Development of a novel prognostic score combining clinicopathologic variables, gene expression, and mutation profiles for lung adenocarcinoma.

BACKGROUND: Integrating phenotypic and genotypic information to improve prognostic prediction is under active investigation for lung adenocarcinoma (LUAD). In this study, we developed a new prognostic model for event-free survival (EFS) and recurrence-free survival (RFS) based on the combination of clinicopathologic variables, gene expression, and mutation data. METHODS: We enrolled a total of 408 patients from the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) project for the study. We pre-selected gene expression or mutation features and constructed 14 different input feature sets for predictive model development. We assessed model performance with multiple evaluation metrics including the distribution of C-index on testing dataset, risk score significance, and time-dependent AUC under competing risks scenario. We stratified patients into higher- and lower-risk subgroups by the final risk score and further investigated underlying immune phenotyping variations associated with the differential risk. RESULTS: The model integrating all three types of data achieved the best prediction performance. The resultant risk score provided a higher-resolution risk stratification than other models within pathologically defined subgroups. The score could account for extra EFS-related variations that were not captured by clinicopathologic scores. Being validated for RFS prediction under a competing risks modeling framework, the score achieved a significantly higher time-dependent AUC as compared to that of the conventional clinicopathologic variables-based model (0.772 vs. 0.646, p value < 0.001). The higher-risk patients were characterized with transcriptional aberrations of multiple immune-related genes, and a significant depletion of mast cells and natural killer cells. CONCLUSIONS: We developed a novel prognostic risk score with improved prediction accuracy, using clinicopathologic variables, gene expression and mutation profiles as input, for LUAD. Such score was a significant predictor of both EFS and RFS. TRIAL REGISTRATION: This study was based on public open data from TCGA and hence the study objects were retrospectively registered.

Combining texture features of whole slide images improves prognostic prediction of recurrence-free survival for cutaneous melanoma patients.

BACKGROUND: Accurate prediction of recurrence-free survival (RFS) is important for the prognosis of cutaneous melanoma patients. The image-based pathological examination remains as the gold standard for diagnosis. It is of clinical interest to account for computer-aided processing of pathology image when performing prognostic analysis. METHODS: We enrolled in this study a total of 152 patients from TCGA-SKCM (The Cancer Genome Atlas Skin Cutaneous Melanoma project) with complete information in recurrence-related survival time, baseline variables (clinicopathologic variables, mutation status of BRAF and NRAS genes), gene expression data, and whole slide image (WSI) features. We preprocessed WSI to segment global or nucleus areas, and extracted 3 types of texture features from each region. We performed cross validation and used multiple evaluation metrics including C-index and time-dependent AUC to determine the best model of predicting recurrence events. We further performed differential gene expression analysis between the higher and lower-risk groups within AJCC pathologic tumor stage III patients to explore the underlying molecular mechanisms driving risk stratification. RESULTS: The model combining baseline variables and WSI features had the best performance among models with any other types of data integration. The prognostic risk score generated by this model could provide a higher-resolution risk stratification within pathologically defined subgroups. We found the selected image features captured important immune-related variations, such as the aberration of expression in T cell activation and proliferation gene sets, and therefore contributed to the improved prediction. CONCLUSIONS: Our study provided a prognostic model based on the combination of baseline variables and computer-processed WSI features. This model provided more accurate prediction than models based on other types of data combination in recurrence-free survival analysis. TRIAL REGISTRATION: This study was based on public open data from TCGA and hence the study objects were retrospectively registered.

Hepatocyte growth factor plays a critical role in the regulation of cytokine production and induction of endothelial progenitor cell mobilization: a pilot gene therapy study in patients with coronary heart disease.

1. There is growing evidence of the beneficial effects of hepatocyte growth factor (HGF) in myocardial infarction, heart failure and occlusive peripheral arterial disease. The aim of the present study was to evaluate the effects of intracoronary administration of an adenovirus vector encoding the human HGF gene (Ad-HGF) on serum levels of cytokines and mobilization of CD34(+) and CD117(+) cells in patients with coronary heart disease. 2. Twenty-one patients with severe coronary artery disease were recruited to the study: 11 patients received both a stent and administration of Ad-HGF; the remaining 10 patients received a stent alone and served as the control group. Blood samples were obtained from the femoral vein before and then 6 and 24 h, 3 and 6 days and 2 weeks after treatment for the isolation of serum and peripheral blood mononuclear cells. Intracoronary administration of Ad-HGF in patients with coronary heart disease resulted in high levels of HGF gene expression, as well as its receptor c-met, compared with the control group, as demonstrated by real-time reverse transcription-polymerase chain reaction. In addition, serum levels of HGF, vascular endothelial growth factor, monocyte chemoattractant protein-1 and interleukin (IL)-10 were increased and serum levels of IL-8 were decreased in patients administered Ad-HGF compared with the control group. The percentage of CD34(+) and CD117(+) cells in the peripheral blood increased in patients administered Ad-HGF. 3. In conclusion, HGF gene therapy may play an important role in the regulation of cytokines and the induction of endothelial progenitor cell mobilization in patients with coronary heart disease.