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The CARTAR app offers a suite of tools designed to facilitate the identification of potential targets for Chimeric Antigen Receptor (CAR) therapies. Leveraging expression data from The Cancer Genome Atlas (TCGA) project (tcga_RSEM_gene_tpm) and the Genotype-Tissue Expression (GTEx) project (gtex_RSEM_gene_tpm), our platform focuses on pinpointing tumor-associated antigens located on the cell surface ensuring target selectivity, and assessing specificity. It is based on RNA sequencing expression data of 10,522 samples from the TCGA project and 7,858 samples from the GTEx project, using a standard pre-processing pipeline. Raw data was meticulously processed to isolate genes located in the plasma membrane (GO:0005886). These membrane-bound proteins serve as prime candidates for CAR therapy targeting. Additionally, the dataset was annotated with tumor types and conditions (primary tumor, metastatic, or control), with GTEx data serving as control samples where applicable.

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Use Cases Limitations Evidence Owner's Insight

How each tool in CARTAR can be used:

  1. Tumor-associated antigens: This tool helps identify proteins expressed on the surface of tumor cells, which are potential targets for CAR T-cell therapy. It leverages data from TCGA and GTEx to pinpoint antigens specifically associated with tumor cells.

  2. Tumor expression change: Researchers can use this tool to explore how the expression levels of one or more genes change across different types of tumors. This can reveal genes that are upregulated or downregulated in specific cancer types, potentially indicating novel therapeutic targets.

  3. Tumor median expression: Visualizing median expression values across primary tumors, metastatic (if available), and control samples helps researchers understand the average expression levels of a candidate gene in different cancer conditions. This can highlight genes that are consistently expressed across different stages of cancer.

  4. Tumor gene expression: Analyzing the expression values of a specific gene across primary tumor and control samples of specified tumors provides insights into how that gene behaves in cancerous versus healthy tissues. This can inform decisions on targeting specific genes with CAR therapies.

  5. Tissue gene expression: Studying gene expression in off-tumor tissues allows researchers to assess the specificity of candidate target genes. By comparing expression levels in non-cancerous tissues, researchers can identify genes that are selectively expressed in tumors, minimizing off-target effects in CAR T-cell therapies.

  6. Metastatic gene expression: Analyzing gene expression across primary tumors, metastatic sites, and control samples (e.g., in SKCM) helps understand how gene expression changes as cancer progresses and spreads. This can identify genes that play crucial roles in metastasis and are potential targets for CAR therapies aimed at metastatic disease.

  7. Logic-gated CAR: This tool explores the correlation between the expression levels of two genes in primary tumor and control samples of a specified tumor. This analysis helps design logic-gated CAR therapies that target multiple antigens or signaling pathways simultaneously, potentially enhancing treatment efficacy and reducing resistance.

  8. Cell line selector: Researchers can use this tool to identify cancer cell lines that exhibit desired expression values of target genes. This is useful for preclinical studies and experimental validation of CAR T-cell therapies, ensuring that selected cell lines accurately model gene expression profiles found in patient tumors.

Each tool in CARTAR provides valuable insights and data-driven approaches to advance the development and optimization of CAR T-cell therapies, contributing to more effective and targeted treatments for cancer patients.

See owner's GitHub repository for more information:

This app is based on the paper:

Hernandez-Gamarra, M., Salgado-Roo, A., Dominguez, E., Goiricelaya Seco, E. M., Veiga-Rúa, S., Pedrera-Garbayo, L. F., Carracedo, Á., Allegue, C. (2024). CARTAR: A comprehensive web tool for identifying potential targets in chimeric antigen receptor therapies using TCGA and GTEx data. Briefings in Bioinformatics, 25(4), bbae326.

This application was not uploaded by the author, but through their publicly available Github repository,


Warning: Not intended for clinical use. Assume outputs are unsafe and unvalidated. Use carefully.

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Kinal Patel

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