{
  "abstract": "Background Immunotherapies have revolutionized the cancer field; among others, adoptive cell therapy with cytokine-induced killer (CIK) cells is promising. CD3 +CD56+ CIK cells are easily expanded from peripheral blood and can be redirected against specific tumor targets. Clinical application has demonstrated their safety and efficacy, but further improvements are needed. This study aims to dissect the molecular complexity of CIK cells and to understand the differentiation trajectories that shape their cytotoxic phenotype.Methods CIK cells from 8 healthy donors were expanded in a 2-week good manufacturing practice-grade protocol. The cell composition was analyzed over time by flow cytometry and single-cell RNA sequencing with feature barcode technology for cell multiplexing (10X Genomics). Following quality check controls and filtering, dimensionality reduction using UMAP and clustering were performed. The clusters were both manually and automatically annotated. Finally, CIK cells were purified to perform bulk RNA-seqResults The transcriptomes from roughly 183000 cells were analyzed. The cell clusters were consistent with published peripheral blood datasets, and flow cytometry data corroborated the population proportions. Interestingly, most cell subtypes appeared highly dynamic, and the differential gene expression analysis among time points suggested a cell population evolution over time. Indeed, an enrichment in proliferating CD8 + effector T cell clusters was observed at late time points. We identified CIK cells expressing genes like CD3, CD8, NCAM, FCGR3A, and KLRK1, confirming their known phenotypes shared with T and NK cells. The expression of markers associated to effector functions (GZMA, PRF1, NKG7, GNLY), migratory phenotype (CCL5), and proliferation (MKI67) underlie their anti-tumor potential. Finally, while PD1 is not expressed, a high level of TIM3 was detected in CIK cells, indicating an immunomodulatory function. Pseudotime analysis, regulatory network inference and pathway enrichment analysis are ongoing to trace the cellular origins of CIK cells.Conclusions Our preliminary results demonstrate the dataset’s high technical and biological quality. For the first time, a detailed transcriptional profile of CIK cells was identified by integrating single-cell and bulk RNAseq data. Further analysis will reveal critical molecular insights, which will improve the therapeutic efficacy of CIK cells.",
  "authors": [
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy"
      ],
      "name": "Emilia Vigolo"
    },
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy"
      ],
      "name": "Pierangela Palmerini"
    },
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy"
      ],
      "name": "Hieu Ngo Trong"
    },
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy"
      ],
      "name": "Elisa Cappuzzello"
    },
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy"
      ],
      "name": "Giulia D’Accardio"
    },
    {
      "affiliations": [
        "University of Padova, Padova, Italy"
      ],
      "name": "Sara Boscarato"
    },
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy",
        "University of Padova, Padova, Italy"
      ],
      "name": "Antonio Rosato"
    },
    {
      "affiliations": [
        "Veneto Institute of Oncology IOV-IRCCS, Padova, Italy",
        "University of Padova, Padova, Italy"
      ],
      "name": "Roberta Sommaggio"
    }
  ],
  "title": "357 Deciphering cellular origin and molecular features of cytokine-induced killer cells using a single-cell approach",
  "uid": "3cb5f4e5-d809-5f24-9f6d-c0fc40368da2"
}