RESUMO
Immune checkpoint therapy (ICT) causes durable tumour responses in a subgroup of patients, but it is not well known how T cell receptor beta (TCRß) repertoire dynamics contribute to the therapeutic response. Using murine models that exclude variation in host genetics, environmental factors and tumour mutation burden, limiting variation between animals to naturally diverse TCRß repertoires, we applied TCRseq, single cell RNAseq and flow cytometry to study TCRß repertoire dynamics in ICT responders and non-responders. Increased oligoclonal expansion of TCRß clonotypes was observed in responding tumours. Machine learning identified TCRß CDR3 signatures unique to each tumour model, and signatures associated with ICT response at various timepoints before or during ICT. Clonally expanded CD8+ T cells in responding tumours post ICT displayed effector T cell gene signatures and phenotype. An early burst of clonal expansion during ICT is associated with response, and we report unique dynamics in TCRß signatures associated with ICT response.
Assuntos
Inibidores de Checkpoint Imunológico , Linfócitos do Interstício Tumoral , Receptores de Antígenos de Linfócitos T alfa-beta , Animais , Inibidores de Checkpoint Imunológico/farmacologia , Inibidores de Checkpoint Imunológico/uso terapêutico , Receptores de Antígenos de Linfócitos T alfa-beta/genética , Receptores de Antígenos de Linfócitos T alfa-beta/metabolismo , Camundongos , Linfócitos do Interstício Tumoral/imunologia , Linfócitos do Interstício Tumoral/efeitos dos fármacos , Linfócitos do Interstício Tumoral/metabolismo , Linfócitos T CD8-Positivos/imunologia , Linfócitos T CD8-Positivos/efeitos dos fármacos , Linfócitos T CD8-Positivos/metabolismo , Humanos , Camundongos Endogâmicos C57BL , FemininoRESUMO
While chemotherapy remains the first-line treatment for many cancers, it is still unclear what distinguishes responders from non-responders. Here, we characterize the chemotherapy-responsive tumor microenvironment in mice, using RNA sequencing on tumors before and after cyclophosphamide, and compare the gene expression profiles of responders with progressors. Responsive tumors have an inflammatory and highly immune infiltrated pre-treatment tumor microenvironment characterized by the enrichment of pathways associated with CD4+ T cells, interferons (IFNs), and tumor necrosis factor alpha (TNF-α). The same gene expression profile is associated with response to cyclophosphamide-based chemotherapy in patients with breast cancer. Finally, we demonstrate that tumors can be sensitized to cyclophosphamide and 5-FU chemotherapy by pre-treatment with recombinant TNF-α, IFNγ, and poly(I:C). Thus, a CD4+ T cell-inflamed pre-treatment tumor microenvironment is necessary for response to chemotherapy, and this state can be therapeutically attained by targeted immunotherapy.
Assuntos
Neoplasias , Linfócitos T , Animais , Camundongos , Fator de Necrose Tumoral alfa/metabolismo , Microambiente Tumoral , Ciclofosfamida/farmacologia , Ciclofosfamida/uso terapêutico , Ciclofosfamida/metabolismo , Neoplasias/patologia , Linfócitos T CD4-Positivos/metabolismoRESUMO
The success of immunotherapy that targets inhibitory T cell receptors for the treatment of multiple cancers has seen the anti-tumor immune response re-emerge as a promising biomarker of response to therapy. Longitudinal characterization of T cells in the tumor microenvironment (TME) helps us understand how to promote effective anti-tumor immunity. However, serial analyses at the tumor site are rarely feasible in clinical practice. Malignant pleural effusions (MPE) associated with thoracic cancers are an abnormal accumulation of fluid in the pleural space that is routinely drained for patient symptom control. This fluid contains tumor cells and immune cells, including lymphocytes, macrophages and dendritic cells, providing a window into the local tumor microenvironment. Recurrent MPE is common, and provides an opportunity for longitudinal analysis of the tumor site in a clinical setting. Here, we review the phenotype of MPE-derived T cells, comparing them to tumor and blood T cells. We discuss the benefits and limitations of their use as potential dynamic biomarkers of response to therapy.
RESUMO
Previous studies have indicated a synergistic effect between radiotherapy and immunotherapy. A better understanding of how this combination affects the immune system can help to clarify its role in the treatment of metastatic cancer. We performed T cell receptor (TCR) sequencing on 46 sequentially collected samples from 15 patients with stage IV non-small cell lung cancer, receiving stereotactic body radiotherapy combined with a programmed cell death ligand-1 (PD-L1) inhibitor. TCR repertoire diversity was assessed using Rényi diversity curves and the Shannon diversity index. TCR clones were tracked over time. We found decreasing or stable diversity in the best responders, and an increase in diversity at progression in patients with an initial response. Expansion of TCR clones was more often seen in responders. Several patients also developed new clones of high abundance. This seemed to be more related to radiotherapy than to immune checkpoint blockade. In summary, we observed similar dynamics in the TCR repertoire as have been described with immunotherapy alone. In addition, the occurrence of new unique clones of high abundance after radiotherapy may indicate that radiotherapy functions as a personalized cancer vaccine.
Assuntos
Carcinoma Pulmonar de Células não Pequenas , Neoplasias Pulmonares , Carcinoma Pulmonar de Células não Pequenas/patologia , Humanos , Inibidores de Checkpoint Imunológico , Imunoterapia , Neoplasias Pulmonares/patologia , Neoplasias Pulmonares/radioterapia , Receptores de Antígenos de Linfócitos T/metabolismoRESUMO
Immunotherapies have revolutionized cancer treatment. In particular, immune checkpoint therapy (ICT) leads to durable responses in some patients with some cancers. However, the majority of treated patients do not respond. Understanding immune mechanisms that underlie responsiveness to ICT will help identify predictive biomarkers of response and develop treatments to convert non-responding patients to responding ones. ICT primarily acts at the level of adaptive immunity. The specificity of adaptive immune cells, such as T and B cells, is determined by antigen-specific receptors. T cell repertoires can be comprehensively profiled by high-throughput sequencing at the bulk and single-cell level. T cell receptor (TCR) sequencing allows for sensitive tracking of dynamic changes in antigen-specific T cells at the clonal level, giving unprecedented insight into the mechanisms by which ICT alters T cell responses. Here, we review how the repertoire influences response to ICT and conversely how ICT affects repertoire diversity. We will also explore how changes to the repertoire in different anatomical locations can better correlate and perhaps predict treatment outcome. We discuss the advantages and limitations of current metrics used to characterize and represent TCR repertoire diversity. Discovery of predictive biomarkers could lie in novel analysis approaches, such as network analysis of amino acids similarities between TCR sequences. Single-cell sequencing is a breakthrough technology that can link phenotype with specificity, identifying T cell clones that are crucial for successful ICT. The field of immuno-sequencing is rapidly developing and cross-disciplinary efforts are required to maximize the analysis, application, and validation of sequencing data. Unravelling the dynamic behavior of the TCR repertoire during ICT will be highly valuable for tracking and understanding anti-tumor immunity, biomarker discovery, and ultimately for the development of novel strategies to improve patient outcomes.
Assuntos
Inibidores de Checkpoint Imunológico/imunologia , Receptores de Antígenos de Linfócitos T/imunologia , Animais , Humanos , Imunoterapia/métodos , Neoplasias/imunologia , Neoplasias/terapiaRESUMO
Immune checkpoint therapy (ICT) results in durable responses in individuals with some cancers, but not all patients respond to treatment. ICT improves CD8+ cytotoxic T lymphocyte (CTL) function, but changes in tumor antigen-specific CTLs post-ICT that correlate with successful responses have not been well characterized. Here, we studied murine tumor models with dichotomous responses to ICT. We tracked tumor antigen-specific CTL frequencies and phenotype before and after ICT in responding and non-responding animals. Tumor antigen-specific CTLs increased within tumor and draining lymph nodes after ICT, and exhibited an effector memory-like phenotype, expressing IL-7R (CD127), KLRG1, T-bet, and granzyme B. Responding tumors exhibited higher infiltration of effector memory tumor antigen-specific CTLs, but lower frequencies of regulatory T cells compared to non-responders. Tumor antigen-specific CTLs persisted in responding animals and formed memory responses against tumor antigens. Our results suggest that increased effector memory tumor antigen-specific CTLs, in the presence of reduced immunosuppression within tumors is part of a successful ICT response. Temporal and nuanced analysis of T cell subsets provides a potential new source of immune based biomarkers for response to ICT.