Progressive chromatin rewiring by ETO2::GLIS2 revealed in a human iPSC model of pediatric leukemia initiation.

Pediatric acute myeloid leukemia frequently harbor fusion oncogenes associated with poor prognosis, including KMT2A, NUP98 and GLIS2 rearrangements. While murine models have demonstrated their leukemogenic activities, the steps from a normal human cell to leukemic blasts remain unclear. Here, we precisely reproduced the inversion of chromosome 16 resulting in ETO2::GLIS2 fusion in human induced pluripotent stem cells (iPSC).

TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma.

Novel individual biomarkers are needed to guide therapeutic decisions for patients with head and neck cancer. We report for the first time, granulomas of TREM2-expressing multinucleated giant macrophages in keratin-rich tumor niches, as a biomarker of favorable prognosis and developed a deep-learning model to automate its quantification on routinely stained pathological slides.

Precision cancer medicine platform trials: Concepts and design of AcSé-ESMART.

Precision cancer medicine brought the promise of improving outcomes for patients with cancer. High-throughput molecular profiling of tumors at treatment failure aims to direct a patient to a treatment matched to the tumor profile. In this way, improved outcome has been achieved in a small number of patients whose tumors exhibit unique targetable oncogenic drivers.

DiPRO1 distinctly reprograms muscle and mesenchymal cancer cells.

We have recently identified the uncharacterized ZNF555 protein as a component of a productive complex involved in the morbid function of the 4qA locus in facioscapulohumeral dystrophy. Subsequently named DiPRO1 (Death, Differentiation, and PROliferation related PROtein 1), our study provides substantial evidence of its role in the differentiation and proliferation of human myoblasts. DiPRO1 operates through the regulatory binding regions of SIX1, a master regulator of myogenesis.

CellsFromSpace: a fast, accurate, and reference-free tool to deconvolve and annotate spatially distributed omics data.

Motivation: Spatial transcriptomics enables the analysis of cell crosstalk in healthy and diseased organs by capturing the transcriptomic profiles of millions of cells within their spatial contexts. However, spatial transcriptomics approaches also raise new computational challenges for the multidimensional data analysis associated with spatial coordinates.

Results: In this context, we introduce a novel analytical framework called CellsFromSpace based on independent component analysis (ICA), which allows users to analyze various commercially available technologies without relying on a single-cell reference dataset.