scholarly journals Transcriptome Analysis Identifies Novel Prognostic Genes in Osteosarcoma

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Junfeng Chen ◽  
Xiaojun Guo ◽  
Guangjun Zeng ◽  
Jianhua Liu ◽  
Bin Zhao

Osteosarcoma (OS), a malignant primary bone tumor often seen in young adults, is highly aggressive. The improvements in high-throughput technologies have accelerated the identification of various prognostic biomarkers for cancer survival prediction. However, only few studies focus on the prediction of prognosis in OS patients using gene expression data due to small sample size and the lack of public datasets. In the present study, the RNA-seq data of 82 OS samples, along with their clinical information, were collected from the TARGET database. To identify the prognostic genes for the OS survival prediction, we selected the top 50 genes of contribution as the initial candidate genes of the prognostic risk model, which were ranked by random forest model, and found that the prognostic model with five predictors including CD180, MYC, PROSER2, DNAI1, and FATE1 was the optimal multivariable Cox regression model. Moreover, based on a multivariable Cox regression model, we also developed a scoring method and stratified the OS patients into groups of different risks. The stratification for OS patients in the validation set further demonstrated that our model has a robust performance. In addition, we also investigated the biological function of differentially expressed genes between two risk groups and found that those genes were mainly involved with biological pathways and processes regarding immunity. In summary, the identification of novel prognostic biomarkers in OS would greatly assist the prediction of OS survival and development of molecularly targeted therapies, which in turn benefit patients’ survival.

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hongjun Fei ◽  
Songchang Chen ◽  
Chenming Xu

Abstract Background Little data is available on prognostic biomarkers and effective treatment options for Kidney Renal Papillary Cell Carcinoma (KIRP) patients, to find potential prognostic biomarkers and new targets was an urgent mission for KIRP therapy. Methods The differentially expressed autophagy-related genes (DEARGs) were screened out according to the RNA sequencing data in The Cancer Genome Atlas database, then identified survival-related DEARGs to establish a prognostic model for survival predicting of KIRP patients. Then we verified the robustness and validity of the prognostic risk model through clinicopathological data. At last, we evaluate the prognostic value of genes that formed the prognostic risk model individually. Results We analyzed the expression of 232 autophagy-related genes (ARGs) in 289 KIRP and 32 non-tumor tissue cases, and 40 mRNAs were screened out as DEARGs. The functional and pathway enrichment analysis was done and protein–protein interaction network was constructed for all DEARGs. To sift candidate DEARGs associated with KIRP patients’ survival and create an autophagy-related risk prognostic model, univariate and multivariate Cox regression analysis were did separately. Eventually 3 desirable independent prognostic DEARGs (P4HB, NRG1, and BIRC5) were picked out and used for construct the autophagy-related risk model. The accuracy of the prognostic risk model for survival prediction was assessed by Kaplan–Meier plotter, receiver-operator characteristic curve, and clinicopathological correlational analyses. The prognostic value of above 3 genes was verified individually by survival analysis and expression analysis on mRNA and protein level. Conclusions The autophagy-related prognostic model is accurate and applicable, it can predict OS independently for KIRP patients. Three independent prognostic DEARGs can benefit for facilitate personalized target treatment too.


2020 ◽  
Vol 13 (5) ◽  
pp. 806-812
Author(s):  
Zhao Xu ◽  
Yifeng Sun ◽  
Tianhong Xu ◽  
Yidan Shi ◽  
Lifan Liang ◽  
...  

AbstractWe performed a retrospective cohort study to analyze all 87 CAD patients with MGUS and 178 CAD patients without MGUS admitted in Zhongshan Hospital Fudan University from 2015 to 2017. Patients were followed up via regular patient visits or telephone, and the median follow-up period was 2.9 years. The end point of follow-up was the occurrence of major adverse cardiac events (MACE). CAD patients with MGUS had a higher risk of MACE than those without MGUS (log-rank P = 0.0015). After adjustment for other markers in the stepwise Cox regression model, MGUS was still related to the increasing risk of MACE incident (P = 0.002, HR = 2.308). Then, we constructed the nomogram based on the Cox regression model, and the concordance index (C-index) was 0.667. Hence, MGUS might be added into the risk model of CAD.


2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S448-S449
Author(s):  
Jongtak Jung ◽  
Pyoeng Gyun Choe ◽  
Chang Kyung Kang ◽  
Kyung Ho Song ◽  
Wan Beom Park ◽  
...  

Abstract Background Acinetobacter baumannii is one of the major pathogens of hospital-acquired infection recently and hospital outbreaks have been reported worldwide. On September 2017, New intensive care unit(ICU) with only single rooms, remodeling from old ICU with multibed bay rooms, was opened in an acute-care tertiary hospital in Seoul, Korea. We investigated the effect of room privatization in the ICU on the acquisition of carbapenem-resistant Acinetobacter baumannii(CRAB). Methods We retrospectively reviewed medical records of patients who admitted to the medical ICU in a tertiary care university-affiliated 1,800-bed hospital from 1 January 2015 to 1 January 2019. Patients admitted to the medical ICU before the remodeling of the ICU were designated as the control group, and those who admitted to the medical ICU after the remodeling were designated as the intervention group. Then we compared the acquisition rate of CRAB between the control and intervention groups. Patients colonized with CRAB or patients with CRAB identified in screening tests were excluded from the study population. The multivariable Cox regression model was performed using variables with p-values of less than 0.1 in the univariate analysis. Results A total of 1,105 cases admitted to the ICU during the study period were analyzed. CRAB was isolated from 110 cases in the control group(n=687), and 16 cases in the intervention group(n=418). In univariate analysis, room privatization, prior exposure to antibiotics (carbapenem, vancomycin, fluoroquinolone), mechanical ventilation, central venous catheter, tracheostomy, the presence of feeding tube(Levin tube or percutaneous gastrostomy) and the length of ICU stay were significant risk factors for the acquisition of CRAB (p< 0.05). In the multivariable Cox regression model, the presence of feeding tube(Hazard ratio(HR) 4.815, 95% Confidence interval(CI) 1.94-11.96, p=0.001) and room privatization(HR 0.024, 95% CI 0.127-0.396, p=0.000) were independent risk factors. Table 1. Univariate analysis of Carbapenem-resistant Acinetobacter baumannii Table 2. Multivariable Cox regression model of the acquisition of Carbapenem-resistant Acinetobacter baumannii Conclusion In the present study, room privatization of the ICU was correlated with the reduction of CRAB acquisition independently. Remodeling of the ICU to the single room would be an efficient strategy for preventing the spreading of multidrug-resistant organisms and hospital-acquired infection. Disclosures All Authors: No reported disclosures


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ilari Kuitunen ◽  
Ville T. Ponkilainen ◽  
Mikko M. Uimonen ◽  
Antti Eskelinen ◽  
Aleksi Reito

Abstract Background Survival analysis and effect of covariates on survival time is a central research interest. Cox proportional hazards regression remains as a gold standard in the survival analysis. The Cox model relies on the assumption of proportional hazards (PH) across different covariates. PH assumptions should be assessed and handled if violated. Our aim was to investigate the reporting of the Cox regression model details and testing of the PH assumption in survival analysis in total joint arthroplasty (TJA) studies. Methods We conducted a review in the PubMed database on 28th August 2019. A total of 1154 studies were identified. The abstracts of these studies were screened for words “cox and “hazard*” and if either was found the abstract was read. The abstract had to fulfill the following criteria to be included in the full-text phase: topic was knee or hip TJA surgery; survival analysis was used, and hazard ratio reported. If all the presented criteria were met, the full-text version of the article was then read. The full-text was included if Cox method was used to analyze TJA survival. After accessing the full-texts 318 articles were included in final analysis. Results The PH assumption was mentioned in 114 of the included studies (36%). KM analysis was used in 281 (88%) studies and the KM curves were presented graphically in 243 of these (87%). In 110 (45%) studies, the KM survival curves crossed in at least one of the presented figures. The most common way to test the PH assumption was to inspect the log-minus-log plots (n = 59). The time-axis division method was the most used corrected model (n = 30) in cox analysis. Of the 318 included studies only 63 (20%) met the following criteria: PH assumption mentioned, PH assumption tested, testing method of the PH assumption named, the result of the testing mentioned, and the Cox regression model corrected, if required. Conclusions Reporting and testing of the PH assumption and dealing with non-proportionality in hip and knee TJA studies was limited. More awareness and education regarding the assumptions behind the used statistical models among researchers, reviewers and editors are needed to improve the quality of TJA research. This could be achieved by better collaboration with methodologists and statisticians and introducing more specific reporting guidelines for TJA studies. Neglecting obvious non-proportionality undermines the overall research efforts since causes of non-proportionality, such as possible underlying pathomechanisms, are not considered and discussed.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 674.1-674
Author(s):  
C. C. Mok ◽  
C. S. Sin ◽  
K. C. Hau ◽  
T. H. Kwan

Background:The goals of treatment of lupus nephritis (LN) are to induce remission, retard the progression of chronic kidney disease, prevent organ complications and ultimately reduce mortality. Previous cohort studies of LN have mainly focused on the risk of mortality and development of end stage renal failure (ESRF) (renal survival). The cumulative frequency of LN patients who survive without organ damage, which correlates better with the balance between treatment efficacy and toxicity, as well as quality of life, has not been well studied.Objectives:To study the organ damage free survival and its predictive factors in patients with active LN.Methods:Consecutive patients who fulfilled ≥4 ACR/SLICC criteria for SLE and with biopsy proven active LN between 2003 and 2018 were retrospectivey analyzed. Those with organ damage before LN onset were excluded. Data on renal parameters and treatment regimens were collected. Complete renal response (CR) was defined as normalization of serum creatinine (SCr), urine P/Cr (uPCR) <0.5 and inactive urinary sediments. Partial renal response (PR) was defined as ≥50% reduction in uPCR and <25% increase in SCr. Organ damage of SLE was assessed by the ACR/SLICC damage index (SDI). The cumulative risk of having any organ damage or mortality since LN was studied by Kaplan-Meier’s analysis. Factors associated with a poor outcome were studied by a forward stepwise Cox regression model, with entry of covariates with p<0.05 and removal with p>0.10.Results:273 LN patients were identified but 64 were excluded (organ damage before LN onset). 211 LN patients were studied (92% women; age at SLE 30.4±13.5 years; SLE duration at LN 1.9±3.1years). 47 (22%) patients had nephrotic syndrome and 60 (29%) were hypertensive. Histological LN classes was: III/IV±V (75.1%), I/II (7.8%) and pure V (17.1%) (histologic activity and chronicity score 7.0±4.2 and 1.8±1.5, respectively). Induction regimens were: prednisolone (33.1±17.5mg/day) in combination with intravenous cyclophosphamide (CYC) (21.4%; 1.0±0.2g per pulse), oral CYC (8.6%; 96.4±37.8mg/day), azathioprine (AZA) (14.3%; 78.6±25.2mg/day), mycophenolate mofetil (MMF) (22.8%; 1.9±0.43g/day) and tacrolimus (TAC) (17.1%; 4.3±1.1mg/day). After a follow-up of 8.6±5.4 years, 94(45%) patient developed organ damage (SDI≥1) and 21(10%) patients died. The commonest organ damage was renal (36.3%) and musculoskeletal (17.9%), and the causes of death were: infection (38.1%), malignancy (19.0%), cardiovascular events (9.5%) and ESRF complications (9.5%). At last visit, 114 (55%) patients survived without any organ damage. The cumulative organ damage free survival at 5, 10 and 15 years after renal biopsy was 73.5%, 59.6% and 48.3%, respectively. The 5, 10 and 15-year renal survival rate were 95.2%, 92.0% and 84.1% respectively. In a Cox regression model, nephritic relapse (HR 3.72[1.78-7.77]), proteinuric relapse (HR 2.30[1.07-4.95]) and older age (HR 1.89[1.05-3.37]) were associated with either organ damage or mortality, whereas CR (HR 0.25[0.12-0.50]) at month 12 were associated with organ damage free survival. Baseline SCr, uPCR and histological LN classes were not significantly associated with a poor outcome. Among patients with class III/IV LN, the long-term organ damage free survival were not significantly different in users of MMF (reference) from CYC (IV/oral) (HR 1.45[0.76- 2.75]) or TAC (HR 1.03[0.26-1.62]) as induction therapy.Conclusion:Organ damage free survival is achieved in 55% of patients with active LN upon 9 years of follow-up. CYC/MMF/TAC based induction regimens did not differ for the long-term outcome of LN. Targeting complete renal response and preventing renal relapses remain important goals of LN treatment.Acknowledgments:NILDisclosure of Interests:None declared


1998 ◽  
Vol 19 (3) ◽  
pp. S78-S79
Author(s):  
Charles Oprian ◽  
Kwan Hur ◽  
William Henderson ◽  
Bharat Thakkar ◽  
Frederick Masoudi ◽  
...  

2019 ◽  
Vol 29 (5) ◽  
pp. 1447-1465 ◽  
Author(s):  
DE McGregor ◽  
J Palarea-Albaladejo ◽  
PM Dall ◽  
K Hron ◽  
SFM Chastin

Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).


Author(s):  
Patrick Bach ◽  
Georg Weil ◽  
Enrico Pompili ◽  
Sabine Hoffmann ◽  
Derik Hermann ◽  
...  

AbstractPharmacological treatment in alcohol use disorder suffers from modest effect sizes. Efforts have been undertaken to identify patient characteristics that help to select individuals that benefit from pharmacological treatment. Previous studies indicated that neural alcohol cue-reactivity (CR) might provide a marker that identifies patients, which benefit from naltrexone treatment.We investigated the reproducibility of the association between ventral striatum (VS) activation and naltrexone (NTX) treatment response by analyzing data from a recent longitudinal clinical trial in N = 44 abstinent treatment-seeking alcohol-dependent patients. A follow-up was conducted over 3 months. We computed the percentage of significant voxels in VS and tested main effects and interactions with NTX treatment on relapse risk using Cox Regression models.We found a significant interaction effect between pre-treatment cue reactivity in the VS and NTX treatment on time to first heavy relapse (Hazard Ratio = 7.406, 95% CI 1.17–46.56, p = 0.033), such that the patient group with high VS activation (defined by a mean split) showed a significant medication effect (Hazard Ratio = 0.140, 95% CI 0.02–0.75, p = 0.022) with a number needed to treat of 3.4 [95% CI 2.413.5], while there was no significant effect in the group with low VS activation (Hazard Ratio = 0.726, p = 0.454).Thus, using an independent sample we replicated the previously described positive association between VS activation and NTX efficacy. Although our results should be considered cautiously in light of the small sample size, our results support the potential of neural alcohol CR as a tool for precision medicine approaches in alcohol dependence.


2020 ◽  
Vol 39 (10) ◽  
pp. 1558-1572
Author(s):  
Euloge C. Kenne Pagui ◽  
Enrico A. Colosimo

2020 ◽  
Author(s):  
Dai Zhang ◽  
Si Yang ◽  
Yiche Li ◽  
Meng Wang ◽  
Jia Yao ◽  
...  

Abstract Background: Ovarian cancer (OV) is deemed as the most lethal gynecological cancer in women. The aim of this study was construct an effective gene prognostic model for OV patients.Methods: The expression profiles of glycolysis-related genes (GRGs) and clinical data of patients with OV were extracted from The Cancer Genome Atlas (TCGA) database. Univariate, multivariate, and least absolute shrinkage and selection operator Cox regression analyses were conducted, and a prognostic signature based on GRGs was constructed. The predictive ability of the signature was analyzed in training and test sets.Results: Based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4), a gene risk signature was identified to predict the outcome of patients with OV. The signature showed a good prognostic ability for OV, particularly high-grade OV, in the TCGA dataset, with areas under the curve of 0.709, 0.762, and 0.808 for 3-, 5- and 10-year survival, respectively. Similar results were found in the test sets, and the signature was also an independent prognostic factor. Moreover, a nomogram combining the prediction model and clinical factors was constructed.Conclusion: Our study established a nine-GRG risk model and a nomogram to better perform on OV patients’ survival prediction. The risk model represents a promising and independent prognostic predictor for OV patients. Moreover, our study of GRGs could offer guidances for underlying mechanisms explorations in the future.


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