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人类白血病转录谱及数据资源全景图。

A comprehensive landscape of transcription profiles and data resources for human leukemia.

机构信息

Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China.

Department of Dermatology, Xiangya Hospital, Central South University, Changsha, People's Republic of China.

出版信息

Blood Adv. 2023 Jul 25;7(14):3435-3449. doi: 10.1182/bloodadvances.2022008410.

Abstract

As a heterogeneous group of hematologic malignancies, leukemia has been widely studied at the transcriptome level. However, a comprehensive transcriptomic landscape and resources for different leukemia subtypes are lacking. Thus, in this study, we integrated the RNA sequencing data sets of >3000 samples from 14 leukemia subtypes and 53 related cell lines via a unified analysis pipeline. We depicted the corresponding transcriptomic landscape and developed a user-friendly data portal LeukemiaDB. LeukemiaDB was designed with 5 main modules: protein-coding gene, long noncoding RNA (lncRNA), circular RNA, alternative splicing, and fusion gene modules. In LeukemiaDB, users can search and browse the expression level, regulatory modules, and molecular information across leukemia subtypes or cell lines. In addition, a comprehensive analysis of data in LeukemiaDB demonstrates that (1) different leukemia subtypes or cell lines have similar expression distribution of the protein-coding gene and lncRNA; (2) some alternative splicing events are shared among nearly all leukemia subtypes, for example, MYL6 in A3SS, MYB in A5SS, HMBS in retained intron, GTPBP10 in mutually exclusive exons, and POLL in skipped exon; (3) some leukemia-specific protein-coding genes, for example, ABCA6, ARHGAP44, WNT3, and BLACE, and fusion genes, for example, BCR-ABL1 and KMT2A-AFF1 are involved in leukemogenesis; (4) some highly correlated regulatory modules were also identified in different leukemia subtypes, for example, the HOXA9 module in acute myeloid leukemia and the NOTCH1 module in T-cell acute lymphoblastic leukemia. In summary, the developed LeukemiaDB provides valuable insights into oncogenesis and progression of leukemia and, to the best of our knowledge, is the most comprehensive transcriptome resource of human leukemia available to the research community.

摘要

作为一组异质性的血液系统恶性肿瘤,白血病在转录组水平已得到广泛研究。然而,不同白血病亚型的综合转录组图谱和资源仍然缺乏。因此,在本研究中,我们通过统一的分析流程整合了来自 14 种白血病亚型和 53 种相关细胞系的 >3000 个样本的 RNA 测序数据集。我们描绘了相应的转录组图谱,并开发了一个用户友好的数据门户 LeukemiaDB。LeukemiaDB 设计有 5 个主要模块:编码蛋白基因、长非编码 RNA(lncRNA)、环状 RNA、可变剪接和融合基因模块。在 LeukemiaDB 中,用户可以搜索和浏览不同白血病亚型或细胞系的表达水平、调控模块和分子信息。此外,对 LeukemiaDB 中的数据进行全面分析表明:(1)不同的白血病亚型或细胞系具有相似的编码蛋白基因和 lncRNA 的表达分布;(2)一些可变剪接事件在几乎所有白血病亚型中都有共享,例如 MYL6 在 A3SS、MYB 在 A5SS、HMBS 在内含子保留、GTPBP10 在互斥外显子和 POLL 在跳过外显子;(3)一些白血病特异性的编码蛋白基因,例如 ABCA6、ARHGAP44、WNT3 和 BLACE,以及融合基因,例如 BCR-ABL1 和 KMT2A-AFF1,参与白血病的发生;(4)在不同的白血病亚型中也鉴定到了一些高度相关的调控模块,例如急性髓系白血病中的 HOXA9 模块和 T 细胞急性淋巴细胞白血病中的 NOTCH1 模块。总之,开发的 LeukemiaDB 为白血病的发生和进展提供了有价值的见解,据我们所知,这是研究界可获得的最全面的人类白血病转录组资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/575a/10362280/f6e7e0110ccf/BLOODA_ADV-2022-008410-fx1.jpg

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