scholarly journals Multivariate gene expression‐based survival predictor model in esophageal adenocarcinoma

2020 ◽  
Vol 11 (10) ◽  
pp. 2896-2908
Author(s):  
Maoyuan Zhao ◽  
Jingsong Wang ◽  
Meng Yuan ◽  
Zeliang Ma ◽  
Yongxin Bao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Adenocarcinoma ◽  
Predictor Model ◽  
Survival Predictor

scholarly journals Identification of miRNAs and genes for predicting Barrett’s esophagus progressing to esophageal adenocarcinoma using miRNA-mRNA integrated analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260353
Author(s):  
Chengjiao Yao ◽  
Yilin Li ◽  
Lihong Luo ◽  
Qin Xiong ◽  
Xiaowu Zhong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Barrett’S Esophagus ◽  
Esophageal Adenocarcinoma ◽  
Barrett's Esophagus ◽  
Trp Channels ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Epstein Barr Virus Infection ◽  
Tissue Samples ◽  
Microarray Datasets

Barrett’s esophagus (BE) is defined as any metaplastic columnar epithelium in the distal esophagus, which predisposes to esophageal adenocarcinoma (EAC). Yet, the mechanism through which BE develops to EAC still remain unclear. Moreover, the miRNA-mRNA regulatory network in distinguishing BE from EAC still remains poorly understood. To identify differentially expressed miRNAs (DEMs) and genes (DEGs) between EAC and BE from tissue samples, gene expression microarray datasets GSE13898, GSE26886, GSE1420 and miRNA microarray datasets GSE16456, GSE20099 were downloaded from Gene Expression Omnibus (GEO) database. GEO2R was used to screen the DEMs and DEGs. Pathway and functional enrichment analysis were performed by DAVID database. The protein–protein interaction (PPI) network was constructed by STRING and been visualized by Cytoscape software. Finnal, survival analysis was performed basing TCGA database. A total of 21 DEMs were identified. The enriched functions and pathways analysis inclued Epstein-Barr virus infection, herpesvirus infection and TRP channels. GART, TNFSF11, GTSE1, NEK2, ICAM1, PSMD12, CTNNB1, CDH1, PSEN1, IL1B, CTNND1, JAG1, CDH17, ITCH, CALM1 and ITGA6 were considered as the hub-genes. Hsa-miR-143 and hsa-miR-133b were the highest connectivity target gene. JAG1 was predicted as the largest number of target miRNAs. The expression of hsa-miR-181d, hsa-miR-185, hsa-miR-15b, hsa-miR-214 and hsa-miR-496 was significantly different between normal tissue and EAC. CDH1, GART, GTSE1, NEK2 and hsa-miR-496, hsa-miR-214, hsa-miR-15b were found to be correlated with survival.

scholarly journals Selective gene expression using a DF3/MUC1 promoter in a human esophageal adenocarcinoma model

Gene Therapy ◽  
2003 ◽  
Vol 10 (3) ◽  
pp. 206-212 ◽  
Author(s):  
V K Gupta ◽  
J O Park ◽  
T Kurihara ◽  
A Koons ◽  
H J Mauceri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Adenocarcinoma

Association of specific gene expression profiles with a pathologic complete response to neoadjuvant therapy in esophageal adenocarcinoma.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 51-51
Author(s):  
Patrick James McLaren ◽  
Anthony P Barnes ◽  
Willy Z Terrell ◽  
Gina M. Vaccaro ◽  
Jack Wiedrick ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Cancer ◽  
Neoadjuvant Therapy ◽  
Esophageal Adenocarcinoma ◽  
Expression Profiles ◽  
Pathologic Complete Response ◽  
Gene Expression Profiles ◽  
Complete Response ◽  
Specific Gene ◽  
Specific Gene Expression

51 Background: Predicting prognosis in esophageal cancer remains an unrealized goal despite studies linking constellations of genes to therapeutic response. In this study, we analyzed specific predictor genes expressed in tumor specimens from our institutional repository. Our aim was to determine if specific gene expression profiles are associated with pathologic complete response (pCR) after neoadjuvant chemo-radiotherapy (CRT). Methods: We investigated eleven genes identified from prior studies (CCL28, SPARC, S100A2, SPRR3, SIRT2, NOV, PERP, PAPSS2, DCK, DKK3, ALDH1) that have significant association with esophageal cancer progression. Patients with esophageal adenocarcinoma treated with neoadjuvant CRT followed by esophagectomy at our institution between January 2011 and July 2015 were included. Quantitative real-time polymerase chain reaction was conducted on pre-treatment biopsy specimens to determine gene expression. Patients were classified into two groups: 1) pCR and, 2) no or poor response (NR) after CRT based on final pathology report. An omnibus test using Mahalanobis distance was applied to evaluate overall genetic expression differences between groups. Log-rank tests compared the differential expression of individual genes. Results: 29 patients (11 pCR and 18 NR) were analyzed. Overall, gene expression profiles were significantly different between pCR and NR patients (p < 0.01). In particular, CCL28 was over-expressed in pCR (Log-HR: 1.53, 95%CI: 0.46-2.59, p = 0.005), and DKK3-was under-expressed in pCR patients (Log-HR: -1.03 95%CI: -1.97, -0.10, p = 0.031). Conclusions: Esophageal adenocarcinoma patients with a pCR after neoadjuvant therapy have genetic profiles that are significantly different from typical NR profiles. In our population, the genes CCL28 and DKK3 are potential predictors of treatment response.

Elucidating the pathogenesis of esophageal adenocarcinoma through meta-analysis of public data.

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 71-71
Author(s):  
Kamal Khorfan ◽  
Jihad Aljabban ◽  
Saad Syed ◽  
Hussam Salhi ◽  
Aderinola Adejare ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Adenocarcinoma ◽  
Poor Prognosis ◽  
Meta Analysis ◽  
Statistical Significance ◽  
Suppressor Gene ◽  
Gene Expression Omnibus ◽  
Incidence And Mortality ◽  
Public Data ◽  
Log Ratio

71 Background: Esophageal adenocarcinoma (EAC) is the sixth most common cause of cancer-related deaths worldwide. It commonly arises in the setting of reflux disease and Barett’s esophagus. It remains incurable and holds a poor prognosis. Dissecting the genetic signature of EAC can pave new therapeutic avenues. Methods: We employed our Search Tag Analyze Resource (STARGEO) platform to conduct meta-analysis using the National Center for Biotechnology’s (NCBI) Gene Expression Omnibus (GEO). We tagged 151 tumor samples from EAC patients and 62 normal esophageal samples as a control. We then analyzed the signature in Ingenuity Pathway Analysis, restricting genes that showed statistical significance (p < 0.05) and an absolute experimental log ratio greater than 0.15 between tumor and control. Results: Our analysis revealed granulocyte adhesion and diapedesis and FXR/RXR signaling as top canonical pathways. TGFB1, TNF, and beta-estradiol were top upstream regulators with predicted activation. TGFB1 and TNF expression have been correlated with poor prognosis in EAC. Also, beta-estradiol has tumorigenic activity in several cancers but has not been investigated in EAC. Among the top upregulated genes were oncogenic genes such as tetraspanin 8, the antiapoptotic factor OLFM4, and the protease cathepsin E (CTSE). SPINK1, a trypsin inhibitor with recently suggested role in cancer, and the choline transporter SLC44A4, a drug target for pancreatic cancer, were also upregulated. The most downregulated genes included alcohol dehydrogenase 7, associated with EAC in alcohol-drinkers, and the pro-apoptotic gene CRCT1. We also found downregulation of the serine peptidase inhibitor SPINK7. SPINK7 is involved in maintaining epithelial-barrier integrity and is implicated in eosinophilic esophagitis pathogenesis. Lastly, there was downregulation of the candidate tumor suppressor gene transglutaminase 3. Conclusions: Despite screening efforts, EAC incidence and mortality continues to increase as does the need for better treatment. This meta-analysis defines the significant gene expression changes within causal disease processes to provide markers for detection, prognostic insight, and therapeutic value for EAC.

scholarly journals Gene expression profiles in esophageal adenocarcinoma predict survival after resection

2013 ◽  
Vol 145 (2) ◽  
pp. 505-513 ◽  
Author(s):  
Arjun Pennathur ◽  
Liqiang Xi ◽  
Virginia R. Litle ◽  
William E. Gooding ◽  
Alyssa Krasinskas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Esophageal Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Differential gene expression profiling of esophageal adenocarcinoma

2009 ◽  
Vol 137 (4) ◽  
pp. 829-834 ◽  
Author(s):  
Zane T. Hammoud ◽  
Sunil Badve ◽  
Qianqian Zhao ◽  
Lang Li ◽  
Romil Saxena ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Esophageal Adenocarcinoma ◽  
Differential Gene Expression ◽  
Expression Profiling ◽  
Differential Gene

scholarly journals Meta-analysis of 1,200 transcriptomic profiles identifies a prognostic model for pancreatic ductal adenocarcinoma

2018 ◽  
Author(s):  
Vandana Sandhu ◽  
Knut Jorgen Labori ◽  
Ayelet Borgida ◽  
Ilinca Lungu ◽  
John Bartlett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Overall Survival ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Prognostic Model ◽  
Meta Analysis ◽  
Early Death ◽  
Receiver Operating Curve ◽  
Ductal Adenocarcinoma ◽  
Survival Predictor

ABSTRACTBackgroundWith a dismal 8% median 5-year overall survival (OS), pancreatic ductal adenocarcinoma (PDAC) is highly lethal. Only 10-20% of patients are eligible for surgery, and over 50% of these will die within a year of surgery. Identify molecular predictors of early death would enable the selection of PDAC patients at high risk.MethodsWe developed the Pancreatic Cancer Overall Survival Predictor (PCOSP), a prognostic model built from a unique set of 89 PDAC tumors where gene expression was profiled using both microarray and sequencing platforms. We used a meta-analysis framework based on the binary gene pair method to create gene expression barcodes robust to biases arising from heterogeneous profiling platforms and batch effects. Leveraging the largest compendium of PDAC transcriptomic datasets to date, we show that PCOSP is a robust single-sample predictor of early death (≤1 yr) after surgery in a subset of 823 samples with available transcriptomics and survival data.ResultsThe PCOSP model was strongly and significantly prognostic with a meta-estimate of the area under the receiver operating curve (AUROC) of 0.70 (P=1.9e-18) and hazard ratio (HR) of 1.95(1.6-2.3) (P=2.6e-16) for binary and survival predictions, respectively. The prognostic value of PCOSP was independent of clinicopathological parameters and molecular subtypes. Over-representation analysis of the PCOSP 2619 gene-pairs (1070 unique genes) unveiled pathways associated with Hedgehog signalling, epithelial mesenchymal transition (EMT) and extracellular matrix (ECM) signalling.ConclusionPCOSP could improve treatment decision by identifying patients who will not benefit from standard surgery/chemotherapy and may benefit from alternate approaches.AbbreviationsAUROCArea under the receiver operating curveGOGene annotationOSOverall survivalPCOSPPancreatic cancer overall survival predictorPDACPancreatic ductal adenocarcinomaTSPTop scoring pairs.

scholarly journals Beyond Field Effect: Analysis of Shrunken Centroids in Normal Esophageal Epithelia Detects Concomitant Esophageal Adenocarcinoma

2007 ◽  
Vol 1 ◽  
pp. BBI.S311 ◽  
Author(s):  
Florin M. Selaru ◽  
Suna Wang ◽  
Jing Yin ◽  
Karsten Schulmann ◽  
Yan Xu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Barrett’S Esophagus ◽  
Esophageal Adenocarcinoma ◽  
Barrett's Esophagus ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Differentially Expressed ◽  
Gene Expression Patterns ◽  
Neoplastic Progression ◽  
Esophageal Epithelium

Background and Aims Because of the extremely low neoplastic progression rate in Barrett's esophagus, it is difficult to diagnose patients with concomitant adenocarcinoma early in their disease course. If biomarkers existed in normal squamous esophageal epithelium to identify patients with concomitant esophageal adenocarcinoma, potential applications would be far-reaching. The aim of the current study was to identify global gene expression patterns in normal esophageal epithelium capable of revealing simultaneous esophageal adenocarcinoma, even located remotely in the esophagus. Methods Tissues comprised normal esophageal epithelia from 9 patients with esophageal adenocarcinoma, 8 patients lacking esophageal adenocarcinoma or Barrett's, and 6 patients with Barrett's esophagus alone. cDNA microarrays were performed, and pattern recognition in each of these subgroups was achieved using shrunken nearest centroid predictors. Results Our method accurately discriminated normal esophageal epithelia of 8/8 patients without esophageal adenocarcinoma or Barrett's esophagus and of 6/6 patients with Barrett's esophagus alone from normal esophageal epithelia of 9/9 patients with Barrett's esophagus and concomitant esophageal adenocarcinoma. Moreover, we identified genes differentially expressed between the above subgroups. Thus, based on their corresponding normal esophageal epithelia alone, our method accurately diagnosed patients who had concomitant esophageal adenocarcinoma. Conclusions These global gene expression patterns, along with individual genes culled from them, represent potential biomarkers for the early diagnosis of esophageal adenocarcinoma from normal esophageal epithelia. Genes discovered in normal esophagus that are differentially expressed in patients with vs. without esophageal adenocarcinoma merit further pursuit in molecular genetic, functional, and therapeutic interventional studies.

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