Holger Heyn

TICK tock. Your Immune clock is ticking!
-Immune Age- @OmniscopeAI is launching a suite of Immune Tracking products at #MWC2025.

-Immune Age- leverages T cells as a living sensors to sense and memorize systemic challenges. Pathogen exposure, for instance, triggers an immune response that leaves a lasting imprint on the T cell repertoire. However, we found that the signals encoded in T cell receptor (#TCR) sequences extend far beyond infections. They carry quantifiable insights into stress, internal and external load, and, ultimately, biological aging.

@OmniscopeAI, together with @FCBarcelona_es, now applies the potential of T cell sequencing as a Diagnostic tool to define Health, to optimize Performance and to avoid Injuries. Our T Cell Clock is a dynamic measure to quantify the accumulation of a player's load and the success of targeted interventions.

No doubt, our -Immune Age- application will go beyond the area of sports, to better define health and to extend healthy aging (#Healthspan). Our T cell sensor approach provides a new Biomarker strategy to quantify #BiologicalAge, complementing the more static Methylation clocks (@EricTopol : erictopol.substack.com/p/steve-horvat…).

Excited to see -Immune Age- to be applied in additional health intervention studies. Please reach out to collaborate! #HealthyAging #Longevity

The missing link: Human-Data-In-The-Loop!

"We are still far from teaching AI how human biology really works. No AI model has yet captured the full complexity of human biology, largely because we still lack sufficient human data in the loop. Experimental model systems, while indispensable, capture only a fraction of the cellular diversity and biological variation that define human health and disease.”

The real breakthrough will come when we bring enough human data into the loop, capturing the natural perturbations of biology across individuals, ages, environments, and disease states. Only then will we be able to build comprehensive models that move beyond describing biology to reliably predicting it.

This is exactly why our work at the @humancellatlas and @OmniscopeAI is so important - Cracking the Code of Biology.

With much more human data is when the ultimate potential of AI × Biology will be realized: when predictive models generate tangible advances in human health and, ultimately, save lives.

Check out the full article at @GENbio by @julemieux1:
genengnews.com/topics/omics/s…

TOUR DE FORCE out now! Our Phase II SERPENTINE trial: 24 patients with longitudinal biopsies, 84 sequencing libraries, 388,196  single cells and 57,902,418 T cell clonotypes!

Massive effort with @AstraZeneca , @OmniscopeAI , @VHIO, and @cnag_eu.

Immune checkpoint inhibitors (#ICIs) have limited efficacy in #metastatic #colorectal #cancer with proficient mismatch repair and microsatellite stability (pMMR/MSS). In Serpentine, we profiled patients with dual PD-L1 and CTLA-4 blockade (ipi/nivo) by integrating paired pre-treatment and on-treatment single-cell transcriptomic and T-cell receptor (TCR) profiling with ultra-deep TCR sequencing of matched peripheral blood.

Why does immunotherapy fail in MSS colorectal cancer when LIVER metastases are present?

🔎 Our findings show that the breakdown is not systemic, but local!
1. While dual immune checkpoint inhibition successfully primes and mobilizes tumor-targeting T-cell clones to both lung and liver lesions, the metastatic microenvironment determines whether that response succeeds.
2. In LUNG metastases, these cells differentiate into productive, tumor-reactive CD8+ effectors that mount an anti-tumor response. In the LIVER, however, the immune response is derailed: suppressive myeloid populations and regulatory T cells expand, exhaustion programs fragment, and effector engagement fails to restrain tumor growth.

👀 Hence, resistance in liver metastases is not a failure of initial immune priming, but a tissue-specific misdirection of immune activation. Overcoming this barrier will require therapies that address multicellular coordination within specific organ niches.

Read the full paper here:
medrxiv.org/content/10.648…

✨ Honored to step into the role of Vice Co-Chair of the Human Cell Atlas ✨ Working together with our new co-chairs Chloé Villani and Muzz Haniffa, alongside my fellow Vice Co-Chair Shyam Prabhakar.

I can’t imagine a better next leadership team for the @humancellatlas. Beyond their strong track record, it’s a pleasure to work with such thoughtful and collaborative colleagues. This is a particularly meaningful moment for me, having been part of the HCA journey for almost a decade. I have had the privilege of co-chairing the HCA Technology Working Group and Industry Partnership Program, and more recently serving on the HCA 2.0 Task Force, helping shape the vision and strategy for this next phase.

As we move towards HCA 2.0, we are defining the future vision and roadmap for the next generation of the Human Cell Atlas #HCANext10. In my new role, I will specifically focus on leading the HCA technology roadmap, working closely with our technology community as well as biotech and pharma partners to integrate the latest single-cell and spatial technologies into the HCA roadmap. I’m very grateful to the HCA community for the trust. Excited for the next chapter of the Human Cell Atlas and for what we can build together.

@sangerinstitute @broadinstitute @ASTARsg @cnag_eu

When Treatment to #Autoimmune Diseases Fail,
Combining Targeted Therapies Offers a Solution.
NOW OUT @CellRepMed! 👀

We introduced Mitigation of Non-Response Signature (MNRS), a framework that uses longitudinal blood transcriptomic data across 6 IMIDs to systematically rank complementary (and incompatible) drug pairs.

Targeted therapies reshaped how we treat immune-mediated inflammatory diseases (IMIDs), but primary non-response remains a major therapeutic ceiling. Combining treatments is a potential solution, yet prioritizing which drug pairs to test in clinical trials out of thousands of combinations is a massive hurdle.

Key Findings:
- Data-Driven Prioritization: MNRS successfully maps complementary pairs of biologics and small molecules using longitudinal patient data.
- A Winning Pair in RA: In rheumatoid arthritis, combining anti-TNF and anti-IL-6R therapies emerged as highly complementary.
- Mechanism Discovered: Single-cell analysis localized this drug complementarity specifically to CD14+ monocytes.
- In Vivo Validation: In a collagen-induced arthritis mouse model, the anti-TNF + anti-IL-6R combination significantly outperformed monotherapy.

Huge thanks to the entire team DOCTIS Project who made this work possible!

@cnag_eu Centro Nacional de Análisis Genómico (CNAG) @OmniscopeAI @DoctisEU

🔗 Read the full open-access paper here:
cell.com/cell-reports-m…