Transcriptomic analysis reveals pro-inflammatory signatures associated with acute myeloid leukemia progression.
Svea StratmannSara Alaa YonesMateusz GarbulowskiJitong SunAron SkaftasonMarkus MayrhoferNina NorgrenMorten Krogh Krogh HerlinChristian Hartmann GeislerAnna ErikssonMartin HöglundJosefine PalleJonas AbrahamssonKirsi JahnukainenMonica Cheng Munthe-KaasBernward ZellerKatja Pokrovskaja TammLucia CavelierJan KomorowskiLinda HolmfeldtPublished in: Blood advances (2021)
During the last decade, numerous studies have been carried out to exploit the complexity of genomic and transcriptomic lesions driving acute myeloid leukemia (AML) initiation. These studies have helped improve risk classification and treatment options. Detailed molecular characterization of longitudinal AML samples are, however, sparse, meanwhile relapse and therapy resistance represent the main challenge in AML care. To this end, we performed transcriptome-wide RNA sequencing of longitudinal diagnosis, relapse and/or primary resistant samples from 47 adult and 23 pediatric AML patients with known mutational background. Gene expression analysis revealed the association of short event-free survival with overexpression of GLI2 and IL1R1, as well as downregulation of ST18. Moreover, CR1-downregulation and DPEP1-upregulation were associated with AML relapse both in adults and children. Finally, machine learning and network-based analysis identified overexpressed CD6 and downregulated INSR as highly co-predictive genes depicting important relapse-associated characteristics among adult AML patients. Our findings point towards the importance of a tumor-promoting inflammatory environment in leukemia progression, as indicated by several of the herein identified differentially expressed genes. Together, this knowledge provides the foundation for novel personalized drug targets and has the potential to maximize the benefit of current treatments, to improve cure rates in AML.
Keyphrases
- acute myeloid leukemia
- free survival
- allogeneic hematopoietic stem cell transplantation
- machine learning
- genome wide
- single cell
- cell proliferation
- healthcare
- genome wide identification
- end stage renal disease
- rna seq
- palliative care
- young adults
- copy number
- chronic kidney disease
- cross sectional
- peritoneal dialysis
- oxidative stress
- acute lymphoblastic leukemia
- big data
- dna methylation
- bone marrow
- transcription factor
- poor prognosis
- case control
- newly diagnosed
- electronic health record
- bioinformatics analysis