Therapies that target the programmed death-1 (PD-1) receptor have shown unprecedented rates of durable clinical responses in patients with various cancer types.1–5 One mechanism by which cancer tissues limit the host immune response is via upregulation of PD-1 ligand (PD-L1) and its ligation to PD-1 on antigen-specific CD8 T-cells (termed adaptive immune resistance).6,7 Here we show that pre-existing CD8 T-cells distinctly located at the invasive tumour margin are associated with expression of the PD-1/PD-L1 immune inhibitory axis and may predict response to therapy. We analyzed samples from 46 patients with metastatic melanoma obtained before and during anti-PD1 therapy (pembrolizumab) using quantitative immunohistochemistry, quantitative multiplex immunofluorescence, and next generation sequencing for T-cell receptors (TCR). In serially sampled tumours, responding patients showed proliferation of intratumoural CD8+ T-cells that directly correlated with radiographic reduction in tumour size. Pre-treatment samples obtained from responding patients showed higher numbers of CD8, PD1, and PD-L1 expressing cells at the invasive tumour margin and inside tumours, with close proximity between PD-1 and PD-L1, and a more clonal TCR repertoire. Using multivariate analysis, we established a predictive model based on CD8 expression at the invasive margin and validated the model in an independent cohort of 15 patients. Our findings indicate that tumour regression following therapeutic PD-1 blockade requires pre-existing CD8+ T cells that are negatively regulated by PD-1/PD-L1 mediated adaptive immune resistance.
Summary
To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single cell analysis of the tumor, non-involved lung and blood cells together with multiplex tissue imaging to assess spatial cell distribution, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies.
An individual's T cell repertoire dynamically encodes their pathogen exposure history. To determine whether pathogen exposure signatures can be identified by documenting public T cell receptors (TCRs), we profiled the T cell repertoire of 666 subjects with known cytomegalovirus (CMV) serostatus by immunosequencing. We developed a statistical classification framework that could diagnose CMV status from the resulting catalog of TCRβ sequences with high specificity and sensitivity in both the original cohort and a validation cohort of 120 different subjects. We also confirmed that three of the identified CMV-associated TCRβ molecules bind CMV in vitro, and, moreover, we used this approach to accurately predict the HLA-A and HLA-B alleles of most subjects in the first cohort. As all memory T cell responses are encoded in the common format of somatic TCR recombination, our approach could potentially be generalized to a wide variety of disease states, as well as other immunological phenotypes, as a highly parallelizable diagnostic strategy.
T and B cell receptor loci undergo combinatorial rearrangement, generating a diverse immune receptor repertoire, which is vital for recognition of potential antigens. Here we use a multiplex PCR with a mixture of primers targeting the rearranged variable and joining segments to capture receptor diversity. Differential hybridization kinetics can introduce significant amplification biases that alter the composition of sequence libraries prepared by multiplex PCR. Using a synthetic immune receptor repertoire, we identify and minimize such biases and computationally remove residual bias after sequencing. We apply this method to a multiplex T cell receptor gamma sequencing assay. To demonstrate accuracy in a biological setting, we apply the method to monitor minimal residual disease in acute lymphoblastic leukaemia patients. A similar methodology can be extended to any adaptive immune locus.
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