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BACKGROUND Cell surface proteins are valuable for generation of targeted and immune-based cancer therapies. While large molecular datasets are available for multiple central nervous system (CNS) tumors, identifying such targets on a tumor-level scale to generate novel therapeutics for patients is limited by a lack of analytical pipelines. Here, we present CARTarT (CAR-T Target identification Tool), a no-code, web application that utilizes user-inputted bulk transcriptomic data to identify putative surface targets for pediatric tumors. METHODS CARTarT was built on R 4.3.1 and performs differential gene expression between tumors and normal tissue (GTEX) utilizing an empirical bayes method. Data is then filtered based on predicted-surfaceome expression, non-immune cell expression, and limited normal tissue expression to mitigate possible off-target toxicities. Targets are finally scored using a weighted scoring metric based on RNA-level log fold change, t-value, average tumoral expression, and prevalence in oncogene databases to prioritize putative targets. Targets with a score less than 0.20 were removed from our final table. A total of 919 samples from OpenPedCan were utilized to validate the tool. RESULTS Amongst diffuse midline glioma specimens (n=196), we identified 100 putative surface targets. 60 (60%) of surface targets were previously identified oncogenic or cancer-associated genes. 17 surface targets (15%) are shown to have previously described immune or targeted therapeutics across cancer types, most notably identifying B7-H3, IL13RA2, EGFR, and GPC2. In addition, we identified 45 targets with potential across multiple pediatric neuro-oncologic malignancies (high grade glioma, medulloblastoma, ependymoma, atypical teratoid/rhabdoid tumor) including CHRNA5, GLP1R, B7-H3 and GPC2. CONCLUSION These findings highlight the potential utility of CARTarT as a no-code solution for surface target identification and describe established and novel surface targets across numerous pediatric CNS tumors. We present CARTarT to the scientific community as an open-access opportunity to advance immune-based and targeted therapies for tumors.
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Joshi et al. (2024) studied this question.
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