scholarly journals Discovery and Validation of Circulating EVL mRNA as a Prognostic Biomarker in Pancreatic Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yan Du ◽  
Kai Yao ◽  
Qingbo Feng ◽  
Feiyu Mao ◽  
Zechang Xin ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Mrna Expression ◽  
Cox Regression ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Mrna Levels ◽  
Plasma Samples ◽  
Patient Prognosis

Background. Circulating plasma mRNAs can be analyzed to identify putative cancer biomarkers. This study was conducted in an effort to detect plasma mRNA biomarkers capable of predicting pancreatic cancer (PACA) patient prognosis. Material and Methods. First, prognostic mRNAs that were differentially expressed in PACA in The Cancer Genome Atlas (TCGA) were established, after which microarray expression profiles from PACA patient plasma samples were utilized to specifically identify potential prognostic plasma mRNA biomarkers associated with this cancer type. In total, plasma samples were then collected from 79 PACA patients and 19 healthy controls to confirm differential mRNA expression via qPCR, while Kaplan–Meier analyses were used to examine the link between mRNA expression and patient overall survival. Results. In total, three prognostic differentially expressed genes were identified in PACA patient plasma samples, including SMAP2, PTPN6, and EVL (Ena/VASP-like). Plasma EVL levels were confirmed via qPCR to be correlated with tumor pathology p < 0.01 , while the overall survival of patients with low plasma EVL levels was poor p < 0.01 . Multivariate Cox regression analyses further confirmed that plasma EVL levels were independent predictors of PACA patient prognosis. Conclusion. We found that PACA is associated with the downregulation of plasma EVL mRNA levels, indicating that this mRNA may be a viable biomarker associated with patient prognosis.

scholarly journals Identification of Hub Prognosis-Associated Oxidative Stress Genes in Pancreatic Cancer Using Integrated Bioinformatics Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Xin Qiu ◽  
Qin-Han Hou ◽  
Qiu-Yue Shi ◽  
Hai-Xing Jiang ◽  
Shan-Yu Qin
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Pancreatic Cancer ◽  
Cancer Progression ◽  
Risk Model ◽  
Cox Regression ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Cox Regression Analysis

BackgroundIntratumoral oxidative stress (OS) has been associated with the progression of various tumors. However, OS has not been considered a candidate therapeutic target for pancreatic cancer (PC) owing to the lack of validated biomarkers.MethodsWe compared gene expression profiles of PC samples and the transcriptome data of normal pancreas tissues from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression (GTEx) databases to identify differentially expressed OS genes in PC. PC patients’ gene profile from the Gene Expression Omnibus (GEO) database was used as a validation cohort.ResultsA total of 148 differentially expressed OS-related genes in PC were used to construct a protein-protein interaction network. Univariate Cox regression analysis, least absolute shrinkage, selection operator analysis revealed seven hub prognosis-associated OS genes that served to construct a prognostic risk model. Based on integrated bioinformatics analyses, our prognostic model, whose diagnostic accuracy was validated in both cohorts, reliably predicted the overall survival of patients with PC and cancer progression. Further analysis revealed significant associations between seven hub gene expression levels and patient outcomes, which were validated at the protein level using the Human Protein Atlas database. A nomogram based on the expression of these seven hub genes exhibited prognostic value in PC.ConclusionOur study provides novel insights into PC pathogenesis and provides new genetic markers for prognosis prediction and clinical treatment personalization for PC patients.

ERCC1 mRNA levels as a useful prognostic biomarker for extrahepatic cholangiocarcinoma with R0 resection.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 239-239
Author(s):  
Shuichiro Uemura ◽  
Hidekazu Kuramochi ◽  
Go Nakajima ◽  
Yasuto Sato ◽  
Ryota Higuchi ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
Mrna Expression ◽  
Biliary Tract ◽  
Prognostic Biomarker ◽  
Biliary Tract Carcinoma ◽  
R0 Resection ◽  
Cancer Type ◽  
Mrna Levels ◽  
Extrahepatic Cholangiocarcinoma

239 Background: To date, no prognostic biomarker for biliary tract carcinoma has been identified. In previous studies of biliary tract carcinoma, no reliable data was found due to the varying composition of the cancer type (gallbladder, cholangiocarcinoma, and ampullary carcinoma), differences in tumor location, a mixture of curative and non-curative operations, and differences in operative methods. Methods: Fifty extrahepatic cholangiocarcinoma patients who underwent a pancreatoduodenectomy with R0 resection at the Tokyo Women’s Medical University Hospital were examined. All patients were pathologically diagnosed as having papillary or tubular adenocarcinoma. T-RNA was extracted from FFPE samples, and mRNA expression levels were measured by real-time RT-PCR. Results: In the preliminary analysis, 10 patients who have survived more than 5 years (LS group) and 10 patients who had a relapse within 2 years (SS group) were selected. EGFR, AREG, EREG, MMP-9, CDH-1, PARP1, and ERCC1 mRNA expression were examined; only the ERCC1 mRNA levels showed a significant difference between the LS and SS groups (median ERCC1: LS 26.5 vs. SS 9.7, p=0.0073). The median survival time (MST) of the patients with high ERCC1 levels was significantly higher than that in patients with a low ERCC1 level (MST: not reached vs. 16M). Then, 30 more patients with the same backgrounds were added to the study, and ERCC1 mRNA levels were measured in all 50 patients. The patients with high ERCC1 mRNA levels had a significantly greater overall survival rate compared with those with low ERCC1 levels (MST: not reached vs. 12.5M, 5-year survival rate: 92% vs 51%; p=0.04). In multivariate analysis, no lymph node metastases or high ERCC1 expression were significantly associated with better overall survival. Conclusions: ERCC1 mRNA expression seemed to be a useful prognostic biomarker for extrahepatic cholangiocarcinoma with R0 resection.

scholarly journals Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sheng Zheng ◽  
Zizhen Zhang ◽  
Ning Ding ◽  
Jiawei Sun ◽  
Yifeng Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
High Efficiency ◽  
Cox Regression ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lasso Regression ◽  
Sequencing Data ◽  
Cox Regression Analysis

Abstract Introduction Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). Methods mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. Results Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusions We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.

scholarly journals Integrative Analysis of miRNA and mRNA Expression Profiles in Mammary Glands of Holstein Cows Artificially Infected with Staphylococcus aureus

Pathogens ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 506
Author(s):  
Xiaolong Wang ◽  
Yongliang Fan ◽  
Yifan He ◽  
Ziyin Han ◽  
Zaicheng Gong ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Mrna Expression ◽  
Calcium Binding ◽  
Expression Profiles ◽  
Bovine Mastitis ◽  
Mammary Glands ◽  
Integrative Analysis ◽  
Differentially Expressed ◽  
Future Application ◽  
Collagen Type Iv

Staphylococcus aureus- induced mastitis is one of the most intractable problems for the dairy industry, which causes loss of milk yield and early slaughter of cows worldwide. Few studies have used a comprehensive approach based on the integrative analysis of miRNA and mRNA expression profiles to explore molecular mechanism in bovine mastitis caused by S. aureus. In this study, S. aureus (A1, B1 and C1) and sterile phosphate buffered saline (PBS) (A2, B2 and C2) were introduced to different udder quarters of three individual cows, and transcriptome sequencing and microarrays were utilized to detected miRNA and gene expression in mammary glands from the challenged and control groups. A total of 77 differentially expressed microRNAs (DE miRNAs) and 1625 differentially expressed genes (DEGs) were identified. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that multiple DEGs were enriched in significant terms and pathways associated with immunity and inflammation. Integrative analysis between DE miRNAs and DEGs proved that miR-664b, miR-23b-3p, miR-331-5p, miR-19b and miR-2431-3p were potential factors regulating the expression levels of CD14 Molecule (CD14), G protein subunit gamma 2 (GNG2), interleukin 17A (IL17A), collagen type IV alpha 1 chain (COL4A1), microtubule associated protein RP/EB family member 2 (MAPRE2), member of RAS oncogene family (RAP1B), LDOC1 regulator of NFKB signaling (LDOC1), low-density lipoprotein receptor (LDLR) and S100 calcium binding protein A9 (S100A9) in bovine mastitis caused by S. aureus. These findings could enhance the understanding of the underlying immune response in bovine mammary glands against S. aureus infection and provide a useful foundation for future application of the miRNA–mRNA-based genetic regulatory network in the breeding cows resistant to S. aureus.

scholarly journals Clinical relevance of kallikrein-related peptidase 6 (KLK6) and 8 (KLK8) mRNA expression in advanced serous ovarian cancer

2016 ◽  
Vol 397 (12) ◽  
pp. 1265-1276 ◽  
Author(s):  
Nancy Ahmed ◽  
Julia Dorn ◽  
Rudolf Napieralski ◽  
Enken Drecoll ◽  
Matthias Kotzsch ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Mrna Expression ◽  
Cox Regression ◽  
Multivariable Analysis ◽  
Progression Free Survival ◽  
Predictive Marker ◽  
Residual Tumor ◽  
Mrna Levels ◽  
Serous Ovarian Cancer ◽  
Cox Regression Analysis

Abstract Most members of the kallikrein-related peptidase family have been demonstrated to be dysregulated in ovarian cancer and modulate tumor growth, migration, invasion, and resistance to chemotherapy. In the present study, we assessed the mRNA expression levels of KLK6 and KLK8 by quantitative PCR in 100 patients with advanced serous ovarian cancer FIGO stage III/IV. A pronounced correlation between KLK6 and KLK8 mRNA expression (rs = 0.636, p < 0.001) was observed, indicating coordinate expression of both peptidases. No significant associations of clinical parameters with KLK6, KLK8, and a combined score KLK6+KLK8 were found. In univariate Cox regression analysis, elevated mRNA levels of KLK6 were significantly linked with shortened overall survival (OS) (hazard ratio [HR] = 2.07, p = 0.007). While KLK8 values were not associated with patients’ outcome, high KLK6+KLK8 values were significantly associated with shorter progression-free survival (HR = 1.82, p = 0.047) and showed a trend towards significance in the case of OS (HR = 1.82, p = 0.053). Strikingly, in multivariable analysis, elevated KLK6 mRNA values, apart from residual tumor mass, remained an independent predictive marker for poor OS (HR = 2.33, p = 0.005). As KLK6 mRNA and protein levels correlate, KLK6 may represent an attractive therapeutic target for potent and specific inhibitors of its enzymatic activity.

scholarly journals mRNA expression profiles obtained from microdissected pancreatic cancer cells can predict patient survival

Oncotarget ◽  
2017 ◽  
Vol 8 (62) ◽  
pp. 104796-104805
Author(s):  
Ana-Barbara García-García ◽  
M. Carmen Gómez-Mateo ◽  
Rebeca Hilario ◽  
Pilar Rentero-Garrido ◽  
Alvaro Martínez-Domenech ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Mrna Expression ◽  
Cancer Cells ◽  
Patient Survival ◽  
Expression Profiles ◽  
Pancreatic Cancer Cells

scholarly journals Development and Validation of a Prognostic Nomogram Based on DNA Methylation-Driven Genes for Patients With Ovarian Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Min Zhou ◽  
Shasha Hong ◽  
Bingshu Li ◽  
Cheng Liu ◽  
Ming Hu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Dna Methylation ◽  
Mrna Expression ◽  
Risk Score ◽  
Cox Regression ◽  
Expression Profiles ◽  
Figo Stage ◽  
Prognostic Indicator ◽  
Tissue Expression ◽  
The Cancer Genome Atlas

Background: DNA methylation affects the development, progression, and prognosis of various cancers. This study aimed to identify DNA methylated-differentially expressed genes (DEGs) and develop a methylation-driven gene model to evaluate the prognosis of ovarian cancer (OC).Methods: DNA methylation and mRNA expression profiles of OC patients were downloaded from The Cancer Genome Atlas, Genotype-Tissue Expression, and Gene Expression Omnibus databases. We used the R package MethylMix to identify DNA methylation-regulated DEGs and built a prognostic signature using LASSO Cox regression. A quantitative nomogram was then drawn based on the risk score and clinicopathological features.Results: We identified 56 methylation-related DEGs and constructed a prognostic risk signature with four genes according to the LASSO Cox regression algorithm. A higher risk score not only predicted poor prognosis, but also was an independent poor prognostic indicator, which was validated by receiver operating characteristic (ROC) curves and the validation cohort. A nomogram consisting of the risk score, age, FIGO stage, and tumor status was generated to predict 3- and 5-year overall survival (OS) in the training cohort. The joint survival analysis of DNA methylation and mRNA expression demonstrated that the two genes may serve as independent prognostic biomarkers for OS in OC.Conclusion: The established qualitative risk score model was found to be robust for evaluating individualized prognosis of OC and in guiding therapy.

scholarly journals Genomic Expression Profiling of Colorectal Cancer in Silico

2021 ◽  
Author(s):  
Feifei Liu ◽  
Yu Wang ◽  
Wenxue Li ◽  
Diancheng Li ◽  
Yuwei Xin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Survival Analysis ◽  
Mrna Expression ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Analysis Tool ◽  
Hub Genes ◽  
Normal Tissues

Abstract Background: Colorectal cancer (CRC) is one of the most common malignancies of the digestive system; the progression and prognosis of which are affected by a complicated network of genes and pathways. The aim of this study was to identify potential hub genes associated with the progression and prognosis of colorectal cancer (CRC).Methods: We obtained gene expression profiles from GEO database to search differentially expressed genes (DEGs) between CRC tissues and normal tissue. Subsequently, we conducted a functional enrichment analysis, generated a protein–protein interaction (PPI) network to identify the hub genes, and analyzed the expression validation of the hub genes. Kaplan–Meier plotter survival analysis tool was performed to evaluate the prognostic value of hub genes expression in CRC patients.Results: A total of 370 samples, involving CRC and normal tissues were enrolled in this article. 283 differentially expressed genes (DEGs), including 62 upregulated genes and 221 downregulated genes between CRC and normal tissues were selected. We finally filtered out 6 hub genes, including INSL5, MTIM, GCG, SPP1, HSD11B2, and MAOB. In the database of TCGA-COAD, the mRNA expression of INSL5, MT1M, HSD11B2, MAOB in tumor is lower than that in normal; the mRNA expression of SPP1 in tumor is higher than that in normal. In the HPA database, the expression of INSL5, GCG, HSD11B2, MAOB in tumor is lower than that in normal tissues; the expression of SPP1 in the tumor is higher than that in normal tissues. Survival analysis revealed that INSL5, GCG, SPP1 and MT1M may serve as prognostic biomarkers in CRC. Conclusions: We screened out six hub genes to predict the occurrence and prognosis of patients with CRC using bioinformatics methods, which may provide new targets and ideas for diagnosis, prognosis and individualized treatment for CRC.

scholarly journals Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Shaojie Chen ◽  
Feifei Huang ◽  
Shangxiang Chen ◽  
Yinting Chen ◽  
Jiajia Li ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Time Dependent ◽  
Concordance Index ◽  
Cox Regression Analysis ◽  
Score Model

ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

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