Xiaoshuai Wang1, Yueyin Han2, Jia Li1, Dongchun Hong3, Zhicheng Xue4, Haoyang Huang5, Zefeng Du6, Yingdong Hou5, Hongbo Li7, Hongyi Li8, Hongyi Liao9, Xianbiao Xie10, Changhai Ding11. 1. Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China. 2. Department of Pulmonary and Critical Care Medicine, Center for Respiratory Diseases, China-Japan Friendship Hospital; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China. 3. Department of Medical Melanoma and Sarcoma, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China. 4. Department of Gastric Surgery, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China. 5. Zhongshan Medical College of Sun Yat-sen University, Guangzhou, Guangdong, China. 6. Department of Hepatobiliary Oncology, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, Guangdong, China. 7. Department of Musculoskeletal Oncology, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China. 8. Department of Orthopedics, Qingyuan People's Hospital, Qingyuan, China. 9. Division of Joint Surgery, Department of Orthopaedic Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China. 10. Department of Musculoskeletal Oncology, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address: xiexbiao@mail.sysu.edu.cn. 11. Clinical Research Centre, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China; Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia. Electronic address: changhai.ding@utas.edu.au.
Abstract
AIMS: RNA regulatory genes were closely associated with tumorigenesis and prognosis in multiple tumors. Copy number variation (CNV) is a frequent characteristic in soft tissue sarcomas (STS). However, little is known regarding their possible roles in STS. MAIN METHODS: RNA sequence profiles and CNV data of 255 STS patients were downloaded from the Cancer Genome Atlas (TCGA). The correlation analysis involved CNVs of RNA regulatory genes, patient survival, immune infiltration, and DNA methylation. Drug sensitivity (IC50) was analyzed and validated by MTT assays in STS cell lines. KEY FINDINGS: CNV events were frequently observed in all kinds (m6A, m5C, ac4C, m1A, m3C, m6Am, m7G, and Ψ) of RNA regulatory genes. Diploid copy number (CN) of METTL4 was associated with better overall survival (OS) in STS and the subtypes (leiomyosarcoma, LMS; dedifferentiated liposarcoma, DDLPS). In STS and LMS, diploid CN of METTL4 was significantly associated with higher infiltration fraction of resting mast cells. In STS and DDLPS, diploid CN of METTL4 possessed lower methylation level in CpG site of cg12105018, which represented better OS. Besides, sensitive drugs for STS cell lines were analyzed according to lower IC50 for the loss CN of METTL4. Temozolomide and Olaparib were identified. Further validation by MTT assays demonstrated that GCT was the most sensitive cell line to both Temozolomide and Olaparib. SIGNIFICANCE: CNV of METTL4 could be a prognostic biomarker for STS by potentially influencing mast cell infiltration and DNA methylation. Besides, STS with loss CN of METTL4 would be sensitive to Temozolomide and Olaparib.
AIMS: RNA regulatory genes were closely associated with tumorigenesis and prognosis in multiple tumors. Copy number variation (CNV) is a frequent characteristic in soft tissue sarcomas (STS). However, little is known regarding their possible roles in STS. MAIN METHODS: RNA sequence profiles and CNV data of 255 STS patients were downloaded from the Cancer Genome Atlas (TCGA). The correlation analysis involved CNVs of RNA regulatory genes, patient survival, immune infiltration, and DNA methylation. Drug sensitivity (IC50) was analyzed and validated by MTT assays in STS cell lines. KEY FINDINGS: CNV events were frequently observed in all kinds (m6A, m5C, ac4C, m1A, m3C, m6Am, m7G, and Ψ) of RNA regulatory genes. Diploid copy number (CN) of METTL4 was associated with better overall survival (OS) in STS and the subtypes (leiomyosarcoma, LMS; dedifferentiated liposarcoma, DDLPS). In STS and LMS, diploid CN of METTL4 was significantly associated with higher infiltration fraction of resting mast cells. In STS and DDLPS, diploid CN of METTL4 possessed lower methylation level in CpG site of cg12105018, which represented better OS. Besides, sensitive drugs for STS cell lines were analyzed according to lower IC50 for the loss CN of METTL4. Temozolomide and Olaparib were identified. Further validation by MTT assays demonstrated that GCT was the most sensitive cell line to both Temozolomide and Olaparib. SIGNIFICANCE: CNV of METTL4 could be a prognostic biomarker for STS by potentially influencing mast cell infiltration and DNA methylation. Besides, STS with loss CN of METTL4 would be sensitive to Temozolomide and Olaparib.
Authors: Miguel Esperança-Martins; Iola F Duarte; Mara Rodrigues; Joaquim Soares do Brito; Dolores López-Presa; Luís Costa; Isabel Fernandes; Sérgio Dias Journal: Int J Mol Sci Date: 2022-09-28 Impact factor: 6.208