神经母细胞瘤中MYCN定位稳健性的定量分析
A Quantitative Analysis of Localized Robustness of MYCN in Neuroblastoma
摘要：
基因MYCN（V-myc骨髓细胞瘤病病毒标记癌基因，神经母细胞瘤衍生）的扩增已被充分证明是神经母细胞瘤（一种儿童癌症）预后不良的指标。不幸的是，在了解MYCN在神经母细胞瘤中的功能方面取得的成功有限，更重要的是，鉴于MYCN被认为是不可治愈的，因此有必要潜在地阐明间接靶向MYCN的关键机会。为此，这项工作采用了一种新兴的定量技术，从网络科学，即网络曲率，量化的MYCN及其周围的邻居的生物鲁棒性。特别地，当在IV期癌症中扩增时，MYCN表现出比具有低表达MYCN水平的那些样品更高的曲率（更稳健）。当检查周围的邻域时，上述论点仍然适用于网络曲率，但当仅分析差异表达时则会丢失-这是肿瘤学家和计算/分子生物学家之间的常见技术。这一发现指出了在复杂性和间接细胞信号转导影响的背景下药物靶向的问题（和可能的解决方案），这些问题经常被传统技术所混淆。
英文摘要：
The amplification of the gene MYCN (V-myc myelocytomatosis viral-valeted oncogene, neuroblastoma derived) has been a well-documented indicator for poor prognosis in neuroblastoma, a childhood cancer. Unfortunately, there has been limited success in understanding MYCN functionality in the landscape of neuroblastoma and more importantly, given that MYCN has been deemed undruggable, the need to potentially illuminate key opportunities that indirectly target MYCN is of great interest. To this end, this work employs an emerging quantitative technique from network science, namely network curvature, to quantify the biological robustness of MYCN and its surrounding neighborhood. In particular, when amplified in Stage IV cancer, MYCN exhibits higher curvature (more robust) than those samples with under expressed MYCN levels. When examining the surrounding neighborhood, the above argument still holds for network curvature, but is lost when only analyzing differential expression - a common technique amongst oncologists and computational/molecular biologists. This finding points to the problem (and possible solution) of drug targeting in the context of complexity and indirect cell signaling affects that have often been obfuscated through traditional techniques.
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