Integration of transcription regulation and functional genomic data reveals lncRNA SNHG6's role in hematopoietic differentiation and leukemia.

IF 9 2区 医学 Q1 CELL BIOLOGY Journal of Biomedical Science Pub Date : 2024-02-28 DOI:10.1186/s12929-024-01015-8
Joshua M Hazan, Raziel Amador, Tahleel Ali-Nasser, Tamar Lahav, Stav Roni Shotan, Miryam Steinberg, Ziv Cohen, Dvir Aran, David Meiri, Yehuda G Assaraf, Roderic Guigó, Assaf C Bester
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Abstract

Background: Long non-coding RNAs (lncRNAs) are pivotal players in cellular processes, and their unique cell-type specific expression patterns render them attractive biomarkers and therapeutic targets. Yet, the functional roles of most lncRNAs remain enigmatic. To address the need to identify new druggable lncRNAs, we developed a comprehensive approach integrating transcription factor binding data with other genetic features to generate a machine learning model, which we have called INFLAMeR (Identifying Novel Functional LncRNAs with Advanced Machine Learning Resources).

Methods: INFLAMeR was trained on high-throughput CRISPR interference (CRISPRi) screens across seven cell lines, and the algorithm was based on 71 genetic features. To validate the predictions, we selected candidate lncRNAs in the human K562 leukemia cell line and determined the impact of their knockdown (KD) on cell proliferation and chemotherapeutic drug response. We further performed transcriptomic analysis for candidate genes. Based on these findings, we assessed the lncRNA small nucleolar RNA host gene 6 (SNHG6) for its role in myeloid differentiation. Finally, we established a mouse K562 leukemia xenograft model to determine whether SNHG6 KD attenuates tumor growth in vivo.

Results: The INFLAMeR model successfully reconstituted CRISPRi screening data and predicted functional lncRNAs that were previously overlooked. Intensive cell-based and transcriptomic validation of nearly fifty genes in K562 revealed cell type-specific functionality for 85% of the predicted lncRNAs. In this respect, our cell-based and transcriptomic analyses predicted a role for SNHG6 in hematopoiesis and leukemia. Consistent with its predicted role in hematopoietic differentiation, SNHG6 transcription is regulated by hematopoiesis-associated transcription factors. SNHG6 KD reduced the proliferation of leukemia cells and sensitized them to differentiation. Treatment of K562 leukemic cells with hemin and PMA, respectively, demonstrated that SNHG6 inhibits red blood cell differentiation but strongly promotes megakaryocyte differentiation. Using a xenograft mouse model, we demonstrate that SNHG6 KD attenuated tumor growth in vivo.

Conclusions: Our approach not only improved the identification and characterization of functional lncRNAs through genomic approaches in a cell type-specific manner, but also identified new lncRNAs with roles in hematopoiesis and leukemia. Such approaches can be readily applied to identify novel targets for precision medicine.

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转录调控和功能基因组数据的整合揭示了 lncRNA SNHG6 在造血分化和白血病中的作用。
背景:长非编码 RNA(lncRNA)是细胞过程中的关键角色,其独特的细胞类型特异性表达模式使其成为具有吸引力的生物标记物和治疗靶标。然而,大多数 lncRNA 的功能作用仍然是个谜。为了满足识别新的可药用lncRNAs的需求,我们开发了一种综合方法,将转录因子结合数据与其他遗传特征整合在一起,生成一个机器学习模型,我们称之为INFLAMeR(利用先进的机器学习资源识别新型功能性lncRNAs):INFLAMeR是在七个细胞系的高通量CRISPR干扰(CRISPRi)筛选中训练出来的,该算法基于71个遗传特征。为了验证预测结果,我们在人类 K562 白血病细胞系中选择了候选 lncRNA,并确定了它们的基因敲除(KD)对细胞增殖和化疗药物反应的影响。我们进一步对候选基因进行了转录组分析。基于这些发现,我们评估了 lncRNA 小核 RNA 宿主基因 6(SNHG6)在髓样细胞分化中的作用。最后,我们建立了小鼠K562白血病异种移植模型,以确定SNHG6 KD是否能抑制体内肿瘤的生长:INFLAMeR模型成功地重建了CRISPRi筛选数据,并预测了之前被忽视的功能性lncRNA。对 K562 中的近 50 个基因进行了深入的细胞学和转录组学验证,发现 85% 预测的 lncRNA 具有细胞类型特异性功能。在这方面,我们基于细胞和转录组的分析预测了 SNHG6 在造血和白血病中的作用。与预测的造血分化作用相一致,SNHG6 的转录受造血相关转录因子的调控。SNHG6 KD可减少白血病细胞的增殖,并使其对分化敏感。用hemin和PMA分别处理K562白血病细胞,结果表明SNHG6抑制红细胞分化,但强烈促进巨核细胞分化。我们利用异种移植小鼠模型证明,SNHG6 KD抑制了体内肿瘤的生长:我们的方法不仅通过基因组学方法以细胞类型特异性的方式改进了功能性lncRNA的鉴定和表征,而且还发现了在造血和白血病中发挥作用的新lncRNA。这种方法可用于识别精准医疗的新靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Biomedical Science
Journal of Biomedical Science 医学-医学:研究与实验
CiteScore
18.50
自引率
0.90%
发文量
95
审稿时长
1 months
期刊介绍: The Journal of Biomedical Science is an open access, peer-reviewed journal that focuses on fundamental and molecular aspects of basic medical sciences. It emphasizes molecular studies of biomedical problems and mechanisms. The National Science and Technology Council (NSTC), Taiwan supports the journal and covers the publication costs for accepted articles. The journal aims to provide an international platform for interdisciplinary discussions and contribute to the advancement of medicine. It benefits both readers and authors by accelerating the dissemination of research information and providing maximum access to scholarly communication. All articles published in the Journal of Biomedical Science are included in various databases such as Biological Abstracts, BIOSIS, CABI, CAS, Citebase, Current contents, DOAJ, Embase, EmBiology, and Global Health, among others.
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