Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer.

BACKGROUND: Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC. METHODS: A total of 323 patients with advanced and metastatic PC were identified from the Chinese People's Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively. RESULTS: In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19-9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19-9, baseline CEA, change in CA 19-9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62-0.71) and 0.74 (95% CI, 0.69-0.77), respectively. CONCLUSION: These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.

Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer.

BACKGROUND: The incidence and mortality of pancreatic cancer (PC) has gradually increased. The aim of this study was to identify survival-related DNA methylation (DNAm)-driven genes and establish a nomogram to predict outcomes in patients with PC. METHODS: The gene expression, DNA methylation database, and PC clinical samples were downloaded from TCGA. DNAm-driven genes were identified by integrating analyses of gene expression and DNA methylation data. Survival-related DNAm-driven genes were screened via univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to develop a risk score model for prognosis. Based on analyses of clinical parameters and risk score, a nomogram was built and validated. The independent cohort from GEO database were used for external validation. RESULTS: A total of 16 differentially expressed methylation-driven genes were identified. Based on LASSO Cox regression and multivariate Cox regression analysis, six genes (FERMT1, LIPH, LAMA3, PPP1R14D, NQO1, VSIG2) were chosen to develop the risk score model. In the Kaplan-Meier analysis, age, T stage, N stage, AJCC stage, radiation therapy history, tumor size, surgery type performed, pathological type, chemotherapy history, and risk score were potential prognostic factors in PC (P < 0.1). In the multivariate analysis, stage, chemotherapy, and risk score were significantly correlated to overall survival (P < 0.05). The nomogram was constructed with the three variables (stage, chemotherapy, and risk score) for predicting the 1-year, 2-year, and 3-year survival rates of PC patients. Nomogram performance was assessed by receiver operating characteristic (ROC) curves and calibration curves. 1-year, 2-year and 3-year AUC of nomogram model was 0.899, 0.765 and 0.776, respectively. CONCLUSIONS: In our study, we successfully identified the six DNAm-driven genes (FERMT1, LIPH, LAMA3, PPP1R14D, NQO1, VSIG2) with a relationship to the outcomes of PC patients. The nomogram including stage, chemotherapy, and risk score could be used to predict survival in PC patients.

The long non-coding RNA AK001796 contributes to poor prognosis and tumor progression in hepatocellular carcinoma.

OBJECTIVE: Increasing studies have indicated the important functions of long non-coding RNAs (lncRNAs) in tumorigenesis and progression including hepatocellular carcinoma (HCC). The study aims to explore the role of long non-coding RNA AK001796 in HCC progression. PATIENTS AND METHODS: Quantitative Real-time polymerase chain reaction (QRT-PCR) analysis was performed to examine the lncRNA AK001796 expression in 73 cases of human HCC tissue samples and matched adjacent normal tissues. Besides, the relationship between lncRNA AK001796 expression and clinicopathologic characteristics was analyzed. Overall survival (OS) curves of patients were constructed by the Kaplan-Meier methods. Multivariate Cox regression analysis was used to evaluate independent risk factors affecting HCC prognosis. Cell proliferation and invasion abilities are analyzed by cell counting kit-8 (CCK-8) and transwell invasion assays. RESULTS: We showed that the lncRNA AK001796 expression was significantly up-regulated in HCC tissues and cell lines, compared to their controls, respectively. Higher lncRNA AK001796 expression closely correlated with tumor size (p<0.05), TNM stage (p<0.05) and the poor overall survival (OS) rate of HCC patients (p<0.05). Besides, multivariate Cox regression analysis found that lncRNA AK001796 expression was identified as an independent risk factor for HCC prognosis. In vitro, we showed that lncRNA AK001796 knockdown markedly suppressed cell proliferation and cell invasion abilities. CONCLUSIONS: Our results suggested that lncRNA AK001796 acts as a predictor of HCC prognosis and may provide an important clinical value for HCC treatment.

Effect of ribonucleotide reductase M1 expression on overall survival in patients with pancreatic cancer receiving gemcitabine chemotherapy: A literature-based meta-analysis.

WHAT IS KNOWN AND OBJECTIVE: The prognostic value of ribonucleotide reductase M1 (RRM1) in patients with pancreatic cancer receiving gemcitabine chemotherapy has been evaluated in several studies. However, the conclusions remain controversial. METHODS: By searching the PubMed and Embase databases, we conducted a meta-analysis to evaluate the prognostic significance of RRM1 expression in patients with pancreatic cancer receiving gemcitabine chemotherapy. Studies were pooled, and the hazard ratio (HR) and its corresponding 95% confidence interval (CI) were calculated. RESULTS: Nine relevant articles were included for this meta-analysis study. Our results revealed that the high-RRM1 expression patients had significantly poorer overall survival (HR = 1.70, 95% CI = 1.33-2.16, Pheterogeneity  = .061, I2  = 44.8%) and disease-free survival (HR = 1.84, 95% CI = 1.56-2.18, Pheterogeneity  = .669, I2  = 0%) than the low-RRM1 expression patients. Furthermore, a statistically significant association between RRM1 expression and OS was found among both Japanese (HR = 1.80, 95% CI = 1.36-2.37, Pheterogeneity  = .843, I2  = 0%) and American patients (HR = 1.76, 95% CI = 1.60-1.94, Pheterogeneity  = .439, I2  = 0%). WHAT IS NEW AND CONCLUSION: In conclusion, the expression of RRM1 can be considered a predictor of poor survival in patients with pancreatic cancer receiving gemcitabine chemotherapy. RRM1 expression assessment could provide more detailed information for patients with pancreatic cancer and could be used to optimize therapeutic schemes.