Comparable prognosis of early gastric cancer between intestinal type and diffuse type in patients of age 75 and older: a SEER-based cohort study.

Background: The prognostic significance of Lauren's classification in elderly early gastric cancer (EGC) patients remains largely unknown. We aim to investigate the characteristics and clinical implications of Lauren's classification in elderly EGC patients. Methods: Patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database based on the inclusion and exclusion criteria. Univariate and multivariate Cox regression, propensity score matching, inverse-probability-weighted analysis, and propensity-score adjustment were utilized to evaluate the association between Lauren's classification and cancer-specific survival (CSS) in elderly EGC patients. Stratification and interaction analyses were used to reveal the effects of confounding factors on the association between Lauren's classification and CSS. Results: The diffuse type (median, 41.0 months) showed a similar survival (37.0 months), and was mainly distributed in female group (62.5% vs. 42.2%) with poorly differentiated or undifferentiated components (89.1% vs. 27.0%) compared with intestinal type in elderly EGC patients. Analyses of univariate and multivariate Cox regression, propensity score matching, inverse-probability-weighted analysis, and propensity-score adjustment showed that Lauren's classification was not significantly CSS in elderly EGC patients (P>0.05). Subgroup and interaction analyses confirmed the stability of the results. Conclusions: Diffuse type was mainly distributed in female patients with more poorly differentiated/undifferentiated components and similar prognosis compared with intestinal type in age 75 and older EGC patients. No significant association was observed between diffuse type and CSS of the elderly EGC patients.

Adaptive metabolic response to short-term intensive fasting.

BACKGROUND & AIMS: Short-term intensive fasting (STIF), known as beego in Chinese phonetic articulation, has been practiced for more than two thousand years. However, the potential risk of STIF and the body's response to the risk have not been adequately evaluated. This study aims to address this issue, focusing on the STIF-triggered metabolic response of the liver and kidney. METHODS: The STIF procedure in the clinical trial includes a 7-day water-only intensive fasting phase and a 7-day gradual refeeding phase followed by a regular diet. The intensive fasting in humans was assisted with psychological induction. To gain insights not available in the clinical trial, we designed a STIF program for mice that resulted in similar phenotypes seen in humans. Plasma metabolic profiling and examination of gene expression as well as liver and kidney function were performed by omics, molecular, biochemical and flow cytometric analyses. A human cell line model was also used for mechanistic study. RESULTS: Clinically significant metabolites of fat and protein were found to accumulate during the fasting phase, but they were relieved after gradual refeeding. Metabolomics profiling revealed a universal pattern in the consumption of metabolic intermediates, in which pyruvate and succinate are the two key metabolites during STIF. In the STIF mouse model, the accumulation of metabolites was mostly counteracted by the upregulation of catabolic enzymes in the liver, which was validated in a human cell model. Kidney filtration function was partially affected by STIF but could be recovered by refeeding. STIF also reduced oxidative and inflammatory levels in the liver and kidney. Moreover, STIF improved lipid metabolism in mice with fatty liver without causing accumulation of metabolites after STIF. CONCLUSIONS: The accumulation of metabolites induced by STIF can be relieved by spontaneous upregulation of catabolic enzymes, suggesting an adaptive and protective metabolic response to STIF stress in the mammalian body.

Establishment and Validation of a Gene Signature-Based Prognostic Model to Improve Survival Prediction in Adrenocortical Carcinoma Patients.

BACKGROUND: The current guideline for the management of adrenocortical carcinoma (ACC) is insufficient for accurate risk prediction to guide adjuvant therapy. Given frequent and severe therapeutic side effects, a better estimate of survival is warranted for risk-specific assignment to adjuvant treatment. We attempted to construct an integrated model based on a prognostic gene signature and clinicopathological features to improve risk stratification and survival prediction in ACC. METHODS: Using a series of bioinformatic and statistical approaches, a gene-expression signature was established and validated in two independent cohorts. By combining the signature with clinicopathological features, a decision tree was generated to improve risk stratification, and a nomogram was constructed to personalize risk prediction. Time-dependent receiver operating characteristic (tROC) and calibration analysis were performed to evaluate the predictive power and accuracy. RESULTS: A three-gene signature could discriminate high-risk patients well in both training and validation cohorts. Multivariate regression analysis demonstrated the signature to be an independent predictor of overall survival. The decision tree could identify risk subgroups powerfully, and the nomogram showed high accuracy of survival prediction. Particularly, expression of a gene hitherto unknown to be dysregulated in ACC, TIGD1, was shown to be prognostically relevant. CONCLUSION: We propose a novel gene signature to guide decision-making about adjuvant therapy in ACC. The score shows unprecedented survival prediction and hence constitutes a huge step towards personalized management. As a secondary important finding, we report the discovery and validation of a new oncogene, TIGD1, which was consistently overexpressed in ACC. TIGD1 might shed further light on the biology of ACC and might give rise to targeted therapies that not only apply to ACC but potentially also to other malignancies.

KIAA1199, a Target of MicoRNA-486-5p, Promotes Papillary Thyroid Cancer Invasion by Influencing Epithelial-Mesenchymal Transition (EMT).

BACKGROUND KIAA1199 has been reported to be associated with malignant progression and poor clinical outcomes in various human malignancies. However, its clinical role and molecular function remain unknown in papillary thyroid cancer (PTC). MATERIAL AND METHODS The Cancer Genome Atlas (TCGA) was used to investigate the expression profiles of KIAA1199 and miR-486-5p in PTC. Immunohistochemistry was used to validate the protein expression of KIAA1199 in PTC. The Weighted Gene Co-expression Network Analysis (WGCNA) and Gene Set Enrichment Analysis (GSEA) were used to explore the potential pathway underling KIAA1199 in PTC. In vitro and in vivo experiments were performed to investigate the biological role of KIAA1199 in PTC progression. Luciferase reporter assays and Western blot analysis were performed to determine whether KIAA1199 is a downstream target of miR-486-5p. RESULTS We found that KIAA1199 was aberrantly elevated in PTC tissues compared with normal tissues, and upregulation of KIAA1199 was positively correlated with more advanced clinical variables. Additionally, bioinformatic analysis indicated that KIAA1199 was involved in cell migration and invasion. KIAA1199 silencing inhibited the invasive ability of PTC cells by affecting epithelial-mesenchymal transition (EMT) in vitro and in vivo. Furthermore, miR-486-5p was identified as an upstream microRNA that directly targets the 3'-UTR region of KIAA1199. CONCLUSIONS The miR-486-5p/KIAA1199/EMT axis might play a critical role in PTC invasion and metastasis and offers a potential therapeutic strategy for PTC.