de Miranda Lab

🚀 Happy to share our new preprint introducing GRIDGENE — a transcript density–based approach for spatial transcriptomics! biorxiv.org/content/10.110… #SpatialTranscriptomics #CancerResearch #Bioinformatics

💡 This enables powerful insights into tissue organization, microenvironments & biological processes — while still being compatible with cell-based methods when needed.

GRIDGENE takes a cell-free approach, using transcript density to define biologically relevant tissue regions such as: ✨ Tissue interfaces ✨ Phenotype-enriched compartments ✨ Gene signature–defined zones

🚀 Happy to share our new preprint introducing GRIDGENE — a transcript density–based approach for spatial transcriptomics! biorxiv.org/content/10.110… #SpatialTranscriptomics #CancerResearch #Bioinformatics

📈 Real Results: In our study, PENGUIN outperformed traditional methods, making image preprocessing for spatial proteomics more accessible and effective than ever.🐧 github.com/deMirandaLab/P…

Instead, PENGUIN preserves critical signal intensity variations, cuts down on noise, and boosts accuracy in tasks like cell segmentation & phenotyping. 🧬💻

🚀 New Tool Alert! 🚀 PENGUIN 🐧is finally published in @CSB_Journal : PENGUIN is a rapid, efficient, and user-friendly tool for denoising and normalizing multiplexed spatial proteomics images! 🔬✨ 🔗sciencedirect.com/science/articl…

Great EORTC Soft Tissue and Bone Sarcoma Group Meeting in Turin! Thanks to all the attendees for the fruitful discussion!! Looking forward to future steps @winanvanhoudt @SilviaStacchia @alegronchi @merlini_ale @SarcomaUniTo @ItaSarcomaGroup @HuangLabICR @deMirandaLab @EORTC

.@tvanwezel @StephSchubert @NfdeMiranda @LUMC_Leiden @dundeeuni identify a heterozygous stop-lost variant in #TP53 that specifically affects p53β isoforms and predisposes to familial cancer #CancerResearch @NatResCancer nature.com/articles/s4146…

Exciting work led by @StephSchubert! We uncover a new variant of the beta isoform of the p53 gene linked to cancer risk. A STOP loss germline mutation increases its oligomerization with the main p53 isoform, affecting its function! #Genetics #Cancer

Happy to share the 'Behind the Paper' on our recent publication about the integration of Imaging Mass Cytometry and Mass Spectrometry Imaging. Can't wait to see what the combination of spatial metabolomics and proteomics will teach us! @deMirandaLab communities.springernature.com/posts/spatiall…

A workflow integrating imaging mass cytometry and mass spectrometry-based imaging on the same tissue sample, developed by @deMirandaLab, enables analysis of metabolic heterogeneity at the single cell level. @MEIjsselsteijn @Joana_BrasNunes @NFdeMiranda nature.com/articles/s4159…

Our latest data proposes that Lynch-associated CRCs have similar immune profiles across all MMR gene defects, challenging the idea of gene-specific immunological differences. #LynchSyndrome #CancerResearch @MaartjeNielsen medrxiv.org/content/10.110…

By sequentially applying MALDI-MSI and IMC on the same tissue section, we can map the cellular makeup of the tissue microenvironment and simultaneously uncover the metabolic phenotypes of individual cells.

Work spearheaded by @Joana_BrasNunes and @meijsselsteijn, in collaboration with the teams of @ahmedElkoussy, @EvertsBart, and Bram Heijs. #MassSpectrometry #Imaging #Metabolomics

🚨 Happy to share our latest work on combining Imaging Mass Cytometry (IMC) and Mass Spectrometry Imaging (MALDI-MSI) to unravel cell-type-specific metabolic profiles in tissues. Thrilled to see it published in @naturemethods! nature.com/articles/s4159…

Tool: github.com/deMirandaLab/P…

@MEIjsselsteijn @miguelprocha

🚀 We just developed a new tool for pre-processing #multiplex #imaging data! 🐧 PENGUIN is an easy, straightforward, and highly effective solution to handle noise while preserving real signals. biorxiv.org/content/10.110…