TP53突变(TP53MT)发生在不同的基因组构型中。特别是,双等位基因失活与癌症总体生存率低相关。仅影响一个等位基因的病变可能不会直接引起白血病,在预后不佳的情况下,质疑隐匿性双等位基因亚克隆的存在。
我们已经收集了7400例髓样肿瘤患者的临床和分子数据,并应用了一种新的模型,通过使用基于采样的生存数据回归的统计稳健策略来确定最佳VAF截止值,从而准确地对TP53等位基因构型进行分类并更准确地评估预后。
总的来说,1010例患者中发现TP53MT。按照传统标准,36%的病例被归类为单次命中,而64%的人表现出双重命中基因组配置。使用新开发的分子算法,我们发现579名(57%)患者具有明确的双等位基因,239(24%)可能包含双等位基因,和192(19%)最有可能的单等位基因TP53MT。有趣的是,我们的方法能够将352个传统单发损伤中的192个(54.5%)升级为可能的双等位基因类别.重新分类后建立的基于生存的模型进一步证实了这种分类。在传统上被认为是单等位基因的病例中,具有可能的单等位基因突变的患者的总生存期与野生型患者相似,并且优于具有双等位基因构型的患者.因此,具有某些双等位基因命中的患者,无论疾病亚型(AML或MDS),有类似的预后。当模型应用于外部组群时,观察到类似的结果。此外,单细胞DNA研究揭示了以前认为的单等位基因病例的双等位基因性质。
我们的新方法更准确地解决了TP53基因组结构,并揭示了遗传镶嵌性,可用于临床环境以改善预后评估。
TP53 mutations (TP53MT) occur in diverse genomic configurations. Particularly, biallelic inactivation is associated with poor overall survival in cancer. Lesions affecting only one allele might not be directly leukemogenic, questioning the presence of cryptic biallelic subclones in cases with dismal prognosis.
We have collected clinical and molecular data of 7400 patients with myeloid neoplasms and applied a novel model by identifying an optimal VAF cutoff using a statistically robust strategy of sampling-based regression on survival data to accurately classify the TP53 allelic configuration and assess prognosis more precisely.
Overall, TP53MT were found in 1010 patients. Following the traditional criteria, 36% of the cases were classified as single hits, while 64% exhibited double hits genomic configuration. Using a newly developed molecular algorithm, we found that 579 (57%) patients had unequivocally biallelic, 239 (24%) likely contained biallelic, and 192 (19%) had most likely monoallelic TP53MT. Interestingly, our method was able to upstage 192 out of 352 (54.5%) traditionally single hit lesions into a probable biallelic category. Such classification was further substantiated by a survival-based model built after re-categorization. Among cases traditionally considered monoallelic, the overall survival of those with probable monoallelic mutations was similar to the one of wild-type patients and was better than that of patients with a biallelic configuration. As a result, patients with certain biallelic hits, regardless of the disease subtype (AML or MDS), had a similar prognosis. Similar results were observed when the model was applied to an external cohort. In addition, single-cell DNA studies unveiled the biallelic nature of previously considered monoallelic cases.
Our novel approach more accurately resolves TP53 genomic configuration and uncovers genetic mosaicism for the use in the clinical setting to improve prognostic evaluation.