Saez-Rodriguez Group

New preprint from my team! led by @remitrimbour.bsky.social in collaboration with the @saezlab.bsky.social, we developped ReCoN a new method to model multicellular coordination and its underlying molecular mechanisms.

📜 Paper: lnkd.in/eJ8SfFNH
💻 Code: lnkd.in/e-qx2iNp

This month we welcome 2 new members and 1 visitor to our lab! 🎉 Veronika Kedlian as a postdoc, Hugo Hakem as a PhD student, and @francescadrummer.bsky.social as a visiting PhD student 🎉

#inflammation #diagnostics #precisionmedicine #liquidbiopsy #machinelearning | Holger Heyn | 40 comments Ladies and gentlemen - Our Atlas of Human Inflammation today out in Nature Medicine 💫 Welcome on stage: The Cell as a Living Biomarker 🩸 We Built an #Inflammation Atlas of Circulating Immune Cells....

Congrats! We’re happy to have contributed to the Atlas of Human Inflammation, improving the interpretability of inflammatory signatures through inference of transcription factor activity (Jose Liñares Blanco, @ricoramirez.bsky.social and @juliosaezrod.bsky.social)

www.linkedin.com/posts/holger...

We recently posted a "2025 Publication Countdown" series on LinkedIn. See here ➡️ www.linkedin.com/company/saez...

We acknowledge the funding from the Heidelberg Faculty of Medicine at @uniheidelberg.bsky.social through the Medical Data Scientist Fellowship.

This study was led by @ahmetrifaioglu.bsky.social, with supervision by @juliosaezrod.bsky.social and @tanevski.bsky.social, and with contributions from @asarigun.bsky.social and @denizgermen.bsky.social. In collaboration with the @bb-lab.bsky.social, with contributions from Egle Helene Ervin.

📌 Across multiple breast cancer proteomic datasets, SpaCEy robustly stratifies patients by overall survival, both across and within established clinical subtypes.

📌 In a spatial proteomic lung cancer cohort, SpaCEy identifies distinct spatial arrangements and protein programs associated with disease progression.

📌 The model highlights compact spatial patterns involving a small set of key protein markers underlying patient stratification, supporting interpretability and clinical relevance.

See 👇 our new manuscript introducing SpaCEy, an explainable method for predicting clinical outcomes from spatial omics data 🧬

📄 Paper: www.biorxiv.org/content/10.6...
💻 Code repo: github.com/saezlab/SpaCEy

🤗 We welcome Jay Chow (Chi Lung), our new Scientific Database Curator. Jay will be joining a collaborative effort between SaezLab, @ebi.embl.org FG team, and GSK for the curation of fibrosis datasets and integration into the Expression Atlases and ArrayExpress collection in BioStudies.

📍 Latest OmniPath paper is out now! ➡️ academic.oup.com/nar/advance-...

It was an honor to speak about Systems Biology of Kidney Disease at the American Society of Nephrology meeting www.youtube.com/watch?v=YLVs...
reflecting from my perspective as patient-scientist (www.nature.com/articles/s41...) & sharing work of @saezlab.bsky.social sp. within www.iganatlas.org

📄 BioContextAI is now slightly updated and published @natbiotech.nature.com

➡️ www.nature.com/articles/s41...

We thank all data authors (incl. Kory Lavine, Patrick Ellinor, and Norbert Hubner’s labs, among others) and enrolled patients. We acknowledge funding from DFG through CRC1550. All code available at github.com/saezlab/rehe...

This study was co-led by @ricoramirez.bsky.social and @jlanzer.bsky.social with supervision by @juliosaezrod.bsky.social and help by Jose Linares, and the group of Norbert Frey (Marco Steier and Ashraf Rangrez) who performed the experimental work.

By integrating transcriptomic datasets across cohorts and technologies, we provide a reference for examining multicellular aspects of heart failure.

An interactive platform allows users to explore gene-expression patterns and project new samples: tinyurl.com/bdwxdf6j

New patients can be positioned on the map:
In a cohort receiving LVADs (data from Kory Lavine’s lab), molecular changes in the map were consistent with clinical improvement, suggesting that the map may help characterize treatment responses.

This allowed us to distinguish genes driven by compositional changes from those primarily affected by molecular regulation.

We also updated the heart-failure transcriptional signature derived from bulk studies and combined it with our multicellular programs to examine how different cell types contribute to gene dysregulation.

The coordinator role of fibroblast was better characterized by a broad phenotypic shift rather than the accumulation of specific cell states.

We also uncovered a network of cell-type dependencies underlying these multicellular programs, with fibroblasts playing a central role, particularly coordinating with cardiomyocyte reprogramming (where we validated several ligand candidates consistent with this interaction).

Using Multicellular Factor Analysis, a patient-level integration method (doi.org/10.7554/eLif...), we constructed a transcriptional patient map summarizing multicellular gene-expression variation in heart failure along two main axes.

Across studies, gene-expression changes associated with heart failure showed a reproducible pattern in both bulk and single-nucleus data. Changes in cell-type composition were more variable, indicating that these two aspects of tissue remodelling may not always occur together.

We curated an extensive compendium of >1500 patients profiled w bulk or single-nuc transcriptomics, building on our previous work tinyurl.com/sn6dxu95. This data engineering effort enabled the comparison and integration of insights to generate a reference of Heart Failure.

Our revised consensus transcriptional patient map of human heart failure across patient cohorts and single-cell and bulk technologies is now published @natcomms.nature.com www.nature.com/articles/s41...

Bonjour! Masters students in France 🇫🇷, we’ve got an internship for you, in collaboration with the French Embassy in London.

Aimed at students of computer science, statistics or bioinformatics.

Deadline: 7 December 2025

Find out more and apply:
www.ebi.ac.uk/about/jobs/i...

👋 @veronicalombardi.bsky.social has completed her 6-month visit period with us. She is a PhD student from the University of Rome La Sapienza, and her contribution focused on generating single-cell and patient-specific networks of pancreatic cancer using our tools LIANA+ and CORNETO. All the best! 🍀

Current Vacancies Whether you're a scientist, IT specialist, accountant or administrator, you'll help us tackle the challenges of improving human health & biodiversity in the face of climate change on a global scal...

We are hiring a Postdoctoral Fellow in Computational Biology at EMBL-EBI (Cambridge, UK). Focus: methods to study cell–cell communication from sc/spatial omics data (building on LIANA+ and NicheNet), in collab with @yvansaeys.bsky.social VIB/Ghent.

Details & apply by 13/10/25: tinyurl.com/4shdw8dk

It was also supported by projects: AI4FOOD-CM (Y2020/TCS6654), FACINGLCOVID-CM (PD2022-004-REACT-EU), INTER-ACTION (PID2021-126521OB-I00 MICINN/FEDER), HumanCAIC (TED2021-131787BI00 MICINN), PowerAI+ (SI4/PJI/2024-00062 Comunidad de Madrid and UAM), and Cátedra ENIA UAM-VERIDAS.