DNMT3A,   General AML

A clinical measure of DNA methylation predicts outcome in de novo acute myeloid leukemia

The ability to predict therapeutic response is essential for improving care of patients with acute myeloid leukemia (AML).  M.Luskin et al., developed a methylation-based risk score (M-score) for AML using random forest classification and demonstrated the association between M-score and overall survival (OS) on a limited cohort of AML patients.

For this current study M.Luskin et al. of UPENN,  investigated whether the M-score could independently predict clinical outcome in 166 patients from UPENN with de novo AML treated with intensive induction chemotherapy controlling for other prognostic markers. Their findings were published in JCI Insight in June 2016.

Here are the key findings from their study:
  • In response to 1 or 2 cycles of induction chemotherapy, 71% achieved complete remission (CR) and 38% were alive at 2 years 
  • The mean M-score for surviving patients was significantly lower than for deceased patients (81.8; 95% CI, 74.3–89.2, vs. 99.5; 95% CI 93.2–105.8, P=0.0005,.
  • Patients achieving CR also had a lower mean M-score compared with those who failed to achieve CR (86.8; 95% CI, 81.3–92.4, vs. 105.8; 95% CI, 96.5–115.0, P=0.0005).
  • A univariate Cox survival analysis demonstrated that a 10-unit increase in the M-score was associated with a 10% increase in the hazard of death (P <0.0001 and a 20% increase in the odds of failing to achieve CR
  • M-score was associated with cytogenetic risk; those with favorable cytogenetics had a lower mean M-score than both the intermediate and unfavorable cytogenetics (P<0.0001 and P=0.001, respectively)
  • There was no difference in mean M-score between intermediate and unfavorable groups (P1.0).
  • The M-score classifier identified groups with different outcome, regardless of whether patients did or did not receive allogeneic stem cell transplant (log-rank P=0.01 and P<0.00001, respectively).

In summary, this study has demonstrated some promising results regarding the robustness of the M-score as a prognostic tool. As correlations between the median M-score and OS and the median M-score and CR were observed.

Abstract
BACKGROUND

Variable response to chemotherapy in acute myeloid leukemia (AML) represents a major treatment challenge. Clinical and genetic features incompletely predict outcome. The value of clinical epigenetic assays for risk classification has not been extensively explored. We assess the prognostic implications of a clinical assay for multilocus DNA methylation on adult patients with de novo AML.

METHODS

We performed multilocus DNA methylation assessment using xMELP on samples and calculated a methylation statistic (M-score) for 166 patients from UPENN with de novo AML who received induction chemotherapy. The association of M-score with complete remission (CR) and overall survival (OS) was evaluated. The optimal M-score cut-point for identifying groups with differing survival was used to define a binary M-score classifier. This classifier was validated in an independent cohort of 383 patients from the Eastern Cooperative Oncology Group Trial 1900 (E1900; NCT00049517).

RESULTS

A higher mean M-score was associated with death and failure to achieve CR. Multivariable analysis confirmed that a higher M-score was associated with death (P = 0.011) and failure to achieve CR (P = 0.034). Median survival was 26.6 months versus 10.6 months for low and high M-score groups. The ability of the M-score to perform as a classifier was confirmed in patients ≤ 60 years with intermediate cytogenetics and patients who achieved CR, as well as in the E1900 validation cohort.

CONCLUSION

The M-score represents a valid binary prognostic classifier for patients with de novo AML. The xMELP assay and associated M-score can be used for prognosis and should be further investigated for clinical decision making in AML patients.

References
  1. Luskin.M et al., A clinical measure of DNA methylation predicts outcome in de novo acute myeloid leukemia JCI Insight. 2016 Jun 16; 1(9): e87323. DOI: 10.1172/jci.insight.87323.