Regression ◽  
Risk Group ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Key Genes ◽  
Validation Set ◽  
Prognostic Prediction

Abstract Background Ferroptosis is a newly discovered form of cell death characterized by iron-dependent lipid peroxidation. This study aims to investigate the potential correlation between ferroptosis and the prognosis of lung adenocarcinoma (LUAD). Methods RNA-seq data were collected from the LUAD dataset of The Cancer Genome Atlas (TCGA) database. Based on ferroptosis-related genes, differentially expressed genes (DEGs) between LUAD and paracancerous specimens were identified. The univariate Cox regression analysis was performed to screen key genes associated with the prognosis of LUAD. LUAD patients were divided into the training set and validation set. Then, we screened out key genes and built a prognostic prediction model involving 5 genes using the least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation and the multivariate Cox regression analysis. After dividing LUAD patients based on the median level of risk score as cut-off value, the generated prognostic prediction model was validated in the validation set. Moreover, we analyzed the somatic mutations, and estimated the scores of immune infiltration in the high-risk and low-risk groups. Functional enrichment analysis of DEGs was performed as well. Results High-risk scores indicated the worse prognosis of LUAD. The maximum area under curve (AUC) of the training set and the validation set in this study was 0.7 and 0.69, respectively. Moreover, we integrated the age, gender, and tumor stage to construct the composite nomogram. The charts indicated that the AUC of LUAD cases with the survival time of 1, 3 and 5 years was 0.698, 0.71 and 0.73, respectively. In addition, the mutation frequency of LUAD patients in the high-risk group was significantly higher than that in the low-risk group. Simultaneously, DEGs were mainly enriched in ferroptosis-related pathways by analyzing the functional results. Conclusions This study constructs a novel LUAD prognosis prediction model involving 5 ferroptosis-related genes, which can be used as a promising tool for decision-making of clinical therapeutic strategies of LUAD.

scholarly journals NDRG2 combined with EGFR improved its prognostic value for lung adenocarcinoma

2019 ◽  
Author(s):  
Bo Yang ◽  
Xiao-Ping Li ◽  
Hong-Gang Zhou ◽  
Tao Jiang ◽  
Ting Xiao ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Growth Factor Receptor ◽  
Prognostic Indicators ◽  
Clinicopathological Parameters ◽  
Clinical Value ◽  
Cox Regression Analysis ◽  
Egfr Expression ◽  
Serum Carcinoembryonic Antigen ◽  
Prediction Of Prognosis

Abstract Background N-Myc downstream-regulated gene2 (NDRG2) plays an important role in lung adenocarcinoma (LUAD). Epidermal growth factor receptor (EGFR) mutation has significantly improved prognosis in patients with adenocarcinoma. We aimed to elucidate the clinical value of NDRG2/EGFR as a prediction of prognosis in patients with lung adenocarcinoma.Materials and Methods Immunohistochemistry and western blot analysis were conducted to detect the expression of NDRG2 protein. Association between NDRG2/EGFR expression and clinicopathological parameters of the patients were examined. Serum Carcinoembryonic antigen (CEA) level was examined prior to treatment in patients with LUAD. Patients’ survival rate was assessed by Kaplan–Meier. Candidates for independent prognostic biomarkers were analyzed using a COX proportional hazard model.Results NDRG2 levels were significantly decreased in patients with lung adenocarcinoma. NDRG2 levels were positively correlated with CEA and EGFR. Advanced stages were significantly associated with low expression of NDRG2. Patients with NDRG2-high combined with EGFR-positive expression had the best prognosis during the 5-year follow-up period. Meanwhile, COX regression analysis showed that the conjoined expressions of NDRG2-low/EGFR-positive, NDRG2-high/EGFR-positive and vascular invasion were independent prognostic indicators for lung adenocarcinoma.Conclusion NDRG2 is of more prognosis value as the biomarker for lung adenocarcinoma when analyzed combined with the EGFR expression.

scholarly journals KK-LC-1 may be an effective prognostic biomarker for gastric cancer

2020 ◽  
Author(s):  
Jun Ji ◽  
Jiahui Chen ◽  
Anqiang Wang ◽  
Wei Zhang ◽  
Hongge Ju ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Cox Regression ◽  
Staining Intensity ◽  
Good Prognosis ◽  
Clinicopathological Parameters ◽  
Chi Square ◽  
Clinical Prognosis ◽  
Cox Regression Analysis ◽  
Normal Tissues

Abstract Background: To detect the expression of Kita-Kyushu lung cancer antigen-1 (KK-LC-1) in gastric cancer (GC) specimens and analyze the associations between KK-LC-1 expression and clinicopathological parameters and clinical prognosis. Methods: A total of 94 patients with GC who underwent surgical resection were enrolled in this study. The expression of KK-LC-1 in GC tissues was detected by immunohistochemistry. The assessment of KK-LC-1 expression was conducted using the H-scoring system. H-score was calculated by the multiplication of the overall staining intensity with the percentage of positive cells. The expression of KK-LC-1 in the cytoplasm and was scored to achieve respective H-score values. The correlations between KK-LC-1 expression and clinicopathological parameters and clinical prognosis were analyzed using Chi-square test, Kaplan-Meier method and Cox regression. Results: In the cytoplasm, the expression of KK-LC-1 in tumor tissues was significantly higher than that in normal tissues (P < 0.001, respectively). Using the median H-score as the cutoff value, it was discovered that, GC patients with higher levels of KK-LC-1expression in the cytoplasm, had favorable overall survival (P =0.016), and it was still statistically meaningful in Cox regression analysis. At the same time, the study found that there was a negative correlation between KK-LC-1’s protein expression and the pathological grade of the tumor (P = 0.036). Conclusions: Our research data shows that KK-LC-1’s expression in GC is higher than that of normal tissues, which is associated with a longer overall survival in GC. KK-LC-1 can be used as a biomarker for GC patients with good prognosis.

scholarly journals Nomogram With a Novel Microenvironment Signature Is Systematically Constructed and Validated to Predict the Survival Rate of Glioma Patients.

2020 ◽  
Author(s):  
Tianhua Li ◽  
Yiguang Chen ◽  
Yongjian Chen ◽  
Guangjie Liu ◽  
Shisheng Zou ◽  
...  
Keyword(s):  
Cox Regression ◽  
Malignant Tumors ◽  
Prognostic Index ◽  
Enrichment Analysis ◽  
Basic Research ◽  
Predictive Performance ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
Cox Regression Analysis ◽  
Kegg Pathways

Glioma accounts for the highest proportion of primary intracranial malignant tumors. Microenvironment enormously influences the process of glioma progression. Our study is to establish an individualized prognostic nomogram for glioma patients with microenvironment signature. Glioma samples of Chinese Glioma Genome Atlas (CGGA) were grouped by the immune and stromal score based on ESTIMATE algorithm. Microenvironment-related genes (MRGs) in glioma were analyzed by R. To determine the best prognostic correlation genes, univariate and multivariate Cox regression analysis were used to analyze MRGs. Use the selected genes (CHI3L1, SOCS3, SLC47A2, COL3A1, SRPX2 and SERPINA3), we established the prognostic risk score model (microenvironment signature) and validated it. Gene Set Enrichment Analysis (GSEA) showed that the high-risk group was mainly enriched in immune and stromal function KEGG pathways. Finally, the nomogram was constructed and evaluated. The receiver operating characteristic (ROC) curve, Calibration plots and decision curve analysis (DCA) of training and validation set indicated the excellent predictive performance of nomogram. In conclusion, the 6-gene microenvironment signature can not only provide directions for the basic research of glioma, but also can be included as an independent prognostic index in nomogram for individual prediction to guide clinical treatment.

Sign in / Sign up

Export Citation Format

Share Document