ABSTRACT
Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.
Subject(s)
Proteogenomics , Thyroid Neoplasms , Humans , Thyroid Cancer, Papillary/genetics , Proto-Oncogene Proteins B-raf/genetics , Metabolomics , Thyroid Neoplasms/geneticsABSTRACT
BACKGROUND: The objective of our study was to develop and validate nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with signet-ring cell carcinoma (SRCC) of the stomach. METHODS: Data were collected from the Surveillance, Epidemiology, and End Results (SEER) database. A total of 1781 patients were randomly allocated to a training set (n = 1335) and a validation set (n = 446). Univariate and multivariate analyses were used to determine the prognostic effect of variables. Nomograms were developed to estimate OS and CSS and assessed using the concordance index (C-index), calibration curves, receiver operating characteristic (ROC), and decision curve analyses (DCA). DCA was utilized to compare the nomograms and the Tumor-Node-Metastasis (TNM) staging system. RESULTS: Age, race, tumor size, T, N, M stage, and use of surgery and/or radiotherapy were included in the nomograms. C-indexes for OS and CSS were 0.74 and 0.75 in the training set, respectively. C-indexes for OS and CSS were 0.76 and 0.76 in the validation set. Calibration plots and receiver operating characteristic (ROC) curves showed good predictive accuracy. According to the decision curve analyses (DCA), the new model was more useful than the TNM staging system. CONCLUSIONS: We developed nomograms to predict OS and CSS in patients with SRCC of the stomach. Nomograms may be a valuable clinical supplement of the conventional TNM staging system.
Subject(s)
Carcinoma, Signet Ring Cell/mortality , Clinical Decision Rules , Nomograms , Stomach Neoplasms/mortality , Adult , Aged , Aged, 80 and over , Carcinoma, Signet Ring Cell/diagnosis , Carcinoma, Signet Ring Cell/pathology , Female , Humans , Male , Middle Aged , Neoplasm Staging , Prognosis , ROC Curve , Retrospective Studies , SEER Program , Stomach Neoplasms/diagnosis , Stomach Neoplasms/pathology , Survival AnalysisABSTRACT
Warburg found that tumor cells exhibit high-level glycolysis, even under aerobic condition, which is known as the 'Warburg effect'. As systemic changes in the entire metabolic network are gradually revealed, it is recognized that metabolic reprogramming has gone far beyond the imagination of Warburg. Metabolic reprogramming involves an active change in cancer cells to adapt to their biological characteristics. Thyroid cancer is a common endocrine malignant tumor whose metabolic characteristics have been studied in recent years. Some drugs targeting tumor metabolism are under clinical trial. This article reviews the metabolic changes and mechanisms in thyroid cancer, aiming to find metabolic-related molecules that could be potential markers to predict prognosis and metabolic pathways, or could serve as therapeutic targets. Our review indicates that knowledge in metabolic alteration has potential contributions in the diagnosis, treatment and prognostic evaluation of thyroid cancer, but further studies are needed for verification as well.