Clinical responses to adoptive T-cell transfer can be modeled in an autologous immune-humanized mouse model

Systems Biology of Cancer Metastasis

Cancer metastasis is no longer viewed as a linear cascade of events but rather as a series of concurrent, partially overlapping processes, as successfully metastasizing cells assume new phenotypes while jettisoning older behaviors. The lack of a systemic understanding of this complex phenomenon has limited progress in developing treatments for metastatic disease. Because metastasis has traditionally been investigated in distinct physiological compartments, the integration of these complex and interlinked aspects remains a challenge for both systems-level experimental and computational modeling of metastasis. Here, we present some of the current perspectives on the complexity of cancer metastasis, the multiscale nature of its progression, and a systems-level view of the processes underlying the invasive spread of cancer cells. We also highlight the gaps in our current understanding of cancer metastasis as well as insights emerging from interdisciplinary systems biology approaches to understand this complex phenomenon.

Surgery for gastrointestinal metastases of malignant melanoma - a retrospective exploratory study

BACKGROUND

Cutaneous melanoma has a rapidly increasing incidence in Sweden, and it has more than doubled in the last two decades. In recent years, new systemic treatments for patients with metastatic disease have increased overall survival. The role of surgery in the metastatic setting has been unclear, and no randomized data exist. Many surgeons still perform metastasectomies; however, the exact role probably has to be redefined. The aim of this single-institution study was to retrospectively examine the safety and efficacy of surgery in abdominal melanoma metastases and to identify prognostic and predictive factors.

METHODS

Retrospective analysis of a consecutive series of all patients with stage IV melanoma with gastrointestinal metastases that underwent abdominal surgery at a single center between January 2010 and December 2018. Fifteen patients who underwent in total 18 abdominal procedures, both acute and elective, were identified and included in the study.

RESULTS

Out of 18 laparotomies, six (33%) were emergency procedures due to ileus (n = 4), small bowel perforation (n = 1), and abdominal abscess (n = 1). Twelve procedures (66%) were elective with the most common indication being persistent anemia (58%, n = 7), abdominal pain and anemia (33%, n = 4), and abdominal pain (8%, n = 1). All procedures were performed by laparotomy. There were 19 small bowel resections, 3 partial colon resections, and 2 omental resections. Radical resection was possible in 56% (n = 10) of cases and 67% (n = 8) when only considering elective procedures. In 17 of 18 procedures (94%), there were mild or no surgical complications (Clavien-Dindo grades 0-I). The median overall survival was 14 months with a 5-year survival of 23%.

CONCLUSIONS

Patients with abdominal melanoma metastases can safely undergo resection with a high grade of radical procedures when performed in the elective setting.

TRIAL REGISTRATION

ClinicalTrials.gov , NCT03879395 . Registered 15 March 2019.

Neoantigens retention in patient derived xenograft models mediates autologous T cells activation in ovarian cancer

Ovarian cancer (OC) has an overall modest number of mutations that facilitate a functional immune infiltrate able to recognize tumor mutated antigens, or neoantigens. Although patient-derived xenografts (PDXs) can partially model the tumor mutational load and mimic response to chemotherapy, no study profiled a neoantigen-driven response in OC PDXs. Here we demonstrate that the genomic status of the primary tumor from an OC patient can be recapitulated in vivo in a PDX model, with the goal of defining autologous T cells activation by neoantigens using in silico, in vitro and in vivo approaches. By profiling the PDX mutanome we discovered three main clusters of mutations defining the expansion, retraction or conservation of tumor clones based on their variant allele frequencies (VAF). RNASeq analyses revealed a strong functional conservation between the primary tumor and PDXs, highlighted by the upregulation of antigen presenting pathways. We tested in vitro a set of 30 neoantigens for recognition by autologous T cells and identified a core of six neoantigens that define a potent T cell activation able to slow tumor growth in vivo. The pattern of recognition of these six neoantigens indicates the pre-existence of anti-tumor immunity in the patient. To evaluate the breadth of T cell activation, we performed single cell sequencing profiling the TCR repertoire upon stimulation with neoantigenic moieties and identified sequence motifs that define an oligoclonal and autologous T cell response. Overall, these results indicate that OC PDXs can be a valid tool to model OC response to immunotherapy.

Collagen density regulates the activity of tumor-infiltrating T cells

Background

Tumor progression is accompanied by dramatic remodeling of the surrounding extracellular matrix leading to the formation of a tumor-specific ECM, which is often more collagen-rich and of increased stiffness. The altered ECM of the tumor supports cancer growth and metastasis, but it is unknown if this effect involves modulation of T cell activity. To investigate if a high-density tumor-specific ECM could influence the ability of T cells to kill cancer cells, we here studied how T cells respond to 3D culture in different collagen densities.

Methods

T cells cultured in 3D conditions surrounded by a high or low collagen density were imaged using confocal fluorescent microscopy. The effects of the different collagen densities on T cell proliferation, survival, and differentiation were examined using flow cytometry. Cancer cell proliferation in similar 3D conditions was also measured. Triple-negative breast cancer specimens were analyzed for the number of infiltrating CD8+ T cells and for the collagen density. Whole-transcriptome analyses were applied to investigate in detail the effects of collagen density on T cells. Computational analyses were used to identify transcription factors involved in the collagen density-induced gene regulation. Observed changes were confirmed by qRT-PCR analysis.

Results

T cell proliferation was significantly reduced in a high-density matrix compared to a low-density matrix and prolonged culture in a high-density matrix led to a higher ratio of CD4+ to CD8+ T cells. The proliferation of cancer cells was unaffected by the surrounding collagen-density. Consistently, we observed a reduction in the number of infiltrating CD8+ T-cells in mammary tumors with high collagen-density indicating that collagen-density has a role in regulating T cell abundance in human breast cancer.

Whole-transcriptome analysis of 3D-cultured T cells revealed that a high-density matrix induces downregulation of cytotoxic activity markers and upregulation of regulatory T cell markers. These transcriptional changes were predicted to involve autocrine TGF-β signaling and they were accompanied by an impaired ability of tumor-infiltrating T cells to kill autologous cancer cells.

Conclusions

Our study identifies a new immune modulatory mechanism, which could be essential for suppression of T cell activity in the tumor microenvironment.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0556-6) contains supplementary material, which is available to authorized users.

HER2 CAR-T Cells Eradicate Uveal Melanoma and T-cell Therapy-Resistant Human Melanoma in IL2 Transgenic NOD/SCID IL2 Receptor Knockout Mice

Chimeric antigen receptors (CAR) can transmit signals akin to those from activated T-cell receptors when bound to a cell surface target. CAR-expressing T cells against CD19 can cause curative effects in leukemia and lymphoma and is approved for clinical use. However, no CAR-T therapy is currently approved for use in solid tumors. We hypothesize that the resistance of solid tumors to CAR-T can be overcome by similar means as those used to reactivate tumor-infiltrating T lymphocytes (TIL), for example, by cytokines or immune checkpoint blockade. Here we demonstrate that CAR-T cells directed against HER2 can kill uveal and cutaneous melanoma cells in vitro and in vivo. Curative effects in vivo were only observed in xenografts grown in a NOD/SCID IL2 receptor gamma (NOG) knockout mouse strain transgenic for human IL2. The effect was target-specific, as CRISPR/Cas9-mediated disruption of HER2 in the melanoma cells abrogated the killing effect of the CAR-T cells. The CAR-T cells were also able to kill melanoma cells from patients resistant to adoptive T-cell transfer (ACT) of autologous TILs. Thus, CAR-T therapy represents an option for patients that do not respond to immunotherapy with ACT of TIL or immune checkpoint blockade. In addition, our data highlight the use of IL2 transgenic NOG mice as models to prove efficacy of CAR-T-cell products, possibly even in a personalized manner. SIGNIFICANCE: These findings demonstrate that a novel humanized mouse model can help clinical translation of CAR-T cells against uveal and cutaneous melanoma that do not respond to TIL therapy or immune checkpoint blockade.

Humanized Mouse Models of Rheumatoid Arthritis for Studies on Immunopathogenesis and Preclinical Testing of Cell-Based Therapies

Rodent models of rheumatoid arthritis (RA) have been used over decades to study the immunopathogenesis of the disease and to explore intervention strategies. Nevertheless, mouse models of RA reach their limit when it comes to testing of new therapeutic approaches such as cell-based therapies. Differences between the human and the murine immune system make it difficult to draw reliable conclusions about the success of immunotherapies. To overcome this issue, humanized mouse models have been established that mimic components of the human immune system in mice. Two main strategies have been pursued for humanization: the introduction of human transgenes such as human leukocyte antigen molecules or specific T cell receptors, and the generation of mouse/human chimera by transferring human cells or tissues into immunodeficient mice. Recently, both approaches have been combined to achieve more sophisticated humanized models of autoimmune diseases. This review discusses limitations of conventional mouse models of RA-like disease and provides a closer look into studies in humanized mice exploring their usefulness and necessity as preclinical models for testing of cell-based therapies in autoimmune diseases such as RA.

Implantable pre-metastatic niches for the study of the microenvironmental regulation of disseminated human tumour cells

Cancer survivors often carry disseminated tumour cells (DTCs), yet owing to DTC dormancy they do not relapse from treatment. Understanding how the local microenvironment regulates the transition of DTCs from a quiescent state to active proliferation could suggest new therapeutic strategies to prevent or delay the formation of metastases. Here, we show that implantable biomaterial microenvironments incorporating human stromal cells, immune cells and cancer cells can be used to examine the post-dissemination phase of the evolution of the tumour microenvironment. After subdermal implantation in mice, porous hydrogel scaffolds seeded with human bone marrow stromal cells form a vascularized niche and recruit human circulating tumour cells released from an orthotopic prostate tumour xenograft. Systemic injection of human peripheral blood mononuclear cells slowed the evolution of the active metastatic niches but did not change the rate of overt metastases, as the ensuing inflammation promoted the formation of DTC colonies. Implantable pre-metastatic niches might enable the study of DTC colonization and proliferation, and facilitate the development of effective anti-metastatic therapies.

Establishment of peripheral blood mononuclear cell-derived humanized lung cancer mouse models for studying efficacy of PD-L1/PD-1 targeted immunotherapy

Animal models used to evaluate efficacies of immune checkpoint inhibitors are insufficient or inaccurate. We thus examined two xenograft models used for this purpose, with the aim of optimizing them. One method involves the use of peripheral blood mononuclear cells and cell line-derived xenografts (PBMCs-CDX model). For this model, we implanted human lung cancer cells into NOD-scid-IL2Rg-/- (NSI) mice, followed by injection of human PBMCs. The second method involves the use of hematopoietic stem and progenitor cells and CDX (HSPCs-CDX model). For this model, we first reconstituted the human immune system by transferring human CD34+ hematopoietic stem and progenitor cells (HSPCs-derived humanized model) and then transplanted human lung cancer cells. We found that the PBMCs-CDX model was more accurate in evaluating PD-L1/PD-1 targeted immunotherapies. In addition, it took only four weeks with the PBMCs-CDX model for efficacy evaluation, compared to 10-14 weeks with the HSPCs-CDX model. We then further established PBMCs-derived patient-derived xenografts (PDX) models, including an auto-PBMCs-PDX model using cancer and T cells from the same tumor, and applied them to assess the antitumor efficacies of anti-PD-L1 antibodies. We demonstrated that this PBMCs-derived PDX model was an invaluable tool to study the efficacies of PD-L1/PD-1 targeted cancer immunotherapies. Overall, we found our PBMCs-derived models to be excellent preclinical models for studying immune checkpoint inhibitors.

Mouse Models for Cancer Immunotherapy Research

Immunotherapy has revolutionized cancer therapy, largely attributed to the success of immune-checkpoint blockade. However, there are subsets of patients across multiple cancers who have not shown robust responses to these agents. A major impediment to progress in the field is the availability of faithful mouse models that recapitulate the complexity of human malignancy and immune contexture within the tumor microenvironment. These models are urgently needed across all malignancies to interrogate and predict antitumor immune responses and therapeutic efficacy in clinical trials. Herein, we seek to review pros and cons of different cancer mouse models, and how they can be used as platforms to predict efficacy and resistance to cancer immunotherapies.Significance: Although immunotherapy has shown substantial benefit in the treatment of a variety of malignancies, a key hurdle toward the advancement of these therapies is the availability of immunocompetent preclinical mouse models that recapitulate human disease. Here, we review the evolution of preclinical mouse models and their utility as coclinical platforms for mechanistic interrogation of cancer immunotherapies. Cancer Discov; 8(11); 1358-65. ©2018 AACR.

Chemokine Receptors and Exercise to Tackle the Inadequacy of T Cell Homing to the Tumor Site

While cancer immune therapy has revolutionized the treatment of metastatic disease across a wide range of cancer diagnoses, a major limiting factor remains with regard to relying on adequate homing of anti-tumor effector cells to the tumor site both prior to and after therapy. Adoptive cell transfer (ACT) of autologous T cells have improved the outlook of patients with metastatic melanoma. Prior to the approval of checkpoint inhibitors, this strategy was the most promising. However, while response rates of up to 50% have been reported, this strategy is still rather crude. Thus, improvements are needed and within reach. A hallmark of the developing tumor is the evasion of immune destruction. Achieved through the recruitment of immune suppressive cell subsets, upregulation of inhibitory receptors and the development of physical and chemical barriers (such as poor vascularization and hypoxia) leaves the microenvironment a hostile destination for anti-tumor T cells. In this paper, we review the emerging strategies of improving the homing of effector T cells (TILs, CARs, TCR engineered T cells, etc.) through genetic engineering with chemokine receptors matching the chemokines of the tumor microenvironment. While this strategy has proven successful in several preclinical models of cancer and the strategy has moved into the first phase I/II clinical trial in humans, most of these studies show a modest (doubling) increase in tumor infiltration of effector cells, which raises the question of whether road blocks must be tackled for efficient homing. We propose a role for physical exercise in modulating the tumor microenvironment and preparing the platform for infiltration of anti-tumor immune cells. In a time of personalized medicine and genetic engineering, this "old tool" may be a way to augment efficacy and the depth of response to immune therapy.

Studying cancer immunotherapy using patient-derived xenografts (PDXs) in humanized mice

Cancer immunotherapy is a promising way to eliminate tumor cells by using the patient’s own immune system. Selecting the appropriate animal models to develop or validate preclinical immunotherapeutic trials is now an important aspect of many cancer research programs. Here we discuss the advantages and limitations of using genetically engineered immunodeficient mouse models, patient-derived xenografts (PDXs), and humanized mouse models for developing and testing immunotherapeutic strategies.

Improvements to mouse models for cancer immunotherapy could enhance the precision of new drugs. Immunotherapy trials require genetically modified animal models, including ‘humanized’ mice with a functioning human immune system, and patient-derived xenograft (PDX) mice, in which cells from patients’ tumors are implanted into immunodeficient mice. Charles Lee at the Jackson Laboratory for Genomic Medicine in Farmington, USA, Yeun-Jun Chung at the Catholic University of Korea in Seoul, and co-workers reviewed developments in both PDX and humanized-PDX mouse models for immunotherapy trials. PDX models improve the chances of finding novel biomarkers for drug development. However, humanized PDX mouse models will allow researchers to study diverse cancers in tumour and immune environments as close as possible to those of humans.

How to find the right drug for each patient? Advances and challenges in pharmacogenomics

Cancer is a highly heterogeneous disease with complex underlying biology. For these reasons, effective cancer treatment is still a challenge. Nowadays, it is clear that a cancer therapy that fits all the cases cannot be found, and as a result the design of therapies tailored to the patient's molecular characteristics is needed. Pharmacogenomics aims to study the relationship between an individual's genotype and drug response. Scientists use different biological models, ranging from cell lines to mouse models, as proxies for patients for preclinical and translational studies. The rapid development of "-omics" technologies is increasing the amount of features that can be measured in these models, expanding the possibilities of finding predictive biomarkers of drug response. Finding these relationships requires diverse computational approaches ranging from machine learning to dynamic modeling. Despite major advances, we are still far from being able to precisely predict drug efficacy in cancer models, let alone directly on patients. We believe that the new experimental techniques and computational approaches covered in this review will bring us closer to this goal.

A patient-derived xenograft pre-clinical trial reveals treatment responses and a resistance mechanism to karonudib in metastatic melanoma

Karonudib (TH1579) is a novel compound that exerts anti-tumor activities and has recently entered phase I clinical testing. The aim of this study was to conduct a pre-clinical trial in patient-derived xenografts to identify the possible biomarkers of response or resistance that could guide inclusion of patients suffering from metastatic melanoma in phase II clinical trials. Patient-derived xenografts from 31 melanoma patients with metastatic disease were treated with karonudib or a vehicle for 18 days. Treatment responses were followed by measuring tumor sizes, and the models were categorized in the response groups. Tumors were harvested and processed for RNA sequencing and protein analysis. To investigate the effect of karonudib on T-cell-mediated anti-tumor activities, tumor-infiltrating T cells were injected in mice carrying autologous tumors and the mice treated with karonudib. We show that karonudib has heterogeneous anti-tumor effect on metastatic melanoma. Thus, based on the treatment responses, we could divide the 31 patient-derived xenografts in three treatment groups: progression group (32%), suppression group (42%), and regression group (26%). Furthermore, we show that karonudib has anti-tumor effect, irrespective of major melanoma driver mutations. Also, we identify high expression of ABCB1, which codes for p-gp pumps as a resistance biomarker. Finally, we show that karonudib treatment does not hamper T-cell-mediated anti-tumor responses. These findings can be used to guide future use of karonudib in clinical use with a potential approach as precision medicine.

Transgenic Mouse Models in Cancer Research

The use of existing mouse models in cancer research is of utmost importance as they aim to explore the casual link between candidate cancer genes and carcinogenesis as well as to provide models to develop and test new therapies. However, faster progress in translating mouse cancer model research into the clinic has been hampered due to the limitations of these models to better reflect the complexities of human tumors. Traditionally, immunocompetent and immunodeficient mice with syngeneic and xenografted tumors transplanted subcutaneously or orthotopically have been used. These models are still being widely employed for many different types of studies, in part due to their widespread availability and low cost. Other types of mouse models used in cancer research comprise transgenic mice in which oncogenes can be constitutively or conditionally expressed and tumor-suppressor genes silenced using conventional methods, such as retroviral infection, microinjection of DNA constructs, and the so-called "gene-targeted transgene" approach. These traditional transgenic models have been very important in studies of carcinogenesis and tumor pathogenesis, as well as in studies evaluating the development of resistance to therapy. Recently, the clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing approach has revolutionized the field of mouse cancer models and has had a profound and rapid impact on the development of more effective systems to study human cancers. The CRISPR/Cas9-based transgenic models have the capacity to engineer a wide spectrum of mutations found in human cancers and provide solutions to problems that were previously unsolvable. Recently, humanized mouse xenograft models that accept patient-derived xenografts and CD34+ cells were developed to better mimic tumor heterogeneity, the tumor microenvironment, and cross-talk between the tumor and stromal/immune cells. These features make them extremely valuable models for the evaluation of investigational cancer therapies, specifically new immunotherapies. Taken together, improvements in both the CRISPR/Cas9 system producing more valid mouse models and in the humanized mouse xenograft models resembling complex interactions between the tumor and its environment might represent one of the successful pathways to precise individualized cancer therapy, leading to improved cancer patient survival and quality of life.

Case study: patient-derived clear cell adenocarcinoma xenograft model longitudinally predicts treatment response

There has been little progress in the use of patient-derived xenografts (PDX) to guide individual therapeutic strategies. In part, this can be attributed to the operational challenges of effecting successful engraftment and testing multiple candidate drugs in a clinically workable timeframe. It also remains unclear whether the ancestral tumor will evolve along similar evolutionary trajectories in its human and rodent hosts in response to similar selective pressures (i.e., drugs). Herein, we combine a metastatic clear cell adenocarcinoma PDX with a timely 3 mouse x 1 drug experimental design, followed by a co-clinical trial to longitudinally guide a patient's care. Using this approach, we accurately predict response to first- and second-line therapies in so far as tumor response in mice correlated with the patient's clinical response to first-line therapy (gemcitabine/nivolumab), development of resistance and response to second-line therapy (paclitaxel/neratinib) before these events were observed in the patient. Treatment resistance to first-line therapy in the PDX is coincident with biologically relevant changes in gene and gene set expression, including upregulation of phase I/II drug metabolism (CYP2C18, UGT2A, and ATP2A1) and DNA interstrand cross-link repair (i.e., XPA, FANCE, FANCG, and FANCL) genes. A total of 5.3% of our engrafted PDX collection is established within 2 weeks of implantation, suggesting our experimental designs can be broadened to other cancers. These findings could have significant implications for PDX-based avatars of aggressive human cancers.

Personalized Medicine in Malignant Melanoma: Towards Patient Tailored Treatment

Despite enormous international efforts, skin melanoma is still a major clinical challenge. Melanoma takes a top place among the most common cancer types and it has one of the most rapidly increasing incidences in many countries around the world. Until recent years, there have been limited options for effective systemic treatment of disseminated melanoma. However, lately, we have experienced a rapid advancement in the understanding of the biology and molecular background of the disease. This has led to new molecular classifications and the development of more effective targeted therapies adapted to distinct melanoma subtypes. Not only are these treatments more effective but they can be rationally prescribed to the patients standing to benefit. As such, melanoma management has now become one of the most developed for personalized medicine. The aim of the present paper is to summarize the current knowledge on melanoma molecular classification, predictive markers, combination therapies, as well as emerging new treatments.