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Classification of gastric cancer by EBV status combined with molecular profiling predicts patient prognosis

机译:通过EBV状态与分子分析相结合的胃癌分类预测患者预后

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Purpose To identify how Epstein‐Barr virus (EBV) status combined with molecular profiling predicts the prognosis of gastric cancer patients and their associated clinical actionable biomarkers. Experimental Design A next‐generation sequencing assay targeting 295 cancer‐related genes was performed in 73 EBV‐associated gastric cancer (EBVaGC) and 75 EBV‐negative gastric cancer (EBVnGC) specimens and these results were compared with overall survival (OS). Results PIK3CA , ARID1A , SMAD4 , and PIK3R1 mutated significantly more frequently in EBVaGC compared with their corresponding mutation rate in EBVnGC. As the most frequently mutated gene in EBVnGC (62.7%), TP53 also displayed a mutation rate of 15.1% in EBVaGC. PIK3R1 was revealed as a novel mutated gene (11.0%) associated almost exclusively with EBVaGC. PIK3CA , SMAD4 , PIK3R1 , and BCOR were revealed to be unique driver genes in EBVaGC. ARID1A displayed a significantly large proportion of inactivated variants in EBVaGC. A notable finding was that integrating the EBV status with tumor mutation burden (TMB) and large genomic instability (LGI) categorized the tumors into four distinct molecular subtypes and optimally predicted patient prognosis. The corresponding median OSs for the EBV+/TMB‐high, EBV+/TMB‐low, EBV‐/LGI‐, and EBV‐/LGI+ subtypes were 96.2, 75.3, 44.4, and 20.2 months, respectively. The different subtypes were significantly segregated according to distinct mutational profiles and pathways. Conclusions Novel mutations in PIK3R1 and TP53 genes, driver genes such as PIK3CA , SMAD4 , PIK3R1 , BCOR , and ARID1A , and distinguished genomic profiles from EBVnGC were identified in EBVaGC tumors. The classification of gastric cancer by EBV, TMB, and LGI could be a good prognostic indicator, and provides distinguishing, targetable markers for treatment.
机译:目的是识别Epstein-Barr病毒(EBV)状态如何结合分子分析预测胃癌患者的预后及其相关的临床可行的生物标志物。实验设计在73个EBV相关的胃癌(EBVAGC)和75个EBV阴性胃癌(EBVNGC)标本中进行靶向295个癌症相关基因的下一代测序测定法,并将这些结果与总存活(OS)进行比较。结果PIK3CA,ARID1A,SMAD4和PIK3R1在EBVNGC中的相应突变率相比,在EBVGC中更频繁地突变。作为EBVNGC中最常见的突变基因(62.7%),TP53在EBVAGC中也显示出15.1%的突变率。 PIK3R1被揭示为几乎完全与EBVAGC相关的新型突变基因(11.0%)。 PIK3CA,SMAD4,PIK3R1和BCOR被揭示为EBVAGC中的独特驾驶员基因。 ARID1A在EBVAGC中显示出显着大比例的灭活变体。值得注意的发现是将EBV状态与肿瘤突变负担(TMB)与大型基因组不稳定性(LGI)分类为四种不同的分子亚型和最佳预测的患者预后。 EBV + / TMB-HIGH,EBV + / TMB-LOW,EBV-/ LGI和EBV-/ LGI +亚型的相应中值分别为96.2,75.3,44.4和20.2个月。根据不同的突变谱和途径,不同的亚型显着分离。结论PIK3R1和TP53基因的新突变,驾驶基因如PIK3CA,SMAD4,PIK3R1,BCOR和ARID1A,以及来自EBVNGC的区分基因组谱系在EBVGC肿瘤中鉴定。通过EBV,TMB和LGI对胃癌的分类可以是良好的预后指示剂,并提供用于治疗的区别,可定位标记。
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