Home | News | Publications | A new methodology predicts the risk of relapse in patients with acute myeloid leukemia

A new methodology predicts the risk of relapse in patients with acute myeloid leukemia


H12O-CNIO Haematological Malignancies Clinical Research Unit Researchers of the H12O-CNIO Haematological Malignancies Clinical Research Unit that have led the study. /CNIO

With a 5-year survival rate of 40%, one of the challenges of the clinic with patients with acute myeloid leukemia is to know if the cancer treatment has destroyed the tumor cells

The researchers have developed a new protocol that can identify the presence of tumor cells in the organism that are not detected by other methods and thus allowing them to predict the risk of relapse in these patients

The research included the collaboration of more than 10 Spanish hospitals and research centers

The paper is published in Haematologica, one of the most important international hematology journals

The acute myeloid leukemia (AML) is the most common haematological cancer in adults. With a 5-year survival rate of around 40% and 10-year survival rate of 30%, the cure rate of this disease is low compared to other types of leukemia. One of the tools that the researchers of the acute myeloid leukemia are currently trying to establish is a test that would determine whether the treatment has eliminated the disease or not, given that the type of follow-up and the survival rate itself depend greatly if the organism is completely free of tumor cells. Researchers from the H12O-CNIO Haematological Malignancies Clinical Research Unit of the Spanish National Cancer Research Centre (CNIO), which includes professionals from the Hospital Universitario 12 de Octubre, have presented a new methodology that perfectly identifies the tumor cells of the acute myeloid leukemia that are otherwise undetectable and thus predict with high probability the risk of relapse.

The paper has been published in Haematologica, one of the most important journals on hematology.

The new method is based on massive sequencing techniques that read the DNA of the sample cells of the patient in search of the mutations that are sign of the illness. However, to get accurate information from massive sequencing, the researchers first have to determine with utmost rigor the way in which the technique is applied – the optimization of the technique should go through a correct design of the primers, the adjustment of the PCR conditions, library constructions and the specific threshold for the number of reads the sequencer amplifies. That is, to achieve a high sensitivity, researchers have to be very strict with details.

This arduous process of developing the protocol, that has to be fully optimized for each studied mutation, has been conducted by the principal author of the article, Esther Onecha, researcher of the H12O-CNIO Haematological Malignancies Clinical Research Unit.

Currently there are methods that detect the so called minimal residual disease (MRD) – the remaining tumor cells that can persist in the organism after the treatment. But they are either not sensitive enough – a lot of the patients relapse even though the minimal residual disease has not been detected – or they are not specific enough to detect the particular tumor cell.

The new methodology is necessary because there are up to 60% of AML patients that, after the first apparently successful treatment, have a relapse. Rosa María Ayala Díaz, manager of the project, stresses “for these patients, if we want to detect the minimum levels and to be able to treat it successfully, a close follow up of the progression of the disease is crucial”. “This is a much better predicting method than flow cytometry or the classic molecular models in the cases where there is a high risk of relapse. This research has reached a sensitivity of quantification of up to 1 tumor cell among 100,000 healthy cells, a completely novel aspect in massive sequencing techniques”.

In its current state, the new methodology has been clinically validated by tracking the four molecular markers that commonly mutate in acute myeloid leukemia, and that cover together more than 40% of the patients. The researchers validated the technique with more than a hundred samples of 63 patients and indeed managed to detect the minimal residual disease with specific nature and sensitivities that are superior to the other techniques used today. That is, “we have a tool that can guide the optimal therapeutic approach for each patient”, says Onecha.

The next goal is to adapt this technique to the rest of the known mutations in AML that involve more than 30 genes so that it can be used for the vast majority of the patients in molecular monitoring. However, the protocol has already been developed and it will need very few modifications, so “the most difficult work has already been done”, explains Miguel Gallardo, research coordinator at the H12O-CNIO Haematological Malignancies Clinical Research Unit.

Furthermore, the new methodology is also applicable on molecular markers of other types of cancer, so that, according to Gallardo, the work “is a methodological milestone with great potential, so we hope other laboratories will introduce it as well”.

“It is important to emphasize the collaboration between the hospitals and researches involved, which in this case have been more than 10 hospitals and/or research centers that worked hard to complete this project and their collaboration has been crucial for its success”, states Joaquín Martínez-López, Head of the H12O-CNIO Haematological Malignancies Clinical Research Unit, and Head of the Hematology Department of the Hospital 12 de Octubre. The hospitals 12 de Octubre in Madrid, Hospital Santa Creu i Sant Pau in Barcelona and Hospital La Fe in Valencia have been part of this project, among others.

The project has been funded by the Instituto de Salud Carlos III, CRIS Cancer Foundation and the Spanish Ministry of Science, Innovation and Universities.

Reference article

Novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia. Onecha E et al (Haematologica 2018). DOI: 10.3324/haematol.2018.194712

Back to the news