Integrated analysis revealing genome‑wide chromosomal copy number variation in supraglottic laryngeal squamous cell carcinoma

Li,Dongjie; Wang,Xianfu; Lu,Shunfei; Wang,Ping; Wang,Xin; Yin,Wanzhong; Zhu,Wei; Li,Shibo

doi:10.3892/ol.2020.11653

Integrated analysis revealing genome‑wide chromosomal copy number variation in supraglottic laryngeal squamous cell carcinoma

Authors:
- Dongjie Li
- Xianfu Wang
- Shunfei Lu
- Ping Wang
- Xin Wang
- Wanzhong Yin
- Wei Zhu
- Shibo Li
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Affiliations: Department of Otorhinolaryngology, Head and Neck Surgery, The First Hospital of Jilin University, Changchun, Jilin 130021, P.R. China, Department of Pediatrics, Genetics Laboratory, University of Oklahoma Health Sciences Center, Oklahoma, OK 73104, USA, Department of Clinical Medicine, Lishui College of Medicine, Lishui, Zhejiang 323000, P.R. China
Published online on: May 21, 2020 https://doi.org/10.3892/ol.2020.11653
Pages: 1201-1212
Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 4.0].

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Abstract

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.

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