Stromal Score-based Gene Signature: A Prognostic Prediction Model for Colon Cancer

2020 ◽  
Author(s):  
Jing Jia ◽  
Yuhan Dai ◽  
Qing Zhang ◽  
Peiyu Tang ◽  
Qiang Fu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Prediction Model ◽  
Differentially Expressed Genes ◽  
Gene Signature ◽  
Rank Test ◽  
Regression Analyses ◽  
Log Rank Test ◽  
Auc Value ◽  
Prognostic Prediction

Abstract BackgroundGrowing evidence has revealed the crucial roles of stromal cells in the microenvironment of various malignant tumors. However, efficient prognostic signatures based on stromal characteristics in colon cancer have not been well-established yet. The present study aimed to construct a stromal score-based multigene prognostic prediction model for colon cancer.MethodStromal scores were calculated based on the expression profiles of a colon cancer cohort from TCGA database applying the ESTIMATE algorithm. Linear models were used to identify differentially expressed genes between low-score and high-score groups by limma R package. Univariate and multivariate CoxPH regression analyses were used successively to select prognostic gene signature. An independent dataset from GEO was used as a validation cohort.ResultsLow stromal score was demonstrated to be a favorable factor to overall survival of colon cancer patients in TCGA cohort (log-rank test p = 0.0046). Three hundred and seven stromal score-related differentially expressed genes were identified. Through univariate and multivariate CoxPH regression analyses, a gene signature consisting of LEP, SYT3, NOG and IGSF11 was recognized to build a prognostic prediction model. Based on the predictive values estimated by the established integrated model, patients were divided into two groups with significantly different overall survival outcomes (log-rank test p < 0.0001). Time-dependent Receiver operating characteristic curve analyses suggested the satisfactory predictive efficacy for 5-year overall survival of the model (AUC value = 0.736). A nomogram with great predictive performance combining the multigene prediction model and clinicopathological factors was developed. The established model was verified to be of significant prognostic value for different subgroups in an independent colon cancer cohort from GEO database, which was demonstrated to be especially accurate for young patients (AUC value = 0.752). ConclusionThe well-established model based on stromal score-related gene signature might serve as a promising tool for the prognostic prediction of colon cancer.

scholarly journals Stromal Score-Based Gene Signature: A Prognostic Prediction Model for Colon Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Jing Jia ◽  
Yuhan Dai ◽  
Qing Zhang ◽  
Peiyu Tang ◽  
Qiang Fu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Prediction Model ◽  
Differentially Expressed Genes ◽  
Cox Regression ◽  
Gene Signature ◽  
Differentially Expressed ◽  
Model Based ◽  
Auc Value ◽  
Prognostic Prediction

BackgroundGrowing evidence has revealed the crucial roles of stromal cells in the microenvironment of various malignant tumors. However, efficient prognostic signatures based on stromal characteristics in colon cancer have not been well-established yet. The present study aimed to construct a stromal score-based multigene prognostic prediction model for colon cancer.MethodsStromal scores were calculated based on the expression profiles of a colon cancer cohort from TCGA database applying the ESTIMATE algorithm. Linear models were used to identify differentially expressed genes between low-score and high-score groups by limma R package. Univariate, LASSO, and multivariate Cox regression models were used successively to select the prognostic gene signature. Two independent datasets from GEO were used as external validation cohorts.ResultsLow stromal score was demonstrated to be a favorable factor to the overall survival of colon cancer patients in TCGA cohort (p = 0.0046). Three hundred and seven stromal score-related differentially expressed genes were identified. Through univariate, LASSO, and multivariate Cox regression analyses, a gene signature consisting of LEP, NOG, and SYT3 was recognized to build a prognostic prediction model. Based on the predictive values estimated by the established integrated model, patients were divided into two groups with significantly different overall survival outcomes (p &lt; 0.0001). Time-dependent Receiver operating characteristic curve analyses suggested the satisfactory predictive efficacy for the 5-year overall survival of the model (AUC value = 0.733). A nomogram with great predictive performance combining the multigene prediction model and clinicopathological factors was developed. The established model was validated in an external cohort (AUC value = 0.728). In another independent cohort, the model was verified to be of significant prognostic value for different subgroups, which was demonstrated to be especially accurate for young patients (AUC value = 0.763).ConclusionThe well-established model based on stromal score-related gene signature might serve as a promising tool for the prognostic prediction of colon cancer.

The impact of nodal metastasis on survival in stage IV colon cancer: Analysis of National Cancer Database 2004-2014.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15042-e15042
Author(s):  
Sukamal Saha ◽  
Mohamed Elgamal ◽  
Meghan Cherry ◽  
Robin Buttar ◽  
David Wiese ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Stage Iv ◽  
Nodal Metastasis ◽  
Rank Test ◽  
National Cancer Database ◽  
Log Rank Test ◽  
Kaplan Meier ◽  
Stage Iv Disease ◽  
The Impact

e15042 Background: Lymph node (LN) metastasis (mets) is the strongest prognostic factor in colon cancer (CCa), however, its significance in Stage IV disease remains controversial. We analysed National Cancer Database (NCDB) to determine the impact of nodal mets on survival in Stage IV CCa patients (pts). Methods: From 2004-2014, NCDB pts with pathologic Stage IV CCa were divided into groups based on LN status and No. of +ve LNs. Only Stage IV CCa pts who underwent surgical resection of their primary tumor with available pathologic data as well as chemotherapy data were included. Kaplan-Meier method and log rank test were used to compare 5-year overall survival. Results: A total of 33574 pts data met the criteria of the study. Adenocarcinoma represented 82.3% of the total pts. Majority of the pts (82.61%) had +ve LN status. Mean survival was 36.3 vs 24.2 months in -ve LN vs +ve LN pts respectively. Overall 5yr survival was better in LN -ve pts ( 23.4%) versus LN +ve pts ( 10.2%) Survival for all years was inversely related to the number of +ve LN ( Table). For LN +ve or LN -ve pts, receiving any form of chemotherapy was associated with significantly improved survival when compared to no chemotherapy. Conclusions: LN status and No. of +ve LNs impact the prognosis of CCa, even in stage IV. Receiving some form of chemotherapy improves the prognosis for both pts with +ve or -ve LN status. These findings suggest that separation of Stage IV LN negative versus positive patients may be warranted in staging and treatment. 5 year survival according to LN status and No. of positive LN. [Table: see text]

scholarly journals Implication of Microsatellite Instability Pathway in Outcome of Colon Cancer in Moroccan Population

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Fatima El Agy ◽  
Ihssane El Otmani ◽  
Asmae Mazti ◽  
Nada Lahmidani ◽  
Abdelmalek Oussaden ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Microsatellite Instability ◽  
Statistical Significance ◽  
Clinicopathological Features ◽  
Rank Test ◽  
Tumor Subtypes ◽  
Log Rank Test ◽  
Kaplan Meier ◽  
Mmr Proteins

Background. Tumors with microsatellite instability (MSI tumors) have distinct clinicopathological features. However, the relation between these tumor subtypes and survival in colon cancer remains controversial. The aim of this study was to evaluate the overall survival (OS) in patients with MSI phenotype, in FES population. Methods. The expression of MMR proteins was evaluated by immunohistochemistry for 330 patients. BRAF, KRAS, and NRAS mutations were examined by Sanger sequencing and pyrosequencing methods. The association of MSI status with a patient’s survival was assessed by the Kaplan–Meier method and log-rank test. Results. The mean age was 54.6 years (range of 19-90 years). The MSI status was found in 11.2% of our population. MSI tumors were significantly associated with male gender, younger patients, stage I-II, right localization, and a lower rate of lymph node and distant metastasis. The OS tends to be longer in MSI tumors than MSS tumors (109.71 versus 74.08), with a difference close to significance (P=0.05). Conclusion. Our study demonstrates that MSI tumors have a particular clinicopathological features. The results of survival analysis indicate that the MSI status was not predictive of improved overall survival in our context with a lower statistical significance (P=0.05) after multivariate analysis.

Concomitant Cisplatin Significantly Improves Locoregional Control in Advanced Head and Neck Cancers Treated With Hyperfractionated Radiotherapy

2004 ◽  
Vol 22 (23) ◽  
pp. 4665-4673 ◽  
Author(s):  
Pia Huguenin ◽  
Karl T. Beer ◽  
Abdelkarim Allal ◽  
Kaspar Rufibach ◽  
Corinne Friedli ◽  
...  
Keyword(s):  
Overall Survival ◽  
Treatment Failure ◽  
Head And Neck ◽  
Combined Treatment ◽  
Late Toxicity ◽  
Locoregional Control ◽  
Rank Test ◽  
Hyperfractionated Radiotherapy ◽  
Log Rank Test ◽  
Metastatic Relapse

Purpose To determine whether the application of two courses of cisplatin simultaneously with hyperfractionated radiotherapy improves the outcome in locally advanced and/or node-positive nonmetastatic carcinomas of the head and neck, compared with hyperfractionated radiotherapy alone. Patients and Methods From July 1994 to July 2000, 224 patients with squamous cell carcinomas of the head and neck (excluding nasopharynx and paranasal sinus) were randomly assigned to hyperfractionated radiotherapy (median dose, 74.4 Gy; 1.2 Gy twice daily) or the same radiotherapy combined with two cycles of concomitant cisplatin (20 mg/m2 on 5 days of weeks 1 and 5). The primary end point was time to any treatment failure; secondary end points were locoregional failure, metastatic relapse, overall survival, and late toxicity. Results There was no difference in radiotherapy between both treatment arms (74.4 Gy in 44 days). The full cisplatin dose was applied in 93% and 71% of patients during the first and second treatment cycles, respectively. Acute toxicity was similar in both arms. Median time to any treatment failure was not significantly different between treatment arms (19 months for combined treatment and 16 months for radiotherapy only, respectively) and the failure-free rate at 2.5 years was 45% and 33%, respectively. Locoregional control and distant disease–free survival were significantly improved with cisplatin (log-rank test, P = .039 and .011, respectively). The difference in overall survival did not reach significance (log-rank test, P = .147). Late toxicity was comparable in both treatment groups. Conclusion The therapeutic index of hyperfractionated radiotherapy is improved by concomitant cisplatin.

Bioinformatics Analysis of The Expression of ATP Binding Cassette Transporters and The Screening of Regulatory Genes in PTEN/PI3K/Akt/mTOR Signaling Pathway in The Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Tingdan Zheng ◽  
Wuqi Song ◽  
Aiying Yang
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Bioinformatics Analysis ◽  
Wilcoxon Test ◽  
Rank Test ◽  
Short Term ◽  
Term Survival ◽  
Log Rank Test ◽  
Short Term Survival

Abstract Objective Here we performed the Bioinformatics analysis on the data from The Cancer Genome Atlas (TCGA), in order to find the correlation between the expression of ATP Binding Cassette (ABC) Transporters’ genes and hepatocellular carcinoma (HCC) prognosis; Methods Transcriptome profiles and clinical data of HCC were obtained from TCGA database. Package edgeR was used to analyze differential gene expression. Patients were divided into low-ABC expression and high-ABC expression groups based on the median expression level of ABC genes in cancer. The overall survival and short-term survival (n= 341) of the two groups was analyzed using the log-rank test and Wilcoxon test; Results We found that ABC gene expression was correlated with the expression of PIK3C2B (p<0.001, ABCC1: r=0.27; ABCC10: r=0.57; ABCC4: r=0.20; ABCC5: r=0.28; ABCB9: r=0.17; ABCD1: r=0.21). All patients with low-ABC expression showed significantly increased overall survival. Significantly decreased overall survival (Log-rank test: p<0.05, Wilcoxon test: p<0.05) was found in patients with high expression of ABCC1 (HR=1.58), ABCD1 (HR=1.45), ABCC4 (HR=1.56), and ABCC5 (HR=1.64), while decreased short-term survival (Log-rank test: p>0.05, Wilcoxon test: p<0.05) was correlated with the increased expression of ABCC10 (HR=1.29), PIK3C2B (HR=1.29) and ABCB9 (HR=1.23); Conclusions Our findings indicate that the specific ABC gene expression correlates with the prognosis of HCC. Therefore, ABC expression profile could be a potential indicator for HCC patients.

Survival Outcomes for Induction vs Adjuvant Chemotherapy in Squamous Cell Carcinoma of the Maxillary Sinus

2018 ◽  
Vol 160 (4) ◽  
pp. 658-663 ◽  
Author(s):  
Phoebe Kuo ◽  
Sina J. Torabi ◽  
Dennis Kraus ◽  
Benjamin L. Judson
Keyword(s):  
Overall Survival ◽  
Adjuvant Chemotherapy ◽  
Maxillary Sinus ◽  
Induction Chemotherapy ◽  
Squamous Cell ◽  
Cox Regression ◽  
Rank Test ◽  
Controlled Clinical Trial ◽  
Log Rank Test ◽  
Kaplan Meier

Objective In advanced maxillary sinus cancers treated with surgery and radiotherapy, poor local control rates and the potential for organ preservation have prompted interest in the use of systemic therapy. Our objective was to present outcomes for induction compared to adjuvant chemotherapy in the maxillary sinus. Study Design Secondary database analysis. Setting National Cancer Database (NCDB). Subjects and Methods In total, 218 cases of squamous cell maxillary sinus cancer treated with surgery, radiation, and chemotherapy between 2004 and 2012 were identified from the NCDB and stratified into induction chemotherapy and adjuvant chemotherapy cohorts. Univariate Kaplan-Meier analyses were compared by log-rank test, and multivariate Cox regression was performed to evaluate overall survival when adjusting for other prognostic factors. Propensity score matching was also used for further comparison. Results Twenty-three patients received induction chemotherapy (10.6%) and 195 adjuvant chemotherapy (89.4%). The log-rank test comparing induction to adjuvant chemotherapy was not significant ( P = .076). In multivariate Cox regression when adjusting for age, sex, race, comorbidity, grade, insurance, and T/N stage, there was a significant mortality hazard ratio of 2.305 for adjuvant relative to induction chemotherapy (confidence interval, 1.076-4.937; P = .032). Conclusion Induction chemotherapy was associated with improved overall survival in comparison to adjuvant chemotherapy in a relatively small cohort of patients (in whom treatment choice cannot be characterized), suggesting that this question warrants further investigation in a controlled clinical trial before any recommendations are made.

scholarly journals Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma

2021 ◽  
Vol 20 ◽  
pp. 153303382110414
Author(s):  
Xiaoyong Li ◽  
Jiaqong Lin ◽  
Yuguo pan ◽  
Peng Cui ◽  
Jintang Xia
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Model ◽  
Cox Regression ◽  
Risk Group ◽  
Gene Signature ◽  
Regression Analyses ◽  
Related Gene ◽  
Cox Regression Analysis

Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.

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.

scholarly journals Identification and Validation of an 11-Ferroptosis Related Gene Signature and Its Correlation With Immune Checkpoint Molecules in Glioma

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhuohui Chen ◽  
Tong Wu ◽  
Zhouyi Yan ◽  
Mengqi Zhang
Keyword(s):  
Overall Survival ◽  
Cox Regression ◽  
Gene Signature ◽  
Curve Analysis ◽  
Regression Analyses ◽  
Related Gene ◽  
Roc Curve Analysis ◽  
Small Molecule Drugs ◽  
The Relationship ◽  
Genome Atlas

BackgroundGlioma is the most common primary malignant brain tumor with significant mortality and morbidity. Ferroptosis, a novel form of programmed cell death (PCD), is critically involved in tumorigenesis, progression and metastatic processes.MethodsWe revealed the relationship between ferroptosis-related genes and glioma by analyzing the mRNA expression profiles from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), GSE16011, and the Repository of Molecular Brain Neoplasia Data (REMBRANDT) datasets. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to construct a ferroptosis-associated gene signature in the TCGA cohort. Glioma patients from the CGGA, GSE16011, and REMBRANDT cohorts were used to validate the efficacy of the signature. Receiver operating characteristic (ROC) curve analysis was applied to measure the predictive performance of the risk score for overall survival (OS). Univariate and multivariate Cox regression analyses of the 11-gene signature were performed to determine whether the ability of the prognostic signature in predicting OS was independent. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to identify the potential biological functions and pathways of the signature. Subsequently, we performed single sample gene set enrichment analysis (ssGSEA) to explore the correlation between risk scores and immune status. Finally, seven putative small molecule drugs were predicted by Connectivity Map.ResultsThe 11-gene signature was identified to divide patients into two risk groups. ROC curve analysis indicated the 11-gene signature as a potential diagnostic factor in glioma patients. Multivariate Cox regression analyses showed that the risk score was an independent predictive factor for overall survival. Functional analysis revealed that genes were enriched in iron-related molecular functions and immune-related biological processes. The results of ssGSEA indicated that the 11-gene signature was correlated with the initiation and progression of glioma. The small molecule drugs we selected showed significant potential to be used as putative drugs.Conclusionwe identified a novel ferroptosis-related gene signature for prognostic prediction in glioma patients and revealed the relationship between ferroptosis-related genes and immune checkpoint molecules.

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