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Chen Z, Huang H, Hong H, Huang H, Weng H, Yu L, Xiao J, Wang Z, Fang X, Yao Y, Yue JX, Lin T. Full-spectral genome analysis of natural killer/T cell lymphoma highlights impacts of genome instability in driving its progression. Genome Med 2024; 16:48. [PMID: 38566223 PMCID: PMC10986005 DOI: 10.1186/s13073-024-01324-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Natural killer/T cell lymphoma (NKTCL) is a clinically and genetically heterogeneous disease with poor prognosis. Genome sequencing and mutation characterization provides a powerful approach for patient stratification, treatment target discovery, and etiology identification. However, previous studies mostly concentrated on base-level mutations in primary NKTCL, whereas the large-scale genomic alterations in NKTCL and the mutational landscapes in relapsed/refractory NKTCL remain largely unexplored. METHODS Here, we assembled whole-genome sequencing and whole-exome sequencing data from 163 patients with primary or relapsed/refractory NKTCL and compared their somatic mutational landscapes at both nucleotide and structure levels. RESULTS Our study not only confirmed previously reported common NKTCL mutational targets like STAT3, TP53, and DDX3X but also unveiled several novel high-frequency mutational targets such as PRDM9, DST, and RBMX. In terms of the overall mutational landscape, we observed striking differences between primary and relapsed/refractory NKTCL patient groups, with the latter exhibits higher levels of tumor mutation burden, copy number variants (CNVs), and structural variants (SVs), indicating a strong signal of genomic instability. Complex structural rearrangements such as chromothripsis and focal amplification are also significantly enriched in relapsed/refractory NKTCL patients, exerting a substantial impact on prognosis. Accordingly, we devised a novel molecular subtyping system (i.e., C0-C4) with distinct prognosis by integrating potential driver mutations at both nucleotide and structural levels, which further provides an informative guidance for novel treatments that target these specific driver mutations and genome instability as a whole. CONCLUSIONS The striking differences underlying the mutational landscapes between the primary and relapsed/refractory NKTCL patients highlight the importance of genomic instability in driving the progression of NKTCL. Our newly proposed molecular subtyping system is valuable in assisting patient stratification and novel treatment design towards a better prognosis in the age of precision medicine.
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Affiliation(s)
- Zegeng Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - He Huang
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Huangming Hong
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China
| | - Huageng Huang
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Huawei Weng
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China
| | - Le Yu
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China
| | - Jian Xiao
- Department of Medical Oncology, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, China
| | - Zhao Wang
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Xiaojie Fang
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Yuyi Yao
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China
| | - Jia-Xing Yue
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
| | - Tongyu Lin
- Department of Medical Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
- Department of Medical Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, 610041, China.
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Wang Z, Luo S, Zhang Z, Zhou T, Zhang J. 4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction. PLoS Comput Biol 2023; 19:e1011722. [PMID: 38109463 PMCID: PMC10760824 DOI: 10.1371/journal.pcbi.1011722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 01/02/2024] [Accepted: 11/28/2023] [Indexed: 12/20/2023] Open
Abstract
Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.
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Affiliation(s)
- Zihao Wang
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Songhao Luo
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Zhenquan Zhang
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Tianshou Zhou
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Jiajun Zhang
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
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