Liu Zhichao, Chen Xi, Roberts Ruth, Huang Ruili, Mikailov Mike, Tong Weida
Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, United States.
ApconiX, BioHub at Alderley Park, Alderley Edge, United Kingdom.
Front Pharmacol. 2021 Apr 23;12:608778. doi: 10.3389/fphar.2021.608778. eCollection 2021.
High-risk neuroblastoma (NB) remains a significant therapeutic challenge facing current pediatric oncology patients. Structural variants such as gene fusions have shown an initial promise in enhancing mechanistic understanding of NB and improving survival rates. In this study, we performed a comprehensive investigation on the translational ability of gene fusions for patient stratification and treatment development for high-risk NB patients. Specifically, three state-of-the-art gene fusion detection algorithms, including ChimeraScan, SOAPfuse, and TopHat-Fusion, were employed to identify the fusion transcripts in a RNA-seq data set of 498 neuroblastoma patients. Then, the 176 high-risk patients were further stratified into four different subgroups based on gene fusion profiles. Furthermore, Kaplan-Meier survival analysis was performed, and differentially expressed genes (DEGs) for the redefined high-risk group were extracted and functionally analyzed. Finally, repositioning candidates were enriched in each patient subgroup with drug transcriptomic profiles from the LINCS L1000 Connectivity Map. We found the number of identified gene fusions was increased from clinical the low-risk stage to the high-risk stage. Although the technical concordance of fusion detection algorithms was suboptimal, they have a similar biological relevance concerning perturbed pathways and regulated DEGs. The gene fusion profiles could be utilized to redefine high-risk patient subgroups with significant onset age of NB, which yielded the improved survival curves (Log-rank value ≤ 0.05). Out of 48 enriched repositioning candidates, 45 (93.8%) have antitumor potency, and 24 (50%) were confirmed with either on-going clinical trials or literature reports. The gene fusion profiles have a discrimination power for redefining patient subgroups in high-risk NB and facilitate precision medicine-based drug repositioning implementation.
高危神经母细胞瘤（NB）仍然是当前儿科肿瘤患者面临的重大治疗挑战。基因融合等结构变异在增强对NB的机制理解和提高生存率方面已初显成效。在本研究中，我们对基因融合在高危NB患者分层和治疗开发中的转化能力进行了全面调查。具体而言，我们采用了三种最先进的基因融合检测算法，包括ChimeraScan、SOAPfuse和TopHat-Fusion，来识别498例神经母细胞瘤患者RNA测序数据集中的融合转录本。然后，根据基因融合谱将176例高危患者进一步分为四个不同亚组。此外，进行了Kaplan-Meier生存分析，提取并对重新定义的高危组中的差异表达基因（DEG）进行了功能分析。最后，利用来自LINCS L1000连接图谱的药物转录组谱在每个患者亚组中富集重新定位的候选药物。我们发现，从临床低危阶段到高危阶段，鉴定出的基因融合数量有所增加。尽管融合检测算法的技术一致性并不理想，但它们在涉及扰动途径和调控的DEG方面具有相似的生物学相关性。基因融合谱可用于重新定义具有显著NB发病年龄的高危患者亚组，从而产生改善的生存曲线（对数秩检验值≤0.05）。在48个富集的重新定位候选药物中，45个（93.8%）具有抗肿瘤效力，其中24个（50%）已在正在进行的临床试验或文献报道中得到证实。基因融合谱在重新定义高危NB患者亚组方面具有鉴别能力，并有助于基于精准医学的药物重新定位实施。
