Dataset Information

Tre2-Bub2-Cdc16 Family Proteins Based Nomogram Serve as a Promising Prognosis Predicting Model for Melanoma.

ABSTRACT: Tre2-Bub2-Cdc16 (TBC) proteins are conserved in eukaryotic organisms and function as negative feedback dominating the GAPs for Rab GTPases, while the function of TBC proteins in melanoma remains unclear. In this study, we observed the differential expression of 33 TBC genes in TCGA datasets classified by clinical features. Seven prognostic-associated TBC genes were identified by LASSO Cox regression analysis. Mutation analysis revealed distinctive frequency alteration in the seven prognostic-associated TBCs between cases with high and low scores. High-risk score and cluster 1 based on LASSO Cox regression and consensus clustering analysis were relevant to clinical features and unfavorable prognosis. GSVA analysis showed that prognostic-associated TBCs were related to metabolism and protein transport signaling pathway. Correlation analysis indicated the relationship between the prognostic-associated TBCs with RAB family members, invasion-related genes and immune cells. The prognostic nomogram model was well established to predict survival in melanoma. What's more, interference of one of the seven TBC proteins TBC1D7 was confirmed to inhibit the proliferation, migration and invasion of melanoma cells in vitro. In summary, we preliminarily investigated the impact of TBCs on melanoma through multiple bioinformatics analysis and experimental validation, which is helpful for clarifying the mechanism of melanoma and the development of anti-tumor drugs.

SUBMITTER: Tang L

PROVIDER: S-EPMC7656061 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Tre2-Bub2-Cdc16 Family Proteins Based Nomogram Serve as a Promising Prognosis Predicting Model for Melanoma.

Tang Ling L Peng Cong C Zhu Su-Si SS Zhou Zhe Z Liu Han H Cheng Quan Q Chen Xiang X Chen Xiao-Ping XP

Frontiers in oncology 20201028

Tre2-Bub2-Cdc16 (TBC) proteins are conserved in eukaryotic organisms and function as negative feedback dominating the GAPs for Rab GTPases, while the function of TBC proteins in melanoma remains unclear. In this study, we observed the differential expression of 33 TBC genes in TCGA datasets classified by clinical features. Seven prognostic-associated TBC genes were identified by LASSO Cox regression analysis. Mutation analysis revealed distinctive frequency alteration in the seven prognostic-ass ...[more]

PMID: 33194704

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Project description:BackgroundAutophagy, a highly conserved lysosomal degradation pathway, is associated with the prognosis of melanoma. However, prognostic prediction models based on autophagy related genes (ARGs) have never been recognized in melanoma. In the present study, we aimed to establish a novel nomogram to predict the prognosis of melanoma based on ARGs signature and clinical parameters.MethodsData from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases were extracted to identify the differentially expressed ARGs. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate analysis were used to select the prognostic ARGs. ARGs signature, age and stage were then enrolled to establish a nomogram to predict the survival probabilities of melanoma. The nomogram was evaluated by concordance index (C-index), receiver operating characteristic (ROC) curve and calibration curve. Decision curve analysis (DCA) was performed to assess the clinical benefits of the nomogram and TNM stage model. The nomogram was validated in GEO cohorts.ResultsFive prognostic ARGs were selected to construct ARGs signature model and validated in the GEO cohort. Kaplan-Meier survival analysis suggested that patients in high-risk group had significantly worse overall survival than those in low-risk group in TCGA cohort (P = 5.859 × 10-9) and GEO cohort (P = 3.075 × 10-9). We then established and validated a novel promising prognostic nomogram through combining ARGs signature and clinical parameters. The C-index of the nomogram was 0.717 in TCGA training cohort and 0.738 in GEO validation cohort. TCGA/GEO-based ROC curve and decision curve analysis (DCA) demonstrated that the nomogram was better than traditional TNM staging system for melanoma prognosis.ConclusionWe firstly developed and validated an ARGs signature based-nomogram for individualized prognosis prediction in melanoma patients, which could assist with decision making for clinicians.

Project description:Serve and serve-reception performance have predicted success in volleyball. Given the impact of serve-reception on the game, we aimed at understanding what it is in the serve and receiver's actions that determines the selection of the type of pass used in serve-reception and its efficacy. Four high-level volleyball players received jump-float serves from four servers in two reception zones-zone 1 and 5. The ball and the receiver's head were tracked with two video cameras, allowing 3D world-coordinates reconstruction. Logistic-regression models were used to predict the type of pass used (overhand or underhand) and serve-reception efficacy (error, out, or effective) from variables related with the serve kinematics and related with the receiver's on-court positioning and movement. Receivers' initial position was different when in zone 1 and 5. This influenced the serve-related variables as well as the type of pass used. Strong predictors of using an underhand rather than overhand pass were higher ball contact of the server, reception in zone 1, receiver's initial position more to the back of the court and backward receiver movement. Receiver's larger longitudinal displacements and an initial position more to the back of the court had a strong relationship with the decreasing of the serve-reception efficacy. Receivers' positioning and movement were the factors with the largest impact on the type of pass used and the efficacy of the reception. Reception zone affected the variance in the ball's kinematics (with the exception of the ball's lateral displacement), as well as in the receivers' positioning (distances from the net and from the target). Also the reception zone was associated with the type of pass used by the receiver but not with reception efficacy. Given volleyball's rotation rule, the receiver needs to master receiving in the different reception zones; he/she needs to adapt to the diverse constraints of each zone to maintain performance efficacy. Thus, being able to flexibly vary positioning and passing, given local (zone) constraints, can yield an advantage in high-level volleyball serve-reception. Further, research needs to consider other serve modes (e.g., power-jump serve) and a full-court context of performance to support the present study's findings.

Project description:BackgroundThe optimal tool for predicting the survival of renal cell carcinoma (RCC) patients with lung metastases remains controversial.MethodsWe selected patients diagnosed with RCC and lung metastases, from 2010 to 2015, from the Surveillance, Epidemiology, and End Results (SEER) database. After the selection of inclusion criteria and exclusion criterion, the rest of the patients were incorporated into model analysis. Least absolute shrinkage and selection operator (LASSO) regression was used to select the most important features for construction of a nomogram predicting cancer-specific survival. A calibration plot and the concordance index (C-index) were used to estimate nomogram efficacy in a validation cohort. The association between important factors selected by LASSO regression, and prognosis was assessed by the Kaplan-Meier (KM) survival curve. The receiver operating characteristic (ROC) curves were drawn to compare sensitivity and specificity between the nomogram we built and the TNM stage-based model.ResultsA total of 1,369 patients met the inclusion criteria, but not the exclusion criteria. The LASSO regression model reduced 15 features to seven potential predictors of survival, including tumor grade, the extent of surgery, N and T status, histological profile, and brain and bone metastasis status. Such features had good discrimination in the KM survival curves. The nomogram showed excellent discriminatory power (C-index, 0.71; 95% confidence interval: 0.70 to 0.72) and good calibration in terms of both 1- and 2-year cancer-specific survival. The nomogram showed great discriminatory power (C-index 0.68) and adequate calibration when applied to the validation cohort. The areas under the curve (AUCs) of nomogram were 0.767 and 0.780, respectively, and the AUCs of TNM stage were 0.617 and 0.618 at 1 and 2 years, respectively.ConclusionsOur nomogram might play a major role in predicting the cancer-specific survival of RCC patients with lung metastases.

Dataset Information

Tre2-Bub2-Cdc16 Family Proteins Based Nomogram Serve as a Promising Prognosis Predicting Model for Melanoma.

Publications

Tre2-Bub2-Cdc16 Family Proteins Based Nomogram Serve as a Promising Prognosis Predicting Model for Melanoma.

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