The identification of gene signatures in patients with extranodal NK/T-cell lymphoma from a pair of twins

BMC Cancer

Xuelei Ma¹  Huashan Shi¹  Liqun Zou²  Ting Yu³  Huaicheng Tan⁴  Yang Wang⁴  Xiaoxuan Chen⁵  Fangqi Jing⁵ 

[1] Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, China;Department of Radiotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China;Department of Head and Neck Cancer, Cancer Center, West China Hospital, Sichuan University, Chengdu, China;Department of Pathology and Laboratory of Pathology, State Key Laboratory of Biotherapy, West China Hospital, West China School of Medicine, Sichuan University, Chengdu, China;Laboratory of Aging Research and Cancer Drug Target, State Key Laboratory of Biotherapy, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, No. 17, Block 3, Southern Renmin Road, 610041, Chengdu, Sichuan, PR China;State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, 610041, Chengdu, China;

关键词: Extranodal NK/T-cell lymphoma;    Sequencing;    Support vector machine-recursive feature elimination;    Machine learning algorithms;    Single sample gene set enrichment analysis;    Immune infiltration;   

DOI  :  10.1186/s12885-021-09023-9

来源: Springer

【 摘 要 】

BackgroundThere is no unified treatment standard for patients with extranodal NK/T-cell lymphoma (ENKTL). Cancer neoantigens are the result of somatic mutations and cancer-specific. Increased number of somatic mutations are associated with anti-cancer effects. Screening out ENKTL-specific neoantigens on the surface of cancer cells relies on the understanding of ENKTL mutation patterns. Hence, it is imperative to identify ENKTL-specific genes for ENKTL diagnosis, the discovery of tumor-specific neoantigens and the development of novel therapeutic strategies. We investigated the gene signatures of ENKTL patients.MethodsWe collected the peripheral blood of a pair of twins for sequencing to identify unique variant genes. One of the twins is diagnosed with ENKTL. Seventy samples were analyzed by Robust Multi-array Analysis (RMA). Two methods (elastic net and Support Vector Machine-Recursive Feature Elimination) were used to select unique genes. Next, we performed functional enrichment analysis and pathway enrichment analysis. Then, we conducted single-sample gene set enrichment analysis of immune infiltration and validated the expression of the screened markers with limma packages.ResultsWe screened out 126 unique variant genes. Among them, 11 unique genes were selected by the combination of elastic net and Support Vector Machine-Recursive Feature Elimination. Subsequently, GO and KEGG analysis indicated the biological function of identified unique genes. GSEA indicated five immunity-related pathways with high signature scores. In patients with ENKTL and the group with high signature scores, a proportion of functional immune cells are all of great infiltration. We finally found that CDC27, ZNF141, FCGR2C and NES were four significantly differential genes in ENKTL patients. ZNF141, FCGR2C and NES were upregulated in patients with ENKTL, while CDC27 was significantly downregulated.ConclusionWe identified four ENKTL markers (ZNF141, FCGR2C, NES and CDC27) in patients with extranodal NK/T-cell lymphoma.

【 授权许可】

CC BY