MLL at the 64th ASH Annual Meeting & Exposition – a Follow-Up Report

The 64th Annual Meeting & Exposition of the American Society of Hematology was held from December 10-13 in New Orleans this year.

MLL participated with 20 contributions, consisting of talks and poster presentations and covering the following topics:

In this article, we will be presenting the research projects that we had the pleasure of presenting at the ASH conference. The MLL presentations covered a wide range of hematology topics – from classification and genetics to prognostics and artificial intelligence. In addition, we were also there with many poster presentations. If you would like to read in more in-depth about them – and about our talks – you will find more information about all of this year’s contributions at the end of this article.

Genetics as the Mainstay of New Classifications

The year 2022 has brought major changes to hemato-oncology – first and foremost, the new classification of the World Health Organization (WHO). Moreover, the “international consensus classification” appeared as well, which raised the question: Does the parallel use of two classifications make diagnosis more difficult for physicians and patients? This question is addressed by Huber et al. using the examples of AML and MDS who also elaborated differences and similarities between the WHO and ICC classifications. What both have in common is that genetics plays a solid supporting role and genetics-based definitions are gaining in importance. However, the fact that the search for the best possible classification is never over is illustrated by the project of Haferlach et al. For example, according to the WHO and ICC, while cytomorphology is essential for diagnosing MDS, this method – unlike genetics – naturally involves a certain amount of subjectivity. As shown by the results of Haferlach et al., however, a purely genetic classification of MDS would be readily feasible and also of clinical relevance.

Genetics Improves Prognosis

This year’s publication of the “Molecular International Prognostic Scoring System” (IPSS-M) represents an important innovation in assessing the prognosis for MDS (Bernard et al. NEJM 2022). By taking molecular genetic information into account, the IPSS-M improves on the IPSS-R prognostic score established for MDS. The predictive superiority of the IPSS-M over the IPSS-R is validated by Baer et al. in an independent cohort. Both the IPSS-M and the personalized prognostic models of Nazha et al. and Bersanelli et al. (both JCO 2021) take molecular genetic factors into account. As Baer et al. show, however, the three molecular models differ in the parameters they select. Age in particular is an important factor here. This varies the prognostic power of each model depending on whether overall survival or leukemia-free survival / leukemic transformation is in focus.

Both the WHO 2022 classification of MDS and the molecular prognostic scores for MDS take TP53 alterations into account, that may be a consequence of deletion, mutation, or copy-neutral loss of heterozygosity. A distinction needs to be made between single-hits (one of the changes mentioned) and double-hits (≥2 changes). In a cohort of 1,520 patients with MDS and AML, Stengel et al. identify TP53 double-hit as the most important prognostic factor. The incidence of TP53 double-hit seems to depend on the proportion of blasts. While single-hit still predominates in cases with TP53 alteration(s) in MDS with <5% blasts, double-hit prevails in MDS with ≥5% blasts as well as in AML.

Artificial Intelligence (AI) on Its Way into Routine Diagnostics

Even though the contributions have very different strongpoints, the development from phenotype to genotype emerges as a common theme. The increasing importance of (molecular) genetics is also generating more and more highly complex data. The ability to evaluate and make the best possible use of this data in the future will depend on the need for artificial intelligence increasing at the same time, including in our laboratory. In this context, Nadarajah et al. are now validating a previously presented classifier in a prospective cohort. Here, the AI succeeds in assigning samples to 33 entities with great accuracy and at high speed. Besides genetics, artificial intelligence is also finding its way into all other diagnostic areas of hematology. For cytomorphology, Haferlach et al. show with the prospective BELUGA study that an AI-driven and cloud-based platform for providing differential blood images improves reproducibility and reduces processing times.

If you would like a deeper insight into our various research projects, you can find overviews of these on our website. Links to the individual presentations and posters at this year’s ASH conference can also be found below:

»Do you have questions regarding this article or do you need further information? Please send me an e-mail.«

Dr. rer. nat. Constanze Kühn

Medical Writer

»Do you have questions regarding this article or do you need further information? Please send me an e-mail.«

Dr. rer. nat. Ines Schmidts

Medical Writer