Detection of response to tumor microenvironment–targeted cellular immunotherapy using nano-radiomics – Science Advances

INTRODUCTION
Cellular immunotherapies such as chimeric antigen receptor (CAR)bearing T cells have shown efficacy in clinical trials of hematologic malignancies (1). However, the efficacy in patients with advanced solid tumors has been low (2). Solid tumors have inhibitory microenvironments that limit the efficacy of targeted therapies (3). Myeloid-derived suppressor cells (MDSCs) play a central role in maintaining the tumor microenvironment (TME) of these solid tumors by suppressing host immunity, establishing new vasculature, and remodeling tissue with tumor-supportive stromal elements (4). The frequency of intratumoral MDSCs correlates with cancer stage, disease progression, and resistance to standard chemo- and radiotherapy (5). Hence, effective immunotherapy for solid tumors will involve strategies that reverse the inhibitory environment by targeting key components of the TME such as MDSCs. As TME-directed therapies emerge, methods to detect changes within the TME will be required to monitor their efficacy.
Response to TME-directed immunotherapy has been difficult to assess by biopsy due to tumor heterogeneity and the impracticality of repeated biopsy. In vivo imaging provides a noninvasive approach for studying whole-tumor dynamics in four-dimensional (4D) domain (3D space + time) and therefore allows the elucidation of inter- and intratumor heterogeneity that is not appreciated using analysis of biopsy samples or 2D microscopy-based techniques (6, 7). However, standard imaging-derived tumor metrics, such as tumor volume derived from conventional computed tomography (CT) and magnetic resonance imaging (MRI), are likely to be ineffective in the assessment of early efficacy of TME-directed therapies. This is because (i) the burden of immunosuppressive cells is substantially low compared with tumor cells in solid tumors, and thus, acute changes in tumor size may not be evident despite alterations in immunosuppressive components like MDSCs, and (ii) the effects of TME-directed therapies on tumor growth are often indirect and delayed (8, 9). Thus, there is a need to investigate advanced imaging methods that may provide early biomarkers of efficacy to immune-based TME-directed therapies.
Radiomics is an emerging field in which 3D images are analyzed to extract quantitative imaging features such as intensity, shape, size, morphology, and texture that can objectively define phenotypic characteristics of tumors (10, 11). These quantitative methods may enable detection of subtle changes in tumor morphology that are not evident by standard imaging tumor metrics. While such methods have been investigated to evaluate tumor response to checkpoint blockade therapies, no preclinical or clinical studies have been conducted to investigate their utility in the context of cellular immunotherapies. Because of increasing interest and ongoing clinical trials in the emerging field of cell-based cancer therapies, we investigated whether the application of radiomics to the human TME would allow for detection of subtle changes in tumor morphology produced after TME-directed cellular immunotherapy.
In prior work, we reported a preclinical xenograft TME model in which human solid tumor cells grow in the presence of human MDSCs and reported the efficacy of gene-modified human natural killer (NK) cells in depleting intratumoral MDSCs (12). NK cells modified to express a chimeric version of the NK cytotoxicity receptor NKG2D, whose ligands are overexpressed on human MDSCs, directly lysed human MDSCs and secreted immune-promoting cytokines. Furthermore, we showed that depletion of MDSCs via gene-modified NK cells by itself did not result in tumor regression or improvement in overall survival but did create a more favorable TME that allowed enhanced antitumor activity of subsequently infused tumor-redirected T cells (12). Thus, we established a model to study the immediate effects of TME-directed cellular immunotherapy that affects immunosuppressive components of the TME such as MDSCs but without mediating direct antitumor effects.
In the current work, we have further characterized the immunosuppressive nature of this unique preclinical TME model and used it to investigate radiomic phenotypes indicative of response to MDSC-directed cellular immunotherapy. Because MDSCs play a central role in angiogenesis and shaping of tumor vasculature, radiomic analysis was performed on high-resolution contrast-enhanced CT images acquired using a long circulating nanoparticle contrast agent. The long blood half-life and the unique ability of nanoparticles to extravasate and accumulate in perivascular regions of high vascular permeability facilitate 3D interrogation of MDSC-influenced tumor vascular architecture (13, 14). Thus, radiomic analysis of nanoparticle contrastenhanced CT imaging features was used to follow changes in MDSC composition within the TME. We use the term nano-radiomics to refer to radiomic analysis of nanoparticle contrastenhanced images and report the first of its kind study. We show that nano-radiomic analysis allows the extraction of quantitative features associated with response to MDSC-directed cellular immunotherapy, a clinically useful finding that may be readily applied during cellular therapy trials to noninvasively assess changes in the TME.
DISCUSSION
TME-directed cellular immunotherapies are undergoing preclinical and clinical development (15). These use live engineered cells that adapt to changing conditions so that they may survive, home, extravasate, and traffic to key intratumoral sites, all while maintaining antitumor effector functions and therefore are distinctly different from checkpoint blockade immunotherapies. Because of the indirect and often delayed effects of TME-targeting strategies on tumor growth, advanced imaging methods that enable detection of response to these therapies would play an important role in patient management. In this preclinical study, we investigated a nano-radiomics approach for identifying quantitative imaging features within a tumor indicative of phenotypic changes after TME-directed cellular immunotherapy. In a TME xenograft model comprising human MDSCs, we show that response to MDSC-directed cellular immunotherapy did not correlate with changes in imaging-derived tumor size, a standard clinical metric for disease evaluation. In contrast, radiomic analysis performed on segmented tumor volumes generated from nanoparticle contrastenhanced delayed CT, CT angio, and noncontrast T2w-MR images revealed RFs that correlated with tumor changes after intratumoral MDSC-depleting cellular immunotherapy.
We used a clinically relevant human xenograft TME model in NSG mice wherein human tumor cells grow in the presence of human suppressive immune cells (12). Physical cell-cell interactions play a critical role in generating an immunosuppressive microenvironment in solid tumors (16). Several adult and pediatric solid tumors, including clinical NB, contain intense infiltrates of MDSCs (17), which should be included in tumor xenograft models used to study human cell therapeutics. Although NSG mice lack a complete immune system in which to examine the effects of multiple endogenous immune components, our ability to engraft human MDSCs within our TME model provides the possibility of simulating immunosuppressive aspects of the solid TME as well as direct testing of human cell therapies that are being developed for clinical trials. These human cellular therapies cannot be tested directly in immune competent mouse models due to differences in targeting epitopes between mouse and human as well as issues with xenorejection. Compared with immune competent tumor models, where the complexity of the TME is often unpredictable, our model allows isolation and perturbation of single variables and direct evaluation of their consequences on tumor response. Further, by varying the tumor burden of suppressive immune cells (i.e., MDSCs), the model enables fine-tuning of TME immunosuppression, thereby allowing us to understand the effect of each TME component on tumor response to engineered cellular immunotherapies that are being developed for clinical trials. As proof of principle for the human MDSC dependence of our xenograft microenvironment, we showed that increasing the dose of MDSCs in tumor xenografts increased intratumoral MDSC burden, immunosuppressive cytokine milieu, and vascular density. In addition, increasing the dose of MDSCs in tumor xenografts led to an MDSC dose-dependent inhibition of tumor antigendirected CAR-T cell activity, thus simulating the treatment-resistant clinical phenotype of solid tumors (18, 19).
In addition to simulating treatment resistance to cell therapy, our model also recapitulates the clinical condition in which response to a therapy directed specifically against cellular players of the TME is not necessarily reflected in the standard clinical tumor evaluation metric: change in overall tumor volume. We show that despite almost complete depletion of intratumoral MDSCs by TME-targeting NK cell immunotherapy, changes in gross tumor volume were minimal. These data are consistent with previous clinical reports showing that changes in tumor size do not accurately capture responses to immune-based therapies in which effects on tumor volume are often indirect or delayed (8, 9). For example, Wolchok et al. (20) reported that response to checkpoint blockade treatment with single-agent ipilimumab was associated with initial decrease in tumor size in only 10% of patients and that many patients with eventual response failed to exhibit initial decreases. It is now evident in the field of immunotherapy that Response Evaluation Criteria in Solid Tumors (RECIST) or World Health Organization criteria, designed to detect early effects of cytotoxic agents, do not provide accurate assessment of response to immunotherapeutic agents. Further, despite recent attempts at defining specific criteria for the evaluation of antitumor responses within the context of immunotherapeutic agents such as checkpoint blockade antibodies or immune-directed small-molecule inhibitors (immune-related RECIST), it remains difficult to apply these modified criteria directly to cellular immunotherapy (20). Cellular immunotherapies (such as CAR-T or CAR-NK cells) are living drugs modified with targeting receptors that not only enable them to sense, seek, and destroy cancer cells with specificity but also have secondary effects such as coordination and expansion of immune responses (21). Conventional imaging-derived standard tumor metrics present challenges in assessing treatment efficacy in the context of cell-based immunotherapies, especially those directed at the TME. Thus, our attempt at an advanced quantitative imaging methodology represents an important initial step in addressing this unique problem.
Because MDSCs play a central role in tumor angiogenesis and reside in perivascular niches with a TME, we hypothesized that depletion of intratumoral MDSCs will alter tumor vascular architecture and, therefore, tumor texture. Thus, a long circulating nanoparticle blood-pool contrast agent that enables interrogation of tumor vasculature was used, in combination with high-resolution CT imaging, to assess response to MDSC-directed immunotherapy. The long blood-circulating property of liposomal-iodine (Lip-I) nanoparticle contrast agent allowed 3D maps of the tumors vascular compartment during the blood pool phase when imaged within a few hours after administration of contrast agent (22). In addition, because nanoparticles gradually extravasate (over a period of days) at sites of increased vascular permeability and reside in perivascular tumor regions for prolonged periods, delayed contrast-enhanced CT images provide 3D tumor maps of regions with high vascular permeability, indicated by high signal intensity voxels, thus allowing the interrogation of tumor leakiness (13, 14). Similar approaches have previously been used to study the effect of tumor vasculaturemodulating therapies, differentiate malignant from benign lesions, and 3D mapping of nanoparticle distribution in tumors (13, 23, 24). Furthermore, delayed imaging with a nanoparticle contrast agent accurately captures vascular architectural changes in tumors that are less prone to artifacts associated with rapid wash-in/wash-out kinetics and bolus injection/tracking protocols used with conventional small-molecule contrast agents.
Our data confirmed that whole-tumor global CT metrics, even when using a nanoparticle contrast agent that uses aspects of MDSC biology, are insensitive to the indirect subtle changes associated with TME-directed therapies. As demonstrated by flow cytometry, tumors in the immunotherapy group exhibited significantly lower MDSC burden compared with the untreated group, consistent with our previous observations demonstrating efficacy of MDSC-directed NK cell therapy (12). Furthermore, immunohistochemical analysis indicated a significant reduction in MVD in the immunotherapy group compared with the untreated group. However, global tumor metrics on CT imaging (overall volume, CT attenuation, and fractional blood volume) did not corroborate with findings of NK cell immunotherapy efficacy (i.e., intratumoral MDSC depletion). Although previous studies have attempted to define noninvasive radiomic biomarkers in the context of checkpoint blockade and tyrosine kinase inhibitors, our study is the first to evaluate nanoparticle contrastbased imaging in the assessment of tumor changes after cellular immunotherapy, especially one that specifically targets the TME. Further, our data underscore the need for advanced analytics in correlating efficacy with tumor changes.
Radiomic analysis was performed on high-resolution nanoparticle contrastenhanced CT images. In addition, radiomic analysis was performed on noncontrast T2w-MR images, which provides native contrast, and has potential for clinical translation because patients with cancer routinely undergo noncontrast MRI for monitoring of treatment response. Analysis of nanoparticle contrastenhanced delayed CT and CT angiograms (CTAs) revealed several RFs that enabled detection of early response to NK cell therapy, i.e., differentiation of the immunotherapy group from the untreated group. These findings suggest that TME-directed immunotherapy induces subtle changes in the tumor architecture that may not be detectable using global tumor imaging metrics but can be detected by quantitative nano-radiomic analysis that involves data mining of high-resolution 3D images. Radiomic analysis of T2w-MR images also revealed RFs, albeit with fewer number of features when compared with features identified from the analysis of nanoparticle contrastenhanced CT images, for the detection of treatment response. Texture-based RFs belonging to GLSZM and GLRLM exhibited the highest discriminatory power for the detection of tumor response to MDSC-directed therapies. GLSZM is a class of texture features that quantifies gray level zones, which is defined as the number of connected voxels with similar intensity levels, within images (11). For instance, GLSZM nonuniformity feature evaluates homogeneity in gray level intensities between zones. A higher value indicates a higher degree of heterogeneity in gray level zones. GLRLM is another class of texture features that quantifies path length of connected voxels that exhibit similar gray level intensities (11). It is likely that depletion of MDSCs by NK cell therapy reduces tumor vascularity, as demonstrated by IHC, which reflects as a heterogeneous pattern of signal intensities on nanoparticle contrastenhanced CT images. Analysis of these features suggests that immunotherapy-driven MDSC depletion results in a high degree of tumor texture heterogeneity. A high correlation was observed between RFs in 3D image maps from the MDSC-containing untreated group, indicating a higher uniform tumor spatial representation when compared with 3D image maps from the immunotherapy group. The low inter-RF correlation in the immunotherapy group could indicate a vast spread of architectural changes, and therefore high texture heterogeneity, in response to TME-directed NK cell therapy. Radiomic analysis of CT images has the advantage of providing rich information by using high spatial resolution imaging. Furthermore, ease of imaging standardization provides additional benefits for reproducible quantitative imaging using this modality (25). Radiomic analysis of contrast-enhanced CT images has been used to assess intratumoral burden of CD8 cells and response to antiPD-1 (programmed cell death protein 1) checkpoint blockade immunotherapy (26, 27). Furthermore, texture-based RFs have demonstrated strong discriminatory power in the prediction of treatment response to a variety of therapies (28, 29).
Our work is important for two main reasons. First, this is the first study applying radiomic analysis to cellular immunotherapies, which are distinctly different from checkpoint blockades and will soon enter clinical trials for treatment of pediatric solid tumors. Furthermore, by using a clinically validated radiomic software, to noninvasively determine image-based quantitative phenotypic features indicative of tumor response to TME-directed cellular immunotherapies, we show its applicability and high potential for clinical translation for treatment response monitoring in the emerging field of cell-based cancer therapies. We believe that radiomics will be immensely useful in the clinic in determining tumor response to next-generation immunotherapies, including cellular immunotherapies, due to substantial heterogeneity in treatment response and the high cost associated with living cell-based therapies. Second, our work is the first application of radiomics to nanoparticle contrastenhanced imaging. Unlike molecular contrast agents, tumor accumulation and intratumoral distribution of nanoparticle contrast agent is predominantly a function of tumor architecture. Furthermore, extravasated NP contrast agent resides in tumor for prolonged period and therefore eliminates the introduction of confounding variables in radiomic analysis that may be present in conventional molecular-based contrast-enhanced images such as dose and rate of contrast administration, bolus timing, and image acquisition, which can affect reproducibility of RFs.
We acknowledge that our study has limitations. Since CT and MR imaging sequences provide a high degree of flexibility with respect to scan parameters, the effect of changes in scan parameters on the robustness of RFs requires further investigation (25). The predictive power of RFs on tumor response to anticancer therapies has not been evaluated in our study. Radiomic analysis was not performed on noncontrast-enhanced CT images due to absence of 3D signal intensity variations in noncontrast CT images. In general, radiomics approaches analyze variations in pattern of signal intensities and tissue texture to extract phenotypic and tissue architectural differences. Absence of signal intensity variations is unlikely to yield RFs indicative of treatment response or tumor phenotype. Exceptions would be spontaneous and orthotopic lesions wherein the signal intensities of tumor boundaries differ substantial from surrounding normal tissue, such as lung cancer. Future studies will build on the promising results of this work to determine the sensitivity and specificity of the RFs in tumor response to combinatorial (antitumor + TME-directed) immunotherapies. Future studies are also warranted to validate RFs in other tumor models, such as sarcoma, where TME-directed cellular therapies in combination with antitumor T cell immunotherapy are undergoing preclinical investigations (15). Although, we used a Lip-I nanoparticle contrast agent in combination with high-resolution CT, it is possible that, because of rapid imaging speed of clinical CT, radiomic analysis of contrast-enhanced CT images obtained using conventional molecular CT contrast agents could yield phenotypic features indicative of treatment efficacy for TME-directed cellular immunotherapies, thus increasing potential for rapid clinical translation of such approaches. In addition, radiomic investigations can be performed in contrast-enhanced MR images acquired using ultrasmall iron oxide nanoparticles, which are being investigated for monitoring burden of intratumoral immune cells in clinical trials (30).
In conclusion, our study describes a preclinical approach for the application of nano-radiomic analysis in the field of cellular immunotherapy. These disciplines have been combined to help further understand efficacy of cellular immunotherapy in harsh solid TMEs. Current attempts in our laboratory at multiparametric optimization of imaging methodologies and sequences in the preclinical domain to enable the selection of the most promising imaging techniques for clinical translation would serve to implement radiomic analysis for monitoring response to cellular immunotherapies.
MATERIALS AND METHODS

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