scholarly journals A Five-Gene Expression Signature Predicts Clinical Outcome of Ovarian Serous Cystadenocarcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Li-Wei Liu ◽  
Qiuhao Zhang ◽  
Wenna Guo ◽  
Kun Qian ◽  
Qiang Wang
Keyword(s):  
Gene Expression ◽  
Survival Time ◽  
Proportional Hazards ◽  
Gene Expression Signature ◽  
High Specificity ◽  
Cox Proportional Hazards ◽  
Assessment Model ◽  
Serous Cystadenocarcinoma ◽  
Specificity And Sensitivity ◽  
Risk Patients

Ovarian serous cystadenocarcinoma is a common malignant tumor of female genital organs. Treatment is generally less effective as patients are usually diagnosed in the late stage. Therefore, a well-designed prognostic marker provides valuable data for optimizing therapy. In this study, we analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data. We observed the correlation between gene expression and patients’ survival and eventually established a risk assessment model of five factors using Cox proportional hazards regression analysis. We found that the survival time in high-risk patients was significantly shorter than in low-risk patients in both training and testing sets after Kaplan-Meier analysis. The AUROC value was 0.67 when predicting the survival time in testing set, which indicates a relatively high specificity and sensitivity. The results suggest diagnostic and therapeutic applications of our five-gene model for ovarian serous cystadenocarcinoma.

scholarly journals Identification of gene expression signature for cigarette smoke exposure response—from man to mouse

2015 ◽  
Vol 34 (12) ◽  
pp. 1200-1211 ◽  
Author(s):  
F Martin ◽  
M Talikka ◽  
J Hoeng ◽  
MC Peitsch
Keyword(s):  
Gene Expression ◽  
Cigarette Smoke ◽  
Whole Blood ◽  
Gene Expression Signature ◽  
High Specificity ◽  
Gene Signature ◽  
Smoke Exposure ◽  
Cigarette Smoke Exposure ◽  
Toxicant Exposure ◽  
Specificity And Sensitivity

Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol.

scholarly journals Immunogenomic determinants of tumor microenvironment correlate with superior survival in high-risk neuroblastoma

2021 ◽  
Vol 9 (7) ◽  
pp. e002417
Author(s):  
Riyue Bao ◽  
Stefani Spranger ◽  
Kyle Hernandez ◽  
Yuanyuan Zha ◽  
Peter Pytel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
T Cell ◽  
High Risk ◽  
Proportional Hazards ◽  
Checkpoint Inhibitors ◽  
Gene Expression Signature ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Models ◽  
Immune Exclusion

BackgroundTumor-infiltrating CD8+ T cells and neoantigens are predictors of a favorable prognosis and response to immunotherapy with checkpoint inhibitors in many types of adult cancer, but little is known about their role in pediatric malignancies. Here, we analyzed the prognostic strength of T cell-inflamed gene expression and neoantigen load in high-risk neuroblastoma. We also compared transcriptional programs in T cell-inflamed and non-T cell-inflamed high-risk neuroblastomas to investigate possible mechanisms of immune exclusion.MethodsA defined T cell-inflamed gene expression signature was used to categorize high-risk neuroblastomas in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) program (n=123), and the Gabriella Miller Kids First (GMKF) program (n=48) into T cell-inflamed, non-T cell-inflamed, and intermediate groups. Associations between the T cell-inflamed and non-T cell-inflamed group, MYCN amplification, and survival were analyzed by Cox proportional hazards models. Additional survival analysis was conducted after integrating neoantigen load predicted from somatic mutations. Pathways activated in non-T cell-inflamed relative to T cell-inflamed tumors were analyzed using causal network analysis.ResultsPatients with T cell-inflamed high-risk tumors showed improved overall survival compared with those with non-T cell-inflamed tumors (p<0.05), independent of MYCN amplification status, in both TARGET and GMKF cohorts. Higher neoantigen load was also associated with better event-free and overall survival (p<0.005) and was independent of the T cell-inflamed signature. Activation of MYCN, ASCL1, SOX11, and KMT2A transcriptional programs was inversely correlated with the T cell-inflamed signature in both cohorts.ConclusionsOur results indicate that tumors from children with high-risk neuroblastoma harboring a strong T cell-inflamed signature have a more favorable clinical outcome, and neoantigen load is a prognosis predictor, independent of T cell inflammation. Strategies to target SOX11 and other signaling pathways associated with non-T cell-inflamed tumors should be pursued as potential immune-potentiating interventions.

scholarly journals Validity of the International Prostate Symptoms Score in predicting urinary retention after joint replacement

2019 ◽  
Vol 27 (3) ◽  
pp. 230949901986867 ◽  
Author(s):  
Alasdair JA Santini ◽  
Chetan A Jakaraddi ◽  
Fotis Polydoros ◽  
Sree Metikala
Keyword(s):  
Urinary Tract ◽  
Urinary Retention ◽  
Preoperative Evaluation ◽  
Age Groups ◽  
High Specificity ◽  
Logistic Regression Models ◽  
Prosthetic Joints ◽  
Specificity And Sensitivity ◽  
Urinary Tract Symptoms ◽  
Risk Patients

Postoperative urinary retention necessitating catheterization after major lower limb arthroplasty surgery adds to the patients’ postoperative discomfort and increases the risk of urinary tract infection with potential risk of transient bacteraemia and seeding of infection to prosthetic joints. Preoperative evaluation of patients with lower urinary tract symptoms may help to identify at-risk patients and the International Prostate Symptoms Score (IPSS) has been used as a screening tool to quantify the severity of symptoms in males. A prospective cohort of 303 patients undergoing total hip or knee arthroplasty was evaluated using the IPSS. Patients were categorized into three symptom groups (mild, moderate and severe based on scores of 0–7, 8–18 and greater than 18, respectively) and four age groups (<50 years, 51–60 years, 61–70 years and greater than 70 years). Twenty-six patients (8.6%) developed urinary retention and were catheterized postoperatively; of these, 16 were male and 10 were female. Statistical analysis using logistic regression models showed significant association between severe IPSS scores (>18) and urinary retention requiring catheterization in both males and females with both high specificity and sensitivity in the test in predicting postoperative catheterization. Hence, this test is a valid preoperative screen in predicting postoperative catheterization.

Abstract 15330: Association Between Elective Percutaneous Coronary Intervention Appropriateness and Publicly Reported Outcomes

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Vinay Kini ◽  
Paul Hess ◽  
Wenhui Liu ◽  
Gary Grunwald ◽  
Michael Ho ◽  
...  
Keyword(s):  
Percutaneous Coronary Intervention ◽  
Proportional Hazards ◽  
Coronary Intervention ◽  
Cox Proportional Hazards ◽  
Veterans Administration ◽  
Elective Percutaneous Coronary Intervention ◽  
Percutaneous Coronary ◽  
National Cohort ◽  
Risk Patients ◽  
Facility Level

Introduction: Public reporting of percutaneous coronary intervention (PCI) outcomes such as readmission and mortality may cause harm by adversely affecting patient selection for PCI. Little is known about the relationship between these outcomes and elective PCI appropriateness - a validated metric of PCI quality. Methods: We identified all patients in the national Veterans Administration healthcare system who underwent elective PCI for stable coronary disease between 2013 and 2015. We defined PCI appropriateness using 2012 criteria. The primary outcome was 90-day all-cause hospitalization or mortality. We used hierarchical Cox proportional hazards regression models adjusted for patient- and facility-level covariates to compare outcomes across PCI appropriateness categories, and a joint survival/logistic model to compare facility-level variation in inappropriate PCI and 90-day outcomes. Results: Among 2,561 patients (mean age 66 years, 99% men) undergoing PCI across 59 sites, 29.6% were classified as appropriate, 10.4% as inappropriate, and 60% as uncertain. The proportion of patients who were readmitted or died were 15.6%, 16.4%, and 15.3% among patients who received appropriate, inappropriate, and uncertain PCI respectively. There were no significant differences in 90-day outcomes between the groups (hazard ratio for appropriate compared to inappropriate PCI 0.82 [CI 0.57 to 1.17; p=0.28]). The site level covariance between inappropriate PCI and 90-day outcomes was -0.033 (95% CI -0.117 to 0.047), indicating no site-level correlation between appropriateness and 90-day outcomes (Figure). Conclusion: We found no association between elective PCI appropriateness and 90-day outcomes among a national cohort of Veterans. Including appropriateness in public reports may 1) characterize PCI quality more fully and 2) potentially mitigate the harms of reporting outcomes by empowering providers to perform appropriate PCI in higher-risk patients.

scholarly journals Failure to reach uric acid target of <0.36 mmol/L in hyperuricaemia of gout is associated with elevated total and cardiovascular mortality

RMD Open ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. e001015 ◽  
Author(s):  
Fernando Pérez Ruiz ◽  
Pascal Richette ◽  
Austin G Stack ◽  
Ravichandra Karra Gurunath ◽  
Ma Jesus García de Yébenes ◽  
...  
Keyword(s):  
Uric Acid ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
First Year ◽  
Cox Proportional Hazards Models ◽  
Crude Mortality ◽  
Risk Patients ◽  
The Impact ◽  
Related Mortality

ObjectiveTo determine the impact of achieving serum uric acid (sUA) of <0.36 mmol/L on overall and cardiovascular (CV) mortality in patients with gout.MethodsProspective cohort of patients with gout recruited from 1992 to 2017. Exposure was defined as the average sUA recorded during the first year of follow-up, dichotomised as ≤ or >0.36 mmol/L. Bivariate and multivariate Cox proportional hazards models were used to determine mortality risks, expressed HRs and 95% CIs.ResultsOf 1193 patients, 92% were men with a mean age of 60 years, 6.8 years’ disease duration, an average of three to four flares in the previous year, a mean sUA of 9.1 mg/dL at baseline and a mean follow-up 48 months; and 158 died. Crude mortality rates were significantly higher for an sUA of ≥0.36 mmol/L, 80.9 per 1000 patient-years (95% CI 59.4 to 110.3), than for an sUA of <0.36 mmol/L, 25.7 per 1000 patient-years (95% CI 21.3 to 30.9). After adjustment for age, sex, CV risk factors, previous CV events, observation period and baseline sUA concentration, an sUA of ≥0.36 mmol/L was associated with elevated overall mortality (HR=2.33, 95% CI 1.60 to 3.41) and CV mortality (HR=2.05, 95% CI 1.21 to 3.45).ConclusionsFailure to reach a target sUA level of 0.36 mmol/L in patients with hyperuricaemia of gout is an independent predictor of overall and CV-related mortality. Targeting sUA levels of <0.36 mmol/L should be a principal goal in these high-risk patients in order to reduce CV events and to extend patient survival.

Quantitative Gene Expression Analysis of Surrogate Markers for Genetic Risk Groups and Survival in CLL

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 4170-4170
Author(s):  
Dirk Kienle ◽  
Axel Benner ◽  
Dirk Winkler ◽  
Manfred Hensel ◽  
Riccardo Dalla-Favera ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Survival Analysis ◽  
Genetic Risk ◽  
Proportional Hazards ◽  
Risk Groups ◽  
Cox Proportional Hazards ◽  
Surrogate Markers ◽  
Mutation Status ◽  
Binet Stage

Abstract In CLL, a variety of surrogate markers for individual genetic features, mostly the VH mutation status, were proposed from gene expression analyses. However, their detailed relation to specific genetic subsets such as V3-21 usage, del11q22-q23 (11q−), and del17p13 (17p−), and their prognostic value in relation to established factors is not elucidated yet. Gene expression markers (ADAM29, ATM, CLLU1, DMD, GLO1, HS1, KIAA0977, LPL, MGC9913, PCDH9, PEG10, SEPT10, TCF7, TP53, Vimentin, ZAP-70, ZNF2) were evaluated using real-time quantitative RT-PCR (RQ-PCR) in purified samples of 151 patients. VH sequencing and FISH screening for genomic aberrations were carried out for all cases, survival information was available for 133 cases. Logistic regression was performed to test the predictive value of gene expression for genetic risk groups, Cox proportional hazards statistics for survival analysis. VH mutation status was best assigned by LPL and ZAP70, followed by TCF7, a marker with a characteristic overexpression in VH mutated CLL patients (correct VH prediction in 83%, 83%, and 75% of the patients, respectively). A similar rate of correct VH assignments was achieved in the subgroup of patients with 11q− or 17p− when using these markers (88%, 86%, and 79%, respectively). In contrast to LPL and TCF7, most of the patients with V3-21 usage were recognized as risk patients by ZAP70 independently of the VH status. Therefore, ZAP70 yielded the best results for the overall recognition of patients with a genetic risk constellation (VH unmutated or V3-21 usage or 11q− or 17p−). Comparison of ZAP-70 determination by RQPCR and flow cytometry was performed for 72 patients and revealed 30% of discordant cases. Thereof, the majority was VH unmutated (including several cases with 11q− or 17p−) showing ZAP-70 negativity by FACS and positivity by RQ-PCR. In multivariate analysis of time to first treatment (TFT), ADAM29 was an independent prognostic factor besides the VH status and Binet stage. In overall survival analysis including the gene expression variables only, LPL was the strongest predictor for overall survival. When genetic and clinical factors were added to this analysis, V3-21 usage, 17p−, age, binet stage, and expression of ATM, ADAM29, SEPT10, and TCL1 were identified as significant prognostic factors. In conclusion, novel gene expression markers allow screening for patients at risk but can not fully substitute for the genetic factors, which should therefore at present remain the basis for risk stratification approaches. Some of the novel markers appear to have a prognostic relevance independently of the established factors, which points to relevant biologic and clinical implications demanding further investigation.

Evidence for a field effect in early prostate cancer (PCa): Gene expression profiles in normal-appearing prostate tissue (NT) adjacent to tumor (T) as predictors of clinical outcome.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 5029-5029 ◽  
Author(s):  
Eric A. Klein ◽  
Sara Moscovita Falzarano ◽  
Nan Zhang ◽  
Dejan Knezevic ◽  
Tara Maddala ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Field Effect ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cox Proportional Hazards ◽  
Clinical Recurrence ◽  
Molecular Alterations ◽  
Cox Proportional Hazards Models

5029 Background: We previously identified genes whose expression predicts aggressive PCa (clinical recurrence (cR), prostate cancer death (PCD), adverse pathology) when assessed in histologically heterogeneous tumor foci and in biopsies (Klein ASCO 2012). These results enabled the definition of a multi-gene Genomic Prostate Score (GPS), which has been clinically validated (Cooperberg AUA 2013). There is interest regarding a possible field effect in PCa, i.e. molecular alterations throughout the gland that may influence PCa development. We conducted exploratory analyses to evaluate gene expression, including GPS, in adjacent normal-appearing tissue (NT) for prediction of cR and PCD. Methods: Cohort sampling was used to select 127 patients with and 374 without cR from 2,641 patients treated with RP for T1/T2 PCa. Expression of 732 genes was measured by qRT-PCR separately in T and NT (defined as > 3 mm from T) specimens. GPS (0-100 units) was determined using the genes and algorithm from the validation study. Analysis used Cox proportional hazards models and Storey’s false discovery rate (FDR) control. Results: 410 evaluable patients had paired T and NT. Of the 405 genes which were predictive of outcome in T (FDR < 20%), 289 (71%) showed similar but weaker effects in NT. 47 genes were associated with cR in NT (FDR < 20%), of which 34 also concordantly predicted cR in T (FDR < 20%). GPS assessed in NT significantly predicted time to cR (HR/20 units = 1.8; 95% CI: 1.3-2.4; p< 0.001) and PCD (HR/20 units = 1.9; 95% CI: 1.2-3.0; p = 0.005) but was less predictive than GPS in T (HR/20 units = 4.8 for cR; 95% CI: 3.7-6.2; p < 0.001 and HR/20 units = 6.9 for PCD; 95% CI: 4.4-10.7; p < 0.001). The strongest components of GPS in predicting cR and PCD in NT were stromal response and androgen signaling genes (p < 0.05); proliferation and cellular organization genes did not consistently provide a significant contribution in NT. Conclusions: These data indicate that gene expression profiles, including GPS, can predict outcome in NT, albeit more weakly than in tumor. These findings suggest that there is an underlying field effect associated with the development of aggressive PCa.

scholarly journals A Prognostic Nomogram Combining Gene Expression Profiles and TNM Stage Predicts Survival in Gastric Cancer

2021 ◽  
Author(s):  
Jian Huang ◽  
Dongcun Wang ◽  
Xiaoliang Wang ◽  
Xiaoxing Ye ◽  
Jiping Da
Keyword(s):  
Gene Expression ◽  
Risk Score ◽  
Proportional Hazards ◽  
Expression Profiles ◽  
Tnm Staging ◽  
Cox Proportional Hazards ◽  
Tnm Stage ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
High Morbidity

Abstract BackgroundGastric carcinoma (GC) is a highly aggressive malignancy and is associated with high morbidity and mortality rates around the world, the current tumor-node-metastasis (TNM) staging system is inadequate to predict overall survival (OS) in GC patients. therefore, potential forecasting methods for prognosis are important to investigate.MethodsDifferentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas (TCGA). We then construct a risk score signature model by univariate Cox proportional hazards regression (CPHR) analysis, the Kaplan-Meier method（KM）and multivariate CPHR analysis. Using TNM stage, we developed a signature-based nomogram. Finally, we utilize an independent Gene Expression Omnibus dataset (GSE62254) validate the prognostic value of risk score signature model and nomogram.ResultsWe identified five OS-related mRNAs among 1113 mRNAs that were differentially expressed between GC and normal samples in the TCGA dataset. We then constructed a five-mRNA signature model, which efficiently distinguished high-risk from low-risk patient in both cohort, and even viable in the TNM stage-III, gender(male, female) and age(＜65-year-old, ≥65-year-old) subgroups (P<0.05). Utilizing TNM stage, we developed a signature-based nomogram, which performed better than use the TNM stage or five-mRNA signature alone for prognostic prediction in the TCGA and GSE62254 dataset.ConclusionsThese results suggest that both risk signature and nomogram were effective prognostic indicators for patients with GCs, and could potentially be used for individualized management of such patients.

scholarly journals Nomogram Model for Dynamic and Individual Prediction of Cardiac Response and Survival for Light Chain Amyloidosis in 737 Patients With Cardiac Involvement

2021 ◽  
Vol 11 ◽  
Author(s):  
Yang Li ◽  
Yanze Cao ◽  
Mingxin Zheng ◽  
Jiaqi Hu ◽  
Wei Yan ◽  
...  
Keyword(s):  
Light Chain ◽  
Cardiac Involvement ◽  
Proportional Hazards ◽  
Dynamic Assessment ◽  
Cox Proportional Hazards ◽  
Assessment System ◽  
Assessment Model ◽  
Cardiac Response ◽  
Related Factors ◽  
Light Chain Amyloidosis

ObjectiveLight chain amyloidosis (AL) with cardiac involvement is associated with poor prognosis. The existing prognostic assessment system does not consider treatment-related factors, and there is currently no effective system for predicting the response. The purpose of this study was to build an individualized, dynamic assessment model for cardiac response and overall survival (OS) for AL patients with cardiac involvement.MethodsThe records of 737 AL patients with cardiac involvement were collected through cooperation with 18 hospitals in the Chinese Registration Network for Light-chain Amyloidosis (CRENLA). We used univariate and multivariate analyses to evaluate the prognostic factors for OS and cardiac response. Then, two nomogram models were developed to predict OS and cardiac response in AL patients with cardiac involvement.ResultsA nomogram including four independent factors from the multivariate Cox proportional hazards analysis—Mayo staging, courses of treatment, hematologic response, and cardiac response—was constructed to calculate the possibility of achieving survival by adding all the points associated with four variables. The higher the score, the more likely death would occur. The other nomogram model included the courses of treatment, hematological response, and different treatment regimens, and was correlated with cardiac response. The higher the score, the more likely a cardiac response would occur.ConclusionIn conclusion, based on the large Chinese cohort of patients with AL and cardiac involvement, we identified nomogram models to predict cardiac response and OS. These models are more individualized and dynamic, and therefore, they have important clinical application value.

Sign in / Sign up

Export Citation Format

Share Document