Johnson Benny, Cooke Laurence, Mahadevan Daruka
Division of Medical Oncology, Mayo Clinic, Rochester, MN, 55905, USA.
The University of Arizona Cancer Center, Tucson, AZ 85719, USA.
J Gastrointest Oncol. 2017 Feb;8(1):20-31. doi: 10.21037/jgo.2016.09.05.
In the management of metastatic colorectal cancer (mCRC), , and mutational status individualizes therapeutic options and identify a cohort of patients (pts) with an aggressive clinical course. We hypothesized that relapsed and refractory mCRC pts develop unique mutational signatures that may guide therapy, predict for a response and highlight key signaling pathways important for clinical decision making.
Relapsed and refractory mCRC pts (N=32) were molecularly profiled utilizing commercially available next generation sequencing (NGS) platforms. Web-based bioinformatics tools (Reactome/Enrichr) were utilized to elucidate mutational profile linked pathways-networks that have the potential to guide therapy.
Pts had progressed on fluoropyrimidines, oxaliplatin, irinotecan, bevacizumab, cetuximab and/or panitumumab. Most common histology was adenocarcinoma (colon N=29; rectal N=3). Of the mutations TP53 was the most common, followed by and . Pts had on average had ≥5 unique mutations. The most frequent activated signaling pathways were: HER2, fibroblast growth factor receptor (FGFR), p38 through BRAF-MEK cascade via RIT and RIN, ARMS-mediated activation of MAPK cascade, and VEGFR2.
Dominant driver oncogene mutations do not always equate to oncogenic dependence, hence understanding pathogenic 'interactome(s)' in individual pts is key to both clinically relevant targets and in choosing the next best therapy. Mutational signatures derived from corresponding 'pathway-networks' represent a meaningful tool to (I) evaluate functional investigation in the laboratory; (II) predict response to drug therapy; and (III) guide rational drug combinations in relapsed and refractory mCRC pts.
在转移性结直肠癌(mCRC)的管理中, 、 和 突变状态可使治疗方案个体化,并识别出具有侵袭性临床病程的患者队列。我们假设复发和难治性mCRC患者会形成独特的突变特征,这可能指导治疗、预测反应并突出对临床决策重要的关键信号通路。
利用市售的下一代测序(NGS)平台对复发和难治性mCRC患者(N = 32)进行分子分析。利用基于网络的生物信息学工具(Reactome/Enrichr)来阐明与突变谱相关的、有可能指导治疗的通路网络。
患者在氟嘧啶、奥沙利铂、伊立替康、贝伐单抗、西妥昔单抗和/或帕尼单抗治疗后病情进展。最常见的组织学类型是腺癌(结肠N = 29;直肠N = 3)。在这些突变中,TP53是最常见的,其次是 和 。患者平均有≥5个独特的突变。最常激活的信号通路是:HER2、成纤维细胞生长因子受体(FGFR)、通过RIT和RIN经BRAF - MEK级联激活的p38、ARMS介导的MAPK级联激活以及VEGFR2。
主要驱动癌基因突变并不总是等同于致癌依赖性,因此了解个体患者中的致病“相互作用组”对于临床相关靶点和选择下一个最佳治疗方法都至关重要。源自相应“通路网络”的突变特征是一种有意义的工具,可用于(I)评估实验室中的功能研究;(II)预测对药物治疗的反应;以及(III)指导复发和难治性mCRC患者的合理联合用药。