scholarly journals 564 Single-cell transcriptomic analysis of immune compartments following combination immunotherapy treatment in poorly immunogenic tumors

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A593-A593
Author(s):  
Ang Cui ◽  
Kelly Moynihan ◽  
Shuqiang Li ◽  
Chensu Wang ◽  
Jackson Southard ◽  
...  
Keyword(s):  
Dendritic Cells ◽  
Lymph Nodes ◽  
Single Cell ◽  
Immune Checkpoint ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
List Type ◽  
Combination Immunotherapy ◽  
Effective Response ◽  
Draining Lymph Nodes

BackgroundA major goal in cancer immunology is to rationally design combination therapies that lead to a higher response rate, especially for poorly immunogenic tumors that do not respond to immune checkpoint blockade therapy alone. We previously developed a combination therapeutic strategy, termed AIPV, consisting of a tumor-targeting antibody, a recombinant interleukin-2 with an extended half-life, an anti-PD-1 antibody, and a T cell vaccine [1]. The full AIPV therapy can eradicate large, aggressive, poorly immunogenic tumors in multiple mouse tumor models. However, the exact cellular and molecular pathways involved in such an effective response remain poorly understood.MethodsIn this study, we used single-cell RNA-sequencing to define the detailed cellular and molecular changes in tumors and tumor-draining lymph nodes following the full AIPV therapy or a less effective sub-combination therapy in mice with poorly immunogenic B16F10 tumors.ResultsUsing our approach, we were able to uncover T cells, NK cells, neutrophils, macrophages/monocytes, classical dendritic cells, and plasmacytoid dendritic cells in tumors. We observed profound remodeling of every immune cell type following the effective therapeutic treatment. In particular, we found that classical dendritic cells take up tumor antigens, become activated, and migrate to draining lymph nodes following the AIPV therapy, but not following the less effective IPV therapy. We characterized the transcriptomic changes of these dendritic cells and found that they over-express molecules involved in antigen uptake.ConclusionsOur study comprehensively characterized a system that can overcome resistance to immune checkpoint blockade therapy, paving a cellular and molecular roadmap for immune-based therapeutic strategies that offer clinical benefits for poorly immunogenic tumors.ReferencesMoynihan KD, Opel CF, Szeto GL, Tzeng A, Zhu EF, Engreitz JM, et al. Eradication of large established tumors in mice by combination immunotherapy that engages innate and adaptive immune responses. Nat Med. 2016;22: 1402–1410.Ethics ApprovalAll mouse experiments were reviewed and approved by the Koch Institute and Broad Institute Animal Care and Use Committee (IACUC) (ID 0222-08-18).

scholarly journals Chemotherapy but not the tumor draining lymph nodes determine the immunotherapy response in secondary tumors

2019 ◽  
Author(s):  
Xianda Zhao ◽  
Beminet Kassaye ◽  
Dechen Wangmo ◽  
Emil Lou ◽  
Subbaya Subramanian
Keyword(s):  
T Cell ◽  
Lymph Nodes ◽  
Immune Checkpoint ◽  
Immune Checkpoint Blockade ◽  
Cytotoxic Chemotherapy ◽  
Checkpoint Blockade ◽  
Secondary Tumors ◽  
Sequential Administration ◽  
Cytotoxic Treatment ◽  
Draining Lymph Nodes

SUMMARYImmunotherapies are used as adjuvant therapies for cancers. However, knowledge of how traditional cancer treatments affect immunotherapies is limited. Using mouse models, we demonstrate that tumor-draining lymph nodes (TdLNs) are critical for tumor antigen-specific T-cell response. However, removing TdLNs concurrently with established primary tumors did not affect the immune checkpoint blockade (ICB) response on localized secondary tumor due to immunotolerance in TdLNs and distribution of antigen-specific T cells in peripheral lymphatic organs. Notably, treatment response improved with sequential administration of 5-fluorouracil (5-FU) and ICB compared to concurrent administration of ICB with 5-FU. Immune profiling revealed that using 5-FU as induction treatment increased tumor visibility to immune cells, decreased immunosuppressive cells in the tumor microenvironment, and limited chemotherapy-induced T-cell depletion. We show that the effect of traditional cytotoxic treatment, not TdLNs, influences immunotherapy response in localized secondary tumors. We postulate essential considerations for successful immunotherapy strategies in clinical conditions.Graphic abstractThe effects of tumor-draining lymph nodes (TdLNs) resection and a combination of cytotoxic chemotherapy on immune checkpoint blockade therapies are evaluated in this study. TdLNs resection was adverse in eliciting an antitumor immune response in early-stage tumors, but not in late-stage tumors. Further, sequential treatments with cytotoxic chemotherapy and immunotherapy showed better tumor control compared to concurrent combinatorial treatments.

scholarly journals Motility Dynamics of T Cells in Tumor-Draining Lymph Nodes: A Rational Indicator of Antitumor Response and Immune Checkpoint Blockade

Cancers ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 4616
Author(s):  
Yasuhiro Kanda ◽  
Taku Okazaki ◽  
Tomoya Katakai
Keyword(s):  
T Cells ◽  
Dendritic Cells ◽  
T Cell ◽  
Lymph Nodes ◽  
Cell Motility ◽  
Immune Checkpoint ◽  
Checkpoint Inhibitors ◽  
Tumor Immunotherapy ◽  
Checkpoint Blockade ◽  
Draining Lymph Nodes

The migration status of T cells within the densely packed tissue environment of lymph nodes reflects the ongoing activation state of adaptive immune responses. Upon encountering antigen-presenting dendritic cells, actively migrating T cells that are specific to cognate antigens slow down and are eventually arrested on dendritic cells to form immunological synapses. This dynamic transition of T cell motility is a fundamental strategy for the efficient scanning of antigens, followed by obtaining the adequate activation signals. After receiving antigenic stimuli, T cells begin to proliferate, and the expression of immunoregulatory receptors (such as CTLA-4 and PD-1) is induced on their surface. Recent findings have revealed that these ‘immune checkpoint’ molecules control the activation as well as motility of T cells in various situations. Therefore, the outcome of tumor immunotherapy using checkpoint inhibitors is assumed to be closely related to the alteration of T cell motility, particularly in tumor-draining lymph nodes (TDLNs). In this review, we discuss the migration dynamics of T cells during their activation in TDLNs, and the roles of checkpoint molecules in T cell motility, to provide some insight into the effect of tumor immunotherapy via checkpoint blockade, in terms of T cell dynamics and the importance of TDLNs.

scholarly journals ACKR4 in Tumor Cells Regulates Dendritic Cell Migration to Tumor-Draining Lymph Nodes and T-Cell Priming

Cancers ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 5021
Author(s):  
Dechen Wangmo ◽  
Prem K. Premsrirut ◽  
Ce Yuan ◽  
William S. Morris ◽  
Xianda Zhao ◽  
...  
Keyword(s):  
T Cell ◽  
Dendritic Cell ◽  
Lymph Nodes ◽  
Mismatch Repair ◽  
Tumor Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
T Cell Priming ◽  
Draining Lymph Nodes

Colorectal cancer (CRC) is one of the most common malignancies in both morbidity and mortality. Immune checkpoint blockade (ICB) treatments have been successful in a portion of mismatch repair-deficient (dMMR) CRC patients but have failed in mismatch repair-proficient (pMMR) CRC patients. Atypical Chemokine Receptor 4 (ACKR4) is implicated in regulating dendritic cell (DC) migration. However, the roles of ACKR4 in CRC development and anti-tumor immunoregulation are not known. By analyzing human CRC tissues, transgenic animals, and genetically modified CRC cells lines, our study revealed an important function of ACKR4 in maintaining CRC immune response. Loss of ACKR4 in CRC is associated with poor immune infiltration in the tumor microenvironment. More importantly, loss of ACKR4 in CRC tumor cells, rather than stromal cells, restrains the DC migration and antigen presentation to the tumor-draining lymph nodes (TdLNs). Moreover, tumors with ACKR4 knockdown become less sensitive to immune checkpoint blockade. Finally, we identified that microRNA miR-552 negatively regulates ACKR4 expression in human CRC. Taken together, our studies identified a novel and crucial mechanism for the maintenance of the DC-mediated T-cell priming in the TdLNs. These new findings demonstrate a novel mechanism leading to immunosuppression and ICB treatment resistance in CRC.

scholarly journals Dendritic cell paucity in mismatch repair–proficient colorectal cancer liver metastases limits immune checkpoint blockade efficacy

2021 ◽  
Vol 118 (45) ◽  
pp. e2105323118
Author(s):  
William W. Ho ◽  
Igor L. Gomes-Santos ◽  
Shuichi Aoki ◽  
Meenal Datta ◽  
Kosuke Kawaguchi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
T Cells ◽  
Dendritic Cells ◽  
Dendritic Cell ◽  
Liver Metastasis ◽  
Liver Metastases ◽  
Mismatch Repair ◽  
Immune Checkpoint ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade

Liver metastasis is a major cause of mortality for patients with colorectal cancer (CRC). Mismatch repair–proficient (pMMR) CRCs make up about 95% of metastatic CRCs, and are unresponsive to immune checkpoint blockade (ICB) therapy. Here we show that mouse models of orthotopic pMMR CRC liver metastasis accurately recapitulate the inefficacy of ICB therapy in patients, whereas the same pMMR CRC tumors are sensitive to ICB therapy when grown subcutaneously. To reveal local, nonmalignant components that determine CRC sensitivity to treatment, we compared the microenvironments of pMMR CRC cells grown as liver metastases and subcutaneous tumors. We found a paucity of both activated T cells and dendritic cells in ICB-treated orthotopic liver metastases, when compared with their subcutaneous tumor counterparts. Furthermore, treatment with Feline McDonough sarcoma (FMS)-like tyrosine kinase 3 ligand (Flt3L) plus ICB therapy increased dendritic cell infiltration into pMMR CRC liver metastases and improved mouse survival. Lastly, we show that human CRC liver metastases and microsatellite stable (MSS) primary CRC have a similar paucity of T cells and dendritic cells. These studies indicate that orthotopic tumor models, but not subcutaneous models, should be used to guide human clinical trials. Our findings also posit dendritic cells as antitumor components that can increase the efficacy of immunotherapies against pMMR CRC.

scholarly journals P854 Construction of the immune landscape of durable response to checkpoint blockade therapy by integrating publicly available datasets

2020 ◽  
Vol 8 (Suppl 1) ◽  
pp. A5.2-A6
Author(s):  
Nils-Petter Rudqvist ◽  
Roberta Zappasodi ◽  
Daniel Wells ◽  
Vésteinn Thorsson ◽  
Alexandria Cogdill ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Checkpoint ◽  
Molecular Mechanisms ◽  
Cross Validation ◽  
Immune Cell ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Immune Gene ◽  
List Type ◽  
Durable Response

BackgroundImmune checkpoint blockade (ICB) has revolutionized cancer treatment. However, long-term benefits are only achieved in a small fraction of patients. Understanding the mechanisms underlying ICB activity is key to improving the efficacy of immunotherapy. A major limitation to uncovering these mechanisms is the limited number of responders within each ICB trial. Integrating data from multiple studies of ICB would help overcome this issue and more reliably define the immune landscape of durable responses. Towards this goal, we formed the TimIOs consortium, comprising researchers from the Society for Immunotherapy of Cancer Sparkathon TimIOs Initiative, the Parker Institute of Cancer Immunotherapy, the University of North Carolina-Chapel Hill, and the Institute for Systems Biology. Together, we aim to improve the understanding of the molecular mechanisms associated with defined outcomes to ICB, by building on our joint and multifaceted expertise in the field of immuno-oncology. To determine the feasibility and relevance of our approach, we have assembled a compendium of publicly available gene expression datasets from clinical trials of ICB. We plan to analyze this data using a previously reported pipeline that successfully determined main cancer immune-subtypes associated with survival across multiple cancer types in TCGA.1MethodsRNA sequencing data from 1092 patients were uniformly reprocessed harmonized, and annotated with predefined clinical parameters. We defined a comprehensive set of immunogenomics features, including immune gene expression signatures associated with treatment outcome,1,2 estimates of immune cell proportions, metabolic profiles, and T and B cell receptor repertoire, and scored all compendium samples for these features. Elastic net regression models with parameter optimization done via Monte Carlo cross-validation and leave-one-out cross-validation were used to analyze the capacity of an integrated immunogenomics model to predict durable clinical benefit following ICB treatment.ResultsOur preliminary analyses confirmed an association between the expression of an IFN-gamma signature in tumor (1) and better outcomes of ICB, highlighting the feasibility of our approach.ConclusionsIn line with analysis of pan-cancer TCGA datasets using this strategy (1), we expect to identify analogous immune subtypes characterizing baseline tumors from patients responding to ICB. Furthermore, we expect to find that these immune subtypes will have different importance in the model predicting response and survival. Results of this study will be incorporated into the Cancer Research Institute iAtlas Portal, to facilitate interactive exploration and hypothesis testing.ReferencesThorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, Yang T-H O, Porta-Pardo E. Gao GF, Plaisier CL, Eddy JA, et al. The Immune Landscape of Cancer. Immunity 2018; 48(4): 812–830.e14. https://doi.org/10.1016/j.immuni.2018.03.023.Auslander N, Zhang G, Lee JS, Frederick DT, Miao B, Moll T, Tian T, Wei Z, Madan S, Sullivan RJ, et al. Robust Prediction of Response to Immune Checkpoint Blockade Therapy in Metastatic Melanoma. Nat. Med 2018; 24(10): 1545. https://doi.org/10.1038/s41591-018-0157-9.

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