Multipanel mass cytometry reveals anti-PD-1 therapy-mediated B and T cell compartment remodeling in tumor-draining lymph nodes

Tumor-draining lymph nodes - friend or foe during immune checkpoint therapy?

The pivotal role of tumor-draining lymph nodes (TDLNs) in supporting antitumor immunity and serving as sites for cancer metastasis presents a clinical challenge: eliminate tumors while preserving antitumor immune responses. In this article, we explore the initiation of tumor-specific immune responses within lymph nodes (LNs), the immunocompromised microenvironment induced by tumors within LNs, and the crucial involvement of TDLNs in immunotherapy. Additionally, we examine the clinical prospects of modifying surgical procedures or therapy sequences to enhance the efficacy of cancer treatment.

The role and clinical significance of tumor-draining lymph nodes in tumor progression and immunotherapy

Tumor-draining lymph nodes (TDLNs) play a pivotal role in tumor growth and the immune response, activating immune cells such as CD8 + T cells and natural killer cells to combat tumors. However, tumors can subvert TDLNs to avoid immune attack. Initially, TDLNs stimulate a robust antitumor response, but as tumor evolve, they infiltrate with immunosuppressive cells that alter the TDLN environment and potentially promote metastasis. Immunotherapy, including immune checkpoint inhibitor (ICI), have emerged as a potential solution to this challenge by reconfiguring the TDLN environment to enhance immune responses and influence the immune status of the primary tumor. The integrity of the TDLNs is crucial for the efficacy of immunotherapy. Conventional surgery often removes TDLNs, but this may impede immune system function and the effectiveness of immunotherapy. It is therefore recommended that removal of TDLNs be considered after neoadjuvant treatment rather than before adjuvant treatment. Accurate identification of patients who require post-neoadjuvant TDLN removal and the determination of metastatic nodes is of paramount importance in tailoring treatment plans, optimizing of patient outcomes, and improving quality of life.

Prognostic patterns in invasion lymph nodes of lung adenocarcinoma reveal distinct tumor microenvironments

Tumor-draining lymph nodes (TDLNs) are usually the first station of tumor metastasis in lung cancer. TDLNs+ have distinct pathomorphologic and tumor microenvironment (TME)-compositional patterns, which still need to be thoroughly investigated in lung adenocarcinoma (LUAD). Here, we enrolled 312 LUAD patients with TDLNs+ from our institution between 2015 and 2019. 3DHISTECH was used to scan all of the TDLNs+. Based on morphologic features, TDLNs+ patterns were classified as polarized-type or scattered-type, and TME-compositional patterns were classified as colloid-type, necrosis-type, specific-type, and common-type. Multivariate analysis revealed an increased risk of early recurrence associated with scattered-type (HR 2.37, 95% CI: 1.06-5.28), colloid-type (HR 1.95, 95% CI: 1.03-3.67), and necrosis-type (HR 2.21, 95% CI: 1.13-4.89). NanoString transcriptional analysis revealed an immunosuppression and vascular invasion hallmark in scattered and necrosis patterns and an immunoactivated hallmark in polarized and common patterns. According to imaging mass cytometry (IMC), the scattered and necrosis patterns revealed that germinal centers (GC) were compromised, GCB cell and T cell proliferation were deficient, tumor cells had the potential for proliferation, and the immune attack may be weaker. In this study, we present evidence that LUAD patients have distinct patterns and immune hallmarks of TDLNs+ related to their prognosis.

Killing two birds with one stone: Abscopal effect mechanism and its application prospect in radiotherapy

Abscopal effects are characterized by the emergence of neoplasms in regions unrelated to the primary radiation therapy site, displaying a gradual attenuation or regression throughout the progression of radiation therapy, which have been of interest to scientists since Mole's proposal in 1953. The incidence of abscopal effects in radiation therapy is intricately linked to the immune system, with both innate and adaptive immune responses playing crucial roles. Biological factors impacting abscopal effects ultimately exert their influence on the intricate workings of the immune system. Although abscopal effects are rarely observed in clinical cases, the underlying mechanism remains uncertain. This article examines the biological and physical factors influencing abscopal effects of radiotherapy. Through a review of preclinical and clinical studies, this article aims to offer a comprehensive understanding of abscopal effects and proposes new avenues for future research in this field. The findings presented in this article serve as a valuable reference for researchers seeking to explore this topic in greater depth.

Anti-PD-1 therapy triggers Tfh cell-dependent IL-4 release to boost CD8 T cell responses in tumor-draining lymph nodes

Anti-PD-1 therapy targets intratumoral CD8+ T cells to promote clinical responses in cancer patients. Recent evidence suggests an additional activity in the periphery, but the underlying mechanism is unclear. Here, we show that anti-PD-1 mAb enhances CD8+ T cell responses in tumor-draining lymph nodes by stimulating cytokine production in follicular helper T cells (Tfh). In two different models, anti-PD-1 mAb increased the activation and proliferation of tumor-specific T cells in lymph nodes. Surprisingly, anti-PD-1 mAb did not primarily target CD8+ T cells but instead stimulated IL-4 production by Tfh cells, the major population bound by anti-PD-1 mAb. Blocking IL-4 or inhibiting the Tfh master transcription factor BCL6 abrogated anti-PD-1 mAb activity in lymph nodes while injection of IL-4 complexes was sufficient to recapitulate anti-PD-1 mAb activity. A similar mechanism was observed in a vaccine model. Finally, nivolumab also boosted human Tfh cells in humanized mice. We propose that Tfh cells and IL-4 play a key role in the peripheral activity of anti-PD-1 mAb.

Tumor-draining lymph nodes: opportunities, challenges, and future directions in colorectal cancer immunotherapy

Tumor-draining lymph nodes (TDLNs) are potential immunotherapy targets that could expand the population of patients with colorectal cancer (CRC) who may benefit from immunotherapy. Currently, pathological detection of tumor cell infiltration limits the acquisition of immune information related to the resected lymph nodes. Understanding the immune function and metastatic risk of specific stages of lymph nodes can facilitate better discussions on the removal or preservation of lymph nodes, as well as the timing of immunotherapy. This review summarized the contribution of TDLNs to CRC responses to immune checkpoint blockade therapy, local immunotherapy, adoptive cell therapy, and cancer vaccines, and discussed the significance of these findings for the development of diagnostics based on TDLNs and the potential implications for guiding immunotherapy after a definitive diagnosis. Molecular pathology and immune spectrum diagnosis of TDLNs will promote significant advances in the selection of immunotherapy options and predicting treatment efficacy.

Systems immunology spanning tumors, lymph nodes, and periphery

The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.

Lymph node metastasis and tumor-educated immune tolerance: Potential therapeutic targets against distant metastasis

Lymph node metastasis has been shown to positively associated with the prognosis of many cancers. However, in clinical treatment, lymphadenectomy is not always successful, suggesting that immune cells in the tumor and sentinel lymph nodes still play a pivotal role in tumor immunosuppression. Recent studies had shown that tumors can tolerate immune cells through multiple strategies, including tumor-induced macrophage reprogramming, T cells inactivation, production of B cells pathogenic antibodies and activation of regulatory T cells to promote tumor colonization, growth, and metastasis in lymph nodes. We reviewed the bidirectional effect of immune cells on anti-tumor or promotion of cancer cell metastasis during lymph node metastasis, and the mechanisms by which malignant cancer cells modify immune cells to create a more favorable environment for the growth and survival of cancer cells. Research and treatment strategies focusing on the immune system in lymph nodes and potential immune targets in lymph node metastasis were also be discussed.

Novel strategies for cancer immunotherapy: counter-immunoediting therapy

The advent of immunotherapy has made an indelible mark on the field of cancer therapy, especially the application of immune checkpoint inhibitors in clinical practice. Although immunotherapy has proven its efficacy and safety in some tumors, many patients still have innate or acquired resistance to immunotherapy. The emergence of this phenomenon is closely related to the highly heterogeneous immune microenvironment formed by tumor cells after undergoing cancer immunoediting. The process of cancer immunoediting refers to the cooperative interaction between tumor cells and the immune system that involves three phases: elimination, equilibrium, and escape. During these phases, conflicting interactions between the immune system and tumor cells result in the formation of a complex immune microenvironment, which contributes to the acquisition of different levels of immunotherapy resistance in tumor cells. In this review, we summarize the characteristics of different phases of cancer immunoediting and the corresponding therapeutic tools, and we propose normalized therapeutic strategies based on immunophenotyping. The process of cancer immunoediting is retrograded through targeted interventions in different phases of cancer immunoediting, making immunotherapy in the context of precision therapy the most promising therapy to cure cancer.

Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer

Pancreatic cancer is currently the third leading cause of cancer death in the United States. The clinical hallmarks of this disease include abdominal pain that radiates to the back, the presence of a hypoenhancing intrapancreatic lesion on imaging, and widespread liver metastases. Technologies such as tissue clearing and three-dimensional (3D) reconstruction of digitized serially sectioned hematoxylin and eosin-stained slides can be used to visualize large (up to 2- to 3-centimeter cube) tissues at cellular resolution. When applied to human pancreatic cancers, these 3D visualization techniques have provided novel insights into the basis of a number of the clinical characteristics of this disease. Here, we describe the clinical features of pancreatic cancer, review techniques for clearing and the 3D reconstruction of digitized microscope slides, and provide examples that illustrate how 3D visualization of human pancreatic cancer at the microscopic level has revealed features not apparent in 2D microscopy and, in so doing, has closed the gap between bench and bedside. Compared with animal models and 2D microscopy, studies of human tissues in 3D can reveal the difference between what can happen and what does happen in human cancers.

Analyzing high-dimensional cytometry data using FlowSOM

The dimensionality of cytometry data has strongly increased in the last decade, and in many situations the traditional manual downstream analysis becomes insufficient. The field is therefore slowly moving toward more automated approaches, and in this paper we describe the protocol for analyzing high-dimensional cytometry data using FlowSOM, a clustering and visualization algorithm based on a self-organizing map. FlowSOM is used to distinguish cell populations from cytometry data in an unsupervised way and can help to gain deeper insights in fields such as immunology and oncology. Since the original FlowSOM publication (2015), we have validated the tool on a wide variety of datasets, and to write this protocol, we made use of this experience to improve the user-friendliness of the package (e.g., comprehensive functions replacing commonly required scripts). Where the original paper focused mainly on the algorithm description, this protocol offers user guidelines on how to implement the procedure, detailed parameter descriptions and troubleshooting recommendations. The protocol provides clearly annotated R code, and is therefore relevant for all scientists interested in computational high-dimensional analyses without requiring a strong bioinformatics background. We demonstrate the complete workflow, starting from data preparation (such as compensation, transformation and quality control), including detailed discussion of the different FlowSOM parameters and visualization options, and concluding with how the results can be further used to answer biological questions, such as statistical comparison between groups of interest. An average FlowSOM analysis takes 1-3 h to complete, though quality issues can increase this time considerably.

Systemic inhibition of PTPN22 augments anticancer immunity

Both epidemiologic and cellular studies in the context of autoimmune diseases have established that protein tyrosine phosphatase non-receptor type 22 (PTPN22) is a key regulator of T cell receptor (TCR) signaling. However, its mechanism of action in tumors and its translatability as a target for cancer immunotherapy have not been established. Here we show that a germline variant of PTPN22, rs2476601, portended a lower likelihood of cancer in patients. PTPN22 expression was also associated with markers of immune regulation in multiple cancer types. In mice, lack of PTPN22 augmented antitumor activity with greater infiltration and activation of macrophages, natural killer (NK) cells, and T cells. Notably, we generated a novel small molecule inhibitor of PTPN22, named L-1, that phenocopied the antitumor effects seen in genotypic PTPN22 knockout. PTPN22 inhibition promoted activation of CD8+ T cells and macrophage subpopulations toward MHC-II expressing M1-like phenotypes, both of which were necessary for successful antitumor efficacy. Increased PD1-PDL1 axis in the setting of PTPN22 inhibition could be further leveraged with PD1 inhibition to augment antitumor effects. Similarly, cancer patients with the rs2476601 variant responded significantly better to checkpoint inhibitor immunotherapy. Our findings suggest that PTPN22 is a druggable systemic target for cancer immunotherapy.

Multi-omic profiling of lung and liver tumor microenvironments of metastatic pancreatic cancer reveals site-specific immune regulatory pathways

BACKGROUND

The majority of pancreatic ductal adenocarcinomas (PDAC) are diagnosed at the metastatic stage, and standard therapies have limited activity with a dismal 5-year survival rate of only 8%. The liver and lung are the most common sites of PDAC metastasis, and each have been differentially associated with prognoses and responses to systemic therapies. A deeper understanding of the molecular and cellular landscape within the tumor microenvironment (TME) metastasis at these different sites is critical to informing future therapeutic strategies against metastatic PDAC.

RESULTS

By leveraging combined mass cytometry, immunohistochemistry, and RNA sequencing, we identify key regulatory pathways that distinguish the liver and lung TMEs in a preclinical mouse model of metastatic PDAC. We demonstrate that the lung TME generally exhibits higher levels of immune infiltration, immune activation, and pro-immune signaling pathways, whereas multiple immune-suppressive pathways are emphasized in the liver TME. We then perform further validation of these preclinical findings in paired human lung and liver metastatic samples using immunohistochemistry from PDAC rapid autopsy specimens. Finally, in silico validation with transfer learning between our mouse model and TCGA datasets further demonstrates that many of the site-associated features are detectable even in the context of different primary tumors.

CONCLUSIONS

Determining the distinctive immune-suppressive features in multiple liver and lung TME datasets provides further insight into the tissue specificity of molecular and cellular pathways, suggesting a potential mechanism underlying the discordant clinical responses that are often observed in metastatic diseases.

A global live cell barcoding approach for multiplexed mass cytometry profiling of mouse tumors

With the advent of cancer immunology, mass cytometry has been increasingly employed to characterize the responses to cancer therapies and the tumor microenvironment (TME). One of its most notable applications is efficient multiplexing of samples into batches by dedicating a number of metal isotope channels to barcodes, enabling robust data acquisition and analysis. Barcoding is most effective when markers are present in all cells of interest. While CD45 has been shown to be a reliable marker for barcoding all immune cells in a given sample, a strategy to reliably barcode mouse cancer cells has not been demonstrated. To this end, we identified CD29 and CD98 as markers widely expressed by commonly used mouse cancer cell lines. We conjugated anti-CD29 and anti-CD98 antibodies to cadmium or indium metals and validated their utility in 10-plex barcoding of live cells. Finally, we established a potentially novel barcoding system incorporating the combination of CD29, CD98, and CD45 to multiplex 10 tumors from s.c. MC38 and KPC tumor models, while successfully recapitulating the known contrast in the PD1-PDL1 axis between the 2 models. The ability to barcode tumor cells along with immune cells empowers the interrogation of the tumor-immune interactions in mouse TME studies.

Progression of Metastasis through Lymphatic System

Lymph nodes are the most common sites of metastasis in cancer patients. Nodal disease status provides great prognostic power, but how lymph node metastases should be treated is under debate. Thus, it is important to understand the mechanisms by which lymph node metastases progress and how they can be targeted to provide therapeutic benefits. In this review, we focus on delineating the process of cancer cell migration to and through lymphatic vessels, survival in draining lymph nodes and further spread to other distant organs. In addition, emerging molecular targets and potential strategies to inhibit lymph node metastasis are discussed.

Prognostic Value of Deep Learning-Mediated Treatment Monitoring in Lung Cancer Patients Receiving Immunotherapy

BACKGROUND

Checkpoint inhibitors provided sustained clinical benefit to metastatic lung cancer patients. Nonetheless, prognostic markers in metastatic settings are still under research. Imaging offers distinctive advantages, providing whole-body information non-invasively, while routinely available in most clinics. We hypothesized that more prognostic information can be extracted by employing artificial intelligence (AI) for treatment monitoring, superior to 2D tumor growth criteria.

METHODS

A cohort of 152 stage-IV non-small-cell lung cancer patients (NSCLC) (73 discovery, 79 test, 903CTs), who received nivolumab were retrospectively collected. We trained a neural network to identify morphological changes on chest CT acquired during patients' follow-ups. A classifier was employed to link imaging features learned by the network with overall survival.

RESULTS

Our results showed significant performance in the independent test set to predict 1-year overall survival from the date of image acquisition, with an average area under the curve (AUC) of 0.69 (p < 0.01), up to AUC 0.75 (p < 0.01) in the first 3 to 5 months of treatment, and 0.67 AUC (p = 0.01) for durable clinical benefit (6 months progression-free survival). We found the AI-derived survival score to be independent of clinical, radiological, PDL1, and histopathological factors. Visual analysis of AI-generated prognostic heatmaps revealed relative prognostic importance of morphological nodal changes in the mediastinum, supraclavicular, and hilar regions, lung and bone metastases, as well as pleural effusions, atelectasis, and consolidations.

CONCLUSIONS

Our results demonstrate that deep learning can quantify tumor- and non-tumor-related morphological changes important for prognostication on serial imaging. Further investigation should focus on the implementation of this technique beyond thoracic imaging.

Cell and tissue engineering in lymph nodes for cancer immunotherapy

In cancer, lymph nodes (LNs) coordinate tumor antigen presentation necessary for effective antitumor immunity, both at the levels of local cellular interactions and tissue-level organization. In this review, we examine how LNs may be engineered to improve the therapeutic outcomes of cancer immunotherapy. At the cellular scale, targeting the LNs impacts the potency of cancer vaccines, immune checkpoint blockade, and adoptive cell transfer. On a tissue level, macro-scale biomaterials mimicking LN features can function as immune niches for cell reprogramming or delivery in vivo, or be utilized in vitro to enable preclinical testing of drugs and vaccines. We additionally review strategies to induce ectopic lymphoid sites reminiscent of LNs that may improve antitumor T cell priming.

Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma

To define the cellular composition and architecture of cutaneous squamous cell carcinoma (cSCC), we combined single-cell RNA sequencing with spatial transcriptomics and multiplexed ion beam imaging from a series of human cSCCs and matched normal skin. cSCC exhibited four tumor subpopulations, three recapitulating normal epidermal states, and a tumor-specific keratinocyte (TSK) population unique to cancer, which localized to a fibrovascular niche. Integration of single-cell and spatial data mapped ligand-receptor networks to specific cell types, revealing TSK cells as a hub for intercellular communication. Multiple features of potential immunosuppression were observed, including T regulatory cell (Treg) co-localization with CD8 T cells in compartmentalized tumor stroma. Finally, single-cell characterization of human tumor xenografts and in vivo CRISPR screens identified essential roles for specific tumor subpopulation-enriched gene networks in tumorigenesis. These data define cSCC tumor and stromal cell subpopulations, the spatial niches where they interact, and the communicating gene networks that they engage in cancer.