BAALC-Associated Mir-3151 Is An Independent Prognostic Factor In Younger Patients With Intermediate-Risk Cytogenetic Acute Myeloid Leukemia

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2577-2577
Author(s):  
Marina Díaz-Beyá ◽  
Alfons Navarro ◽  
Marta Pratcorona ◽  
Salut Brunet ◽  
Josep F Nomdedeu ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Prognostic Value ◽  
Prognostic Significance ◽  
Intermediate Risk ◽  
Mirna Signature ◽  
Training Set ◽  
Molecular Subgroup ◽  
Younger Patients ◽  
Expression Levels ◽  
Validation Set

Abstract Introduction Patients with intermediate-risk cytogenetic AML (IR-AML) have a heterogeneous prognosis, and are currently further stratified based on determined gene mutations. However, the optimal post-remission therapy, especially in younger patients, is unclear. Recently, miR-3151, a novel microRNA (miRNA) located in intron 1 of the BAALC gene, has been identified. High miR-3151 expression –either alone or in combination with high BAALClevels– independently correlates with poor prognosis in patients ≥ 60 years with normal cytogenetics AML (CN-AML) (Eisfeld AK, et al. Blood 2012). However, the prognostic value of miR-3151 in younger patients (≤60 years) with IR-AML has not been examined. We hypothesized that miR-3151 expression could also be a prognostic marker in younger patients. Aim To analyze whether miR-3151 expression – either alone or in combination with BAALC– improved prognostic assessment in younger patients (up to 60 years) with IR-AML and to characterize in this subset of patients the miRNA signature associated with high miR-3151 expression. Methods Samples were available from two separate cohorts of patients with IR-AML who had received intensive therapy: a training set of 76 patients from a single institution and a validation set of 108 patients from several centers who had been treated within the CETLAM AML-2003 protocol. Information on NPM1, FLT3-ITD and CEBPA was available for both patient cohorts. The expression levels of 670 miRNAs had previously been analyzed in the 76 patients in the training set. In the present study, the expression of miR-3151 and BAALC was analyzed using TaqMan® MicroRNA Assay and TaqMan® Gene Expression Assay (Applied Biosystems), respectively. Expression levels of miR-3151 and BAALC –both alone and in combination – were correlated with patient outcome. Statistical analyses were performed with SPSS v.15.0.1, R software v.2.9.0 and TIGR MultiExperiment Viewerv4.0. Results In the training set, higher expression of miR-3151(dichotomized by its median value of normalized expression) correlated with a shorter 5-year overall survival (OS) (32%±17% vs. 61±17%, p=0.029) and 5-year leukemia-free survival (LFS) (29%±17% vs. 58±17%, p=0.036) in patients ≤ 60 yrs. When the analysis was restricted to patients with CN-AML, miR-3151 expression retained its prognostic significance (p= 0.016). In addition, increased BAALCexpression was associated with shorter OS (28%±20% vs. 58±14%, p=0.054) and LFS (17%±18% vs. 55±14%, p=0.039). In the multivariate analysis for OS and LFS, including age, WBC, NPM1mut, FLT3-ITD, BAALC and miR-3151 expression levels as covariates, miR-3151 showed independent prognostic significance for OS (p=0.016; HR=2.52, 95% CI: 1.2-5.4),and a statistical trend for LFS (p=0.09). Patients with low expression of both miR-3151 and BAALC had better prognosis (OS: 66%±18% vs. 34±16%, p=0.027; LFS: 67%±20% vs. 27±16%, p=0.009).Interestingly, the combination of both miR-3151 and BAALC retained a significant prognostic value for LFS within the favorable molecular subgroup/ ELN favorable subgroup (patients harboring NPM1mut without FLT3-ITD or biallelic CEBPAmut; LFS: 44%±30% vs. 100%, p=0.017) and showed a trend in the unfavorable molecular subgroup/ELN Intermediate I&II subgroups (patients lacking both NPM1 and CEBPA mutations and/or harboring FLT3-ITD; OS: p=0.064 and LFS: p=0.072). In the validation set, miR-3151 overexpression confirmed its prognostic impact in patients in the univariate analysis for OS (45%±12% vs. 26±19%, p=0.039) and LFS (51%±14% vs. 30±24%, p=0.034) and in the multivariate analysis for OS (OS: p=0.038; HR 1.88, IC 95%: 1.06-3.34) and LFS (p= 0.014; HR 2.411 (1.198-4.855) Finally, a supervised analysis revealed that samples exhibiting high levels of miR-3151 expression had a distinctive miRNA signature including miR-509, miR-135a, miR-100*, miR-186*, let-7a* and miR-501. Conclusion miR-3151 is an independent prognostic marker in patients with IR-AML. The study of miR-3151 refines the molecular prognostic stratification of these patients and hence could be of help to guide therapy. Acknowledgments Marina Díaz-Beyá is supported by Fundación Española de Hematologia y Hemoterapia. This research is supported by Sociedad Española de Hematologia y Hemoterapia and by grants from Fondo de Investigaciones Sanitarias FIS-PI080158. Disclosures: No relevant conflicts of interest to declare.

Circulating Exosomal microRNAs Are Prognostic Markers in Multiple Myeloma

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1770-1770
Author(s):  
Salomon Manier ◽  
Herve Avet-Loiseau ◽  
Federico Campigotto ◽  
Karma Salem ◽  
Daisy Huynh ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Risk Score ◽  
Prognostic Value ◽  
Prognostic Significance ◽  
Newly Diagnosed ◽  
Mirna Signature ◽  
Training Set ◽  
Advisory Committees ◽  
Exosomal Mirnas ◽  
Validation Set

Abstract Background Exosomes are secreted by several cell types including cancer cells and can be isolated from peripheral blood. They contain proteins and nucleic acids and promote tumorigenesis in many types of cancer. We aimed to establish the prognostic significance of circulating exosomal microRNAs (miRNAs) in multiple myeloma (MM). Methods We first analyzed the miRNAs content of circulating exosomes in MM by small RNA sequencing of 10 samples from MM patients and 5 healthy controls. We then analyzed 156 serum samples from newly diagnosed patients with MM, uniformly treated with a Bortezomib and Dexamethasone based regimen. Using a quantitative RT-PCR array for 23 miRNAs, we assessed the associations between exosomal miRNAs and progression-free survival. Findings By next generation sequencing, we identified 158 differentially expressed miRNAs in MM compared to normal healthy controls, notably including let-7 family members, miR-17/92 or miR-99b/125a clusters. We further identified a three-miRNA signature based on 156 MM samples (combining miR-106b, miR-18a and let-7e) and calculated a risk score to classify patients as high risk or low risk. Compared to low risk score, patients with a high risk score had a shorter PFS in the training set (hazard ratio [HR] 1·8, 95% CI 1·0-3·0; p=0·0375) and the validation set (HR 2·6, 1·5-4·4; p=0·0005). To further validate this signature, we generated 500 randomly computed re-sampling of the data sets. The three-miRNA signature was consistently significant with a p-value < 0·05 in more than 78% and < 0·10 in 86% of the 500 randomizations. The circulating exosomal miRNA signature was an independent prognostic marker after adjusting for cytogenetics and ISS. In a receiver operating characteristic (ROC) analysis, a combination of this signature together with International Staging System (ISS) and cytogenetics had a better prognostic value than ISS and cytogenetics alone in the training set (2 years area under the ROC curve 0·64 [95% CI 0·56-0·72] vs. 0·60 [95% CI 0·52-0·69]) and the validation set (0·67 [0·59-0·75] vs. 0·58 [0·50-0·66]). Interpretation This study demonstrates unprecedented evidence of the prognostic significance of exosomal miRNAs in patients with MM. We identified a three-miRNA signature in circulating exosomes that adds prognostic value to ISS and cytogenetic status and helps improve prognostic identification of newly diagnosed MM patients. Disclosures Avet-Loiseau: jansen: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; celgene: Membership on an entity's Board of Directors or advisory committees; onyx: Membership on an entity's Board of Directors or advisory committees; onyx: Membership on an entity's Board of Directors or advisory committees; jansen: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; millenium: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees. Moreau:Celgene, Janssen, Takeda, Novartis, Amgen: Membership on an entity's Board of Directors or advisory committees. Facon:Onyx: Membership on an entity's Board of Directors or advisory committees; Millenium: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; Pierre Fabre: Membership on an entity's Board of Directors or advisory committees.

scholarly journals Prediction Model of HBsAg Seroclearance in Patients with Chronic HBV Infection

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Jing Cao ◽  
Jiao Gong ◽  
Christ-Jonathan Tsia Hin Fong ◽  
Cuicui Xiao ◽  
Guoli Lin ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Hepatitis B ◽  
Cox Regression ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Hbsag Loss ◽  
Actual Observation ◽  
Hbsag Seroclearance ◽  
Low Incidence ◽  
Validation Set

Background. Prediction of HBsAg seroclearance, defined as the loss of circulating HBsAg with or without development of antibodies for HBsAg in patients with chronic hepatitis B (CHB), is highly difficult and challenging due to its low incidence. This study is aimed at developing and validating a nomogram for prediction of HBsAg loss in CHB patients. Methods. We analyzed a total of 1398 patients with CHB. Two-thirds of the patients were randomly assigned to the training set (n=918), and one-third were assigned to the validation set (n=480). Univariate and multivariate analysis by Cox regression analysis was performed using the training set, and the nomogram was constructed. Discrimination and calibration were performed using the training set and validation set. Results. On multivariate analysis of the training set, independent factors for HBsAg loss including BMI, HBeAg status, HBsAg titer (quantitative HBsAg), and baseline hepatitis B virus (HBV) DNA level were incorporated into the nomogram. The HBsAg seroclearance calibration curve showed an optimal agreement between predictions by the nomogram and actual observation. The concordance index (C-index) of nomogram was 0.913, with confirmation in the validation set where the C-index was 0.886. Conclusions. We established and validated a novel nomogram that can individually predict HBsAg seroclearance and non-seroclearance for CHB patients, which is clinically unprecedented. This practical prognostic model may help clinicians in decision-making and design of clinical studies.

Incorporation of PBRM1, BAP1, TP53 mutation status into the Memorial Sloan Kettering Cancer Center (MSKCC) risk model: A genomically annotated tool to improve stratification of patients (pts) with advanced renal cell carcinoma (RCC).

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 639-639 ◽  
Author(s):  
Martin Henner Voss ◽  
Yuan Cheng ◽  
Mahtab Marker ◽  
Fengshen Kuo ◽  
Toni K. Choueiri ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Prognostic Value ◽  
Risk Model ◽  
Original Model ◽  
Phase Iii ◽  
Training Set ◽  
First Line ◽  
Mutation Status ◽  
New Model ◽  
Validation Set

639 Background: The MSKCC risk model, an established prognostic tool fo r metastatic RCC, integrates clinical + laboratory data, but is ignorant to tumor genomics. Mutations in BAP1, PBRM1, TP53, cumulatively found in over 50% of pts, have prognostic value in RCC. We sought to study the use of integrating mutation status into the MSKCC model using two large clinical trial datasets. Methods: Pts had received first line sunitinib or pazopanib on the phase III COMPARZ (training set, n = 357) or the phase II RECORD3 trial (validation set, n = 130). Genes were evaluated by next generation sequencing using archival tissue. Association of mutation status and overall survival (OS) was tested by multivariate Cox regression analysis (MVA) in the training set. An annotated model was constructed combining the original clinical variables and mutation status for the 3 genes. We compared risk group assignment and concordance index (c-index) for the original vs. new model in training and validation set. Results: Mutation status for each gene: BAP1, TP53 and PBRM1 independently correlated with OS on MVA (p≤0.0035). Comparing the original (clinical only) to the annotated (clinical + genomics) model, risk categories changed in 139 pts (39%). The C-index was improved with integration of genomic information (0.595 original model - > 0.628 new model). The independent validation cohort confirmed improvement of c-index for predicting OS with integration of genomic data (c-index 0.622 original model - > 0.641 new model). Conclusions: Mutation status for BAP1, PBRM1, and TP53 has prognostic value in pts with advanced RCC. The annotated risk model alters risk status in over 1/3 of pts and improves accuracy of estimating outcomes in patients receiving first-line therapy. Clinical trial information: NCT00720941. [Table: see text]

Serum microRNA signatures for the detection of pancreatobiliary cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15718-e15718
Author(s):  
Shuichi Mitsunaga ◽  
Shogo Nomura ◽  
Kazuo Hara ◽  
Yukiko Takayama ◽  
Makoto Ueno ◽  
...  
Keyword(s):  
Validation Cohort ◽  
External Validation ◽  
Diagnostic Value ◽  
Healthy Controls ◽  
Mirna Signature ◽  
Training Set ◽  
Linear Discriminant ◽  
Serum Mirna ◽  
Validation Set ◽  
Sensitivity Specificity

e15718 Background: The diagnostic value of serum microRNAs (miRNA) in a highly sensitive microarray for pancreatobiliary cancer (PBca) has been demonstrated. This study attempted to build and validate a signature comprised of multiple serum miRNA markers for discriminating PBca from healthy controls. Methods: A multicenter prospective study on the diagnostic performance of serum miRNAs was conducted. The patients (pts) with treatment-naïve PBca and healthy participants aged ≥60 years were enrolled. Clinical data and sera were collected. Target population was randomly divided to training or validation cohort with an allocation ratio of 2:1. Twenty-nine serum miRNA markers on the microarray data were analyzed. Using any combinations of the markers, a Fisher’s linear discriminant analysis was performed, and the resulting sensitivity, specificity and AUC of ROC curve to discriminate PBca from healthy controls were calculated for each combination. Marker combinations with a sensitivity/specificity (SN/SP) of ≥80%/90% and high AUC in comparison with AUC of CA19-9 were defined as the diagnostic miRNA signature, which were selected in the training cohort. Next, the signatures were screened out which showed a good reproducibility in the validation cohort. As an independent external cohort, PBca pts and healthy with pooled frozen sera were enrolled and the identified miRNA signatures were further validated. Results: Total of 546 participants (80 healthy and 223 PBca in training set, 40 healthy and 104 PBca in validation set, 49 healthy and 50 PBca in external validation set) were analyzed in this study. Four serum miRNA combinations were identified as the diagnostic miRNA signature. In the training set, four miRNA signatures, consisted of 10 miRNAs, were developed. For the best-performed miRNA signature, the SN/SP and AUC in the validation and external validation cohorts were 84/90% and 0.95 (CA19-9: 73/95% and 0.88) and 84/90% and 0.93 (CA19-9: 80/94% and 0.87), respectively. Conclusions: The diagnostic serum miRNA signatures for PBca were identified in this study.

scholarly journals The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis–Trans Isomerase Gene Signature in Hepatocellular Carcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Huadi Shi ◽  
Fulan Zhong ◽  
Xiaoqiong Yi ◽  
Zhenyi Shi ◽  
Feiyan Ou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Risk Score ◽  
Prognostic Value ◽  
Prognostic Model ◽  
Stepwise Regression ◽  
Gene Signature ◽  
Training Set ◽  
Model Based ◽  
Kaplan Meier ◽  
Validation Set

Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis–trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma.Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis–trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis–trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis–trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan–Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score.Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan–Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p &lt; 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal.Conclusion: A prognostic model based on 3 peptidyl prolyl cis–trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma.

Gene Expression Signature With Independent Prognostic Significance in Epithelial Ovarian Cancer

2004 ◽  
Vol 22 (23) ◽  
pp. 4700-4710 ◽  
Author(s):  
Dimitrios Spentzos ◽  
Douglas A. Levine ◽  
Marco F. Ramoni ◽  
Marie Joseph ◽  
Xuesong Gu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Prognostic Factors ◽  
Epithelial Ovarian Cancer ◽  
Prognostic Significance ◽  
Gene Expression Signature ◽  
Cox Proportional Hazards ◽  
Gene Profiling ◽  
Training Procedure ◽  
Training Set ◽  
Validation Set

Purpose Currently available clinical and molecular prognostic factors provide an imperfect assessment of prognosis for patients with epithelial ovarian cancer (EOC). In this study, we investigated whether tumor transcription profiling could be used as a prognostic tool in this disease. Methods Tumor tissue from 68 patients was profiled with oligonucleotide microarrays. Samples were randomly split into training and validation sets. A three-step training procedure was used to discover a statistically significant Kaplan-Meier split in the training set. The resultant prognostic signature was then tested on an independent validation set for confirmation. Results In the training set, a 115-gene signature referred to as the Ovarian Cancer Prognostic Profile (OCPP) was identified. When applied to the validation set, the OCPP distinguished between patients with unfavorable and favorable overall survival (median, 30 months v not yet reached, respectively; log-rank P = .004). The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. The hazard ratio for death in the unfavorable OCPP group was 4.8 (P = .021 by Cox proportional hazards analysis). Conclusion The OCPP is an independent prognostic determinant of outcome in EOC. The use of gene profiling may ultimately permit identification of EOC patients appropriate for investigational treatment approaches, based on a low likelihood of achieving prolonged survival with standard first-line platinum-based therapy.

Predictive Value of Nomogram Based on Kyoto Classification of Gastritis to Diagnosis of Gastric Cancer

2021 ◽  
Author(s):  
Jiejun Lin ◽  
Huang Su ◽  
Yaqi Guan ◽  
Qingjie Zhou ◽  
Jie Pan ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Multivariate Analysis ◽  
Calibration Curve ◽  
Predictive Value ◽  
Predictive Accuracy ◽  
Bootstrap Method ◽  
Characteristic Curve ◽  
Training Set ◽  
Validation Set

Abstract Background and Aim. It is of importance to predict the risk of gastric cancer (GC) for endoscopists because early detection of GC determines the determines the selection of best treatment strategy and the prognosis of patients. The aim of the study was to evaluate the utility of a predictive nomogram based on Kyoto classification of gastritis for GC. Methods. It was a retrospective study that included 2639 patients who received esophagogastroduodenoscopy and serum pepsinogen (PG) assay from January 2020 to November 2020 at the Endoscopy Center of the Department of Gastroenterology, Wenzhou Central Hospital. Routine biopsy was conducted to determine the benign and malignant lesions pathologically. All cases were randomly divided into the training set (70%) and the validation set (30%) by using bootstrap method. A nomogram was formulated according to multivariate analysis of training set. The predictive accuracy and discriminative ability of the nomogram were assessed by concordance index (C-index), area under the curve (AUC) of receiver operating characteristic curve (ROC) as well as calibration curve and were validated by validation set.Results. Multivariate analysis indicated that age, sex, PG I/II ratio and Kyoto classification scores were independent predictive variables for GC. The C-index of the nomogram of the training set was 0.79 (95% CI: 0.74 to 0.84) and the AUC of ROC is 0.79. The calibration curve of the nomogram demonstrated an optimal agreement between predicted probability and observed probability of the risk of GC. In the validation set, the C-index was 0.86 (95% CI: 0.79 to 0.94) with a calibration curve of better concurrence.Conclusion. The nomogram formulated was proven to be of high predictive value for GC.

scholarly journals FAM225B Is a Prognostic lncRNA for Patients with Recurrent Glioblastoma

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Junsheng Li ◽  
Qian Zhang ◽  
Peicong Ge ◽  
Chaofan Zeng ◽  
Fa Lin ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Value ◽  
Cox Regression ◽  
Recurrent Glioblastoma ◽  
Regulation Of Transcription ◽  
Training Set ◽  
Cox Regression Analysis ◽  
Kaplan Meier ◽  
Validation Set ◽  
Pathway Analyses

Objective. The overall survival of patients with recurrent glioblastoma (rGBM) is quite different, so clinical outcome prediction is necessary to guide personalized clinical treatment for patients with rGBM. The expression level of lncRNA FAM225B was analyzed to determine its prognostic value in rGBMs. Methods. We collected 109 samples of Chinese Glioma Genome Atlas (CGGA) RNA sequencing dataset and divided into training set and validation set. Then, we analyzed the expression of FAM225B, clinical characteristics, and overall survival (OS) information. Kaplan-Meier survival analysis was used to estimate the OS distributions. The prognostic value of FAM225B in rGBMs was tested by univariate and multivariate Cox regression analyses. Moreover, we analyzed the biological processes and signaling pathways of FAM225B. Results. We found that FAM225B was upregulated in rGBMs ( P = 0.0009 ). The expression of FAM225B increased with the grades of gliomas ( P < 0.0001 ). The OS of rGBMs in the low-expression group was significantly longer than that in the high-expression group ( P = 0.0041 ). Similar result was found in the training set ( P = 0.0340 ) and verified in the validation set ( P = 0.0292 ). In multivariate Cox regression analysis, FAM225B was identified to be an independent prognostic factor for rGBMs ( P = 0.003 ). Biological process and KEGG pathway analyses implied FAM225B mainly played a functional role on transcription, regulation of transcription, cell migration, focal adhesion, etc. Conclusions. FAM225B is expected to be as a new prognostic biomarker for the identification of rGBM patients with poor outcome. And our study provided a potential therapeutic target for rGBMs.

scholarly journals Integrative Analyses and Verification of the Expression and Prognostic Significance for RCN1 in Glioblastoma Multiforme

2021 ◽  
Vol 8 ◽  
Author(s):  
Weicheng Lu ◽  
Hong Chen ◽  
Bo Liang ◽  
Chaopeng Ou ◽  
Mingwei Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Glioblastoma Multiforme ◽  
Cell Invasion ◽  
Calcium Binding ◽  
Prognostic Significance ◽  
Sequencing Data ◽  
Training Set ◽  
Glioblastoma Multiform ◽  
Validation Set ◽  
The Impact

Glioblastoma multiform is a lethal primary brain tumor derived from astrocytic, with a poor prognosis in adults. Reticulocalbin-1 (RCN1) is a calcium-binding protein, dysregulation of which contributes to tumorigenesis and progression in various cancers. The present study aimed to identify the impact of RCN1 on the outcomes of patients with Glioblastoma multiforme (GBM). The study applied two public databases to require RNA sequencing data of Glioblastoma multiform samples with clinical data for the construction of a training set and a validation set, respectively. We used bioinformatic analyses to determine that RCN1 could be an independent factor for the overall survival of Glioblastoma multiform patients. In the training set, the study constructed a predictive prognostic model based on the combination of RCN1 with various clinical parameters for overall survival at 0.5-, 1.0-, and 1.5-years, as well as developed a nomogram, which was further validated by validation set. Pathways analyses indicated that RCN1 was involved in KEAS and MYC pathways and apoptosis. In vitro experiments indicated that RCN1 promoted cell invasion of Glioblastoma multiform cells. These results illustrated the prognostic role of RCN1 for overall survival in Glioblastoma multiform patients, indicated the promotion of RCN1 in cell invasion, and suggested the probability of RCN1 as a potential targeted molecule for treatment in Glioblastoma multiform.

scholarly journals Early identification of potential brain death organ donors based on prediction of spontaneous respiratory arrest

2020 ◽  
Vol 8 (5) ◽  
pp. 1789
Author(s):  
Guixing Xu ◽  
Yanxia Yang ◽  
Luke Wu ◽  
Donghua Zheng
Keyword(s):  
Multivariate Analysis ◽  
Brain Injury ◽  
Brain Death ◽  
Prediction Model ◽  
Early Identification ◽  
Respiratory Arrest ◽  
Organ Donors ◽  
Training Set ◽  
Cough Reflex ◽  
Validation Set

Background: This study was designed to build a Nomogarm prediction model of spontaneous respiratory arrest (SRA) in nerocritical patients within 72 hours after brain injury for early identification of potential brain death organ donors.Methods: From October 2017 to May 2019, the neurocritical patients admitted to the First Affiliated Hospital of Sun Yat-sen University, were enrolled. The occurrence of SRA within 72 hours after brain injury was regarded as the time interest point and grouping factor, factors associated with SRA were screened by univariate and multivariate analysis, and then the Nomogarm prediction model was developed. Finally, the Nomogarm prediction model was tested in the validation set.Results: In training set, univariate and multivariate analysis showed that the midline shift (OR=4.56, 95% 1.87-19.21), absent of ambient cistern (OR=4.83, 95% 1.35-16.34), cough reflex absence (OR=3.82, 95% 1.15-12.42), intraventricular hemorrhage (OR=3.16, 95% 1.53-14.52) and serum Na+<125mmol/L (OR=3.06, 95% 1.53-13.44) were associated with SRA within 72 hours. In the training set and validation set, the predicted C index of SRA rate within 72 hours was 0.81 (95% CI 0.76-0.85) and 0.80 (95% CI 0.75-0.83), respectively. Further statistical analysis showed that 140 points, 160 points and 170 points were dangerous cut-off points, of which 140 points, 160 points and 170 points were 30.1%, 65.6% and 93.4% associated with SRA within 72 hours, respectively.Conclusions: Nomogram prediction model based on brain injury assessment parameters can predict the time of SRA in neurocritical patients, and can be used for early identification of potential brain death organ donors.

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