scholarly journals New Onset of DiabetEs in aSsociation with pancreatic ductal adenocarcinoma (NODES Trial): protocol of a prospective, multicentre observational trial

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037267
Author(s):  
Dóra Illés ◽  
Emese Ivány ◽  
Gábor Holzinger ◽  
Klára Kosár ◽  
M Gordian Adam ◽  
...  
Keyword(s):  
High Risk ◽  
Early Detection ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Clinical Symptoms ◽  
Risk Group ◽  
High Risk Group ◽  
Ductal Adenocarcinoma ◽  
Onset Diabetes ◽  
Dismal Prognosis ◽  
New Onset

IntroductionPancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis with an overall 5-year survival of approximately 8%. The success in reducing the mortality rate of PDAC is related to the discovery of new therapeutic agents, and to a significant extent to the development of early detection and prevention programmes. Patients with new-onset diabetes mellitus (DM) represent a high-risk group for PDAC as they have an eightfold higher risk of PDAC than the general population. The proposed screening programme may allow the detection of PDAC in the early, operable stage. Diagnosing more patients in the curable stage might decrease the morbidity and mortality rates of PDAC and additionally reduce the burden of the healthcare.Methods and analysisThis is a prospective, multicentre observational cohort study. Patients ≥60 years old diagnosed with new-onset (≤6 months) diabetes will be included. Exclusion criteria are (1) Continuous alcohol abuse; (2) Chronic pancreatitis; (3) Previous pancreas operation/pancreatectomy; (4) Pregnancy; (5) Present malignant disease and (6) Type 1 DM. Follow-up visits are scheduled every 6 months for up to 36 months. Data collection is based on questionnaires. Clinical symptoms, body weight and fasting blood will be collected at each, carbohydrate antigen 19–9 and blood to biobank at every second visit. The blood samples will be processed to plasma and analysed with mass spectrometry (MS)-based metabolomics. The metabolomic data will be used for biomarker validation for early detection of PDAC in the high-risk group patients with new-onset diabetes. Patients with worrisome features will undergo MRI or endoscopic ultrasound investigation, and surgical referral depending on the radiological findings. One of the secondary end points is the incidence of PDAC in patients with newly diagnosed DM.Ethics and disseminationThe study has been approved by the Scientific and Research Ethics Committee of the Hungarian Medical Research Council (41085-6/2019). We plan to disseminate the results to several members of the healthcare system includining medical doctors, dietitians, nurses, patients and so on. We plan to publish the results in a peer-reviewed high-quality journal for professionals. In addition, we also plan to publish it for lay readers in order to maximalise the dissemination and benefits of this trial.Trial registration numberClinicalTrials.gov NCT04164602

Targeting individuals with new-onset diabetes for early detection of pancreatic cancer in this high risk group

Pancreatology ◽  
2016 ◽  
Vol 16 (3) ◽  
pp. S19
Author(s):  
Lucy Oldfield ◽  
Claire Jenkinson ◽  
Tejpal Purewal ◽  
Robert Sutton ◽  
John P. Neoptolemos ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
High Risk ◽  
Early Detection ◽  
Risk Group ◽  
High Risk Group ◽  
Onset Diabetes ◽  
New Onset

scholarly journals N6-Methylandenosine-Related lncRNAs Play an Important Role in the Prognosis and Immune Microenvironment of Pancreatic Ductal Adenocarcinoma

2021 ◽  
Author(s):  
YuHai Hu ◽  
YiPing Chen
Keyword(s):  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Tumor Immunity ◽  
Prognostic Value ◽  
Risk Group ◽  
Epigenetic Modification ◽  
High Risk Group ◽  
Cancer Genome ◽  
Ductal Adenocarcinoma ◽  
Training Cohort

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive, fatal tumor. N6-methylandenosine (m6A) methylation is the major epigenetic modification of RNA including lncRNAs. The roles of m6A-related lncRNAs in PDAC have not been fully clarified. The aim of this study is to assess gene signatures and prognostic value of m6A-related lncRNAs in PDAC. Methods The Cancer Genome Atlas (TCGA) dataset and the International Cancer Genome Consortium (ICGC) dataset were explored to identify m6A-related lncRNAs. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were performed to construct the m6A-related lncRNAs prognostic riskscore (m6A-LPR) model to predict the overall survival (OS) in the TCGA training cohort. Kaplan–Meier curve with log-rank test and receiver operating characteristic (ROC) curve were used to evaluate the prognostic value of the m6A-LPR. Furthermore, the robustness of the m6A-LPR was further validated in the ICGC cohort. Tumor immunity was evaluated using ESTIMATE and CIBERSORT algorithms. Results A total of 262 m6A-related lncRNAs were identified in two datasets. In the TCGA training cohort, 28 prognostic m6A-related lncRNAs were identified and the m6A-LPR including four m6A-related lncRNAs was constructed. The m6A-LPR was able to identify high-risk patients with significantly poorer OS and accurately predict OS in both the TCGA training cohort and the ICGC validation cohort. Analysis of tumor immunity revealed that high-risk group had remarkably lower stromal, immune, and ESTIMATE scores. Moreover, high-risk group was associated with significantly higher levels of plasma B cells and resting NK cells infiltration, and lower levels of infiltrating resting memory CD4 T cells, monocytes and resting mast cells. Conclusions Our study proposed a robust m6A-related prognostic signature of lncRNAs for predicting OS in PDAC, which provides some clues for further studies focusing on the mechanism process underlying m6A modification of lncRNAs.

Evaluation of Early Prognostic Factors in Patients With Pancreatic Ductal Adenocarcinoma Receiving Gemcitabine Together With Nab-paclitaxel

2021 ◽  
Vol 1 (5) ◽  
pp. 399-409
Author(s):  
WATARU IZUMO ◽  
RYOTA HIGUCHI ◽  
TORU FURUKAWA ◽  
TAKEHISA YAZAWA ◽  
SHUICHIRO UEMURA ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prognostic Factors ◽  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Nutrition Status ◽  
Ductal Adenocarcinoma ◽  
Changing Rate

Background: Gemcitabine together with nab-paclitaxel (GnP) has been shown to improve outcomes in patients with pancreatic ductal adenocarcinoma (PDAC). However, the predictive markers for treatment effects remain unclear. This study aimed to identify early prognostic factors in patients with PDAC receiving GnP. Patients and Methods: We analyzed 113 patients who received GnP for PDAC and evaluated the relationship between clinical factors and outcomes. Results: The median survival time (MST) was 1.2 years. In multivariate analysis, baseline carbohydrate antigen 19-9 (CA19-9) ≥747 U/ml [hazard ratio (HR)=1.9], baseline controlling nutrition status (CONUT) score ≥5 (HR=3.7) and changing rate of CA19-9 after two GnP cycles ≥0.69 (HR=3.7) were independent risk factors for poor prognosis. When examining outcomes according to pre-chemotherapeutic measurable factors (baseline CA19-9 and CONUT), the MSTs of patients with pre-chemotherapeutic zero risk factors (pre-low-risk group, n=63) and one or more risk factors (pre-high-risk group, n=50) were 1.7 and 0.65 years (p<0.001), respectively. The MST for those with a changing rate of CA19-9 after two GnP cycles <0.69 and ≥0.69 was significantly different in both groups (2.0 and 1.2 years in the pre-low-risk group, p<0.001; 1.0 and 0.52 years in the pre-high-risk group, p<0.001). Conclusion: These results may be useful for decision-making regarding treatment strategies in patients with PDAC receiving GnP.

scholarly journals Glycolysis-Related Gene Expression Profiling Screen for Prognostic Risk Signature of Pancreatic Ductal Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Wenjing Song ◽  
Xin He ◽  
Pengju Gong ◽  
Yan Yang ◽  
Sirui Huang ◽  
...  
Keyword(s):  
High Risk ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Group ◽  
Mrna Level ◽  
High Risk Group ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Ductal Adenocarcinoma ◽  
Related Gene

Objective: Pancreatic ductal adenocarcinoma (PDAC) is highly lethal. Although progress has been made in the treatment of PDAC, its prognosis remains unsatisfactory. This study aimed to develop novel prognostic genes related to glycolysis in PDAC and to apply these genes to new risk stratification.Methods: In this study, based on the Cancer Genome Atlas (TCGA) PAAD cohort, the expression level of glycolysis-related gene at mRNA level in PAAD and its relationship with prognosis were analyzed. Non-negative matrix decomposition (NMF) clustering was used to cluster PDAC patients according to glycolytic genes. Prognostic glycolytic genes, screened by univariate Cox analysis and LASSO regression analysis were established to calculate risk scores. The differentially expressed genes (DEGs) in the high-risk group and the low-risk group were analyzed, and the signal pathway was further enriched to analyze the correlation between glycolysis genes. In addition, based on RNA-seq data, CIBERSORT was used to evaluate the infiltration degree of immune cells in PDAC samples, and ESTIMATE was used to calculate the immune score of the samples.Results: A total of 319 glycolysis-related genes were retrieved, and all PDAC samples were divided into two clusters by NMF cluster analysis. Survival analysis showed that PDAC patients in cluster 1 had shorter survival time and worse prognosis compared with cluster 2 samples (P &lt; 0.001). A risk prediction model based on 11 glycolysis genes was constructed, according to which patients were divided into two groups, with significantly poorer prognosis in high-risk group than in low-risk group (P &lt; 0.001). Both internal validation and external dataset validation demonstrate good predictive ability of the model (AUC = 0.805, P &lt; 0.001; AUC = 0.763, P &lt; 0.001). Gene aggregation analysis showed that DEGs highly expressed in high-risk group were mainly concentrated in the glycolysis level, immune status, and tumor cell proliferation, etc. In addition, the samples in high-risk group showed immunosuppressed status and infiltrated by relatively more macrophages and less CD8+T cell.Conclusions: These findings suggested that the gene signature based on glycolysis-related genes had potential diagnostic, therapeutic, and prognostic value for PDAC.

scholarly journals Screening Circulating Tumor Cells as a Noninvasive Cancer Test in 3388 Individuals from High-Risk Groups (ICELLATE2)

2018 ◽  
Vol 2018 ◽  
pp. 1-5 ◽  
Author(s):  
Juan Castro ◽  
Luis Sanchez ◽  
María Teresa Nuñez ◽  
Ming Lu ◽  
Tomas Castro ◽  
...  
Keyword(s):  
High Risk ◽  
Early Detection ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Clinical Symptoms ◽  
Risk Groups ◽  
Circulating Tumor Cell ◽  
High Risk Group ◽  
Screening Tests ◽  
Cancer Risk Factors

Cancer is known to spread up to 12 years before clinical symptoms occur, but few screening tests exist. Early detection would give the opportunity for early treatment, potentially improving prognosis. To this end, 3388 subjectively healthy individuals of age 45 to 80 who had been exposed to cancer risk factors were screened for the occurrence of circulating tumor cells in their blood. Presence of circulating tumor cells is a suspicious finding indicative of spreading cancer, since cancer metastasizes by way of the blood and offers the opportunities to (a) follow up the individual clinically based on established guidelines for early detection of cancer and (b) evaluate the cells further analytically. 107 individuals showed one or more circulating tumor cells in a 7.5 ml blood sample, which constitutes a positive circulating tumor cell test, based on the iCellate IsoPic™ laboratory test. That number compares favorably with the cancer incidence per 100,000 people/year that is 157.1 in Peru, given that a high-risk group of individuals was screened and that the screening results would be expected to correspond to an accumulated incidence of up to 12 years. The present findings therefore identify screening for circulating tumor cells as a promising new test.

Age-specific peculiarities of the clinical picture of acute cholecystitis

2016 ◽  
Vol 94 (2) ◽  
pp. 133-137
Author(s):  
Gaik Z. Balayan
Keyword(s):  
High Risk ◽  
Elderly Patients ◽  
Acute Cholecystitis ◽  
Clinical Picture ◽  
Clinical Symptoms ◽  
Risk Group ◽  
High Risk Group ◽  
Treatment Results ◽  
Poor Treatment ◽  
Late Stages

The problem of acute cholecystitis is now becoming ever more urgent bearing in mind a rise in morbidity and poor treatment results especially in elderly patients. Hence, the importance of studying age-specific peculiarities of clinical picture and evolution of this condition. The present study included 1273 patients with acute cholecystitis divided in 2 groups. It was shown that patients of advanced age more frequently suffer complicated cholecystitis. It is concluded that patients aged 60 years and more make up a high-risk group characterized by mildly manifest clinical symptoms and hospitalization at the late stages of the disease.

scholarly journals A Novel S100 Family-Based Signature Associated with Prognosis and Immune Microenvironment in Glioma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Yifang Hu ◽  
Jiahang Song ◽  
Zhen Wang ◽  
Jingbao Kan ◽  
Yaoqi Ge ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Immune Microenvironment ◽  
S100 Family ◽  
Kaplan Meier ◽  
Dismal Prognosis ◽  
Family Based ◽  
Genome Atlas

Background. Glioma is the most common central nervous system (CNS) cancer with a short survival period and a poor prognosis. The S100 family gene, comprising 25 members, relates to diverse biological processes of human malignancies. Nonetheless, the significance of S100 genes in predicting the prognosis of glioma remains largely unclear. We aimed to build an S100 family-based signature for glioma prognosis. Methods. We downloaded 665 and 313 glioma patients, respectively, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database with RNAseq data and clinical information. This study established a prognostic signature based on the S100 family genes through multivariate COX and LASSO regression. The Kaplan–Meier curve was plotted to compare overall survival (OS) among groups, whereas Receiver Operating Characteristic (ROC) analysis was performed to evaluate model accuracy. A representative gene S100B was further verified by in vitro experiments. Results. An S100 family-based signature comprising 5 genes was constructed to predict the glioma that stratified TCGA-derived cases as a low- or high-risk group, whereas the significance of prognosis was verified based on CGGA-derived cases. Kaplan–Meier analysis revealed that the high-risk group was associated with the dismal prognosis. Furthermore, the S100 family-based signature was proved to be closely related to immune microenvironment. In vitro analysis showed S100B gene in the signature promoted glioblastoma (GBM) cell proliferation and migration. Conclusions. We constructed and verified a novel S100 family-based signature associated with tumor immune microenvironment (TIME), which may shed novel light on the glioma diagnosis and treatment.

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