Functional Classification of TP53 Mutations in Acute Myeloid Leukemia

Abstract

In more than 50% of human cancers, somatically acquired aberrations of the tumor suppressor gene TP53 are encountered. Approx. 10% of patients with acute myeloid leukemia (AML) reveal TP53 mutations with higher incidences in therapy-related subtypes and erythroleukemias. These mutations are regarded early events of leukemogenesis. In contrast to mere deletions at the TP53 locus, TP53 mutations confer an exceedingly adverse prognosis in AML even when occurring at a subclonal level. However whether different TP53 mutations in AML exhibit a different functional impact on disease progression or outcome remains unknown. In the present study, we have investigated this issue using four TP53 specific, functional scoring systems in a large cohort of patients of the German-Austrian AML study group (AMLSG). The AMLSG cohort consisted of a total of 1537 patients with newly diagnosed AML who were intensively treated within three multicenter, clinical trials. A total of 108 TP53 mutations were detected in 98 patients using targeted amplicon sequencing - 88 (81.4%) missense, 8 (7.4%) nonsense and 6 (5.6%) splice site mutations as well as 6 small insertions and deletions. For each of the four functional TP53 scores, we have assessed their impact on overall survival (OS) and event-free survival (EFS). First, we compared the impact of TP53 missense mutations in 84 patients with all other types of mutations (n= 14). In a next approach, TP53 mutations were grouped into disruptive (n=42) and non-disruptive (n=56) ones, based on the impact of the particular mutations on the protein structure predicted from the crystal structure of p53-DNA complexes (Poeta et al. New Engl J Med 2007). We then classified missense TP53 mutations (n=84) based on their "Evolutionary Action Scores (EAp53)" (Neskey et al. Cancer Res 2015). This algorithm takes evolutionary sensitivity and amino acid conservation into account and scores missense TP53 mutations from 0 to 100. Mutations with the high EAp53 score are considered high risk whereas wild type TP53 has an EAp53 score of zero. We extracted the EAp53 score of those AMLSG patients showing missense mutations from the respective server (http://mammoth.bcm.tmc.edu/EAp53) and used the threshold of 75 from the initial publication to divide the patients into low-risk (<75, n=49) and high-risk groups (≥75, n=35). However, with these three functional scoring systems, no difference regarding OS and EFS could be shown between the mutational groups. The "Relative Fitness Score (RFS)" was recently developed for the TP53 DNA binding domain (DBD) mutants as an indicator of their functional impact (Kotlar et al. Molecular Cell 2018). A catalogue of 9833 TP53 DBD mutants were generated and their selective growth was assessed in p53 null cancer cell lines. The RFS score for each mutant is the median of its relative enrichment or depletion in culture, calculated at 3 time points and depicted as a log (base 2) value. A high RFS indicates selective growth of the mutant corresponding to its higher fitness. We extracted the RFS for the TP53 DBD mutations of the AMLSG cohort (n=83) using the online data resource (GSE115072) and performed a receiver-operating characteristics (ROC) analysis to calculate the optimal threshold of RFS separating deceased from survivors most efficiently. Thereby, the best RFS cut-off value according to the Youden index was -0.135. Applying this threshold (low-risk RFS ≤ -0.135, n=25; high-risk RFS > -0.135, n= 58) we demonstrated a significantly better OS (P=0.009) and EFS (P=0.037) for patients with a low-risk RFS in multivariable analyses adjusting for age, white blood cell count, cytogenetics and type of AML. Using the AML-specific TP53 RFS score, we could show that more than 30% of patients with TP53 mutations (25/83) reveal a significantly better survival indicating that this score is of prognostic value. Based on these findings, we propose that - along with clinical parameters - RFS values of TP53 mutations should also be considered for a comprehensive risk assessment of TP53 mutated AML patients. Disclosures Zebisch: Celgene: Honoraria; Novartis: Honoraria, Other: Advisory board; AbbVie: Other: Advisory board; Roche: Honoraria. Bullinger:Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Daiichi Sankyo: Honoraria; Gilead: Honoraria; Hexal: Honoraria; Menarini: Honoraria; Novartis: Honoraria; Astellas: Honoraria; Pfizer: Honoraria; Sanofi: Honoraria; Seattle Genetics: Honoraria; Bayer: Other: Financing of scientific research; Abbvie: Honoraria; Amgen: Honoraria; Janssen: Honoraria; Jazz Pharmaceuticals: Honoraria. Döhner:Daiichi: Honoraria; Jazz: Honoraria; Novartis: Honoraria; Celgene: Honoraria; Janssen: Honoraria; CTI Biopharma: Consultancy, Honoraria. Sill:Novartis: Other: Advisory board; AbbVie: Other: Advisory board; Astellas: Other: Advisory board; Astex: Other: Advisory board.