Dataset Information

Genome wide copy number analyses of superficial esophageal squamous cell carcinoma with and without metastasis.

ABSTRACT: Superficial esophageal squamous cell carcinoma (ESCC) is generally considered a subtype of less invasive ESCC. Yet a subset of these superficial ESCC would have metastasis after esophagostomy or endoscopic resection and lead to poor prognosis. The objective of this study is to determine biomarkers that can identify such subset of superficial ESCC that would have metastasis after surgery using genome wide copy number alteration (CNA) analyses. The CNAs of 38 cases of superficial ESCCs originated from radical surgery, including 19 without metastasis and 19 with metastasis within 5 years' post-surgery, were analyzed using Affymetrix OncoScan™ FFPE Assay. A 39-gene signature was identified which characterized the subset of superficial ESCC with high risk of metastasis after surgery. In addition, recurrent CNAs of superficial ESCC were also investigated in the study. Amplification of 11q13.3 (FGF4) and deletion of 9p21.3 (CDKN2A) were found to be recurrent in all 38 superficial ESCCs analyzed. Notably amplifications of 3p26.33 (SOX2OT), 8q24.21 (MYC), 14q21.1 (FOXA1) and deletion of 3p12.1 (GBE1) were only found to be recurrent in metastaic superficial ESCCs. In conclusion, using CNAs analyses, we identify a 39-gene signature which characterizes the high risk metastatic superficial ESCCs and discover several recurrent CNAs that might be the driver alterations in metastasis among superficial ESCCs.

SUBMITTER: Wang P

PROVIDER: S-EPMC5354893 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Genome wide copy number analyses of superficial esophageal squamous cell carcinoma with and without metastasis.

Wang Pengjiao P Shan Ling L Xue Liyan L Zheng Bo B Ying Jianming J Lu Ning N

Oncotarget 20170101 3

Superficial esophageal squamous cell carcinoma (ESCC) is generally considered a subtype of less invasive ESCC. Yet a subset of these superficial ESCC would have metastasis after esophagostomy or endoscopic resection and lead to poor prognosis. The objective of this study is to determine biomarkers that can identify such subset of superficial ESCC that would have metastasis after surgery using genome wide copy number alteration (CNA) analyses. The CNAs of 38 cases of superficial ESCCs originated ...[more]

PMID: 27974698

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Project description:Laryngeal squamous cell carcinoma (LSCC) is a genetically complex tumor type and one of the leading causes of cancer-associated disability and mortality. Genetic instability, such as chromosomal instability, is associated with the tumorigenesis of LSCC. Copy number variations (CNVs) have been demonstrated to contribute to the genetic diversity of tumor pathogenesis. Comparative genomic hybridization (CGH) has emerged as a high-throughput genomic technology that facilitates the aggregation of high-resolution data of cancer-associated genomic imbalances. In the present study, a total of 38 primary supraglottic LSCC cases were analyzed by high-resolution array-based CGH (aCGH) to improve the understanding of the genetic alterations in LSCC. Additionally, integration with bioinformatic analysis of microarray expression profiling data from the Gene Expression Omnibus (GEO) database provided a fundamental method for the identification of putative target genes. Genomic CNVs were detected in all cases. The size of net genomic imbalances per case ranged between a loss of 682.3 Mb (~24% of the genome) and a gain of 1,958.6 Mb (~69% of the genome). Recurrent gains included 2pter-q22.1, 3q26.1-qter, 5pter-p12, 7p22.3p14.1, 8p12p11.22, 8q24.13q24.3, 11q13.2q13.4, 12pter-p12.2, 18pter-p11.31 and 20p13p12.1, whereas recurrent losses included 3pter-p21.32, 4q28.1-q35.2, 5q13.2-qter, 9pter-p21.3 and monosomy 13. Gains of 3q26.1-qter were associated with tumor stage, poor differentiation and smoking history. Additionally, through integration with bioinformatic analysis of data from the GEO database, putative target oncogenes, including sex-determining region Y-box 2, eukaryotic translation initiation factor 4 gamma 1, fragile X-related gene 1, disheveled segment polarity protein 3, defective n cullin neddylation 1 domain containing 1, insulin like growth factor 2 mRNA binding protein 2 and CCDC26 long non-coding RNA, and tumor suppressor genes, such as CUB and sushi multiple domains 1, cyclin dependent kinase inhibitor 2A, protocadherin 20, serine peptidase inhibitor Kazal type 5 and Nei like DNA glycosylase 3, were identified in supraglottic LSCC. Supraglottic LSCC is a genetically complex tumor type and aCGH was demonstrated to be effective in the determination of molecular profiles with higher resolution. The present results enable the identification of putative target oncogenes and tumor suppressor gene mapping in supraglottic LSCC.

Project description:The lymphovascular invasion (LVI) status facilitates the determination of the optimal therapeutic strategy for superficial esophageal squamous cell carcinoma (SESCC), but in clinical practice, LVI must be confirmed by postoperative pathology. However, studies of the risk factors for LVI in SESCC are limited. Consequently, this study aimed to identify the risk factors for LVI and use these factors to establish a prediction model. The data of 516 patients who underwent radical esophagectomy between January 2007 and September 2019 were retrospectively collected (training set, n=361, January 2007 to May 2015; validation set, n=155, June 2015 to September 2019). In the training set, least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were utilized to identify predictive factors for LVI in patients with SESCC. A nomogram was then developed using these predictors. The area under the curve (AUC), calibration curve, and decision curve were used to evaluate the efficiency, accuracy, and clinical utility of the model. LASSO regression indicated that the tumor size, depth of invasion, tumor differentiation, lymph node metastasis (LNM), sex, circumferential extension, the presence of multiple lesions, and the resection margin were correlated with LVI. However, multivariate analysis revealed that only the tumor size, depth of invasion, tumor differentiation, and LNM were independent risk factors for LVI. Incorporating these four variables, model 1 achieved an AUC of 0.817 in predicting LVI. Adding circumferential extension to model 1 did not appreciably change the AUC and integrated discrimination improvement, but led to a significant increase in the net reclassification improvement (p=0.011). A final nomogram was constructed by incorporating tumor size, depth of invasion, tumor differentiation, LNM, and circumferential extension and showed good discrimination (training set, AUC=0.833; validation set, AUC=0.819) and good calibration in the training and validation sets. Decision curve analysis demonstrated that the nomogram was clinically useful in both sets. Thus, it is possible to predict the status of LVI using this nomogram scoring system, which can aid the selection of an appropriate treatment plan.

Dataset Information

Genome wide copy number analyses of superficial esophageal squamous cell carcinoma with and without metastasis.

Publications

Genome wide copy number analyses of superficial esophageal squamous cell carcinoma with and without metastasis.

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