The Prognostic Significance of Nomogram-Based Pretreatment Inflammatory Indicators in Patients With Esophageal Squamous Cell Carcinoma Receiving Intensity-Modulated Radiotherapy.

BACKGROUND: At present, there is no objective prognostic index available for patients with esophageal squamous cell carcinoma (ESCC) who underwent intensity-modulated radiotherapy (IMRT). This study is to develop a nomogram based on hematologic inflammatory indices for ESCC patients treated with IMRT. METHODS: 581 patients with ESCC receiving definitive IMRT were enrolled in our retrospective study. Of which, 434 patients with treatment-naïve ESCC in Fujian Cancer Hospital were defined as the training cohort. Additional 147 newly diagnosed ESCC patients were used as the validation cohort. Independent predictors of overall survival (OS) were employed to establish a nomogram model. The predictive ability was evaluated by time-dependent receiver operating characteristic curves, the concordance index (C-index), net reclassification index (NRI), and integrated discrimination improvement (IDI). Decision curve analysis (DCA) was performed to assess the clinical benefits of the nomogram model. The entire series was divided into 3 risk subgroups stratified by the total nomogram scores. RESULTS: Clinical TNM staging, primary gross tumor volume, chemotherapy, neutrophil-to-lymphocyte ratio and platelet lymphocyte ratio were independent predictors of OS. Nomogram was developed incorporating these factors. Compared with the 8th American Joint Committee on Cancer (AJCC) staging, the C-index for 5-year OS (.627 and .629) and the AUC value of 5-year OS (.706 and .719) in the training and validation cohorts (respectively) were superior. Furthermore, the nomogram model presented higher NRI and IDI. DCA also demonstrated that the nomogram model provided greater clinical benefit. Finally, patients with <84.8, 84.8-151.4, and >151.4 points were categorized into low-risk, intermediate-risk, and high-risk groups. Their 5-year OS rates were 44.0%, 23.6%, and 8.9%, respectively. The C-index was .625, which was higher than the 8th AJCC staging. CONCLUSIONS: We have developed a nomogram model that enables risk-stratification of patients with ESCC receiving definitive IMRT. Our findings may serve as a reference for personalized treatment.

Integrated analysis of methylation-driven genes and pretreatment prognostic factors in patients with hepatocellular carcinoma.

BACKGROUND: The potential reversibility of aberrant DNA methylation indicates an opportunity for oncotherapy. This study aimed to integrate methylation-driven genes and pretreatment prognostic factors and then construct a new individual prognostic model in hepatocellular carcinoma (HCC) patients. METHODS: The gene methylation, gene expression dataset and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Methylation-driven genes were screened with a Pearson's correlation coefficient less than - 0.3 and a P value less than 0.05. Univariable and multivariable Cox regression analyses were performed to construct a risk score model and identify independent prognostic factors from the clinical parameters of HCC patients. The least absolute shrinkage and selection operator (LASSO) technique was used to construct a nomogram that might act to predict an individual's OS, and then C-index, ROC curve and calibration plot were used to test the practicability. The correlation between clinical parameters and core methylation-driven genes of HCC patients was explored with Student's t-test. RESULTS: In this study, 44 methylation-driven genes were discovered, and three prognostic signatures (LCAT, RPS6KA6, and C5orf58) were screened to construct a prognostic risk model of HCC patients. Five clinical factors, including T stage, risk score, cancer status, surgical method and new tumor events, were identified from 13 clinical parameters as pretreatment-independent prognostic factors. To avoid overfitting, LASSO analysis was used to construct a nomogram that could be used to calculate the OS in HCC patients. The C-index was superior to that from previous studies (0.75 vs 0.717, 0.676). Furthermore, LCAT was found to be correlated with T stage and new tumor events, and RPS6KA6 was found to be correlated with T stage. CONCLUSION: We identified novel therapeutic targets and constructed an individual prognostic model that can be used to guide personalized treatment in HCC patients.

[Analysis of risk factors for spontaneous rupture of hepatocellular carcinoma].

OBJECTIVE: To assess the risk factors for spontaneous rupture of hepatocellular carcinoma (SRHC). METHODS: A retrospective analysis of 34 consecutive patients with SRHC treated by emergency interventional embolization in our hospital from July 2003 to July 2011 was conducted. General condition, laboratory examination and imaging data were analyzed, and compared with the data of 34 patients with primary hepatocellular carcinoma but without rupture, randomly selected from 215 concurrent patients. The patients with SRHC were selected for risk factor analysis, and the non-SRHC patients were taken as control group. RESULTS: No significant difference between the SRHC group and control group was found in age, sex, Child-Turcotte-Pugh (CTP) grade, Barcelona clinic liver cancer (BCLC) stage, HBsAg, HBsAb, HBeAg, HBeAb, HBcAb, prothrombin time (PT), thrombin time (TT), international normalized ratio (INR), glucose (GLU), cirrhosis, portal tumor thrombus, the maximum diameter of tumor, location, and cholecystitis or cholelithiasis. The univariate analysis showed that activated partial thromboplastin time (APTT), lower or normal plasma fibrinogen (FIB) level, alpha fetoprotein (AFP), tumor protrusion > 1 cm above the liver surface were all associated with increased risk of SRHC (P < 0.05). Multivariate analysis only showed that lower or normal level of FIB (P = 0.033) and tumor protrusion > 1 cm above the liver surface (P = 0.041) were significant independent risk factors for SRHC. CONCLUSION: Lower or normal level of FIB and tumor protrusion > 1 cm above the liver surface are significant independent risk factors for spontaneous rupture of hepatocellular carcinoma.

Development of a prognostic nomogram and risk stratification system for upper thoracic esophageal squamous cell carcinoma.

Background: The study aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC). Methods: Newly diagnosed 568 patients with upper ESCC at Fujian Medical University Cancer Hospital were taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI). Results: In this study, multivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume were independent prognostic factors for OS in the training cohort. The nomogram based on these factors presented favorable prognostic efficacy in the both training and validation cohorts, with concordance statistics (C-index) of 0.622, 0.713, and area under the curve (AUC) value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. Additionally, net reclassification index (NRI) and integrated discrimination improvement (IDI) of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, decision curve analysis (DCA) of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage. Conclusion: We built an effective nomogram model for predicting OS of upper ESCC, which may improve clinicians' abilities to predict individualized survival and facilitate to further stratify the management of patients at risk.

Complete and durable response to crizotinib in a patient with malignant pleural mesothelioma harboring CD74-ROS1 fusion.

Malignant pleural mesothelioma (MPM) is a rare and deadly malignancy with an extremely poor prognosis. The median overall survival (OS) of this disease is 12-18 months. However, the oncogenic driver mutations of MPM are rarely understood, and the targeted therapy for it is still under investigation. In this report, we describe a case of MPM with CD74-ROS1 fusion who obtains complete and durable response after receiving crizotinib. By the time of submission, the progression-free survival (PFS) with crizotinib has been 6.0 years, and the patient has survived for 7.6 years. Currently, he is still in complete remission (CR). To the best of our knowledge, this case represents the first report of CD74-ROS1 fusion identified in MPM. Meanwhile, it is also the first report of complete and long-term response to crizotinib in a patient with MPM positive for CD74-ROS1 fusion. This case report might contribute to the tumorigenesis and targeted therapy of this deadly disease.

Prognostic Value of a Ferroptosis-Related Gene Signature in Patients With Head and Neck Squamous Cell Carcinoma.

Background: Ferroptosis is an iron-dependent programmed cell death (PCD) form that plays a crucial role in tumorigenesis and might affect the antitumor effect of radiotherapy and immunotherapy. This study aimed to investigate distinct ferroptosis-related genes, their prognostic value and their relationship with immunotherapy in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The differentially expressed ferroptosis-related genes in HNSCC were filtered based on multiple public databases. To avoid overfitting and improve clinical practicability, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were performed to construct a prognostic risk model. Moreover, a nomogram was constructed to forecast individual prognosis. The differences in tumor mutational burden (TMB), immune infiltration and immune checkpoint genes in HNSCC patients with different prognoses were investigated. The correlation between drug sensitivity and the model was firstly analyzed by the Pearson method. Results: Ten genes related to ferroptosis were screened to construct the prognostic risk model. Kaplan-Meier (K-M) analysis showed that the prognosis of HNSCC patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and the area under the curve (AUC) of the 1-, 3- and 5-year receiver operating characteristic (ROC) curve increased year by year (0.665, 0.743, and 0.755). The internal and external validation further verified the accuracy of the model. Then, a nomogram was build based on the reliable model. The C-index of the nomogram was superior to a previous study (0.752 vs. 0.640), and the AUC (0.729 vs. 0.597 at 1 year, 0.828 vs. 0.706 at 3 years and 0.853 vs. 0.645 at 5 years), calibration plot and decision curve analysis (DCA) also shown the satisfactory predictive capacity. Furthermore, the TMB was revealed to be positively correlated with the risk score in HNSCC patients (R = 0.14; P < 0.01). The differences in immune infiltration and immune checkpoint genes were significant (P < 0.05). Pearson analysis showed that the relationship between the model and the sensitivity to antitumor drugs was significant (P < 0.05). Conclusion: Our findings identified potential novel therapeutic targets, providing further potential improvement in the individualized treatment of patients with HNSCC.

Prognostic value of fatty acid metabolism-related genes in patients with hepatocellular carcinoma.

The deregulation of fatty acid metabolism plays a crucial role in cancer. However, the prognostic value of genes involved in the metabolism in hepatocellular carcinoma (HCC) remains largely unknown. We first constructed a multi-fatty acid metabolic gene prognostic model of HCC based on The Cancer Genome Atlas (TCGA) and further validated it using the International Cancer Genome Consortium (ICGC) database. The model was integrated with the clinical parameters, and a nomogram was built and weighted. Moreover, immune cell infiltration of the tumor microenvironment was investigated. A prognostic model was constructed using 6 selected fatty acid metabolism-related genes, and HCC patients were divided into high- and low-risk groups. Receiver operating characteristic curve (ROC) analysis, principal component analysis (PCA), and t-distributed stochastic neighbor embedding (t-SNE) analysis showed the optimal performance of the model. The concordance index (C-index), ROC curve, calibration plot and decision curve analysis (DCA) all confirmed the satisfactory predictive capacity of the nomogram. The analysis of immune cell infiltration in HCC patients revealed a correlation with different risk levels. Our findings indicate that a prognostic model based on fatty acid metabolism-related genes has superior predictive capacities, which provides the possibility for further improving the individualized treatment of patients with HCC.