PO.TB05.01 · 肿瘤生物学
婴儿KMT2A::AFF1急性淋巴细胞白血病干细胞模型揭示对蛋白质组的早期影响
Infant KMT2A::AFF1 acute lymphoblastic leukemia stem cell model reveals early impact on the proteome
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
急性淋巴细胞白血病婴儿（iALL）尽管接受强化治疗，仍面临早期复发、快速进展和生存不良的高风险。KMT2A重排（KMT2A-r）是这些病例的既定特征，可产生一种融合癌基因，导致表观基因组失调。基因组研究未能发现协同致癌驱动因素，以解释为何与携带相同重排的年长患者相比，婴儿的复发风险如此之高。为拓展我们对KMT2A驱动的白血病发生的理解，我们应用全局蛋白质组学分析，以识别可能提供新型治疗靶点的非基因组驱动因素。在本研究中，我们使用KMT2A-r iALL的人诱导多能干细胞模型（iPSC）进行蛋白质组学研究。我们采用一个已确立的多西环素（dox）调控平台，将人KMT2A-r转基因构建体（与最常见的伙伴AFF1重排）整合到该模型中进行了工程改造。这些细胞仅在dox处理的响应下才紧密表达KMT2A::AFF1转基因。我们已开发出功能性造血干细胞（HSPC），并用dox诱导其表达KMT2A-r，代表白血病前期状态。使用dox诱导的KMT2A::AFF1 HSPC及未加dox对照的重复样本，我们通过数据非依赖采集（DIA）在timsTOF HT（Bruker）上生成蛋白质组谱。数据在DIA-NN中使用Bruker谱库和于2024年5月5日从Uniprot下载的人类蛋白数据库进行检索。数据分析在R 4.3.3中进行，包括使用limma 3.58.1的差异表达分析、使用gProfiler 0.2.3的通路富集分析，以及使用STRING 12.0的网络分析。差异表达分析鉴定出，与对照相比，KMT2A-r HSPC中有149个蛋白表达升高、381个蛋白表达降低（p<0.05，|log2FC|>1）。组蛋白结合是显著性最高的蛋白中排名靠前的上调通路（校正后p<0.05），这与表观基因组调控因子的诱导相符合。在KMT2A-r HSPC中下调的通路主要涉及细胞外环境（例如，细胞黏附介导活性、胶原结合、细胞外基质组织）。对下调蛋白的STRING分析同样显示细胞外因子的突出地位（即MFAP4、L1CAM、COL5A1）。与该模型同一时间点的批量RNA测序进行比较，显示蛋白表达与基因表达约有一半时间相关。磷酸化蛋白质组学已完成，目前正在分析以作进一步比较。白血病前期的KMT2A-r HSPC表现出蛋白质组的早期变化，提示细胞外环境可能在白血病发生中发挥关键作用。通过对这些因子的进一步验证和测试，我们将致力于识别可能为这一毁灭性疾病提供新治疗靶点的关键驱动因素。
查看英文原文 English abstract
Infants with acute lymphoblastic leukemia (iALL) are at high risk of early relapse, rapid progression, and poor survival despite intensive therapies. Rearrangement of KMT2A ( KMT2A -r) is an established feature of these cases, creating a fusion oncogene that leads to epigenomic dysregulation. Genomic studies have failed to find collaborating oncogenic drivers that would explain why infants have such a high risk of relapse compared to older patients with the same rearrangement. To expand our understanding of KMT2A - driven leukemogenesis, we applied global proteomic profiling to identify potential nongenomic drivers that could provide novel therapeutic targets.For this study, we performed proteomics with our human inducible pluripotent stem cell model (iPSC) of KMT2A- r iALL. We have engineered this model with a human KMT2A- r transgene construct (rearranged with the most common partner AFF1 ) incorporated with an established doxycycline (dox) regulated platform. These cells tightly express the KMT2A::AFF1 transgene only in response to dox treatment. We have developed functional hematopoietic stem cells (HSPC) that we have induced with dox to express KMT2A- r and represent the preleukemic state. With replicates of dox-induced KMT2A::AFF1 HSPC and of non-dox control, we generated proteomic profiles via data independent acquisition (DIA) using the timsTOF HT (Bruker). Data were searched in DIA-NN using the Bruker spectral library and human protein database downloaded from Uniprot on 05-05-2024. Data analysis was performed in R 4.3.3 including differential expression analysis using limma 3.58.1, pathway enrichment using gProfiler 0.2.3, and network analysis using STRING 12.0.Differential expression analysis identified 149 proteins with higher and 381 proteins with lower expression in KMT2A- r HSPC as compared to the control (p <0.05, |log2FC| >1). Histone binding is a top upregulated pathway of proteins with the most significance (adjusted p <0.05), which is what we would expect with induction of a epigenomic regulator. Pathways downregulated in KMT2A- r HSPC largely involve the extracellular environment (for example, cell adhesion mediator activity, collagen binding, extracellular matrix organization). STRING analysis of the downregulated proteins also demonstrates a prominence of extracellular factors (i.e. MFAP4, L1CAM, COL5A1). Comparison to bulk RNA sequencing on the model at the same timepoint reveals protein expression correlates with gene expression about half of the time. Phosphoproteomics has been performed and is currently being analyzed for further comparison. Preleukemic KMT2A- r HSPC demonstrate early changes in the proteome that suggest the extracellular environment may play a key role in leukemogenesis. With further validation and testing of these factors, we will aim to identify essential drivers that may provide new therapeutic targets for this devastating disease.
利益披露 Disclosure
A. Prosser-Dombrowski, None..
P. Prem Kumar, None.