scholarly journals A Cluster-Based Approach for Identifying Prognostic microRNA Signatures in Digestive System Cancers

2021 ◽  
Vol 22 (4) ◽  
pp. 1529
Author(s):  
Jun Zhou ◽  
Xiang Cui ◽  
Feifei Xiao ◽  
Guoshuai Cai

Cancer remains the second leading cause of death all over the world. Aberrant expression of miRNA has shown diagnostic and prognostic value in many kinds of cancer. This study aims to provide a novel strategy to identify reliable miRNA signatures and develop improved cancer prognostic models from reported cancer-associated miRNAs. We proposed a new cluster-based approach to identify distinct cluster(s) of cancers and corresponding miRNAs. Further, with samples from TCGA and other independent studies, we identified prognostic markers and validated their prognostic value in prediction models. We also performed KEGG pathway analysis to investigate the functions of miRNAs associated with the cancer cluster of interest. A distinct cluster with 28 cancers and 146 associated miRNAs was identified. This cluster was enriched by digestive system cancers. Further, we screened out 8 prognostic miRNA signatures for STAD, 5 for READ, 18 for PAAD, 24 for LIHC, 12 for ESCA and 18 for COAD. These identified miRNA signatures demonstrated strong abilities in discriminating the overall survival time between high-risk group and low-risk group (p-value < 0.05) in both TCGA training and test datasets, as well as four independent Gene Expression Omnibus (GEO) validation datasets. We also demonstrated that these cluster-based miRNA signatures are superior to signatures identified in single cancers for prognosis. Our study identified significant miRNA signatures with improved prognosis accuracy in digestive system cancers. It also provides a novel method/strategy for cancer prognostic marker selection and offers valuable methodological directions to similar research topics.

2021 ◽  
Vol 11 ◽  
Author(s):  
Baoai Han ◽  
Minlan Yang ◽  
Xiuping Yang ◽  
Mengzhi Liu ◽  
Qiang Xie ◽  
...  

Alternative splicing (AS) is a key mechanism involved in regulating gene expression and is closely related to tumorigenesis. The incidence of thyroid cancer (THCA) has increased during the past decade, and the role of AS in THCA is still unclear. Here, we used TCGA and to generate AS maps in patients with THCA. Univariate analysis revealed 825 AS events related to the survival of THCA. Five prognostic models of AA, AD, AT, ES, and ME events were obtained through lasso and multivariate analyses, and the final prediction model was established by integrating all the AS events in the five prediction models. Kaplan–Meier survival analysis revealed that the overall survival rate of patients in the high-risk group was significantly shorter than that of patients in the low-risk group. The ROC results revealed that the prognostic capabilities of each model at 3, 5, and 8 years were all greater than 0.7, and the final prognostic capabilities of the models were all greater than 0.9. By reviewing other databases and utilizing qPCR, we verified the established THCA gene model. In addition, gene set enrichment analysis showed that abnormal AS events might play key roles in tumor development and progression of THCA by participating in changes in molecular structure, homeostasis of the cell environment and in cell energy. Finally, a splicing correlation network was established to reveal the potential regulatory patterns between the predicted splicing factors and AS event candidates. In summary, AS should be considered an important prognostic indicator of THCA. Our results will help to elucidate the underlying mechanism of AS in the process of THCA tumorigenesis and broaden the prognostic and clinical application of molecular targeted therapy for THCA.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15565-e15565
Author(s):  
Qiqi Zhu ◽  
Du Cai ◽  
Wei Wang ◽  
Min-Er Zhong ◽  
Dejun Fan ◽  
...  

e15565 Background: Few robust predictive biomarkers have been applied in clinical practice due to the heterogeneity of metastatic colorectal cancer (mCRC) . Using the gene pair method, the absolute expression value of genes can be converted into the relative order of genes, which can minimize the influence of the sequencing platform difference and batch effects, and improve the robustness of the model. The main objective of this study was to establish an immune-related gene pairs signature (IRGPs) and evaluate the impact of the IRGPs in predicting the prognosis in mCRC. Methods: A total of 205 mCRC patients containing overall survival (OS) information from the training cohort ( n = 119) and validation cohort ( n = 86) were enrolled in this study. LASSO algorithm was used to select prognosis related gene pairs. Univariate and multivariate analyses were used to validate the prognostic value of the IRGPs. Gene sets enrichment analysis (GSEA) and immune infiltration analysis were used to explore the underlying biological mechanism. Results: An IRGPs signature containing 22 gene pairs was constructed, which could significantly separate patients of the training cohort ( n = 119) and validation cohort ( n = 86) into the low-risk and high-risk group with different outcomes. Multivariate analysis with clinical factors confirmed the independent prognostic value of IRGPs that higher IRGPs was associated with worse prognosis (training cohort: hazard ratio (HR) = 10.54[4.99-22.32], P < 0.001; validation cohort: HR = 3.53[1.24-10.08], P = 0.012). GSEA showed that several metastasis and immune-related pathway including angiogenesis, TGF-β-signaling, epithelial-mesenchymal transition and inflammatory response were enriched in the high-risk group. Through further analysis of the immune factors, we found that the proportions of CD4+ memory T cell, regulatory T cell, and Myeloid dendritic cell were significantly higher in the low-risk group, while the infiltrations of the Macrophage (M0) and Neutrophil were significantly higher in the high-risk group. Conclusions: The IRGPs signature could predict the prognosis of mCRC patients. Further prospective validations are needed to confirm the clinical utility of IRGPs in the treatment decision.


2019 ◽  
Vol 25 ◽  
pp. 107602961985363 ◽  
Author(s):  
Xueyan Zhao ◽  
Jianxin Li ◽  
Xiaofang Tang ◽  
Ying Xian ◽  
Lin Jiang ◽  
...  

The Patterns of non-Adherence to Anti-Platelet Regimen in Stented Patients (PARIS) thrombotic risk score is a novel score for predicting the risk of coronary thrombotic events after percutaneous coronary intervention (PCI). We assessed the prognostic value of this score for mortality in patients with PCI. In this prospective, observational study, we enrolled 10 724 consecutive patients underwent PCI. The primary end point was all-cause death and the secondary end point was major adverse cardiovascular and cerebrovascular events (MACCE) as a composite of all-cause death, myocardial infarction, revascularization, stent thrombosis, or stroke. Among 9782 patients without in-hospital events, a total of 97 deaths and 1002 MACCE occurred during the 2-year follow-up. The mortality risk of patients in the high-risk group was 2.31 times higher than that in the low-risk group (hazard ratio, 2.31; P = .001). This risk score showed prognostic value in evaluating mortality (area under the receiver operating characteristic curve [AUROC], 0.607; 95% confidence interval [CI], 0.551-0.663) and MACCE (AUROC, 0.544; 95% CI, 0.526-0.563; both P < .001). The prognostic value of mortality was higher than that of MACCE (Z = 2.09, P = .04). The PARIS thrombotic risk score shows modest prognostic value for mortality and MACCE, and the prognostic value of mortality is better than that of MACCE.


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 186-186 ◽  
Author(s):  
Inhye E. Ahn ◽  
Xin Tian ◽  
Maher Albitar ◽  
Sarah E. M. Herman ◽  
Erika M. Cook ◽  
...  

Abstract Introduction: We previously reported a prognostic scoring system in CLL using pre-treatment factors in patients treated with ibrutinib [Ahn et al, 2016 ASH Annual Meeting]. Here we present long-term follow-up results and validation of the prognostic models in a large independent cohort of patients. We also determine the incidence of resistance-conferring mutations in BTK and PLCG2 genes in different clinical risk groups. Methods and Patients: The discovery cohort comprised 84 CLL patients on a phase II study with either TP53 aberration (deletion 17p or TP53 mutation) or age ≥65 years (NCT01500733). The validation cohort comprised 607 patients pooled from four phase II and III studies for ibrutinib in treatment-naïve or relapsed/refractory CLL (NCT01105247; NCT01578707; NCT01722487; NCT01744691). All patients received single-agent ibrutinib 420mg once daily. We used Cox regression models to identify independent predictors of PFS, Kaplan-Meier method to estimate probabilities of PFS, log-rank test to compare PFS, and Cochran-Armitage trend test to compare the incidence of mutation among subgroups. We used R version 3.5.0 or SAS® version 9.3 for statistical analyses. For biomarker correlation, we tested cellular DNA or cell-free DNA collected from patients in the discovery cohort with the targeted sequencing of BTK and PLCG2 genes. Result: At a median follow-up of 5.2 years, 28 (33.3%) of 84 patients in the discovery cohort progressed or died. 52 (61.9%) patients had treatment-naïve CLL. Independent factors of PFS on univariate analysis were; TP53 aberration, prior treatment, and β-2 microglobulin (B2M) >4mg/L (P<0.05 for all tests). Unmutated IGHV and advanced Rai stage (III/IV) showed a trend toward inferior outcome without reaching statistical significance. Because higher levels of B2M were associated with relapsed/refractory CLL, we performed two multivariate Cox regression models to assess B2M and prior treatment status separately. Risk groups were determined by the presence of TP53 aberration, advanced Rai stage, and B2M >4mg/L for Model 1, and TP53 aberration, advanced Rai stage, and relapsed/refractory CLL for Model 2 (Table 1). The high-risk group had all three adverse risk factors; the intermediate-risk group had two risk factors; and the low-risk group, none or one. The median PFS of the high-risk group was 38.9 months for Model 1 and 38.4 months for Model 2, and was significantly shorter than those of intermediate and low-risk groups. In the validation cohort, 254 (41.8%) of 607 patients progressed or died at a median follow-up of 4.2 years. 167 (27.5%) patients had treatment-naïve CLL. Both models showed statistically significant differences in PFS by risk groups (Table 1). For the high-risk group, 4-year PFS was 30.2% in Model 1 and 30.5% in Model 2, which were inferior to those of intermediate (53.4 and 52.4%) and low-risk groups (68.7 and 73.7%). Model 1 classified 20% of patients and Model 2 classified 28% of patients to the high-risk group. BTK and PLCG2 mutations are common genetic drivers of ibrutinib resistance in CLL. To determine whether the incidence of these mutations correlates with prognostic risk groups, we performed targeted sequencing of BTK and PLCG2 of samples collected from patients in the discovery cohort. We used cell-free DNA for patients who received long-term ibrutinib (≥3 years) and had low circulating tumor burden, and cellular DNA, for samples collected within 3 years on ibrutinib or at progression. Of 84 patients, 69 (82.1%) were tested at least once, and 37 (44.0%) were tested at least twice. The frequency of testing was similar across the risk groups by two models (P>0.05). The cumulative incidences of mutations at 5 years in the low-, intermediate-, and high-risk groups were: 21.4%, 44.8% and 50%, respectively, by Model 1 (P=0.02); and 22.6%, 41.4% and 66.7%, respectively, by Model 2 (P=0.01). Conclusion: We developed and validated prognostic models to predict the risk of disease progression or death in CLL patients treated with ibrutinib. Risk groups classified by three commonly available pre-treatment factors showed statistically significant differences in PFS. The clinically-defined high-risk disease was linked to higher propensity to develop clonal evolution with BTK and/or PLCG2 mutations, which heralded ibrutinib resistance. Disclosures Albitar: Neogenomics Laboratories: Employment. Ma:Neogenomics Laboratories: Employment. Ipe:Pharmacyclics, an AbbVie Company: Employment, Other: Travel; AbbVie: Equity Ownership. Tsao:Pharmacyclics LLC, an AbbVie Company: Employment. Cheng:Pharmacyclics LLC, an AbbVie Company: Employment. Dean:CTI BioPharma Corp.: Employment, Equity Ownership; Pharmacyclics LLC, an AbbVie Company: Employment, Equity Ownership. Wiestner:Pharmacyclics LLC, an AbbVie Company: Research Funding.


2021 ◽  
Vol 12 ◽  
Author(s):  
Junli Wang ◽  
Qi Zhang ◽  
Fukang Shi ◽  
Dipesh Kumar Yadav ◽  
Zhengtao Hong ◽  
...  

Purpose: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant diseases worldwide and has a poor prognosis. Gene-based prognostic models have been reported to predict the overall survival of patients with HCC. Unfortunately, most of the genes used in earlier prognostic models lack prospective validation and, thus, cannot be used in clinical practice.Methods: Candidate genes were selected from GEPIA (Gene Expression Profiling Interactive Analysis), and their associations with patients’ survival were confirmed by RT-PCR using cDNA tissue microarrays established from patients with HCC after radical resection. A multivariate Cox proportion model was used to calculate the coefficient of corresponding gene. The expression of seven genes of interest (MKI67, AR, PLG, DNASE1L3, PTTG1, PPP1R1A, and TTR) with two reference genes was defined to calculate a risk score which determined groups of different risks.Results: Our risk scoring efficiently classified patients (n = 129) with HCC into a low-, intermediate-, and high-risk group. The three groups showed meaningful distinction of 3-year overall survival rate, i.e., 88.9, 74.5, and 20.6% for the low-, intermediate-, and high-risk group, respectively. The prognostic prediction model of risk scores was subsequently verified using an independent prospective cohort (n = 77) and showed high accuracy.Conclusion: Our seven-gene signature model performed excellent long-term prediction power and provided crucially guiding therapy for patients who are not a candidate for surgery.


Author(s):  
Keerthana Batyala ◽  
M. V. Nagabhushana ◽  
Malli Dorasanamma

Background: To compare TIMI & HEART SCORE for their risk stratification in Acute Myocardial Infarction Patients,  prognostic accuracy and Arrhythmia incidence.Methods: This observational study is conducted in a Tertiary care hospital over a period of 2 years from August 2017 to July 2019. A total of 100 patients presented to ER with Chest Pain are selected for study. Patients were monitored for a period of one month in ICCU.Results: In present study out of 61 cases with TIMI score ≥5, mortality of 11.5%(7 cases, p value 0.028). Heart score more than 6  constitutes high risk group, out of which mortality was observed in 7.45% cases (p=0.48). Most of the arrhythmias (70.49%) in present study observed in patients with TIMI score ≥5 (High risk group) which is statistically significant with p value 0.002. Most of the arrhythmias in present study observed in patients with HS ≥8 which is not statistically significant with p value 0.135.Conclusions: In present study, overall mortality rate was 7% and these patients who died constitutes to high risk group with TIMI. HEART SCORE identified more patients as low risk compared to TIMI SCORE. TIMI SCORE is a good predictor of arrhythmia incidence.


2021 ◽  
Vol 11 ◽  
Author(s):  
Jiacheng Huang ◽  
Zhitao Chen ◽  
Chenchen Ding ◽  
Shengzhang Lin ◽  
Dalong Wan ◽  
...  

BackgroundPancreatic cancer is one of the principal causes of tumor-related death worldwide. CXC chemokines, a subfamily of functional chemotactic peptides, affect the initiation of tumor cells and clinical outcomes in several human malignant tumors. However, the specific biological functions and clinical significance of CXC chemokines in pancreatic cancer have not been clarified.MethodsBioinformatics analysis tools and databases, including ONCOMINE, GEPIA2, the Human Protein Atlas, DAVID, GeneMANIA, cBioPortal, STRING, DGidb, MethSurv, TRRUST, SurvExpress, SurvivalMeth, and TIMER, were utilized to clarify the clinical significance and biological functions of CXC chemokine in pancreatic cancer.ResultsExcept for CXCL11/12, the transcriptional levels of other CXC chemokines in PAAD tissues were significantly elevated, and the expression level of CXCL16 was the highest among these CXC chemokines. Our findings also suggested that all of the CXC chemokines were linked to tumor-immune dysfunction involving the abundance of immune cell infiltration, and the Cox proportional hazard model confirmed that dendritic and CXCL3/5/7/8/11/17 were significantly associated with the clinical outcome of PAAD patients. Furthermore, increasing expressions of CXCL5/9/10/11/17 were related to unfavorable overall survival (OS), and only CXCL17 was a prognostic factor for disease-free survival (DFS) in PAAD patients. The expression pattern and prognostic power of CXC chemokines were further validated in the independent GSE62452 dataset. For the prognostic value of single CpG of DNA methylation of CXC chemokines in patients with PAAD, we identified 3 CpGs of CXCL1, 2 CpGs of CXCL2, 2 CpGs of CXCL3, 3 CpGs of CXCL4, 10 CpGs of CXCL5, 1 CpG of CXCL6, 1 CpG of CXCL7, 3 CpGs of CXCL12, 3 CpGs of CXCL14, and 5 CpGs of CXCL17 that were significantly associated with prognosis in PAAD patients. Moreover, the prognostic value of CXC chemokine signature in PAAD was explored and tested in two independent cohort, and results indicated that the patients in the low-risk group had a better OS compared with the high-risk group. Survival analysis of the DNA methylation of CXC chemokine signature demonstrated that PAAD patients in the high-risk group had longer survival times.ConclusionsThese findings reveal the novel insights into CXC chemokine expression and their biological functions in the pancreatic cancers, which might serve as accurate prognostic biomarkers and suitable immunotherapeutic targets for patients with pancreatic cancer.


2022 ◽  
Author(s):  
Xingyun Wang ◽  
Jinli Ji ◽  
Ying Jiang ◽  
Yiyang Zhao ◽  
Zheyao Song ◽  
...  

Abstract Venous thromboembolism (VTE) is one of the major complications of digestive system cancer, and coagulation-fibrinolysis genes play an important role in VTE. We used univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox analysis to construct 3-PCFGs (prognostic coagulation-fibrinolysis genes) model based on six prognostic coagulation-fibrinolysis genes. Gene set enrichment analysis (GSEA) was used to analyze the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the high- and low-risk groups. In addition, we classified digestive system pancancer patients into three clusters A, B, and C based on 3-PCFGs by K means. High-risk group and cluster C were associated with poor prognosis in digestive system pancancer. The m6A-related genes ALKBH5, FTO, RBM15, YTHDC1, and YTHDC2 (P<0.001) were highly expressed in the high-risk group and cluster C. The risk score was positively correlated with cancer-associated fibroblasts and endothelial cells. Cluster C had the highest immune score and stromal score. The poor prognosis in the high-risk group and cluster C may be affected by m6A epigenetic modification and immune microenvironment components in the digestive system pancancer.


2021 ◽  
Author(s):  
YuHai Hu ◽  
YiPing Chen

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.


2021 ◽  
Vol 8 ◽  
Author(s):  
Kaiming Zhang ◽  
Liqin Ping ◽  
Tian Du ◽  
Gehao Liang ◽  
Yun Huang ◽  
...  

Background: Ferroptosis, a regulated cell death which is driven by the iron-dependent peroxidation of lipids, plays an important role in cancer. However, studies about ferroptosis-related Long non-coding RNAs (lncRNAs) in breast cancer (BC) are limited. Besides, the prognostic role of ferroptosis-related lncRNAs and their relationship to immune microenvironment in breast cancer remain unclear. This study aimed to explore the potential prognostic value of ferroptosis-related lncRNAs and their relationship to immune microenvironment in breast cancer.Methods: RNA-sequencing data of female breast cancer patients were downloaded from TCGA database. 937 patients were randomly separated into training or validation cohort in 2:1 ratio. Ferroptosis-related lncRNAs were screened by Pearson correlation analysis with 239 reported ferroptosis-related genes. A ferroptosis-related lncRNAs signature was constructed with univariate and multivariate Cox regression analyses in the training cohort, and its prognostic value was further tested in the validation cohort.Results: An 8-ferroptosis-related-lncRNAs signature was developed by multivariate Cox regression analysis to divide patients into two risk groups. Patients in the high-risk group had worse prognosis than patients in the low-risk group. Multivariate Cox regression analysis showed the risk score was an independent prognostic indicator. Receiver operating characteristic curve (ROC) analysis proved the predictive accuracy of the signature. The area under time-dependent ROC curve (AUC) reached 0.853 at 1 year, 0.802 at 2 years, 0.740 at 5 years in the training cohort and 0.791 at 1 year, 0.778 at 2 years, 0.722 at 5 years in the validation cohort. Further analysis demonstrated that immune-related pathways were significantly enriched in the high-risk group. Analysis of the immune cell infiltration landscape showed that breast cancer in the high-risk group tended be immunologically “cold”.Conclusion: We identified a novel ferroptosis-related lncRNA signature which could precisely predict the prognosis of breast cancer patients. Ferroptosis-related lncRNAs may have a potential role in the process of anti-tumor immunity and serve as therapeutic targets for breast cancer.


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