{
  "abstract": "Background Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases, with EGFR-mutant NSCLC among never-smokers particularly prevalent in Asian populations. A major clinical challenge in treating advanced NSCLC is the development of resistance to tyrosine kinase inhibitors (TKIs), highlighting the need to comprehensively profile the cellular mechanisms underlying drug resistance. We propose to address this by investigating the adaptive features of residual and resistant cancer cells, as well as the role of the tumour microenvironment in sustaining tumour growth, resistance, and disease progression.Methods In this study, we utilise single-nucleus and spatial transcriptomic profiling, integrated with matched genomic sequencing, to characterise the response of EGFR-mutant tumours in 41 samples from 34 NSCLC patients before, during, and after TKI treatment, including cases with acquired resistance. We present an analytical framework that maps consensus gene expression programs in residual cancer and immune cells that persist through treatment and at resistance. Furthermore, we investigate how interactions between cancer and immune cells, including T lymphocytes and mononuclear phagocytes, shape tumour cell states.Results We present the most comprehensive single-cell atlas to date of EGFR-mutant NSCLC. Our findings reveal that cancer cells engage coordinated gene expression programs that define distinct cell states following TKI treatment. Moreover, our data suggest that immune-mediated cues, particularly metabolic and paracrine signals from myeloid populations, may contribute to the persistence of treatment-tolerant cancer cell subsets.Conclusions As part of our ongoing efforts, we are integrating data from clinical trials and preclinical models to further dissect immune dynamics between treatment-persistent and fully resistant tumours, with the ultimate goal of guiding therapeutic strategies that target early adaptive and persister cancer cell populations.",
  "authors": [
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore",
        "Duke-NUS Medical School, Singapore, Singapore"
      ],
      "name": "Regina Hoo"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore",
        "Duke-NUS Medical School, Singapore, Singapore"
      ],
      "name": "Aaron Tan"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore"
      ],
      "name": "Dawn Lau"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore",
        "Institute of Molecular and Cell Biology, Singapore, Singapore"
      ],
      "name": "Komal Gupta"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore"
      ],
      "name": "Kenneth Chow"
    },
    {
      "affiliations": [
        "Genome Institute of Singapore, Singapore, Singapore"
      ],
      "name": "Jia Chi Yeo"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore",
        "Duke-NUS Medical School, Singapore, Singapore"
      ],
      "name": "Stephanie Saw"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore"
      ],
      "name": "Lan Ying Wang"
    },
    {
      "affiliations": [
        "Institute of Molecular and Cell Biology, Singapore, Singapore",
        "Singapore General Hospital, Singapore, Singapore"
      ],
      "name": "Joe Poh Sheng Yeong"
    },
    {
      "affiliations": [
        "Genome Institute of Singapore, Singapore, Singapore"
      ],
      "name": "Anders J Skanderup"
    },
    {
      "affiliations": [
        "National Cancer Centre Singapore, Singapore, Singapore",
        "Duke-NUS Medical School, Singapore, Singapore"
      ],
      "name": "Daniel SW Tan"
    }
  ],
  "title": "841 Tracking adaptation and response to targeted therapies in EGFR-mutant non-small cell lung cancer",
  "uid": "39dd2564-9caa-5401-aa90-f6844831b150"
}