# CAR-DWK

- **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:** [Dongwoo Kim](https://cerebralvalley.ai/u/DDW)
- **GitHub:** https://github.com/2DW-K/BuiltwithClaude-In-vivo-insertional-screen-for-CAR-T-persistence-in-human
- **Demo video:** https://youtu.be/VEUX8OUoodU
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/207

Please check the final report on the GitHub repo!

1. What We Investigated and Built:
Conventional CAR-T screens fail to replicate the complex, months-long in vivo tumor environment. We built an automated single-cell multi-omics pipeline using the EpiVIA framework to perform an unbiased insertional-mutagenesis screen. By repurposing the semi-random lentiviral integration site (IS) as a natural genetic barcode, we tracked exactly which host genes were disrupted during manufacturing, monitored their clonal expansion post-infusion, estimated their T cell status inside the body, and selected final candidates for Next-Gen CAR-T engineering.


2. What We Found
- Clonal Expansion: From the BCMA dataset, KDM2A/ATF7IP/SMYD4/ERCC6L2/FANCA show long-term persistence with a cycling phenotype and exhaustion resistance as potential candidates. Especially, KDM2A surfaced as a powerful candidate, where 13 independent in vivo integrations near the locus drove a massive late-stage clonal expansion.

- Recurrent Targets: Across three independent datasets (human and mouse), CBLB, CYLD, and FNBP1 consistently emerged as non-essential, cross-cohort drivers of in vivo survival.

- Escaping Exhaustion: Late-surviving clones systematically avoided the epigenetic exhaustion scar, shifting instead to a sustained cycling and effector state.


3. Why It Matters
Our pipeline reads actual in vivo biology from patients actively clearing tumors, bypassing the limitations of engineered in vitro models. Because it is unbiased and resolves multi-hit (MOI > 1) cells, it can nominate unexpected targets for in vivo long-term persistence. This open-source tool provides a robust, clinically grounded platform to discover and prioritize targets for next-generation, exhaustion-resistant CAR-T therapies.

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