scholarly journals Identification of a Vascular Invasion-Related miRNA Signature For Predicting the Prognosis of Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xinze Qiu ◽  
Jiangni Wu ◽  
Zichen Huang ◽  
Shibo Luo ◽  
Jiean Huang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Risk Score ◽  
Vascular Invasion ◽  
Risk Group ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
High Risk Group ◽  
Mirna Signature ◽  
Training Set ◽  
Validation Set

Abstract Background: Vascular invasion is closely related to the prognosis of hepatocellular carcinoma (HCC). Increasing evidence suggests that miRNAs can serve as biomarks to predict prognosis in various tumors. Thus, the aim of this study was to develop a novel, vascular invasion-related miRNA signature for prediction of HCC prognosis.Methods: Differentially expressed miRNAs (DEMs) between HCC samples with vascular invasion and without vascular invasion were obtained from GSE67140. MiRNAs expression profiles and clinical information for 344 patients were collected from The Cancer Genome Atlas database, and the patients were randomized (1:1) to training set and validation set. LASSO regression model was employed to identify survival-associated DEMs and establish risk score in the training set. Moreover, risk score was verified in the validation set. And nomogram based on risk score and clinical information was constructed to improve the prediction of prognosis. Meanwhile, four online tools were used to predict target genes and enrichment analysis was utilized to explore the biological pathway of the miRNAs.Results: A novel three-miRNA signature was screened including hsa-mir-210, hsa-mir-149 and hsa-mir-99a, and risk score was established for HCC prognosis prediction. Patients were divided into the low-risk group and high-risk group according to risk score. High-risk group both have higher hazard of death compared with low-risk group in training set and validation set. And the 5-year AUC of risk score were 0.718, 0.674 and 0.697 in training set, validation set and the total set, respectively. The C-index of nomogram was 0.724, and calibration curves showed nomogram had high concordance to predict 1- ,3- , and 5-year survival rates among HCC patients. Furthermore, enrichment analysis identified several tumor-associated pathways including Ras signaling pathway, PI3K-Akt signaling pathway, and MAPK signaling pathway and so on, which may contribute to explain the potential molecular mechanisms of above miRNAs.Conclusion: This study developed a risk assessment model based on three miRNAs, which could accurately predict the prognosis of HCC.

scholarly journals Identification of 3-miRNA Signature for Predicting Prognosis in Patients with Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xinze Qiu ◽  
Jiangni Wu ◽  
Zichen Huang ◽  
Shibo Luo ◽  
Jiean Huang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Risk Score ◽  
Vascular Invasion ◽  
Risk Group ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
High Risk Group ◽  
Mirna Signature ◽  
Training Set ◽  
Validation Set

Abstract Background: Vascular invasion is closely related to the prognosis of hepatocellular carcinoma (HCC). Increasing evidence suggests that miRNAs can serve as biomarks to predict prognosis in various tumors. Thus, the aim of this study was to develop a novel, vascular invasion-related miRNA signature for prediction of HCC prognosis.Methods: Differentially expressed miRNAs (DEMs) between HCC samples with vascular invasion and without vascular invasion were obtained from GSE67140. MiRNAs expression profiles and clinical information for 344 patients were collected from The Cancer Genome Atlas database, and the patients were randomized (1:1) to training set and validation set. LASSO regression model was employed to identify survival-associated DEMs and establish risk score in the training set. Moreover, risk score was verified in the validation set. And nomogram based on risk score and clinical information was constructed to improve the prediction of prognosis. Meanwhile, four online tools were used to predict target genes and enrichment analysis was utilized to explore the biological pathway of the miRNAs.Results: A novel three-miRNA signature was screened including hsa-mir-210, hsa-mir-149 and hsa-mir-99a, and risk score was established for HCC prognosis prediction. Patients were divided into the low-risk group and high-risk group according to risk score. High-risk group both have higher hazard of death compared with low-risk group in training set and validation set. And the 5-year AUC of risk score were 0.718, 0.674 and 0.697 in training set, validation set and the total set, respectively. The C-index of nomogram was 0.724, and calibration curves showed nomogram had high concordance to predict 1- ,3- , and 5-year survival rates among HCC patients. Furthermore, enrichment analysis identified several tumor-associated pathways including Ras signaling pathway, PI3K-Akt signaling pathway, and MAPK signaling pathway and so on, which may contribute to explain the potential molecular mechanisms of above miRNAs.Conclusion: This study developed a risk assessment model based on three miRNAs, which could accurately predict the prognosis of HCC.

scholarly journals An 8 miRNA-Based Risk Score System for Predicting the Prognosis of Patients With Papillary Thyroid Cancer

2020 ◽  
Vol 19 ◽  
pp. 153303382096559
Author(s):  
Wanwan Yi ◽  
Jin Liu ◽  
Shuping Qu ◽  
Hengwei Fan ◽  
Zhongwei Lv
Keyword(s):  
Signaling Pathway ◽  
Risk Score ◽  
Hedgehog Signaling ◽  
Mirna Gene ◽  
Enrichment Analysis ◽  
Training Set ◽  
Score System ◽  
Gene Regulatory ◽  
Validation Set ◽  
Risk Score System

Background: Dysregulation of microRNAs (miRNAs) in papillary thyroid cancer (PTC) might influence prognosis of PTC. This study is aimed to develop a risk score system for predicting prognosis of PTC. Methods: The miRNA and gene expression profiles of PTC were obtained from The Cancer Genome Atlas database. PTC samples were randomly separated into training set (n = 248) and validation set (n = 248). The differentially expressed miRNAs (DE-miRNAs) in the training set were screened using limma package. The independent prognosis-associated DE-miRNAs were identified for building a risk score system. Risk score of PTC samples in the training set was calculated and samples were divided into high risk group and low risk group. Kaplan-Meier curves and receiver operating characteristic (ROC) curve were used to assess the accuracy of the risk score system in the training set, validation set and entire set. Finally, a miRNA-gene regulatory network was visualized by Cytoscape software, followed by enrichment analysis. Results: Totally, 162 DE-miRNAs between tumor and control groups in the training set were identified. An 8 independent prognosis-associated DE-miRNAs, (including miR-1179, miR-133b, miR-3194, miR-3912, miR-548j, miR-6720, miR-6734, and miR-6843) based risk score system was developed. The area under ROC curve in the training set, validation set and entire set was all above 0.93. A miRNA-gene regulatory network involving the 8 DE-miRNAs were built and functional enrichment analysis suggested the genes in the network were significantly enriched into 13 pathways, including calcium signaling pathway and hedgehog signaling pathway. Conclusion: The risk score system developed this study might be used for predicting the prognosis of PTC. Besides, the 8 miRNAs might affect the prognosis of PTC via hedgehog signaling pathway and calcium signaling pathway.

A Hypoxia-related LncRNA Signature Predicts Survival of Primary Lower-grade glioma

2021 ◽  
Author(s):  
Yanjia Hu ◽  
Jing Zhang ◽  
Jing Chen
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Gene Set Enrichment Analysis ◽  
Lower Grade ◽  
Prognostic Signature ◽  
Gene Set Enrichment

Abstract Background Hypoxia-related long non-coding RNAs (lncRNAs) have been proven to play a role in multiple cancers and can serve as prognostic markers. Lower-grade gliomas (LGGs) are characterized by large heterogeneity. Methods This study aimed to construct a hypoxia-related lncRNA signature for predicting the prognosis of LGG patients. Transcriptome and clinical data of LGG patients were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LGG cohort in TCGA was chosen as training set and LGG cohorts in CGGA served as validation sets. A prognostic signature consisting of fourteen hypoxia-related lncRNAs was constructed using univariate and LASSO Cox regression. A risk score formula involving the fourteen lncRNAs was developed to calculate the risk score and patients were classified into high- and low-risk groups based on cutoff. Kaplan-Meier survival analysis was used to compare the survival between two groups. Cox regression analysis was used to determine whether risk score was an independent prognostic factor. A nomogram was then constructed based on independent prognostic factors and assessed by C-index and calibration plot. Gene set enrichment analysis and immune cell infiltration analysis were performed to uncover further mechanisms of this lncRNA signature. Results LGG patients with high risk had poorer prognosis than those with low risk in both training and validation sets. Recipient operating characteristic curves showed good performance of the prognostic signature. Univariate and multivariate Cox regression confirmed that the established lncRNA signature was an independent prognostic factor. C-index and calibration plots showed good predictive performance of nomogram. Gene set enrichment analysis showed that genes in the high-risk group were enriched in apoptosis, cell adhesion, pathways in cancer, hypoxia etc. Immune cells were higher in high-risk group. Conclusion The present study showed the value of the 14-lncRNA signature in predicting survival of LGGs and these 14 lncRNAs could be further investigated to reveal more mechanisms involved in gliomas.

scholarly journals Genome-Wide Identification of a Novel Autophagy-Related Signature for Colorectal Cancer

Dose-Response ◽  
2019 ◽  
Vol 17 (4) ◽  
pp. 155932581989417 ◽  
Author(s):  
Zhi Huang ◽  
Jie Liu ◽  
Liang Luo ◽  
Pan Sheng ◽  
Biao Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Signaling Pathway ◽  
Risk Score ◽  
Low Risk ◽  
Training Data ◽  
The Cancer Genome Atlas ◽  
Training Set ◽  
Data Set ◽  
Validation Set ◽  
Cox Analysis

Background: Plenty of evidence has suggested that autophagy plays a crucial role in the biological processes of cancers. This study aimed to screen autophagy-related genes (ARGs) and establish a novel a scoring system for colorectal cancer (CRC). Methods: Autophagy-related genes sequencing data and the corresponding clinical data of CRC in The Cancer Genome Atlas were used as training data set. The GSE39582 data set from the Gene Expression Omnibus was used as validation set. An autophagy-related signature was developed in training set using univariate Cox analysis followed by stepwise multivariate Cox analysis and assessed in the validation set. Then we analyzed the function and pathways of ARGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Finally, a prognostic nomogram combining the autophagy-related risk score and clinicopathological characteristics was developed according to multivariate Cox analysis. Results: After univariate and multivariate analysis, 3 ARGs were used to construct autophagy-related signature. The KEGG pathway analyses showed several significantly enriched oncological signatures, such as p53 signaling pathway, apoptosis, human cytomegalovirus infection, platinum drug resistance, necroptosis, and ErbB signaling pathway. Patients were divided into high- and low-risk groups, and patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both training set and validation set. Furthermore, the nomogram for predicting 3- and 5-year OS was established based on autophagy-based risk score and clinicopathologic factors. The area under the curve and calibration curves indicated that the nomogram showed well accuracy of prediction. Conclusions: Our proposed autophagy-based signature has important prognostic value and may provide a promising tool for the development of personalized therapy.

A Simple Clinical Prognostic Scoring System for Newly Diagnosed Cytogenetically Normal Acute Myeloid Leukemia: a Retrospective Analysis on 530 Patients

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 4848-4848
Author(s):  
Michele Malagola ◽  
Crisitina Skert ◽  
Marco Vignetti ◽  
Alfonso Piciocchi ◽  
Giovanni Martinelli ◽  
...  
Keyword(s):  
High Risk ◽  
Myeloid Leukemia ◽  
Regression Coefficient ◽  
Risk Group ◽  
High Risk Group ◽  
Newly Diagnosed ◽  
Training Set ◽  
Secondary Aml ◽  
Induction Regimen ◽  
Validation Set

Abstract Abstract 4848 Objectives: the prognosis of patients with cytogenetically normal acute myeloid leukemia (CN-AML) is highly variable and can be influenced by several clinical and biological variables. Nevertheless, some biological data may be conflicting and difficult to combine with the clinical ones. Methods: in order to propose a simple scoring system, we retrospectively analysed the clinical data of 337 patients newly diagnosed with CN-AMLs, aged less than 65 years, consecutively treated in eleven hematological Italian Centres from 1990 to 2005. Two hundred nineteen patients (65%) received a fludarabine-based induction regimen. All the other patients received a conventional induction regimen, including cytarabine, one anthracycline with or without etoposide. Univariate and multivariate analysis on event free survival and overall survival (EFS and OS) were performed. Patients addressed to allogeneic stem cell transplantation were censored at the time of transplant. Factors found to be significant in univariate analysis were tested in multivariate analysis. A numerical score was derived from the regression coefficients of each independent prognostic variable. The Prognostic Index Score (PIS) for each patient was then calculated by totalling up the score of each independent variable. Patients could thus be stratified into low-risk (score = 0–1), intermediate-risk (score = 2) and high-risk group (score grater than 3). The score obtained in this group of patients (training set) was then tested on 193 patients with newly diagnosed with CN-AMLs, aged less than 65 years, enrolled in the GIMEMA LAM99p clinical trial (validation set). Results: the clinical variables that were independent prognostic factors on EFS in the training set of patients were: age > 50 yrs (regression coefficient: 0.39, HR 1.5, score = 1), secondary AML (regression coefficient: 0.90, HR 2.5, score = 2) and WBC > 20 × 10^9/L (regression coefficient: 0.83, HR 2.3, score = 2). For what concerns the OS, the same variables showed the followings statistical data: age > 50 yrs (regression coefficient: 0.48, HR 1.6, score = 1), secondary AML (regression coefficient: 0.99, HR 2.7, score = 2) and WBC > 20 × 10^ 9/L (regression coefficient: 0.87, HR 2.4, score = 2). In the training set of patients, the median EFS was 22, 12 and 8 months in the low, intermediate and high-risk group (p<0.0001). The median OS was not reached in the low-risk group and was 20 and 10 months in the intermediate and high-risk group (p<0.0001). In the validation set of patients, the median EFS was 66, 16 and 3 months in the low, intermediate and high-risk group (p<0.0001). The median OS was 66, 16 and 4 months in the low, intermediate and high-risk group (p<0.0001). Conclusions: this simple and reproducible prognostic score may be useful for clinical-decision making in newly diagnosed patients with CN-AMLs, aged less than 65 yrs. Moreover, it can be clinically useful when the molecular prognostic markers are lacking (e.g. in emerging laboratories of some developing countries) or give contradictory results. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Identification of the 11-lncRNA signatures associated with the prognosis of endometrial carcinoma

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042110065
Author(s):  
Jing Wan ◽  
Peigen Chen ◽  
Yu Zhang ◽  
Jie Ding ◽  
Yuebo Yang ◽  
...  
Keyword(s):  
High Risk ◽  
Endometrial Carcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Training Set ◽  
Lncrna Expression ◽  
Robust Likelihood

Endometrial carcinoma (EC) is the fourth most common cancer in women. Some long non-coding RNAs (lncRNAs) are regarded as potential prognostic biomarkers or targets for treatment of many types of cancers. We aim to screen prognostic-related lncRNAs and build a possible lncRNA signature which can effectively predict the survival of patients with EC. We obtained lncRNA expression profiling from the TCGA database. The patients were classified into training set and verification set. By performing Univariate Cox regression model, Robust likelihood-based survival analysis, and Cox proportional hazards model, we developed a risk score with the Cox co-efficient of individual lncRNAs in the training set. The optimum cut-off point was selected by ROC analysis. Patients were effectively divided into high-risk group and low-risk group according to the risk score. The OS of the low-risk patients was significantly prolonged compared with that of the high-risk group. At last, we validated this 11-lncRNA signature in the verification set and the complete set. We identified an 11-lncRNA expression signature with high stability and feasibility, which can predict the survival of patients with EC. These findings provide new potential biomarkers to improve the accuracy of prognosis prediction of EC.

scholarly journals Development and Validation of a Lncrnas-Based Nomogram for Survival Prediction in Neuroblastoma Patients

2021 ◽  
Author(s):  
Yong Lv ◽  
ShuGuang Jin ◽  
Bo Xiang
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Validation Cohort ◽  
Risk Group ◽  
Enrichment Analysis ◽  
High Risk Group ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment

Abstract BackgroundTreatment of neuroblastoma is evolving toward precision medicine. LncRNAs can be used as prognostic biomarkers in many types of cancer.MethodsBased on the RNA-seq data from GSE49710, we built a lncRNAs-based risk score using the least absolute shrinkage and selection operation (LASSO) regression. Cox regression, receiver operating characteristic curves were used to evaluate the association of the LASSO risk score with overall survival. Nomograms were created and then validated in an external cohort from TARGET database. Gene set enrichment analysis was performed to identify the significantly changed biological pathways. ResultsThe 16-lncRNAs-based LASSO risk score was used to separate patients into high-risk and low-risk groups. In GSE49710 cohort, the high-risk group exhibited a poorer OS than those in the low-risk group (P<0.001). Moreover, multivariate Cox regression analysis demonstrated that LASSO risk score was an independent risk factor (HR=6.201;95%CI:2.536-15.16). The similar prognostic powers of the 16-lncRNAs were also achieved in the external cohort and in stratified analysis. In addition, a nomogram was established and worked well both in the internal validation cohort (C-index=0.831) and external validation cohort (C-index=0.773). The calibration plot indicated the good clinical utility of the nomogram. Gene set enrichment analysis (GSEA) indicated that high-risk group was related with cancer recurrence, metastasis and inflammatory associated pathways.ConclusionThe lncRNA-based LASSO risk score is a promising and potential prognostic tool in predicting the survival of patients with neuroblastoma. The nomogram combined the lncRNAs and clinical parameters allows for accurate risk assessment in guiding clinical management.

Circulating Exosomal microRNAs Are Prognostic Markers in Multiple Myeloma

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1770-1770
Author(s):  
Salomon Manier ◽  
Herve Avet-Loiseau ◽  
Federico Campigotto ◽  
Karma Salem ◽  
Daisy Huynh ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Risk Score ◽  
Prognostic Value ◽  
Prognostic Significance ◽  
Newly Diagnosed ◽  
Mirna Signature ◽  
Training Set ◽  
Advisory Committees ◽  
Exosomal Mirnas ◽  
Validation Set

Abstract Background Exosomes are secreted by several cell types including cancer cells and can be isolated from peripheral blood. They contain proteins and nucleic acids and promote tumorigenesis in many types of cancer. We aimed to establish the prognostic significance of circulating exosomal microRNAs (miRNAs) in multiple myeloma (MM). Methods We first analyzed the miRNAs content of circulating exosomes in MM by small RNA sequencing of 10 samples from MM patients and 5 healthy controls. We then analyzed 156 serum samples from newly diagnosed patients with MM, uniformly treated with a Bortezomib and Dexamethasone based regimen. Using a quantitative RT-PCR array for 23 miRNAs, we assessed the associations between exosomal miRNAs and progression-free survival. Findings By next generation sequencing, we identified 158 differentially expressed miRNAs in MM compared to normal healthy controls, notably including let-7 family members, miR-17/92 or miR-99b/125a clusters. We further identified a three-miRNA signature based on 156 MM samples (combining miR-106b, miR-18a and let-7e) and calculated a risk score to classify patients as high risk or low risk. Compared to low risk score, patients with a high risk score had a shorter PFS in the training set (hazard ratio [HR] 1·8, 95% CI 1·0-3·0; p=0·0375) and the validation set (HR 2·6, 1·5-4·4; p=0·0005). To further validate this signature, we generated 500 randomly computed re-sampling of the data sets. The three-miRNA signature was consistently significant with a p-value < 0·05 in more than 78% and < 0·10 in 86% of the 500 randomizations. The circulating exosomal miRNA signature was an independent prognostic marker after adjusting for cytogenetics and ISS. In a receiver operating characteristic (ROC) analysis, a combination of this signature together with International Staging System (ISS) and cytogenetics had a better prognostic value than ISS and cytogenetics alone in the training set (2 years area under the ROC curve 0·64 [95% CI 0·56-0·72] vs. 0·60 [95% CI 0·52-0·69]) and the validation set (0·67 [0·59-0·75] vs. 0·58 [0·50-0·66]). Interpretation This study demonstrates unprecedented evidence of the prognostic significance of exosomal miRNAs in patients with MM. We identified a three-miRNA signature in circulating exosomes that adds prognostic value to ISS and cytogenetic status and helps improve prognostic identification of newly diagnosed MM patients. Disclosures Avet-Loiseau: jansen: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; onyx: Membership on an entity's Board of Directors or advisory committees; onyx: Membership on an entity's Board of Directors or advisory committees; jansen: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Moreau:Celgene, Janssen, Takeda, Novartis, Amgen: Membership on an entity's Board of Directors or advisory committees. Facon:Onyx: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Pierre Fabre: Membership on an entity's Board of Directors or advisory committees.

scholarly journals Prognostic Value of an Immunohistochemical Signature in Patients With Head and Neck Mucosal Melanoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Qing-Qing Xu ◽  
Qing-Jie Li ◽  
Cheng-Long Huang ◽  
Mu-Yan Cai ◽  
Mei-Fang Zhang ◽  
...  
Keyword(s):  
High Risk ◽  
Head And Neck ◽  
Risk Group ◽  
High Risk Group ◽  
Mucosal Melanoma ◽  
Low Risk ◽  
Training Set ◽  
T Stage ◽  
Validation Set ◽  
Ihc Markers

PurposeWe aimed to develop a prognostic immunohistochemistry (IHC) signature for patients with head and neck mucosal melanoma (MMHN).MethodsIn total, 190 patients with nonmetastatic MMHN with complete clinical and pathological data before treatment were included in our retrospective study.ResultsWe extracted five IHC markers associated with overall survival (OS) and then constructed a signature in the training set (n=116) with the least absolute shrinkage and selection operator (LASSO) regression model. The validation set (n=74) was further built to confirm the prognostic significance of this classifier. We then divided patients into high- and low-risk groups according to the IHC score. In the training set, the 5-year OS rate was 22.0% (95% confidence interval [CI]: 11.2%- 43.2%) for the high-risk group and 54.1% (95% CI: 41.8%-69.9%) for the low-risk group (P&lt;0.001), and in the validation set, the 5-year OS rate was 38.1% (95% CI: 17.9%-81.1%) for the high-risk group and 43.1% (95% CI: 30.0%-61.9%) for the low-risk group (P=0.26). Multivariable analysis revealed that IHC score, T stage, and primary tumor site were independent variables for predicting OS (all P&lt;0.05). We developed a nomogram incorporating clinicopathological risk factors (primary site and T stage) and the IHC score to predict 3-, 5-, and 10-year OS.ConclusionsA nomogram was generated and confirmed to be of clinical value. Our IHC classifier integrating five IHC markers could help clinicians make decisions and determine optimal treatments for patients with MMHN.

scholarly journals Development and Validation of a Seven-Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yingqing Zhang ◽  
Xiaoping Zhang ◽  
Xiaodong Lv ◽  
Ming Zhang ◽  
Xixi Gao ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
Clinical Information ◽  
R Package ◽  
Tumor Stage ◽  
Gene Signature ◽  
High Risk Group ◽  
Kaplan Meier

Background. Prognosis is a main factor affecting the survival of patients with lung adenocarcinoma (LUAD), yet no robust prognostic model of high effectiveness has been developed. This study is aimed at constructing a stable and practicable gene signature-based model via bioinformatics methods for predicting the prognosis of LUAD sufferers. Methods. The mRNA expression data were accessed from the TCGA-LUAD dataset, and paired clinical information was collected from the GDC website. R package “edgeR” was employed to select the differentially expressed genes (DEGs), which were then used for the construction of a gene signature-based model via univariate COX, Lasso, and multivariate COX regression analyses. Kaplan-Meier and ROC survival analyses were conducted to comprehensively evaluate the performance of the model in predicting LUAD prognosis, and an independent dataset GSE26939 was accessed for further validation. Results. Totally, 1,655 DEGs were obtained, and a 7-gene signature-based risk score was developed and formulated as risk_score=0.000245∗NTSR1+7.13E−05∗RHOV+0.000505∗KLK8+7.01E−05∗TNS4+0.000288∗C1QTNF6+0.00044∗IVL+0.000161∗B4GALNT2. Kaplan-Meier survival curves revealed that the survival rate of patients in the high-risk group was lower in both the TCGA-LUAD dataset and GSE26939 relative to that of patients in the low-risk group. The relationship between the risk score and clinical characteristics was further investigated, finding that the model was effective in prognosis prediction in the patients with different age (age>65, age<65) and TNM stage (N0&N1, T1&T2, and tumor stage I/II). In sum, our study provides a robust predictive model for LUAD prognosis, which boosts the clinical research on LUAD and helps to explore the mechanism underlying the occurrence and progression of LUAD.

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