# ai星星

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [Seishin Sakai](https://cerebralvalley.ai/u/Seisei)
- **GitHub:** https://github.com/seishin0125/BuiltWithClaude_LifeSceince_Hackathon/blob/main/research_writeup.md
- **Demo video:** https://youtu.be/0poE8tlOu_g
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/55

What we investigated. We started from an asset rather than a disease: a genome-scale CD4⁺ T-cell Perturb-seq dataset (a CRISPR knockout screen read out in single cells). The question we set was inverted from the usual pipeline — instead of picking a disease and hunting for data, we asked which disease would let this perturbation asset reveal a high-impact drug target? We chose Sézary syndrome (SS), a leukemic cutaneous T-cell lymphoma driven by a circulating malignant CD4⁺ T cell, because it satisfied three criteria: public clinical single-cell transcriptomes are available, blood CD4⁺ T cells are central to the pathology, and the CD4⁺ T cell itself is the therapeutic target.

What we built. On a 7 GB laptop, we integrated five public SS scRNA-seq datasets (≈180,000 cells) with Harmony, isolated the malignant Sézary T-cell population (63,127 cells) with a signature score, and defined the SS-specific expression profile — reproducing the known diagnostic hallmarks (loss of CD7; gain of KIR3DL2, TOX, GATA3). We then defined a reversal score: for each of ~34,000 knockouts we compared its transcriptional effect to the SS disease signature by weighted cosine similarity and flipped the sign, so a positive score means the knockout pushes cells from the disease state back toward healthy (connectivity-map logic).

What we found.

IL2RB (CD122) is the single largest disease-axis mover among 7,822 high-confidence knockouts — reversing the disease signature ~2× more than the targets of drugs already approved for SS (bexarotene/RXR, HDAC inhibitors).
This target is invisible to standard analysis. The reversal score is essentially uncorrelated with a gene's own expression change in SS (Spearman ρ = +0.055) — so IL2RB would never surface from differential-expression or enrichment analysis. It only appears through functional perturbation.
A route to drug it. IL2RB is a membrane protein with no small-molecule pocket, and existing IL-2-receptor antibodies act by cell depletion, not signal blockade. Because Perturb-seq measures loss-of-function, the faithful pharmacological equivalent is degradation. Screening degradation machinery in SS T cells, only RNF43/RNF149/RNF167 are expressed in CD4⁺ T cells; RNF149 stands out — expressed in 42% of malignant cells and ~8× restricted to blood/lymphoid tissue, offering potential T-cell selectivity and reduced off-target toxicity.
Why it matters. SS has high unmet need and no IL2RB-targeted, degradation-based therapy in the competitive landscape. Our conclusion — degradation of IL2RB via RNF149 would be a promising therapeutic strategy for SS — is a reproducible, computationally derived hypothesis that demonstrates a generalizable discovery pattern: pairing a disease's clinical transcriptome with a functional perturbation screen surfaces targets that expression-based analysis alone cannot.

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Markdown version of https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/55. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt