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Kinobead Profiling Reveals Reprogramming of B-cell Receptor Signaling in Response to Therapy Within Primary Chronic Lymphocytic Leukemia Cells.
bioRxiv - Cancer Biology Pub Date : 2020-06-04 , DOI: 10.1101/841312
Adam J Linley , Laura Karydis , Anil Mondru , Annalisa D'Avola , Silvia Cicconi , Rebecca Griffin , Francesco Forconi , Andrew R Pettitt , Nagesh Kalakonda , Andy Rawstron , Peter Hillmen , Andrew J Steele , David J MacEwan , Graham Packham , Ian Prior , Joseph Slupsky

Signaling via the B-cell receptor (BCR) is critical for driving CLL pathobiology, promoting both malignant cell survival and disease progression. However, understanding of this pathway is limited, particularly in relation to potential changes in response to therapy. Here, we describe a kinobead-based protocol, used in conjunction with mass-spectrometry to study surface-IgM signaling in primary CLL cells. We identified a fingerprint of over 30 kinases which displayed unique, patient specific response following sIgM stimulation. Matched analysis of CLL cells in samples taken from clinical trials showed that BCR-induced kinome responses altered between baseline and disease progression in patients who relapsed from chemoimmunotherapy. Moreover, adaptive changes to BCR signaling were also observed in CLL cells from clinical trial patients receiving ibrutinib; longitudinal profiling revealed increased signaling despite BTK inhibition. Collectively, these data comprise the first comprehensive investigation into BCR signaling response within CLL where kinobead profiling reveals unique evidence of adaptive reprogramming in response to therapy.

中文翻译:

Kinobead分析揭示了对原发性慢性淋巴细胞白血病细胞内治疗反应的B细胞受体信号重编程。

通过B细胞受体(BCR)发出的信号对于推动CLL病理生物学,促进恶性细胞存活和疾病进展至关重要。但是,对该途径的理解是有限的,特别是在对治疗反应的潜在变化方面。在这里,我们描述了一种基于kinobead的协议,该协议与质谱结合使用以研究原代CLL细胞中的表面IgM信号传导。我们鉴定了超过30种激酶的指纹图谱,这些指纹图谱在sIgM刺激后显示出独特的患者特异性反应。从临床试验样本中对CLL细胞进行的匹配分析表明,在化学免疫疗法复发的患者中,BCR诱导的激酶反应在基线和疾病进展之间改变。此外,在接受依鲁替尼的临床试验患者的CLL细胞中也观察到了BCR信号的适应性改变。纵断面分析显示,尽管有BTK抑制,信号传导仍增加。总的来说,这些数据是对CLL内BCR信号反应的首次全面调查,其中,kinobead分析显示了针对治疗的适应性重编程的独特证据。
更新日期:2020-06-04
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