{
  "abstract": "Background Chimeric antigen receptor (CAR) T-cell therapy has revolutionized cancer immunotherapy for hematological malignancies but faces critical barriers in solid tumors due to tumor antigen heterogeneity and on-target, off-tumor toxicities. Logic-gated multi-antigen targeting using Boolean operators (AND, OR, NOT) represents an emerging precision immunotherapy engineering approach to overcome these challenges.Methods We developed LogiCAR designer, a genetic algorithm-based computational framework that systematically identifies optimal logic-gated antigen combinations ( i.e., ‘circuits’) from single-cell transcriptomics data. The algorithm identifies CAR circuits consisting of 1-5 antigens from 2,758 cell surface proteins, optimizing tumor-targeting efficacy while maintaining stringent safety requirements in normal tissues. We curated and applied this to the largest breast cancer single-cell dataset: ~2 million cells including >620k tumor cells from 342 patients across 17 cohorts spanning all major subtypes. Safety evaluation utilized 689,601 normal cells from 31 Human Protein Atlas tissues.Results LogiCAR designer demonstrates superior efficiency, reducing computational time from ~450 days (brute force) to ~1 hour for 3-gene circuits. The best shared 3-gene circuit (’GABRP | PRLR | VTCN1’) achieved 60% mean tumor-targeting efficacy—234% more effective than the best current CAR-T clinical trial targets. Newly identified circuits significantly outperformed existing computational methods and clinical targets across independent validation cohorts (p<0.05), with superior tissue-specificity addressing critical toxicity concerns. However, shared circuits were still ineffective for some patients, highlighting the need for personalized approaches. To address this limitation, we demonstrated individual patient-specific CAR circuit design achieving remarkable efficacy: in our new 82-patient multi-ethnicity cohort, 76% of patients reached estimated complete response-equivalent targeting (>99% efficacy score) and all patients achieved at least estimated partial response (>66% efficacy score), with a 98% mean efficacy.Conclusions LogiCAR designer represents a comprehensive computational framework for systematic logic-gated CAR immunotherapy design, identifying circuits with unprecedented efficacy-safety profiles. While shared circuits substantially advance current approaches, personalized design offers transformative potential for precision CAR immunotherapy across cancer types.Ethics Approval Study participants were recruited from University of Maryland [NCI-Maryland BRCA studies (1993-2003 and 2012-2016), Aga Khan University Hospital, Nairobi, Kenya (AKUHN), and the AIC Kijabe Hospital, Kijabe, Kenya (both 2019-2021)]. All participants provided written informed consent prior to study enrollment and provided biospecimens at the time of surgery. Research pertaining to the NCI-Maryland studies was approved by the University of Maryland IRB for the participating institutions (University of Maryland Medical Center and four surrounding hospitals in the Baltimore, Maryland, area) and by the NIH Office for Human Research Protections, as previously described. The AKUHN and AIC Kijabe studies were approved by the Research and Ethics Committees at Aga Khan University Hospital, Nairobi (Ref: 2018/REC-80) and AIC Kijabe Hospital (KH IERC-02718/2019). A research license was obtained from the National Commission for Science and Technology (NACOSTI/P/24/33420) and a material transfer permit obtained from the Ministry of Health (MOH/ADM/1/1/81) in Kenya and followed recognized ethical guidelines as defined by the Declaration of Helsinki and the U.S. Common Rule.",
  "authors": [
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Sanna Madan"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Tian-Gen Chang"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Alexandra Harris"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Huaitian Liu"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Andrew Martinez"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Saugato Rahman Dhruba"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Binbin Wang"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Padma Rajagopal"
    },
    {
      "affiliations": [
        "NCI-Designated Cancer Center Sanford Burnham Prebys, San Diego, USA"
      ],
      "name": "Sanju Sinha"
    },
    {
      "affiliations": [
        "University of Maryland College Park, College Park, MD, USA"
      ],
      "name": "Aravind Srinivasan"
    },
    {
      "affiliations": [
        "Cedars-Sinai Medical Center, Los Angeles, CA, USA"
      ],
      "name": "Simon Knott"
    },
    {
      "affiliations": [
        "Aga Khan University, Nairobi, Nairobi County, Kenya"
      ],
      "name": "Shahin Sayed"
    },
    {
      "affiliations": [
        "Mount Kenya University, Thika, Kiambu County, Kenya"
      ],
      "name": "Francis Makokha"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Chi-Ping Day"
    },
    {
      "affiliations": [
        "National Cancer Institute, Shady Grove, MD, USA"
      ],
      "name": "Gretchen Gierach"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Stefan Ambs"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Alejandro A Schaffer"
    },
    {
      "affiliations": [
        "National Cancer Institute, National Institutes of Health, Bethesda, MD, USA"
      ],
      "name": "Eytan Ruppin"
    }
  ],
  "title": "1111 Single-cell-driven design of logic-gated CAR circuits for enhanced solid tumor immunotherapy",
  "uid": "7aa0ab22-2814-585a-89e1-9ff0a3f2ed76"
}