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Background: A considerable controversy over performing thyroidectomy and central lymph node dissection in patients with papillary thyroid microcarcinoma (PTMC) remained. However, accurate prediction of central lymph node metastasis (CLNM) is crucial for surgical extent and proper management. The aim of this study was to develop and validate a practical nomogram for predicting CLNM in patients with PTMC. Methods: A total of 1,029 patients with PTMC who underwent thyroidectomy and central lymph node dissection at Tangdu Hospital (the Second Affiliated Hospital of Air Force Medical University) and Xijing Hospital (the First Affiliated Hospital of Air Force Medical University) were selected. Seven hundred and nine patients were assigned to the training set and 320 patients to the validation set. Data encompassing demographic characteristics, ultrasonography results, and biochemical indicators were obtained. Stepwise backward selection and multiple logistic regression were used to screen the variables and establish the nomogram. Concordance index (C-index), receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA) were employed to evaluate the nomogram's distinguishability, accuracy, and clinical utility. Results: Young age, multifocality, bigger tumor, presence of microcalcification, aspect ratio (height divided by width) ≥1, loss of fatty hilum, high free thyroxine (FT4), and lower anti-thyroid peroxidase antibody (TPOAb) were significantly associated with CLNM. The nomogram showed strong predictive capacity, with a C-index and accuracy of 0.784 and 0.713 in the training set and 0.779 and 0.703 in the external validation set, respectively. DCA indicated that the nomogram demonstrated strong clinical applicability. Conclusions: We established a reliable, cost-effective, reproducible, and noninvasive nomogram for predicting CLNM in patients with PTMC. This tool could be a valuable guidance for deciding on management in PTMC.
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BACKGROUND: Potassium voltage-gated channel subfamily Q member 1 (KCNQ1), is implicated in the onset and progression of gastric carcinoma (GC), one of the most common types of stomach malignancies. This research aims to investigate the potential prognostic implications of KCNQ1 mRNA in GC using various databases such as The Cancer Genome Atlas (TCGA), The Human Protein Atlas (HPA), LinkedOmics, TISIDB, ESTIMATE, and TIMER. METHODS: We searched the HPA database to obtain information on KCNQ1 levels in human normal tissues, organs, and cell lines as well as in pan-cancer tissues. Then, we used TIMER and UALCAN to comparatively analyze the KCNQ1 mRNA levels in different types of cancers relative to their adjacent normal counterparts. Based on TCGA and Gene Expression Omnibus, the correlation of clinical information with KCNQ1 expression was analyzed using logistic regression model. Univariable and Multivariate Cox analyses were then carried out to compare differences in survival among patients with different clinical characteristics. The multivariate methods, such as Kaplan-Meier plotter and GEPIA survival curves, were further employed to identify the correlation of KCNQ1 expression with overall survival (OS). Besides, LinkedOmics was used to identify differentially expressed genes for functional enrichment analysis. RESULTS: KCNQ1 exhibited tissue-specific imprinting and expression in human normal tissues, organs and cell lines, while it was aberrantly expressed in pan-cancer tissues. Lower KCNQ1 mRNA expression was determined in GC tissue samples versus normal counterparts. In GC cases, elevated KCNQ1 levels were strongly linked to a longer OS and strongly correlated with invasion depth (χ2=12.631, P=0.006), TNM stage (χ2=8.750, P=0.033), differentiation grade (χ2=7.426, P=0.024), and vital status (χ2=5.676, P=0.017). Furthermore, KCNQ1 was identified by univariable and multivariate Cox analyses as an independent risk factor for GC. Based on Gene Ontology analysis, digestion as well as tricarboxylic acid metabolic, carbohydrate catabolic, and small molecule catabolic processes were differentially enriched in the up-regulated KCNQ1 phenotypic pathway. While carbon metabolism, fatty acid degradation, peroxisome, and citrate cycle (TCA cycle) were identified by the Kyoto Encyclopedia of Genes and Genomes-based analysis as pathways with differential enrichment. CONCLUSION: Being a prognostic biomarker, KCNQ1 may play an inhibitory role and involve in the metabolic process of GC.
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Ferroptosis, being classified as a form of regulated cell death, was driven by the oxidative injury induced by lipid peroxidation (LPO). Recently, ferroptosis has been confirmed to exert a critical effect in the pathogenesis and treatment of various tumors, including gastric cancer (GC). Erastin, as a frequently used ferroptosis inducer, caused ferroptosis by downregulating the xCT expression resulting in increasing reactive oxygen species (ROS) and aggravating the LPO. However, the mechanisms of Erastin in ferroptosis regulation, especially in GC, remain largely elusive. This work firstly demonstrated that Erastin inhibited cell growth and promoted apoptosis and ferroptosis in AGS and BGC823 cells. Then, based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of Erastin-related targets screened by using PharmMapper Web, the P38MAPK signaling was explored and validated in AGS and BGC-823 cells. Besides, the Fer-1 and P38 inhibitor were performed to investigate the mechanisms of ferroptosis induced by Erastin in depth. This work revealed a feedback mode among xCT, ROS and the P38MAPK pathway, which affected each other. It meant that Erastin regulated ferroptosis through the xCT-mediated ROS/P38MAPK signaling feedback loop. In addition, it was noticed that in co-operation with Erastin, the cytotoxic effects of Afatinib on cells were aggravated by further strengthening ferroptosis with activation of the P38MAPK pathway. In summary, those works provided evidence that Erastin plays an important role in increasing the cytotoxic effect on GC cells treated with Afitinib. Furthermore, the Erastin-induced ferroptosis via the xCT-mediated ROS/P38MAPK pathway feedback loop provides new strategies for GC comprehensive treatment.
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Neoplasias Gástricas , Humanos , Espécies Reativas de Oxigênio/metabolismo , Afatinib , Neoplasias Gástricas/tratamento farmacológico , Neoplasias Gástricas/genética , RetroalimentaçãoRESUMO
BACKGROUND: Gastric cancer (GC) is one of the most malignant diseases and threatens the health of individuals across the globe. Hitherto, the identification of prognosis risk stratification on GC has mainly depended on the TNM staging, but owing to its inaccuracy and incompleteness, the prognostic value it offers remains controversial in the current clinical setting. Thus, an effective prognostic model for GC after radical gastrectomy is still needed. METHODS: Patients with pathologically confirmed GC who underwent radical gastrectomy from 2 different centers were retrospectively enrolled into a training and the validation cohort, respectively. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to select variables among multiple factors, including clinical characteristics, pathological parameters, and surgery- and treatment-related indicators. The multivariate Cox regression method was used to establish the model to predict 1-, 2-, and 3-year survival. Both internal and external validations of the nomogram were then completed in terms of discrimination, calibration, and clinical utility. Finally, prognostic risk stratification of GC was conducted with X-tile software. RESULTS: A total of 1,424 patients with GC were eligible in this study, including 1,010 in the training cohort and 414 in the validation cohort. Seven indicators were selected by LASSO to develop the nomogram, including the number of positive lymph nodes, tumor size, adjacent organ invasion, vascular invasion, the level of carbohydrate antigen 125 (CA 125), depth of invasion, and human epidermal growth factor receptor 2 (HER2) status. The nomogram demonstrated a robust predictive capacity with favorable accuracy, discrimination, and clinical utility both in the internal and external validations. Moreover, we divided the population into 3 risk groups of survival according to the cutoff points generated by X-tile, and in this way, the nomogram was further improved into a risk-stratified prognosis model. CONCLUSIONS: We have developed a prognostic risk stratification nomogram for GC patients after radical gastrectomy with 7 available indicators that may guide clinical practice and help facilitate tailored decision-making, thus avoiding overtreatment or undertreatment and improving communication between clinicians and patients.
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BACKGROUND: Gastric cancer (GC) is one of the most significant health problems worldwide. Some studies have reported associations between Phospholipase C epsilon 1 (PLCE1) single-nucleotide polymorphisms (SNPs) and GC susceptibility, but its relationship with GC prognosis lacked exploration, and the specific mechanisms were not elaborated fully yet. This study aimed to further explore the possible mechanism of the association between PLCE1 polymorphisms and GC. MATERIALS AND METHODS: A case-control study, including 588 GC patients and 703 healthy controls among the Chinese Han population, was performed to investigate the association between SNPs of PLCE1 and GC risk by logistic regression in multiple genetic models. The prognostic value of PLCE1 in GC was evaluated by the Kaplan-Meier plotter. To explored the potential functions of PLCE1, various bioinformatics analyses were conducted. Furthermore, we also constructed the spatial structure of PLCE1 protein using the homology modeling method to analyze its mutations. RESULTS: Rs3765524 C > T, rs2274223 A > G and rs3781264 T > C in PLCE1 were associated with the increased risk of GC. The overall survival and progression-free survival of patients with high expression of PLCE1 were significantly lower than those with low expression [HR (95% CI) = 1.38 (1.1-1.63), P < 0.01; HR (95% CI) = 1.4 (1.07-1.84), P = 0.01]. Bioinformatic analysis revealed that PLCE1 was associated with protein phosphorylation and played a crucial role in the calcium signal pathway. Two important functional domains, catalytic binding pocket and calcium ion binding pocket, were found by homology modeling of PLCE1 protein; rs3765524 polymorphism could change the efficiency of the former, and rs2274223 polymorphism affected the activity of the latter, which may together play a potentially significant role in the tumorigenesis and prognosis of GC. CONCLUSION: Patients with high expression of PLCE1 had a poor prognosis in GC, and SNPs in PLCE1 were associated with GC risk, which might be related to the changes in spatial structure of the protein, especially the variation of the efficiency of PLCE1 in the calcium signal pathway.