Finally out📯: 1st population-level picture of AML+ALL incidence & outcomes across all age groups in Germany! My colleague David Baden took the long tour to aggregate this data:
doi.org/10.1016/j.la... - Will be intro Figurę 1 to many presentations, David!🙏

In n=31/1210 B-ALL cases (2.6%), #IntegrateALL identified drivers from two different subtypes in one sample! One gene expression signature dominated in most cases, supporting unsupervised screening for drivers.

Analysis with our ICC/WHO-HAEM5 based rule-set yielded ~80% unambiguous subtype definitions based on driver calls and corresponding gene expression signatures, which was validated across independent cohorts. - Many thanks to collaborators @ www.mll.com!

With #IntegrateALL, we extract from RNA-seq:

- Expression counts
- B-ALL subtypes via #ALLCatchR
- Driver gene fusions
- SNVs
- Virtual karyotypes

For classifying #RNASeqCNV B-ALL karyotypes, we built #KaryALL, a machine-learning classifier reaching 0.98 accuracy!

Excited to share our preprint📯:
We introduce #IntegrateALL, an open-source RNA-seq pipeline for interpretable molecular diagnostics in acute lymphoblastic leukemia!🧬
Big thanks to Nadine Wolgast & team @ www.uksh.de
, catchall-kfo5010.com!
See: doi.org/p7k5 and 🧵

What determines Inotuzumab sensitivity in #ALL?
New @bloodjournal.bsky.social study from C. Escherich &
@junjyang.bsky.social Lab highlights the role of B cell developmental state and EBF1. It was a pleasure to provide a commentary!
🔬 doi.org/10.1182/bloo...
🗒️ doi.org/10.1182/bloo...