Using Single Cell Genomics To Change The Treatment Of Lung Cancer.
JOURNAL OF CLINICAL ONCOLOGY(2019)
摘要
e20563 Background: Lung cancer (LC) is common with a dismal prognosis. Although treatment with immunotherapy (IO) has improved survival outcomes, these therapies remain expensive. Even using biomarker selection, response rates still fall short of 50%. The majority of immune cell profiling done previously uses samples taken from early stage patients focusing on a single immune cell subtype. Here we use single cell RNA sequencing (scRNA-seq) and Cellular Indexing of Transcriptome and Epitopes by sequencing (CITE-seq) to characterise the innate and adaptive immune cell activation state and assess the response to exposure to IO in vitro from patients with advanced LC. Methods: Patients with locally advanced or metastatic LC having an Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) have biopsies collected for analysis. Cells are grown in culture +/- nivolumab for 48 hours. scRNA-seq and CITE-seq is conducted using established protocols. Transcriptomic and proteomic data on the innate and adaptive immune cell subsets assess markers of immune activation and/or suppression and the changes after nivolumab are quantified. Results are correlated with clinical outcomes. Results: In a locally advanced/metastatic population, EBUS-TBNA biopsies yield highly cellular samples with a heterogeneous population of immune cells able to be cultured +/- IO using novel, inclusive techniques. Transcriptomic clustering reveals distinct sub-populations within the T-cell, B-cell and innate immune cell compartments. Within these clusters, CITE-seq shows protein expression on individual cells can determine states of exhaustion, cytolytic ability, migratory potential and innate immune activation. Conclusions: Single cell genomics is feasible and informative in patients with advanced LC. This work will form the basis of a functional, real-time assay to assess individualised responses to IO therapy that has the potential to predict IO response.
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关键词
Treatment,Intratumor Heterogeneity,Cancer Genomics
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