scholarly journals P2.04-62 TCR Repertoire Analysis of Peripheral CD8+PD-1+ T Cells Is Effective as a Predictive Biomarker for Response to the Immune Checkpoint Inhibitor

2019 ◽  
Vol 14 (10) ◽  
pp. S732
Author(s):  
S. Matsumoto ◽  
T. Matsutani ◽  
Y. Fujita ◽  
K. Kitaura ◽  
Y. Nakamura ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Predictive Biomarker ◽  
Repertoire Analysis ◽  
Tcr Repertoire

scholarly journals Deep immune profiling reveals targetable mechanisms of immune evasion in immune checkpoint inhibitor-refractory glioblastoma

2021 ◽  
Vol 9 (6) ◽  
pp. e002181
Author(s):  
Erin F Simonds ◽  
Edbert D Lu ◽  
Oscar Badillo ◽  
Shokoufeh Karimi ◽  
Eric V Liu ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Cells ◽  
Immune Evasion ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Prolonged Survival ◽  
Tumor Associated Macrophages ◽  
The Brain ◽  
Immune Profiling

BackgroundGlioblastoma (GBM) is refractory to immune checkpoint inhibitor (ICI) therapy. We sought to determine to what extent this immune evasion is due to intrinsic properties of the tumor cells versus the specialized immune context of the brain, and if it can be reversed.MethodsWe used CyTOF mass cytometry to compare the tumor immune microenvironments (TIME) of human tumors that are generally ICI-refractory (GBM and sarcoma) or ICI-responsive (renal cell carcinoma), as well as mouse models of GBM that are ICI-responsive (GL261) or ICI-refractory (SB28). We further compared SB28 tumors grown intracerebrally versus subcutaneously to determine how tumor site affects TIME and responsiveness to dual CTLA-4/PD-1 blockade. Informed by these data, we explored rational immunotherapeutic combinations.ResultsICI-sensitivity in human and mouse tumors was associated with increased T cells and dendritic cells (DCs), and fewer myeloid cells, in particular PD-L1+ tumor-associated macrophages. The SB28 mouse model of GBM responded to ICI when grown subcutaneously but not intracerebrally, providing a system to explore mechanisms underlying ICI resistance in GBM. The response to ICI in the subcutaneous SB28 model required CD4 T cells and NK cells, but not CD8 T cells. Recombinant FLT3L expanded DCs, improved antigen-specific T cell priming, and prolonged survival of mice with intracerebral SB28 tumors, but at the cost of increased Tregs. Targeting PD-L1 also prolonged survival, especially when combined with stereotactic radiation.ConclusionsOur data suggest that a major obstacle for effective immunotherapy of GBM is poor antigen presentation in the brain, rather than intrinsic immunosuppressive properties of GBM tumor cells. Deep immune profiling identified DCs and PD-L1+ tumor-associated macrophages as promising targetable cell populations, which was confirmed using therapeutic interventions in vivo.

Abstract LB037:89ZED88082A PET imaging to visualize CD8+T cells in patients with cancer treated with immune checkpoint inhibitor

2021 ◽  
Author(s):  
Laura Kist de Ruijter ◽  
Pim P. van de Donk ◽  
Jahlisa S. Hooiveld-Noeken ◽  
Danique Giesen ◽  
Alexander Ungewickell ◽  
...  
Keyword(s):  
T Cells ◽  
Cd8 T Cells ◽  
Pet Imaging ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Patients With Cancer

PS-025-Elevated tissue homing of monocytes and increased cytotoxic activity of CD8+ T-cells in immune checkpoint inhibitor-induced hepatitis

2019 ◽  
Vol 70 (1) ◽  
pp. e19-e20
Author(s):  
Cathrin L.C. Gudd ◽  
Tong Liu ◽  
Evangelos Triantafyllou ◽  
David J. Pinato ◽  
You Yone ◽  
...  
Keyword(s):  
T Cells ◽  
Cytotoxic Activity ◽  
Cd8 T Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor

Deep learning-based predictive biomarker for immune checkpoint inhibitor response in metastatic non-small cell lung cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 9094-9094
Author(s):  
Sehhoon Park ◽  
Chang Ho Ahn ◽  
Geunyoung Jung ◽  
Sarah Lee ◽  
Kyunghyun Paeng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Predictive Biomarker ◽  
Small Cell ◽  
Small Cell Lung

9094 Background: In the era of immunotherapy, immune checkpoint inhibitor (ICI) has changed the treatment paradigm in metastatic non-small cell lung cancer (NSCLC). Along with clinical trials, there is an ongoing investigation to discover the predictive biomarker of ICI which so far has unsatisfactory reliability. As an effort to enhance the predictive value of ICI treatment, we applied deep learning and developed artificial intelligent (AI) score (range from 0 to 1) to analyze the specific context of immune-tumor microenvironment (TME) extracted by scanned images from H&E slides. Methods: As a ground work, deep learning-based H&E image analyzer, Lunit SCOPE, has been trained with H&E images (n = 1824) from ICI naive NSCLC samples. For the calculation of AI score, training was conducted using responder/non-responder labeled ICI treated samples from the exploratory cohort. The ICI responder was defined as the patient with a best overall response of partial or complete response and stable disease for more than 6 months. The positivity of PD-L1 immunohistochemistry (IHC) was assessed manually by pathologists. Results: The exploratory cohort is composed of NSCLC patients treated with ICI (n = 189) in Samsung Medical Center, and response to ICI was observed in 72 (38.1%) patients. Median follow-up duration was 6.8 months (6.6~8.2). Samples with PD-L1 IHC positive, defined by ≥ 1%, was observed in 138 (73.0%) patients. AI score was significant higher in the responder group (median: 0.391 vs 0.205, P = 6.14e-5), and the patients with AI score above the cut-off (0.337) showed a better response to ICI (odds ratio [OR] 3.47 P = 7.34e-5) which is higher than patients with PD-L1 ≥ 1% (OR 1.92, P = 0.069). High AI score group (n = 83) showed significantly favorable PFS compared to low AI score group (n = 106, median PFS: 5.1m vs 1.9m, hazard ratio [HR] 0.51, P = 9.6e-5) and this outcome was independent with PD-L1 status (P = 6.0e-5). In subgroup analysis, PFS of PD-L1 high / AI score high group (n = 63) had longer median PFS (6.7m) compared to both PD-L1 high / AI score low group (n = 70, 4.0m, P = 0.001) and PD-L1 low/AI score low group (n = 35, 1.9m, P = 4.0e-6). Tumor infiltrating lymphocyte (TIL) density of cancer epithelium was significantly correlated with AI score (Pearson’s r = 0.310, P = 1.43e-5), which suggests that AI score may partly reflect TME represented by TIL. Conclusions: The AI score by machine-learned information, extracted from H&E images without additional IHC stain, could predict responsiveness and PFS of ICI treatment independent of PD-L1 IHC positivity.

scholarly journals Influence of Tumor Immune Infiltration on Immune Checkpoint Inhibitor Therapeutic Efficacy: A Computational Retrospective Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Rong Liu ◽  
Fang Yang ◽  
Ji-Ye Yin ◽  
Ying-Zi Liu ◽  
Wei Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Therapeutic Efficacy ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Progression Free Survival ◽  
Cytolytic Activity ◽  
Consensus Clustering ◽  
Tfh Cells

The tumor immune microenvironment (TIME) is likely an important determinant of sensitivity to immune checkpoint inhibitor (ICI) treatment. However, a comprehensive analysis covering the complexity and diversity of the TIME and its influence on ICI therapeutic efficacy is still lacking. Data from 782 samples from 10 ICI clinical trials were collected. To infer the infiltration of 22 subsets of immune cells, CIBERSORTx was applied to the bulk tumor transcriptomes. The associations between each cell fraction and the response to ICI treatment, progression-free survival (PFS) and overall survival (OS) were evaluated, modeling cellular proportions as quartiles. Activity of the interferon-γ pathway, the cytolytic activity score and the MHC score were associated with good prognosis in melanoma. Of the immune cells investigated, M1 macrophages, activated memory CD4+ T cells, T follicular helper (Tfh) cells and CD8+ T cells correlated with response and prolonged PFS and OS, while resting memory CD4+ T cells was associated with unfavorable prognosis in melanoma and urothelial cancer. Consensus clustering revealed four immune subgroups with distinct responses to ICI therapy and survival patterns. The cluster with high proportions of infiltrated CD8+ T cells, activated memory CD4+ T cells, and Tfh cells and low levels of resting memory CD4+ T cells exhibited a higher tumor mutation burden and neoantigen load in melanoma and conferred a higher probability of response and improved survival. Local systemic immune cellular differences were associated with outcomes after ICI therapy. Further investigations of the tumor-infiltrating cellular immune response will lay the foundation for achieving durable efficacy.

scholarly journals 805 Clonal, activated CD8+ T cells recognizing cardiac alpha-myosin drive immune checkpoint inhibitor associated myocarditis in mice

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A842-A842
Author(s):  
Margaret Axelrod ◽  
Wouter Meijers ◽  
Elie Tannous ◽  
Xiaopeng Sun ◽  
Juan Qin ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Cell Lines ◽  
Cd8 T Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Animal Experiments ◽  
Eligibility Criteria

BackgroundNearly half of all U.S. oncology patients meet FDA eligibility criteria to receive treatment with an immune checkpoint inhibitor (ICI). With increasing use of ICIs, preventing, diagnosing and treating immune-related adverse events (irAEs) are urgent clinical challenges. Myocarditis is an uncommon irAE, affecting < 1% of ICI-treated patients, but is highly fatal, with a mortality rate of nearly 50%. Genetically altered Pdcd1-/-Ctla4± mice die prematurely and specifically due to myocarditis. This model recapitulates the clinical and pathological features of ICI-myocarditis, including abundant cardiac infiltrating CD8+ T cells. The potential autoantigen(s) involved in ICI-myocarditis are unknown for both human disease and our murine model.MethodsWe used Pdcd1-/-Ctla4± mice on the C57BL6 background as a model of ICI-myocarditis. Single cell RNA and T cell receptor (TCR) sequencing was performed on sorted CD45+ cardiac immune cells from four affected Pdcd1-/-Ctla4± mice compared to six healthy wild type mice. The most three clonal TCRs (TCR-A, B, C), derived from two independent Pdcd1-/-Ctla4± mice, were reconstructed using stiTChR and transduced into reporter T cell lines for antigen discovery. Alpha-myosin was selected as a candidate autoantigen due to lack of presentation in the thymus. Reporter TCR-A, B, and C cells were screened using a library of overlapping 20 amino acid peptides derived from alpha-myosin in co-culture with bone marrow derived dendritic cells.ResultsTreatment with anti-CD8, but not anti-CD4, depleting antibodies rescues survival of Pdcd1-/-Ctla4± mice. Furthermore, adoptive transfer of splenocytes from Pdcd1-/-Ctla4± mice with myocarditis to Rag1-/- recipient mice was sufficient to induce fatal myocarditis. Single cell RNA/TCR sequencing on the cardiac immune infiltrate of Pdcd1-/-Ctla4± mice identified highly activated, clonal CD8+ T cells as the dominant cell population. The TCR-A cell line, the most clonal TCR identified in single cell TCR sequencing, activates NFAT, NFkB, and AP-1 reporters in response to the alpha-myosin epitope VIQYFASI. The TCR-B and TCR-C cell lines activate their reporters in response to the alpha myosin peptide DALLVIQWNIRAFMGVKNWP, indicating that alpha-myosin is an autoantigen in this mouse model of ICI-myocarditis.ConclusionsClonal, activated CD8+ T cells are critical for the development of ICI-myocarditis. Alpha-myosin is an autoantigen recognized by the most clonal cardiac CD8+ T cells. Efforts are currently underway to determine whether human TCRs derived from ICI-myocarditis samples recognize similar antigens. These studies are the first to identify a candidate autoantigen in ICI-myocarditis and may yield new insights into irAE pathogenesis.Ethics ApprovalAll animal experiments were in accordance with the VUMC Institutional Animal Care and Use Committee (IACUC), protocol # M2000067

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