Epigenetic profiles of blood cancer cells could aid in diagnosis and treatment

Research in biomedical laboratories has been changing significantly in recent years, to the point that test tubes have given way to computers on many occasions. In this context, many discoveries now begin with detailed studies of molecular and cellular databases, followed by the validation and expansion of these findings through experiments conducted in the classic white lab coat, and finally by the translation of this knowledge into clinical settings, thanks to the white-coated professionals in hospitals. The so-called “database engineering” has opened the doors to biomedical research for many computer scientists and mathematicians, who often play essential roles on this chessboard.

Today, an article published in the journal Leukemia, part of the Nature group, led by Dr. Manel Esteller, ICREA Research Professor at the Josep Carreras Leukaemia Research Institute (IJC) and Chairman of Genetics at the School of Medicine of the University of Barcelona, provides a new example of the power of bioinformatics by making available to the scientific community the epigenetic maps of more than 200 cell lines derived from a variety of malignant blood diseases and their associated organs, such as leukaemia and lymphoma. The work is first-authored by Dr. Aleix Noguera-Castells and counts with the collaboration of Dr. Josep Maria Ribera’s Lab, also from the Josep Carreras Institute.

Dr. Esteller explains that the team has obtained “the epigenetic profiles of the most extensive collection of cultured cells derived from transformed cells in the bloodstream, bone marrow, and lymph nodes up to date, examining in them over 800,000 sites of genome modification due to DNA methylation”. This includes both human and mouse malignant samples, making the patterns obtained potentially useful to basic, applied, and clinical researchers.

Esteller also stresses that “a particularly important point is that the epigenomes we obtained are very similar to those of patients’ primary tumours”, meaning that, using computational algorithms, this database can serve as a reference for diagnosing blood cancer when doubts exist about its identity and classification. “We have previously proven the success of this method with brain tumours and sarcomas” reminds Dr. Esteller.

Besides the pure characterisation of the malignant cells’ epigenome, the study also cross-referenced the epigenetic data with information on the sensitivity of over 300 drugs, so “now, a separate algorithm can predict which epigenetic lesion is associated with sensitivity or resistance to a medication”, an important milestone for clinical research according to Dr. Esteller.

Together with the broad availability of the data, uploaded to online public repositories, the research team is confident that the reported characterisation linked to drug sensitivity will be a valuable asset to properly identify tumours of unknown origin and help decide the best therapeutic option.

This research has been partly funded by grants from the Spanish and Catalan governments, Cellex foundation, “La Caixa” foundation and the Spanish Association Against Cancer (AECC). No generative AI tools have been used in the writing of this news piece.