Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

Abstract Background Cancer stem cells (CSCs) are crucial to malignant behavior and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established and reported in PDAC. Methods This signature was developed and validated in seven independent PDAC datasets. MTAB-6134 cohort was used as training set, while one Chinese local cohort and five other public cohorts were used for external validation. CSC-related genes with credible prognostic roles were selected to form the signature, and its predictive performance was evaluated by Kaplan-Meier survival, receiver operating characteristic (ROC), and calibration curves. Correlation analysis was employed to clarify the potential biological characteristics. Results A robust signature comprising DCBLD2, GSDMD, PMAIP1, and PLOD2 was developed. It could classify patients into high-risk and low-risk groups, and high risk patients had significantly shorter overall survival (OS) and disease-free survival (DFS) compared with low risk patients. Calibration curves and Cox regression analysis demonstrated the powerful predictive performance. ROC curves showed an improved survival prediction provided by this model. Functional analysis revealed positive association between risk score and CSC marker. These results had cross-dataset compatibility. Conclusions We established a novel four-gene signature based on CSC-related genes which could serve as a powerful prognostic tool in PDAC. Impact This signature can offer potential help for further improving current TNM staging system, and providing data for the development of novel personalized therapeutic strategies in the future.

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Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

10.21203/rs.3.rs-17949/v2 ◽

2020 ◽

Author(s):

Zengyu Feng ◽

Minmin Shi ◽

Kexian Li ◽

Yang Ma ◽

Lingxi Jiang ◽

...

Keyword(s):

High Risk ◽

Pancreatic Ductal Adenocarcinoma ◽

External Validation ◽

Predictive Performance ◽

Low Risk ◽

Ductal Adenocarcinoma ◽

Survival Prediction ◽

Cox Regression Analysis ◽

Calibration Curves ◽

Risk Patients

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Development and validation of a cancer stem cell-related signature for prognostic prediction in pancreatic ductal adenocarcinoma

Journal of Translational Medicine ◽

10.1186/s12967-020-02527-1 ◽

2020 ◽

Vol 18 (1) ◽

Author(s):

Zengyu Feng ◽

Minmin Shi ◽

Kexian Li ◽

Yang Ma ◽

Lingxi Jiang ◽

...

Keyword(s):

High Risk ◽

Pancreatic Ductal Adenocarcinoma ◽

External Validation ◽

Predictive Performance ◽

Low Risk ◽

Ductal Adenocarcinoma ◽

Survival Prediction ◽

Cox Regression Analysis ◽

Calibration Curves ◽

Risk Patients

Abstract Background Cancer stem cells (CSCs) are crucial to the malignant behaviour and poor prognosis of pancreatic ductal adenocarcinoma (PDAC). In recent years, CSC biology has been widely studied, but practical prognostic signatures based on CSC-related genes have not been established or reported in PDAC. Methods A signature was developed and validated in seven independent PDAC datasets. The MTAB-6134 cohort was used as the training set, while one local Chinese cohort and five other public cohorts were used for external validation. CSC-related genes with credible prognostic roles were selected to form the signature, and their predictive performance was evaluated by Kaplan–Meier survival, receiver operating characteristic (ROC), and calibration curves. Correlation analysis was employed to clarify the potential biological characteristics of the gene signature. Results A robust signature comprising DCBLD2, GSDMD, PMAIP1, and PLOD2 was developed. It classified patients into high-risk and low-risk groups. High-risk patients had significantly shorter overall survival (OS) and disease-free survival (DFS) than low-risk patients. Calibration curves and Cox regression analysis demonstrated powerful predictive performance. ROC curves showed the better survival prediction by this model than other models. Functional analysis revealed a positive association between risk score and CSC markers. These results had cross-dataset compatibility. Impact This signature could help further improve the current TNM staging system and provide data for the development of novel personalized therapeutic strategies in the future.

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A tool to identify patients with embolic stroke of undetermined source at high recurrence risk

Neurology ◽

10.1212/wnl.0000000000008571 ◽

2019 ◽

Vol 93 (23) ◽

pp. e2094-e2104 ◽

Cited By ~ 1

Author(s):

George Ntaios ◽

Georgios Georgiopoulos ◽

Kalliopi Perlepe ◽

Gaia Sirimarco ◽

Davide Strambo ◽

...

Keyword(s):

High Risk ◽

Cox Regression ◽

External Validation ◽

Low Risk ◽

Embolic Stroke ◽

Stroke Recurrence ◽

Intermediate Risk ◽

Cox Regression Analysis ◽

Derivation Cohort ◽

Risk Patients

ObjectiveA tool to stratify the risk of stroke recurrence in patients with embolic stroke of undetermined source (ESUS) could be useful in research and clinical practice. We aimed to determine whether a score can be developed and externally validated for the identification of patients with ESUS at high risk for stroke recurrence.MethodsWe pooled the data of all consecutive patients with ESUS from 11 prospective stroke registries. We performed multivariable Cox regression analysis to identify predictors of stroke recurrence. Based on the coefficient of each covariate of the fitted multivariable model, we generated an integer-based point scoring system. We validated the score externally assessing its discrimination and calibration.ResultsIn 3 registries (884 patients) that were used as the derivation cohort, age, leukoaraiosis, and multiterritorial infarct were identified as independent predictors of stroke recurrence and were included in the final score, which assigns 1 point per every decade after 35 years of age, 2 points for leukoaraiosis, and 3 points for multiterritorial infarcts (acute or old nonlacunar). The rate of stroke recurrence was 2.1 per 100 patient-years (95% confidence interval [CI] 1.44–3.06) in patients with a score of 0–4 (low risk), 3.74 (95% CI 2.77–5.04) in patients with a score of 5–6 (intermediate risk), and 8.23 (95% CI 5.99–11.3) in patients with a score of 7–12 (high risk). Compared to low-risk patients, the risk of stroke recurrence was significantly higher in intermediate-risk (hazard ratio [HR] 1.78, 95% CI 1.1–2.88) and high-risk patients (HR 4.67, 95% CI 2.83–7.7). The score was well-calibrated in both derivation and external validation cohorts (8 registries, 820 patients) (Hosmer-Lemeshow test χ2: 12.1 [p = 0.357] and χ2: 21.7 [p = 0.753], respectively). The area under the curve of the score was 0.63 (95% CI 0.58–0.68) and 0.60 (95% CI 0.54–0.66), respectively.ConclusionsThe proposed score can assist in the identification of patients with ESUS at high risk for stroke recurrence.

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A 5-Genomic Mutation Signature Can Predict the Survival for Patients With NSCLC Receiving Atezolizumab

Frontiers in Immunology ◽

10.3389/fimmu.2021.606027 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jiamao Lin ◽

Xiaohui Wang ◽

Chenyue Zhang ◽

Shuai Bu ◽

Chenglong Zhao ◽

...

Keyword(s):

High Risk ◽

Gene Mutation ◽

Training Group ◽

Low Risk ◽

Survival Prediction ◽

Cox Regression Analysis ◽

High Risk Patients ◽

Risk Patients ◽

Genomic Mutation ◽

Testing Group

BackgroundAt present, there is a lack of studies focusing on the survival prediction of patients with non-small cell lung cancer (NSCLC) receiving atezolizumab in light of gene mutation characteristic.MethodsPatients with NSCLC receiving atezolizumab from the OAK study were defined as the training group. LASSO Cox regressions were applied to establish the gene mutation signature model to predict the overall survival (OS) rate of the training group. NSCLC patients receiving atezolizumab from the POPLAR study were defined as the testing group to validate the gene mutation signature model. In addition, we compared the OS rate between patients receiving atezolizumab and docetaxel classified according to their risk score based on our gene mutation signature model.ResultsWe successfully established a 5-genomic mutation signature that included CREBBP, KEAP1, RAF1, STK11 and TP53 mutations. We found it was superior to the blood tumor mutation burden (bTMB) score and programmed death ligand 1 (PDL1) expression in the prediction of the OS rate for patients receiving atezolizumab. High-risk patients receiving atezolizumab had a worse OS rate compared with low-risk patients in the training (P = 0.0004) and testing (P = 0.0001) groups. In addition, low-risk patients using atezolizumab had a better OS rate compared with those in use of docetaxel for the training (P <0.0001) and testing groups (P = 0.0095). High-risk patients of the training group (P = 0.0265) using atezolizumab had a better OS rate compared with those using docetaxel. However, the OS difference between atezolizumab and docetaxel was not found in high-risk patients from the testing group (P = 0.6403). Multivariate Cox regression analysis showed that the risk model in light of 5-genomic mutation signature was an independent prognostic factor on OS for patients receiving atezolizumab (P <0.0001). In addition, significant OS benefit could only be found in low-risk patients receiving atezolizumab compared with docetaxel (P <0.0001).ConclusionsThe 5-genomic mutation signature could predict OS benefit for patients with NSCLC receiving atezolizumab. Therefore, the establishment of the 5-genomic mutation panel will guide clinicians to identify optimal patients who could benefit from atezolizumab treatment.

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Development and Verification of the Hypoxia- and Immune-Associated Prognostic Signature for Pancreatic Ductal Adenocarcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.728062 ◽

2021 ◽

Vol 12 ◽

Author(s):

Dongjie Chen ◽

Hui Huang ◽

Longjun Zang ◽

Wenzhe Gao ◽

Hongwei Zhu ◽

...

Keyword(s):

High Risk ◽

Pancreatic Ductal Adenocarcinoma ◽

Risk Score ◽

Cox Regression ◽

Pearson Correlation ◽

Risk Groups ◽

Low Risk ◽

Ductal Adenocarcinoma ◽

Prognostic Signature ◽

Score Model

We aim to construct a hypoxia- and immune-associated risk score model to predict the prognosis of patients with pancreatic ductal adenocarcinoma (PDAC). By unsupervised consensus clustering algorithms, we generate two different hypoxia clusters. Then, we screened out 682 hypoxia-associated and 528 immune-associated PDAC differentially expressed genes (DEGs) of PDAC using Pearson correlation analysis based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression project (GTEx) dataset. Seven hypoxia and immune-associated signature genes (S100A16, PPP3CA, SEMA3C, PLAU, IL18, GDF11, and NR0B1) were identified to construct a risk score model using the Univariate Cox regression and the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, which stratified patients into high- and low-risk groups and were further validated in the GEO and ICGC cohort. Patients in the low-risk group showed superior overall survival (OS) to their high-risk counterparts (p < 0.05). Moreover, it was suggested by multivariate Cox regression that our constructed hypoxia-associated and immune-associated prognosis signature might be used as the independent factor for prognosis prediction (p < 0.001). By CIBERSORT and ESTIMATE algorithms, we discovered that patients in high-risk groups had lower immune score, stromal score, and immune checkpoint expression such as PD-L1, and different immunocyte infiltration states compared with those low-risk patients. The mutation spectrum also differs between high- and low-risk groups. To sum up, our hypoxia- and immune-associated prognostic signature can be used as an approach to stratify the risk of PDAC.

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Preoperative Score to Stratify Recurrence Risk After Curative Resection of Resectable Pancreatic Ductal Adenocarcinoma: A Retrospective Cohort Study

10.21203/rs.3.rs-697919/v1 ◽

2021 ◽

Author(s):

Yu Jiang ◽

SIYI Zou ◽

Weishen Wang ◽

Haoda Chen ◽

Qian Zhan ◽

...

Keyword(s):

High Risk ◽

Pancreatic Ductal Adenocarcinoma ◽

Prognostic Score ◽

Multidisciplinary Treatment ◽

Multivariable Analysis ◽

Disease Free Survival ◽

Ductal Adenocarcinoma ◽

Final Model ◽

Significant Difference ◽

Risk Patients

Abstract Background: Oncological survival after operation of resectable pancreatic ductal adenocarcinoma (R-PDAC) is variable depending on various factors. Preoperative risk stratification could guide decision-making in multidisciplinary treatment concepts. We develop and validate a prognostic score for disease-free survival (DFS) in R-PDAC to solve this issue.Methods: 421 R-PDAC patients between January 2012 and December 2015 were enrolled. Performance of the final model was evaluated with respect to discrimination, calibration and clinical usefulness. A prognostic score based on the final model was developed, and external validated in 290 patients.Results: On multivariable analysis, age, tumor size, carbohydrate antigen (CA)19-9, CA125, lymphocyte-monocyte ratio, and systemic-immune-inflammation index were independently associated with DFS. Final model had acceptable calibration, discrimination and internal validity. The prognostic score could delineate low- and high-risk groups with median DFS of 19.6 and 10.1 months (P<0.0001). Tumors in high-risk group exhibited more aggressive pathobiological behaviors. Additionally, at 1-year follow-up, the restricted mean survival time was longer with adjuvant chemotherapy than those without in low-risk patients. However, no significant difference was detected in high-risk patients.Discussion: The prognostic score could accurately predict DFS preoperatively in R-PDAC patients and provide reference for risk-adapted strategies formulation for R-PDAC management in the future.

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Transcriptomic Profiling Identifies DCBLD2 as a Diagnostic and Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.659168 ◽

2021 ◽

Vol 8 ◽

Author(s):

Zengyu Feng ◽

Kexian Li ◽

Yulian Wu ◽

Chenghong Peng

Keyword(s):

Pancreatic Ductal Adenocarcinoma ◽

Extracellular Vesicles ◽

Immune Cell ◽

Cox Regression ◽

Univariate Analysis ◽

Functional Enrichment ◽

Ductal Adenocarcinoma ◽

Survival Curves ◽

Cox Regression Analysis ◽

Calibration Curves

Background: Accumulating evidence shows that the elevated expression of DCBLD2 (discoidin, CUB and LCCL domain-containing protein 2) is associated with unfavorable prognosis of various cancers. However, the correlation of DCBLD2 expression value with the diagnosis and prognosis of pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated. Methods: Univariate Cox regression analysis was used to screen robust survival-related genes. Expression pattern of selected genes was investigated in PDAC tissues and normal tissues from multiple cohorts. Kaplan–Meier (K–M) survival curves, ROC curves and calibration curves were employed to assess prognostic performance. The relationship between DCBLD2 expression and immune cell infiltrates was conducted by CIBERSORT software. Biological processes and KEGG pathway enrichment analyses were adopted to clarify the potential function of DCBLD2 in PDAC. Results: Univariate analysis, K–M survival curves and calibration curves indicated that DCBLD2 was a robust prognostic factor for PDAC with cross-cohort compatibility. Upregulation of DCBLD2 was observed in dissected PDAC tissues as well as extracellular vesicles from both plasma and serum samples of PDAC patients. Both DCBLD2 expression in tissue and extracellular vesicles had significant diagnostic value. Besides, DCBLD2 expression was correlated with infiltrating level of CD8+ T cells and macrophage M2 cells. Functional enrichment revealed that DCBLD2 might be involved in cell motility, angiogenesis, and cancer-associated pathways. Conclusion: Our study systematically analyzed the potential diagnostic, prognostic and therapeutic value of DCBLD2 in PDAC. All the findings indicated that DCBLD2 might play a considerably oncogenic role in PDAC with diagnostic, prognostic and therapeutic potential. These preliminary results of bioinformatics analyses need to be further validated in more prospective studies.

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A Novel DNA Replication-Related Signature Predicting Recurrence After R0 Resection of Pancreatic Ductal Adenocarcinoma: Prognostic Value and Clinical Implications

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.619549 ◽

2021 ◽

Vol 9 ◽

Author(s):

Zengyu Feng ◽

Kexian Li ◽

Jianyao Lou ◽

Mindi Ma ◽

Yulian Wu ◽

...

Keyword(s):

Dna Replication ◽

Pancreatic Ductal Adenocarcinoma ◽

Risk Model ◽

Cox Regression ◽

External Validation ◽

Gene Signature ◽

Ductal Adenocarcinoma ◽

R0 Resection ◽

Pathway Enrichment Analysis ◽

Cox Regression Analysis

The aim of any surgical resection for pancreatic ductal adenocarcinoma (PDAC) is to achieve tumor-free margins (R0). R0 margins give rise to better outcomes than do positive margins (R1). Nevertheless, postoperative morbidity after R0 resection remains high and prognostic gene signature predicting recurrence risk of patients in this subgroup is blank. Our study aimed to develop a DNA replication-related gene signature to stratify the R0-treated PDAC patients with various recurrence risks. We conducted Cox regression analysis and the LASSO algorithm on 273 DNA replication-related genes and eventually constructed a 7-gene signature. The predictive capability and clinical feasibility of this risk model were assessed in both training and external validation sets. Pathway enrichment analysis showed that the signature was closely related to cell cycle, DNA replication, and DNA repair. These findings may shed light on the identification of novel biomarkers and therapeutic targets for PDAC.

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External validation of the Glasgow prognostic score (mGPS) for renal cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.5_suppl.378 ◽

2012 ◽

Vol 30 (5_suppl) ◽

pp. 378-378

Author(s):

Viraj A. Master ◽

Timothy V. Johnson ◽

Omer Kucuk ◽

Daniel Canter ◽

John Pattaras ◽

...

Keyword(s):

High Risk ◽

Cox Regression ◽

Inflammatory Responses ◽

Prognostic Score ◽

External Validation ◽

Glasgow Prognostic Score ◽

Low Risk ◽

High Risk Patients ◽

Increased Risk ◽

Risk Patients

378 Background: Inflammation has been termed the 7th hallmark of cancer (Hanahan and Weinberg Cell 2011). Measurement of systemic inflammatory responses in malignancy is possible using a selective combination of two commonly available, cost-effective serum assays. The combination of these two serum markers, C-reactive protein (CRP) and albumin, is termed the modified Glasgow prognostic score (mGPS), and is strongly correlated with outcome in a variety of cancers, including mRCC. Recently, mGPS has been shown to be predictive of outcome in localized RCC (ASCO GU 2010 #390). We sought to externally validate these results. Methods: Nephrectomized patients with clinically localized (T1-T4N0M0) clear cell RCC with negative surgical margins were followed for a mean of 25 months (range: 1-81 months). Relapse and survival was identified through routine follow-up. Patients were categorized by mGPS score as Low Risk (mGPS = 0 points), Intermediate Risk (mGPS = 1 point), and High Risk (mGPS = 2 points). One point was assigned to patients for an elevated CRP (>10 mg/L) and hypoalbuminemia (<3.5 mg/dL). Patients with normal CRP and hypoalbuminemia were assigned 0 points. Kaplan-Meier and multivariate Cox regression analyses examined relapse-free survival (RFS) and overall survival (OS) across patient and disease characteristics. Results: Of 248 patients, 17.9% relapsed and 18.6% died. Of Low, Intermediate, and High Risk patients, 7.2%, 7.7%, and 45.5%, respectively relapsed and 5.2%, 15.4%, and 39.4%, respectively died during the study. In multivariate analysis including stage and grade, mGPS was significantly associated with RFS and OS. Compared to Low-Risk patients, High-Risk patients experienced a 3-fold (OR: 2.906, 95% CI: 1.055-8.001) increased risk of relapse and 4-fold (HR: 3.722, 95% CI: 1.046-13.245) increased risk of mortality. AUC is 0.813, which compares very favorably to existing prognostic algorithms. Conclusions: In this external validation cohort of US patients, mGPS continues to be a predictor of relapse and overall mortality following nephrectomy for localized RCC. Clinicians may consider using mGPS as an adjunct to identify high-risk patients for possible enrollment into clinical trials, or for patient counseling.

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