scholarly journals A novel five-gene signature for predicting prognosis in liver cancer

2020 ◽  
Author(s):  
Qiuyue Zhong ◽  
Yu Shuai ◽  
Qiong Luo ◽  
Guangyong Feng ◽  
Mingna Wu ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Receiver Operating Characteristic ◽  
Clinical Data ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Gene Signature ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Cancer Data ◽  
Receiver Operating

Abstract Purpose Liver cancer is one of the most common malignant tumors in China, ranked 5th among the malignant common tumors in the world, which is still difficult to diagnose early and treat effectively. Therefore, exploring some indicators for prognostic prediction is imperative in the treatment of liver cancer. Methods Liver cancer data was obtained from The Cancer Genome Atlas (TCGA). We obtained differentially expressed genes (DEGs) by R software from TCGA database. Risk scores were acquired to assess the weighted gene-expression levels by Cox regression analysis and predict the prognosis of patients with liver cancer. Using the KEGG and GO databases, pathway enrichment was performed by identifying the analysis of DEGs. The display of receiver-operating characteristic (ROC) curves and area under the curve (AUC) could show the validity and the prognostic value of this model in liver cancer. Results In total, 1897 DEGs of transcriptome genes in liver cancer and 1197 DEGs of clinical data were extracted from the TCGA database. We identified a novel five-gene signature associated with liver cancer, including CDCA8, NR0B1, GAGE2A, AC018641.1, and SPANXC. Among of them, CDCA8 and NR0B1 were negatively related to 5-year OS, displaying a worse prognosis (P < 0.05). In particular, we also found that GAGE2A is related to lymphatic metastasis from the clinical data analysis in liver cancer. Receiver-operating characteristic (ROC) curve assessed the accuracy and sensitivity of the gene signature. In the heat map, each of the five genes for patients was presented with the distribution of the risk score. Conclusions We figured out a novel five-gene signature for the prognosis of patients with liver cancer, which may be an effective predictor for patients’ prognosis in the future.

scholarly journals A novel five-gene signature for predicting prognosis in liver cancer

2019 ◽  
Author(s):  
Qiuyue Zhong ◽  
Yu Shuai ◽  
Qiong Luo ◽  
Guangyong Feng ◽  
Mingna Wu ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Receiver Operating Characteristic ◽  
Clinical Data ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Gene Signature ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Cancer Data ◽  
Receiver Operating

Abstract Purpose Liver cancer is one of the most common malignant tumors in China, ranked 5th among the malignant common tumors in the world, which is still difficult to diagnose early and treat effectively. Therefore, exploring some indicators for prognostic prediction is imperative in the treatment of liver cancer. Methods Liver cancer data was obtained from The Cancer Genome Atlas (TCGA). We obtained differentially expressed genes (DEGs) by R software from TCGA database. Risk scores were acquired to assess the weighted gene-expression levels by Cox regression analysis and predict the prognosis of patients with liver cancer. Using the KEGG and GO databases, pathway enrichment was performed by identifying the analysis of DEGs. The display of receiver-operating characteristic (ROC) curves and area under the curve (AUC) could show the validity and the prognostic value of this model in liver cancer. Results In total, 1897 DEGs of transcriptome genes in liver cancer and 1197 DEGs of clinical data were extracted from the TCGA database. We identified a novel five-gene signature associated with liver cancer, including CDCA8, NR0B1, GAGE2A, AC018641.1, and SPANXC. Among of them, CDCA8 and NR0B1 were negatively related to 5-year OS, displaying a worse prognosis (P < 0.05). In particular, we also found that GAGE2A is related to lymphatic metastasis from the clinical data analysis in liver cancer. Receiver-operating characteristic (ROC) curve assessed the accuracy and sensitivity of the gene signature. In the heat map, each of the five genes for patients was presented with the distribution of the risk score. Conclusions We figured out a novel five-gene signature for the prognosis of patients with liver cancer, which may be an effective predictor for patients’ prognosis in the future.

scholarly journals Επίπεδα VEGF σε πλευριτική συλλογή και περιφερικό δείγμα αίματος σε ασθενείς με καρκίνο πνεύμονα

2015 ◽  
Author(s):  
Ιωάννης Γκιόζος
Keyword(s):  
Regression Analysis ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Performance Status ◽  
Roc Curves ◽  
Characteristic Curves ◽  
Cox Regression Analysis ◽  
Receiver Operating Characteristic Curves ◽  
Receiver Operating

Ο πρωταρχικός σκοπός της παρούσας μελέτης ήταν η προοπτική διερεύνηση της δυνητικής προγνωστικής αξίας των προθεραπευτικών επιπέδων VEGF ορού και πλευριτικού υγρού σε ασθενείς με μη μικροκυτταρικό καρκίνο πνεύμονα (ΜΜΚΠ) που παρουσιάζονται με κακοήθη πλευριτική συλλογή. Επιπρόσθετος στόχος ήταν η διαλεύκανση της διαγνωστικής χρησιμότητας των προθεραπευτικών επιπέδων VEGF ορού για τη διάκριση μεταξύ ασθενών με ΜΜΚΠ και υγιών ατόμων. Στο παρόν ερευνητικό έργο μελετήσαμε προοπτικά 40 συνεχόμενους νεοδιαγνωσθέντες ασθενείς με ΜΜΚΠ, με κακοήθη πλευριτική συλλογή χωρίς απομακρυσμένες μεταστάσεις, που παραπέμφθηκαν για ογκολογική θεραπεία και αντιμετωπίστηκαν στην Ογκολογική Μονάδα της 3ης Πανεπιστημιακής Παθολογικής Κλινικής του Γενικού Νοσοκομείου Αθηνών «Η Σωτηρία», μεταξύ Σεπτεμβρίου 2009 και Σεπτεμβρίου 2013. Τα επίπεδα VEGF ορού και πλευριτικού υγρού μετρήθηκαν με τη χρήση ανοσοενζυμικής μεθόδου (ELISA). Τα επίπεδα VEGF ορού μετρήθηκαν επίσης σε πενήντα υγιείς μάρτυρες, εξομοιωμένους ως προς το φύλο και την ηλικία με τους ασθενείς (p=0.517 και p=0.795, αντιστοίχως). Η διαγνωστική ακρίβεια των επιπέδων VEGF ορού για τη διάκριση μεταξύ ασθενών με ΜΜΚΠ και υγιών μαρτύρων υπολογίστηκε με τη χρήση καμπυλών λειτουργικού χαρακτηριστικού δέκτη (Receiver operating characteristic curves, ROC curves). Τα επίπεδα VEGF ορού και πλευριτικού υγρού συσχετίσθηκαν με δημογραφικές και κλινικοπαθολογοανατομικές παραμέτρους, συμπεριλαμβανομένου του φύλου, της ηλικίας, του ιστορικού καπνίσματος, του performance status,του ιστολογικού τύπου του όγκου και της ανταπόκρισης στη θεραπεία. Η προγνωστική αξία κάθε μεταβλητής για τη συνολική επιβίωση και το διάστημα ελεύθερο προόδου νόσου αξιολογήθηκε με μονοπαραγοντική και πολυπαραγοντική ανάλυση παλινδρόμησης του Cox (univariate and multivariate Cox regression analysis). Οι διάμεσες τιμές VEGF ορού ήταν στατιστικώς σημαντικά υψηλότερες στους ασθενείς σε σύγκριση με τους υγιείς μάρτυρες (p<0.001), ενώ το βέλτιστο διαχωριστικό όριο όσον αφορά στις τιμές VEGF ορού για τη διάκριση μεταξύ ασθενών και μαρτύρων ήταν 375 pg/ml, με τιμές ευαισθησίας και ειδικότητας 76.9% και 98.0%, αντιστοίχως. Επίπεδα VEGF ορού μεγαλύτερα απο 375 pg/ml και επίπεδα VEGF πλευριτικού υγρού μεγαλύτερα από τη διάμεση τιμή, καθώς και η παρουσία προόδου νόσου, συσχετίσθηκαν με χαμηλότερο διάστημα PFS και χαμηλότερη συνολική επιβίωση, τόσο στη μονοπαραγοντική όσο και στην πολυπαραγοντική ανάλυση επιβίωσης. Στατιστικά σημαντική συσχέτιση παρατηρήθηκε επίσης μεταξύ των επιπέδων VEGF ορού και πλευριτικού υγρού (p<0.001).Τα αποτελέσματα της μελέτης μας υποδεικνύουν ότι τα επίπεδα VEGF ορού μπορεί να χρησιμεύουν για τη διάκριση μεταξύ ασθενών με ΜΜΚΠ και υγιών, καθώς και ότι τα αυξημένα προθεραπευτικά επίπεδα VEGF τόσο στον ορό και στο πλευριτικό υγρό ασθενών με ΜΚΚΠ προχωρημένου σταδίου μπορεί να αντιπροσωπεύουν ανεξάρτητους δείκτες δυσμενούς πρόγνωσης σε αυτή την υποομάδα των ασθενών. Για την επιβεβαίωση των ευρημάτων του παρόντος ερευνητικού έργου και την περαιτέρω διερεύνηση της πιθανής αξίας των ως άνω βιοδεικτών ως δεικτών πρόβλεψης όχι μόνο της επιβίωσης των ασθενών αυτών αλλά και της ανταπόκρισής τους στις στοχευμένες αντι-αγγειογενετικές θεραπείες, απαιτείται η διενέργεια μελλοντικών προοπτικών ερευνών σε μεγαλύτερες σειρές ασθενών.

scholarly journals Clinical Characteristics and Prognostic Nomogram in Patients With Pineoblastoma

2020 ◽  
Author(s):  
YaJun JING ◽  
WenShuai DENG ◽  
YunXia JIANG ◽  
MingXia BI ◽  
MingChao FAN ◽  
...  
Keyword(s):  
Receiver Operating Characteristic Curve ◽  
Receiver Operating Characteristic ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Treatment Options ◽  
Concordance Index ◽  
Cox Regression Analysis ◽  
Operating Characteristic Curve ◽  
Receiver Operating

Abstract Background: Pineoblastoma (PB) is an infrequent entity of the central nervous system. The data about clinical outcomes of PB is exceedingly limited due to its rarity. Notably, the optimal treatment approaches and prognostic factors on PB is still unclear. Thus the aims of this study are to identify prognosis-associated factors and develop a predictive nomogram of PB.Method: Data of 243 patients with PB (≤29 years), collected by the Surveillance, Epidemiology, and End Results database, were randomly carved up the primary (n=172) and validation cohort (n=71) two groups. A prognostic nomogram was developed based on primary cohorts and optimized via the Akaike Information Criterion. Calibration curves were applied to show the results of validation (internal, external, and cross-validation). Additionally, its predictive performance was evaluated by the concordance index and receiver operating characteristic curve. Finally, decision curve analyses were employed to assess its clinical utility. Results: Age, year of diagnosis, treatment, tumor size, and tumor extension were identified as independent predictors of PB based on multivariate Cox regression analysis. The model presented an excellent discriminating ability (concordance index of the nomogram: 0.805; 95% confidence interval: 0.78–0.83; area under the receiver operating characteristic curve with a range from 0.7 to 0.9). The calibration plots (probability of survival) is consistent with the results predicted by the nomogram. The results of the decision curve analysis showed that the nomogram has potential clinical applicability.Conclusion: The nomogram can be used to assess prognosis and determine appropriate treatment options.

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.

Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of outcomes in inflammatory breast cancer

2021 ◽  
Author(s):  
Ouissam Al Jarroudi ◽  
Khalid El Bairi ◽  
Naima Abda ◽  
Adil Zaimi ◽  
Laila Jaouani ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Receiver Operating Characteristic ◽  
Inflammatory Breast Cancer ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Menopausal Status ◽  
Pathologic Complete Response ◽  
Disease Free Survival ◽  
Prognostic Impact ◽  
Receiver Operating

Background: Inflammatory breast cancer (IBC) is uncommon, aggressive and associated with poor survival outcomes. The lack of prognostic biomarkers and therapeutic targets specific to IBC is an added challenge for clinical practice and research. Inflammatory biomarkers such as neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios (NLR and PLR) demonstrated independent prognostic impact for survival in breast cancer. In our study, these biomarkers were investigated in a cohort of patients with nonmetastatic IBC. Methods: A retrospective cohort of 102 IBC patients with nonmetastatic disease was conducted at the Mohammed VI University Hospital (Oujda, Morocco) between January 2010 and December 2014. NLR and PLR were obtained from blood cell count at baseline before neoadjuvant chemotherapy (NACT) from patients’ medical records. The receiver operating characteristic was used to find the optimal cut-off. Correlation between these blood-based biomarkers and response to NACT was analyzed by Chi-squared and Fisher's exact test. Their prognostic value for predicting disease-free survival (DFS) and overall survival (OS) was performed based on Cox regression models. Results: Totally, 102 patients with IBC were included in the analysis. Pathologic complete response (pCR) after NACT, defined by the absence of an invasive tumor in the breast tissues and nodes after surgery (ypT0 ypN0), was observed in eight patients (7.8%). NACT response was found to be associated with menopausal status (p = 0.039) and nodal status (p < 0.001). Patients with a low NLR had a higher pCR rate as compared with the high-NLR group (p = 0.043). However, the pCR rate was not significantly associated with age (p = 0.122), tumor side (p = 0.403), BMI (p = 0.615), histological grade (p = 0.059), hormone receptors status (p = 0.206), human epidermal growth factor receptor 2 (p = 0.491) and PLR (p = 0.096). Pre-treatment blood-based NLR of 2.28 was used as the cut-off value to discriminate between high and low NLR according to the receiver operating characteristic curves. Similarly, a value of 178 was used as the cut off for PLR. Patients with low-NLR had a significantly better 5-year DFS (p < 0.001) and OS (p < 0.001) than the high-NLR group. Moreover, low-PLR was significantly associated with higher DFS (p = 0.001) and OS (p = 0.003). The NLR showed a significant prognostic impact for DFS (HR: 2.57; 95% CI: 1.43–4.61; p = 0.01) and for OS (HR: 2.92; 95% CI: 1.70–5.02; p < 0.001). Similarly, a meaningful association between PLR and 5-year DFS (HR: 1.95; 95% CI: 1.10–3.46; p = 0.021) and OS (HR: 1.82; 95% CI: 1.06–3.14; p = 0.03) was noticed. Conclusions: High NLR and PLR were found associated with reduced DFS and OS in nonmetastatic IBC. Further studies are awaited to confirm these findings.

Biomarker panels may be superior over single molecules in prediction of renal flares in systemic lupus erythematosus: an exploratory study

Rheumatology ◽  
2020 ◽  
Vol 59 (11) ◽  
pp. 3193-3200
Author(s):  
Serena Fasano ◽  
Luciana Pierro ◽  
Alessia Borgia ◽  
Melania Alessia Coscia ◽  
Ranieri Formica ◽  
...  
Keyword(s):  
Receiver Operating Characteristic ◽  
Adhesion Molecule ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Receiver Operating Characteristic Analysis ◽  
Characteristic Analysis ◽  
Factors Associated ◽  
Biomarker Panel ◽  
Renal Flare ◽  
Receiver Operating

Abstract Objective Recent evidence suggests that some urinary biomarkers, namely Vascular Cell Adhesion Molecule-1 (VCAM-1), Intercellular Adhesion Molecule-1 (ICAM-1), Monocyte Chemoattractant Protein 1 (MCP-1), Neutrophil Gelatinase Associated Lipocalcin and Lipocalin-type Prostaglandin D-Synthetase (L-PGDS), might discriminate SLE patients with ongoing renal activity from those with stable disease. The objective of this study was to assess the role of these markers in predicting renal flares in comparison with conventional biomarkers and to derive a biomarker panel which may improve diagnostic accuracy. Methods Eligible participants were SLE patients prospectively followed at our clinic. Urinary biomarker levels were measured in urinary sample by ELISA assay and were compared by the unpaired Student’s t test or the Mann–Whitney U test as appropriate. Receiver operating characteristic analysis was used to calculate the area under the curve. Cox regression was used to identify independent factors associated with disease flares. Results Urine was collected from 61 patients. During 8 months’ follow-up, eight patients experienced a renal flare. Urinary L-PGDS, ICAM-1 and VCAM-1 levels were significantly increased in the patients who subsequently experienced a renal flare with respect to the remaining 53. At Cox regression analysis, L-PGDS, ICAM-1, VCAM-1, hypocomplementemia and anti-dsDNA antibodies were factors associated with renal flares. Based on receiver operating characteristic analysis, a combination of novel and conventional biomarkers demonstrated an excellent ability for accurately identifying a flare. Conclusion This study might suggest the usefulness of a novel biomarker panel in predicting a renal flare in SLE.

scholarly journals Identification of Prognostic Gene Signature Associated with Tumor Microenvironment of Cholangiocarcinoma

2021 ◽  
Author(s):  
Jixiang Cao ◽  
Xi Chen ◽  
Guang Lu ◽  
Haowei Wang ◽  
Xinyu Zhang ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Prognostic Model ◽  
Cox Regression ◽  
Gene Signature ◽  
Risk Scores ◽  
Tumor Infiltration ◽  
Prognostic Signature ◽  
Cox Regression Analysis

Abstract Background: Cholangiocarcinoma (CCA) is the most common malignancy of the biliary tract with a dismal prognosis. Increasing evidence suggests that tumor microenvironment (TME) is closely associated with cancer prognosis. However, the prognostic signature for CCA based on TME has not yet been reported. This study aimed to develop a TME-related prognostic signature for accurately predicting the prognosis of patients with CCA. Methods: Based on the TCGA database, we calculated the stromal and immune scores using the ESTIMATE algorithm to assess TME in stromal and immune cells derived from CCA. TME-related differentially expressed genes were identified, followed by functional enrichment analysis and PPI network analysis. Univariate Cox regression analysis, Lasso Cox regression model and multivariable Cox regression analysis were performed to identify and construct the TME-related prognostic gene signature. Gene Set Enrichment Analyses (GSEA) was performed to further investigate the potential molecular mechanisms. The correlations between the risk scores and tumor infiltration immune cells were analyzed using Tumor Immune Estimation Resource (TIMER) database. Results: A total of 784 TME-related differentially expressed genes (DEGs) were identified, which were mainly enriched in immune-related processes and pathways. Among these TME-related DEGs, A novel two‑gene signature (including GAD1 and KLRB1) was constructed for CCA prognosis prediction. The AUC of the prognostic model for predicting the survival of patients at 1-, 2-, and 3- years was 0.811, 0.772, and 0.844, respectively. Cox regression analysis showed that the two‑gene signature was an independent prognostic factor. Based on the risk scores of the prognostic model, CCA patients were divided into high- and low-risk groups, and patients with high-risk score had shorter survival time than those with low-risk score. Furthermore, we found that the risk scores were negatively correlated with TME-scores and the number of several tumor infiltration immune cells, including B cells and CD4+ T cells. Conclusion: Our study established a novel TME-related gene signature to predict the prognosis of patients with CCA. This might provide a new understanding of the potential relationship between TME and CCA prognosis, and serve as a prognosis stratification tool for guiding personalized treatment of CCA patients.

scholarly journals Comprehensive Analysis of the Prognostic Significance of Hsa-miR-100-5p and Its Related Gene Signature in Stomach Adenocarcinoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Gaoming Wang ◽  
Ludi Yang ◽  
Miao Hu ◽  
Renhao Hu ◽  
Yongkun Wang ◽  
...  
Keyword(s):  
High Risk ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Tumor Development ◽  
Risk Groups ◽  
Gene Signature ◽  
Risk Scores ◽  
Prognostic Signature ◽  
Cox Regression Analysis ◽  
Stomach Adenocarcinoma

Stomach adenocarcinoma (STAD) is one of the most common cancers in the world. However, the prognosis of STAD remains poor, and the therapeutic effect of chemotherapy and immunotherapy varies from person to person. MicroRNAs (miRNAs) play vital roles in tumor development and metastasis and can be used for cancer diagnosis and prognosis. In this study, hsa-miR-100-5p was identified as the only dysregulated miRNA in STAD samples through an analysis of three miRNA expression matrices. A weighted gene co-expression network analysis (WGCNA) was performed to select hsa-miR-100-5p-related genes. A least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to establish a miR-100-5p-related prognostic signature. Kaplan–Meier analyses, nomograms, and univariate and multivariate Cox regression analyses were used to evaluate the prognostic signature, which was subsequently identified as an independent risk factor for STAD patients. We investigated the tumor immune environment between low- and high-risk groups and found that, among component types, M2 macrophages contributed the most to the difference between these groups. A drug sensitivity analysis suggested that patients with high-risk scores may be more sensitive to docetaxel and cisplatin chemotherapy and that patients in the low-risk group may be more likely to benefit from immunotherapy. Finally, external cohorts were evaluated to validate the robustness of the prognostic signature. In summary, this study may provide new ideas for developing more individualized therapeutic strategies for STAD patients.

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