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ScaiDigest Volume 5: Unlocking the Secrets of AML

ScaiDigest Volume 5

ScaiDigest Volume 5

ScaiDigest Volume 5

The latest edition of ScaiDigest, our bi-weekly scientific series, is out now! 

In this volume, our Principal Expert Scientist, Diana Stoycheva, dives deep into the world of single-cell technologies and their profound impact on AML research. 

Single-cell sequencing methods have opened new doors to understanding AML heterogeneity, clonal evolution, and resistance mechanisms. Diana explores groundbreaking research, including a study by Mumme et al. in Nature Communications and work by Zhang et al. in Cancer Science. These findings promise to revolutionize our approach to AML diagnosis, treatment, and prognosis. 

Read Diana’s insightful post and stay at the forefront of scientific advancements in the field!

“My enthusiasm for cutting-edge science and the conviction of the impact that single-cell technologies bring in solving complex biological problems are further reinforced in their application in AML research.

The advancements in single-cell sequencing methods enable researchers to delve into genomic, transcriptomic, proteomic, and epigenomic data at the individual cell level, offering valuable insights into AML heterogeneity, clonal evolution, and resistance mechanisms. These insights not only enhance our understanding of AML but also hold the potential to significantly improve diagnosis, treatment, and prognosis through the identification of unique predictive markers and therapeutic targets.

In a recent publication in Nature Communications, Mumme et al. (1) dissect the tumor microenvironment of pediatric AML with scRNA-seq. The TME of AML exhibits dynamic shifts during disease progression. Leveraging single-cell RNA sequencing (scRNA-seq), the study explores AML bone marrow (BM) samples from diagnosis (Dx), end of induction (EOI), and relapse phases. The authors discover a distinctive 7-gene signature (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH) specific to AML blasts, validated across independent datasets.

While T-cell exhaustion correlated with relapse-associated samples at Dx, inflammatory M1 macrophages prevailed in continuous clinical remission samples. Post-therapy, residual blasts showed elevated expression of fatty acid oxidation, tumor growth, and stemness genes. The interplay between AML blasts and the microenvironment informs the way for targeted interventions and therapeutic innovations in the challenging landscape of pediatric AML.

The work by Zhang et al. in Cancer Science (2) on the TME in AML confirms these findings providing deeper insights into the AML immunosuppressive microenvironment, which is critical for immunotherapies. A review by Zou at al. (3) on the topic summarizes the significant contributions of single-cell technologies toward enhancing our understanding of AML heterogeneity, identifying prognostic markers, uncovering therapeutic targets, and formulating more personalized treatment strategies.

I celebrate how scRNA-seq revolutionizes our understanding of inflammatory TME, deciphering its cellular complexity, developmental trajectories, prognostic and predictive markers, and intricate interactions. As these insights translate into targeted therapies, scRNA-seq stands as a transformative approach, offering hope in the fight against cancer by unravelling the complexities of inflammatory TME.”

Articles mentioned in this ScaiDigest:

Single-cell analysis reveals altered tumor microenvironments of relapse- and remission-associated pediatric acute myeloid leukemia

Single-cell RNA-seq reveals a microenvironment and an exhaustion state of T/NK cells in acute myeloid leukemia

Big data and single-cell sequencing in acute myeloid leukemia research

About Scailyte

Scailyte is an ETH Zürich spin-off with a best-in-class artificial intelligence platform for the discovery of complex disease patterns from single-cell data. Our solution provides unprecedented insight into the disease and patients’ biology and enables the discovery of new clinically-relevant biomarker signatures by uncovering human’s hidden “single-cell” secrets. 

Scailyte’s proprietary best-in-class data analysis platform ScaiVision™ associates multimodal single-cell datasets (RNA-/TCR-/BCR-seq, proteomics, etc.) with clinical endpoints, such as disease diagnosis, progression, severity, treatment response, and toxicity response to identify ultra-sensitive biomarker signatures and cell functionality states. The performance and clinically-relevant applications of Scailyte’s platform ScaiVision have been demonstrated in well established CAR-T cell therapies and various clinical projects in Oncology and Immunology.

For more information, visit www.scailyte.com and connect on social media @LinkedIn and @Twitter.

ScailyteTM and ScaiVisionTM are registered trademarks proprietary to Scailyte AG.

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