Abstract P34: Bayesian networks modeling identifies a reliance of TP53 mutant AML on NF kappa B signaling

IF 11.5 Q1 HEMATOLOGY Blood Cancer Discovery Pub Date : 2024-03-04 DOI:10.1158/2643-3249.bcdsymp24-p34
Daniel Chang, Klara E Noble-Orcutt, Marie L Antony, Yoonkyu Lee, Fiona He, Karen Sachs, Chad L Myers, Z. Sachs
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引用次数: 0

Abstract

In acute myeloid leukemia (AML), TP53 mutations ( TP53Mut ) confer the worst prognosis. Leukemia stem cells (LSCs) are rare AML cells endowed with self-renewal capacity, allowing them to recapitulate leukemia after therapy and cause disease progression. In human AML, signaling pathways associated with inflammation have been implicated in the pathogenesis of TP53Mut AML, but the pathways that mediate self-renewal in human TP53Mut AML are not well-known. To define the signaling pathways that are activated in TP53Mut human LSCs, we used CyTOF, a form of flow cytometry that can measure up to 40 proteins simultaneously at single-cell resolution. We compared the levels of activated signaling molecules in the LSC-enriched (CD34+CD38−) subset of seven TP53Mut and seven TP53 wild-type ( TP53WT ) AML samples. Phosphorylated NF kappa B (pNFkB), pSTAT1, and pP38 are significantly higher in TP53Mut AMLs. In contrast, Ki67 and pMAPKAPKII are higher in TP53WT AML. These data demonstrate a unique signaling activation state in TP53Mut AML. The influence of signaling molecules on downstream targets can vary by cellular context. Therefore, we asked whether the influence and interaction of the activated signaling molecules vary between TP53Mut and TP53WT LSCs. To model the signaling architecture, we performed Bayesian networks modeling, a machine learning algorithm that has been validated as a method to discover statistical correlations and dependencies between signaling molecules. We found a similar global signaling network structure and hierarchy in TP53Mut and TP53WT AMLs. However, TP53Mut model showed NFkB have strong influences on phosphorylated Histone H3 (pHIS3) and Ki67, suggesting that proliferation depends on NFkB levels in TP53Mut LSCs. Furthermore, NFkB levels were highly dependent on pSTAT1 in TP53Mut LSCs. Next, we compared the transcriptional profiles of TP53Mut and TP53WT samples in the BEAT AML dataset and found that TP53Mut AML displayed significant enrichment of all the NFkB gene sets (n=19) in the molecular signatures database, providing more evidence for a unique reliance of TP53Mut human AML on NFkB signaling. Therefore, we used lentivirus transduced shRNA constructs to determine the influence of mutant p53 on signaling in human AML. We found that knockdown of TP53Mut reduced NFkB protein levels in Kasumi AML cells (which are TP53R248Q/ − ) but not in MOLM13 AML cells (which are TP53WT). RNA sequencing of transduced Kasumi cells showed that TP53Mut knockdown led to loss of NFkB and LSC self-renewal signatures. Knockdown of TP53Mut in primary human TP53Mut AMLs (S127F/- and S241Y/-) led to a similar loss of NFkB and LSC signatures in these primary samples as well. Colony formation in Kasumi cells and TP53Mut primary human AML were also abrogated after TP53Mut knockdown. These data show TP53Mut promotes NFkB activation in human AML and suggests that human TP53Mut LSCs may be dependent on NFkB for self-renewal. These data implicate NFkB as a possible therapeutic strategy to target TP53Mut human LSCs. Citation Format: Daniel Chang, Klara Noble-Orcutt, Marie Lue Antony, Yoonkyu Lee, Fiona He, Karen Sachs, Chad L Myers, Zohar Sachs. Bayesian networks modeling identifies a reliance of TP53 mutant AML on NF kappa B signaling [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P34.
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摘要 P34:贝叶斯网络建模确定了 TP53 突变型 AML 对 NF kappa B 信号的依赖性
在急性髓性白血病(AML)中,TP53突变(TP53Mut)的预后最差。白血病干细胞(LSCs)是罕见的急性髓性白血病细胞,具有自我更新能力,可在治疗后再现白血病并导致疾病进展。在人类急性髓细胞性白血病中,与炎症相关的信号通路被认为与TP53Mut急性髓细胞性白血病的发病机制有关,但介导人类TP53Mut急性髓细胞性白血病自我更新的通路却不为人所知。为了确定在 TP53Mut 人类 LSCs 中被激活的信号通路,我们使用了 CyTOF,这是一种流式细胞术,能以单细胞分辨率同时测量多达 40 种蛋白质。我们比较了 7 个 TP53Mut 和 7 个 TP53 野生型(TP53WT)AML 样本的 LSC 富集(CD34+CD38-)亚组中活化信号分子的水平。在 TP53Mut AMLs 中,磷酸化 NF kappa B(pNFkB)、pSTAT1 和 pP38 明显升高。相比之下,TP53WT AML 中的 Ki67 和 pMAPKAPKII 则更高。这些数据证明了 TP53Mut AML 独特的信号激活状态。信号分子对下游靶点的影响可能因细胞环境而异。因此,我们想知道在 TP53Mut 和 TP53WT LSCs 之间,被激活的信号分子的影响和相互作用是否有所不同。为了建立信号结构模型,我们采用了贝叶斯网络建模,这是一种机器学习算法,已被证实是一种发现信号分子间统计相关性和依赖性的方法。我们在 TP53Mut 和 TP53WT AMLs 中发现了相似的全局信号网络结构和层次。然而,TP53Mut模型显示NFkB对磷酸化组蛋白H3(pHIS3)和Ki67有很大的影响,这表明TP53Mut LSCs的增殖依赖于NFkB水平。此外,TP53Mut LSCs 中的 NFkB 水平高度依赖 pSTAT1。接下来,我们比较了 BEAT AML 数据集中 TP53Mut 和 TP53WT 样本的转录谱,发现 TP53Mut AML 显示出分子特征数据库中所有 NFkB 基因组(n=19)的显著富集,为 TP53Mut 人类 AML 对 NFkB 信号的独特依赖提供了更多证据。因此,我们使用慢病毒转导的 shRNA 构建物来确定突变 p53 对人类 AML 信号转导的影响。我们发现,敲除 TP53Mut 能降低 Kasumi AML 细胞(TP53R248Q/-)的 NFkB 蛋白水平,但不能降低 MOLM13 AML 细胞(TP53WT)的 NFkB 蛋白水平。转导的 Kasumi 细胞的 RNA 测序显示,TP53Mut 基因敲除导致 NFkB 和 LSC 自我更新特征丧失。在原代人类 TP53Mut AMLs(S127F/- 和 S241Y/-)中敲除 TP53Mut 也会导致这些原代样本中 NFkB 和 LSC 特征的类似丧失。TP53Mut基因敲除后,Kasumi细胞和TP53Mut原代人类AML的集落形成也会减弱。这些数据显示 TP53Mut 促进了人类 AML 中 NFkB 的激活,并表明人类 TP53Mut LSCs 的自我更新可能依赖于 NFkB。这些数据表明,NFkB可能是针对TP53Mut人LSCs的一种治疗策略。引用格式:Daniel Chang, Klara Noble-Orcutt, Marie Lue Antony, Yoonkyu Lee, Fiona He, Karen Sachs, Chad L Myers, Zohar Sachs.贝叶斯网络建模确定了 TP53 突变 AML 对 NF kappa B 信号的依赖性 [摘要].在:血癌发现研讨会论文集》,2024 年 3 月 4-6 日,马萨诸塞州波士顿。费城(宾夕法尼亚州):AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P34.
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来源期刊
CiteScore
12.70
自引率
1.80%
发文量
139
期刊介绍: The journal Blood Cancer Discovery publishes high-quality Research Articles and Briefs that focus on major advances in basic, translational, and clinical research of leukemia, lymphoma, myeloma, and associated diseases. The topics covered include molecular and cellular features of pathogenesis, therapy response and relapse, transcriptional circuits, stem cells, differentiation, microenvironment, metabolism, immunity, mutagenesis, and clonal evolution. These subjects are investigated in both animal disease models and high-dimensional clinical data landscapes. The journal also welcomes submissions on new pharmacological, biological, and living cell therapies, as well as new diagnostic tools. They are interested in prognostic, diagnostic, and pharmacodynamic biomarkers, and computational and machine learning approaches to personalized medicine. The scope of submissions ranges from preclinical proof of concept to clinical trials and real-world evidence. Blood Cancer Discovery serves as a forum for diverse ideas that shape future research directions in hematooncology. In addition to Research Articles and Briefs, the journal also publishes Reviews, Perspectives, and Commentaries on topics of broad interest in the field.
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