Multiparametric magnetic resonance imaging in the assessment of anti-EGFRvIII chimeric antigen receptor T cell therapy in patients with recurrent glioblastoma

Interleukin 6 and cancer resistance in glioblastoma multiforme

Despite unprecedented survival in patients with glioblastoma (GB), the aggressive primary brain cancer remains largely incurable and its mechanisms of treatment resistance have gained particular attention. The cytokine interleukin 6 (IL-6) and its receptor weave through the hallmarks of malignant gliomas and may represent a key vulnerability to GB. Known for activating the STAT3 pathway in autocrine fashion, IL-6 is amplified in GB and has been recognized as a negative biomarker for GB prognosis, rendering it a putative target of novel GB therapies. While it has been recognized as a biologically active component of GB for three decades only with concurrent advances in understanding of complementary immunotherapy has the concept of targeting IL-6 for a human clinical trial gained scientific footing.

CAR-T Cells Therapy in Glioblastoma: A Systematic Review on Molecular Targets and Treatment Strategies

The most common primary brain tumor is glioblastoma (GBM), yet the current therapeutic options for this disease are not promising. Although immunotherapeutic techniques have shown poor success in GBM thus far despite efforts, new developments provide optimism. One of these developments is chimeric antigen receptor (CAR)-T cell treatment, which includes removing and genetically modifying autologous T cells to produce a receptor that targets a GBM antigen before reintroducing the cells into the patient's body. A number of preclinical studies have produced encouraging results, which have led to the start of clinical trials assessing these CAR-T cell treatments for GBM and other brain tumors. Although results in tumors such as diffuse intrinsic pontine gliomas and lymphomas have been promising, preliminary findings in GBM have not produced any clinical benefits. The paucity of particular antigens in GBM, their inconsistent expression patterns, and the possible immunoediting-induced loss of these antigens after antigen-targeted therapy are some possible causes for this discrepancy. The goal of this systematic literature review is to assess potential approaches for creating CAR-T cells that are more effective for this indication, as well as the clinical experiences that are already being had with CAR-T cell therapy in GBM. Up until 9 May 2024, a thorough search was carried out across the three main medical databases: PubMed, Web of Science, and Scopus. Relevant Medical Subject Heading (MeSH) terms and keywords associated with "glioblastoma", "CAR-T", "T cell therapy", "overall survival", and "progression free survival" were employed in the search approach. Preclinical and clinical research on the application of CAR-T cells as a therapeutic approach for GBM are included in the review. A total of 838 papers were identified. Of these, 379 articles were assessed for eligibility, resulting in 8 articles meeting the inclusion criteria. The included studies were conducted between 2015 and 2023, with a total of 151 patients enrolled. The studies varied in CAR-T cell types. EGFRvIII CAR-T cells were the most frequently investigated, used in three studies (37.5%). Intravenous delivery was the most common method of delivery (62.5%). Median OS ranged from 5.5 to 11.1 months across the studies. PFS was reported in only two studies, with values of 7.5 months and 1.3 months. This systematic review highlights the evolving research on CAR-T cell therapy for GBM, emphasizing its potential despite challenges. Targeting antigens like EGFRvIII and IL13Rα2 shows promise in treating recurrent GBM. However, issues such as antigen escape, tumor heterogeneity, and immunosuppression require further optimization. Innovative delivery methods, combination therapies, and personalized approaches are crucial for enhancing CAR-T cell efficacy. Ongoing research is essential to refine these therapies and improve outcomes for GBM patients.

Correlation of Ktrans derived from dynamic contrast-enhanced MRI with treatment response and survival in locally advanced NSCLC patients undergoing induction immunochemotherapy and concurrent chemoradiotherapy

PURPOSE

This study aimed to investigate the prognostic significance of pretreatment dynamic contrast-enhanced (DCE)-MRI parameters concerning tumor response following induction immunochemotherapy and survival outcomes in patients with locally advanced non-small cell lung cancer (NSCLC) who underwent immunotherapy-based multimodal treatments.

MATERIAL AND METHODS

Unresectable stage III NSCLC patients treated by induction immunochemotherapy, concurrent chemoradiotherapy (CCRT) with or without consolidative immunotherapy from two prospective clinical trials were screened. Using the two-compartment Extend Tofts model, the parameters including Ktrans, Kep, Ve, and Vp were calculated from DCE-MRI data. The apparent diffusion coefficient was calculated from diffusion-weighted-MRI data. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to assess the predictive performance of MRI parameters. The Cox regression model was used for univariate and multivariate analysis.

RESULTS

111 unresectable stage III NSCLC patients were enrolled. Patients received two cycles of induction immunochemotherapy and CCRT, with or without consolidative immunotherapy. With the median follow-up of 22.3 months, the median progression-free survival (PFS) and overall survival (OS) were 16.3 and 23.8 months. The multivariate analysis suggested that Eastern Cooperative Oncology Group score, TNM stage and the response to induction immunochemotherapy were significantly related to both PFS and OS. After induction immunochemotherapy, 67 patients (59.8%) achieved complete response or partial response and 44 patients (40.2%) had stable disease or progressive disease. The Ktrans of primary lung tumor before induction immunochemotherapy yielded the best performance in predicting the treatment response, with an AUC of 0.800. Patients were categorized into two groups: high-Ktrans group (n=67, Ktrans＞164.3×10-3/min) and low-Ktrans group (n=44, Ktrans≤164.3×10-3/min) based on the ROC analysis. The high-Ktrans group had a significantly higher objective response rate than the low-Ktrans group (85.1% (57/67) vs 22.7% (10/44), p<0.001). The high-Ktrans group also presented better PFS (median: 21.1 vs 11.3 months, p=0.002) and OS (median: 34.3 vs 15.6 months, p=0.035) than the low-Ktrans group.

CONCLUSIONS

Pretreatment Ktrans value emerged as a significant predictor of the early response to induction immunochemotherapy and survival outcomes in unresectable stage III NSCLC patients who underwent immunotherapy-based multimodal treatments. Elevated Ktrans values correlated positively with enhanced treatment response, leading to extended PFS and OS durations.

MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma

BACKGROUND

The tumor immune microenvironment can influence the prognosis and treatment response to immunotherapy. We aimed to develop a non-invasive radiomic signature in high-grade glioma (HGG) to predict the absolute density of tumor-associated macrophages (TAMs), the preponderant immune cells in the microenvironment of HGG. We also aimed to evaluate the association between the signature, and tumor immune phenotype as well as response to immunotherapy.

METHODS

In this retrospective setting, total of 379 patients with HGG from three independent cohorts were included to construct a radiomic model named Radiomics Immunological Biomarker (RIB) for predicting the absolute density of M2-like TAM using the mRMR feature ranking method and LASSO classifier. Among them, 145 patients from the TCGA microarray cohort were randomly allocated into a training set (N=101) and an internal validation set (N=44), while the immune-phenotype cohort (N=203) and the immunotherapy-treated cohort (N=31, patients from a prospective clinical trial treated with DC vaccine) recruited from Huashan Hospital were used as two external validation sets. The immunotherapy-treated cohort was also used to evaluate the relationship between RIB and immunotherapy response. Radiogenomic analysis was performed to find functional annotations using RNA sequencing data from TAM cells.

RESULTS

An 11-feature radiomic model for M2-like TAM was developed and validated in four datasets of HGG patients (area under the curve = 0.849, 0.719, 0.674, and 0.671) using MRI images of post contrast enhanced T1-weighted (T1CE). Patients with high RIB scores had a strong inflammatory response. Four hub-genes (SLC7A7, RNASE6, HLA-DRB1 and CD300A) expressed by TAM were identified to be closely related to the RIB, providing important evidence for biological interpretation. Only individuals with a high RIB score were shown to have survival benefits from DC vaccine [DC vaccine vs. Placebo: median progression-free survival (mPFS), 10.0 mos vs. 4.5 mos, HR=0.17, P=0.0056, 95%CI=0.041-0.68; median overall survival (mOS), 15.0 mos vs. 7.0 mos, HR=0.17, P =0.0076, 95%CI=0.04-0.68]. Multivariate analyses also confirmed that treatment by DC vaccine was an independent factor for improved survival in the high RIB score group. However, in the low RIB score group, DC vaccine was not associated with improved survival. Furthermore, a radiomic nomogram based on the RIB score and clinical factors could efficiently predict the 1-, 2-, and 3-year survival rates, as confirmed by ROC curve analysis (AUC for 1-, 2- and 3-year survival: 0.705, 0.729 and 0.684, respectively).

CONCLUSIONS

The radiomic model could allow for non-invasive assessment of the absolute density of TAM from MRI images in HGG patients. Of note, our RIB model is the first immunological radiomic model confirmed to have the ability to predict survival benefits from DC vaccine in gliomas, thereby providing a novel tool to inform treatment decisions and monitor patient treatment course by radiomics.

Bispecific T-Cell Engagers and Chimeric Antigen Receptor T-Cell Therapies in Glioblastoma: An Update

Glioblastoma is the most common malignant primary brain tumor in adults. The prognosis is extremely poor even with standard treatment of maximal safe resection, radiotherapy, and chemotherapy. Recurrence is inevitable within months, and treatment options are very limited. Chimeric antigen receptor T-cell therapy (CART) and bispecific T-cell engagers (TCEs) are two emerging immunotherapies that can redirect T-cells for tumor-specific killing and have shown remarkable success in hematological malignancies and been under extensive study for application in glioblastoma. While there have been multiple clinical trials showing preliminary evidence of safety and efficacy for CART, bispecific TCEs are still in the early stages of clinical testing, with preclinical studies showing very promising results. However, there are multiple shared challenges that need to be addressed in the future, including the route of delivery, antigen escape, the immunosuppressive tumor microenvironment, and toxicity resulting from the limited choice of tumor-specific antigens. Efforts are underway to optimize the design of both these treatments and find the ideal combination therapy to overcome these challenges. In this review, we describe the work that has been performed as well as novel approaches in glioblastoma and in other solid tumors that may be applicable in the future.

Taming Glioblastoma in "Real Time": Integrating Multimodal Advanced Neuroimaging/AI Tools Towards Creating a Robust and Therapy Agnostic Model for Response Assessment in Neuro-Oncology

The highly aggressive nature of glioblastoma carries a dismal prognosis despite aggressive multimodal therapy. Alternative treatment regimens, such as immunotherapies, are known to intensify the inflammatory response in the treatment field. Follow-up imaging in these scenarios often mimics disease progression on conventional MRI, making accurate evaluation extremely challenging. To this end, revised criteria for assessment of treatment response in high-grade gliomas were successfully proposed by the RANO Working Group to distinguish pseudoprogression from true progression, with intrinsic constraints related to the postcontrast T1-weighted MRI sequence. To address these existing limitations, our group proposes a more objective and quantifiable "treatment agnostic" model, integrating into the RANO criteria advanced multimodal neuroimaging techniques, such as diffusion tensor imaging (DTI), dynamic susceptibility contrast-perfusion weighted imaging (DSC-PWI), dynamic contrast enhanced (DCE)-MRI, MR spectroscopy, and amino acid-based positron emission tomography (PET) imaging tracers, along with artificial intelligence (AI) tools (radiomics, radiogenomics, and radiopathomics) and molecular information to address this complex issue of treatment-related changes versus tumor progression in "real-time", particularly in the early posttreatment window. Our perspective delineates the potential of incorporating multimodal neuroimaging techniques to improve consistency and automation for the assessment of early treatment response in neuro-oncology.

Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model

PURPOSE

Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L.

METHODS

Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables.

RESULTS

Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts.

CONCLUSION

Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.

Validation of multiparametric MRI based prediction model in identification of pseudoprogression in glioblastomas

BACKGROUND

Accurate differentiation of pseudoprogression (PsP) from tumor progression (TP) in glioblastomas (GBMs) is essential for appropriate clinical management and prognostication of these patients. In the present study, we sought to validate the findings of our previously developed multiparametric MRI model in a new cohort of GBM patients treated with standard therapy in identifying PsP cases.

METHODS

Fifty-six GBM patients demonstrating enhancing lesions within 6 months after completion of concurrent chemo-radiotherapy (CCRT) underwent anatomical imaging, diffusion and perfusion MRI on a 3 T magnet. Subsequently, patients were classified as TP + mixed tumor (n = 37) and PsP (n = 19). When tumor specimens were available from repeat surgery, histopathologic findings were used to identify TP + mixed tumor (> 25% malignant features; n = 34) or PsP (< 25% malignant features; n = 16). In case of non-availability of tumor specimens, ≥ 2 consecutive conventional MRIs using mRANO criteria were used to determine TP + mixed tumor (n = 3) or PsP (n = 3). The multiparametric MRI-based prediction model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI derived parameters from contrast enhancing regions. In the next step, PP values were used to characterize each lesion as PsP or TP+ mixed tumor. The lesions were considered as PsP if the PP value was < 50% and TP+ mixed tumor if the PP value was ≥ 50%. Pearson test was used to determine the concordance correlation coefficient between PP values and histopathology/mRANO criteria. The area under ROC curve (AUC) was used as a quantitative measure for assessing the discriminatory accuracy of the prediction model in identifying PsP and TP+ mixed tumor.

RESULTS

Multiparametric MRI model correctly predicted PsP in 95% (18/19) and TP+ mixed tumor in 57% of cases (21/37) with an overall concordance rate of 70% (39/56) with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.56; p < 0.001). The ROC analyses revealed an accuracy of 75.7% in distinguishing PsP from TP+ mixed tumor. Leave-one-out cross-validation test revealed that 73.2% of cases were correctly classified as PsP and TP + mixed tumor.

CONCLUSIONS

Our multiparametric MRI based prediction model may be helpful in identifying PsP in GBM patients.

[Management of neurotoxicity following CAR-T cell therapy: Recommendations of the SFGM-TC]

The immune effector cell-associated syndrome (ICANS) has been described as the second most frequent specific complication following CAR-T cell therapy. The median time to the onset of neurological symptoms is five days after CAR-T infusion. ICANS can be concomitant to cytokine release syndrome but often follows the resolution of the latter. However, 10 % of patients experience delayed onset after 3 weeks of CAR-T cell infusion. The duration of symptoms is usually short, around five days if an early appropriate treatment is given. Symptoms are heterogeneous, ranging from mild symptoms quickly reversible (alterations of consciousness, deterioration in handwriting) to more serious forms with seizures or even a coma. The ICANS severity is currently based on the ASTCT score. The diagnosis of ICANS is clinical but EEG, MRI and lumbar punction can help ruling out alternative diagnoses. The first line treatment consists of high-dose corticosteroids. During the twelfth edition of practice harmonization workshops of the Francophone Society of Bone Marrow Transplantation and Cellular Therapy (SFGM-TC), a working group focused its work on updating the SFGM-TC recommendations on the management of ICANS. In this review we discuss the management of ICANS and other neurological toxicities in patients undergoing of CAR-T cell therapy. These recommendations apply to commercial CAR-T cells, in order to guide strategies for the management neurological complications associated with this new therapeutic approach.

EGFR, the Lazarus target for precision oncology in glioblastoma

The Lazarus effect is a rare condition that happens when someone seemingly dead shows signs of life. The epidermal growth factor receptor (EGFR) represents a target in the fatal neoplasm glioblastoma (GBM) that through a series of negative clinical trials has prompted a vocal subset of the neuro-oncology community to declare this target dead. However, an argument can be made that the core tenets of precision oncology were overlooked in the initial clinical enthusiasm over EGFR as a therapeutic target in GBM. Namely, the wrong drugs were tested on the wrong patients at the wrong time. Furthermore, new insights into the biology of EGFR in GBM vis-à-vis other EGFR-driven neoplasms, such as non-small cell lung cancer, and development of novel GBM-specific EGFR therapeutics resurrects this target for future studies. Here, we will examine the distinct EGFR biology in GBM, how it exacerbates the challenge of treating a CNS neoplasm, how these unique challenges have influenced past and present EGFR-targeted therapeutic design and clinical trials, and what adjustments are needed to therapeutically exploit EGFR in this devastating disease.

MRI techniques for immunotherapy monitoring

MRI is a widely available clinical tool for cancer diagnosis and treatment monitoring. MRI provides excellent soft tissue imaging, using a wide range of contrast mechanisms, and can non-invasively detect tissue metabolites. These approaches can be used to distinguish cancer from normal tissues, to stratify tumor aggressiveness, and to identify changes within both the tumor and its microenvironment in response to therapy. In this review, the role of MRI in immunotherapy monitoring will be discussed and how it could be utilized in the future to address some of the unique clinical questions that arise from immunotherapy. For example, MRI could play a role in identifying pseudoprogression, mixed response, T cell infiltration, cell tracking, and some of the characteristic immune-related adverse events associated with these agents. The factors to be considered when developing MRI imaging biomarkers for immunotherapy will be reviewed. Finally, the advantages and limitations of each approach will be discussed, as well as the challenges for future clinical translation into routine clinical care. Given the increasing use of immunotherapy in a wide range of cancers and the ability of MRI to detect the microstructural and functional changes associated with successful response to immunotherapy, the technique has great potential for more widespread and routine use in the future for these applications.

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.

Safety and Efficacy of Chimeric Antigen Receptor T-Cell Therapy for Glioblastoma: A Systemic Review and Meta-Analysis

Background

Chimeric antigen receptor (CAR) T-cell therapy is a promising treatment option for patients with refractory hematological malignancies. However, its efficacy in glioblastoma remains unclear. Here, we performed a systematic review to summarize the safety and efficacy of CAR T-cell therapy in glioblastoma.

Methods

The PubMed, EMBASE, and Cochrane databases were searched to identify articles published before June 30, 2021 describing the use of CAR T-cell therapy in glioblastoma. Information on the toxicity of CAR T-cell therapy was summarized. The pooled objective response rate (ORR) and overall survival (OS) of patients who underwent CAR T-cell therapy were estimated using a random-effects model with an inverse-variance weighting model and quantile estimation method, respectively.

Results

Of 397 articles identified, eight studies including 63 patients with recurrent glioblastoma treated with various CAR T-cell regimens were included in the analysis. Six (9.5%) patients developed cytokine release syndrome (grade ≤2), and 16 (25.4%) experienced non-critical neurological events. The pooled ORR was 5.1% (95% confidence interval [CI], 0.0-10.4; I 2 = 0.05%), and the pooled median OS was 8.1 months (95% CI, 6.7-9.5; I 2 = 0.00%).

Conclusion

Although CAR T-cell therapy is a relatively safe therapeutic option in patients with glioblastoma, it shows marginal efficacy, suggesting that further research is necessary for its translation into clinical practice for the treatment of recurrent glioblastoma.

Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism

Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.

Molecular Pathogenesis of Glioblastoma in Adults and Future Perspectives: A Systematic Review

Glioblastoma (GBM) is the most common and malignant tumour of the central nervous system. Recent appreciation of the heterogeneity amongst these tumours not only changed the WHO classification approach, but also created the need for developing novel and personalised therapies. This systematic review aims to highlight recent advancements in understanding the molecular pathogenesis of the GBM and discuss related novel treatment targets. A systematic search of the literature in the PubMed library was performed following the PRISMA guidelines for molecular pathogenesis and therapeutic advances. Original and meta-analyses studies from the last ten years were reviewed using pre-determined search terms. The results included articles relevant to GBM development focusing on the aberrancy in cell signaling pathways and intracellular events. Theragnostic targets and vaccination to treat GBM were also explored. The molecular pathophysiology of GBM is complex. Our systematic review suggests targeting therapy at the stemness, p53 mediated pathways and immune modulation. Exciting novel immune therapy involving dendritic cell vaccines, B-cell vaccines and viral vectors may be the future of treating GBM.

Imaging Biomarkers of Glioblastoma Treatment Response: A Systematic Review and Meta-Analysis of Recent Machine Learning Studies

OBJECTIVE

Monitoring biomarkers using machine learning (ML) may determine glioblastoma treatment response. We systematically reviewed quality and performance accuracy of recently published studies.

METHODS

Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis: Diagnostic Test Accuracy, we extracted articles from MEDLINE, EMBASE and Cochrane Register between 09/2018-01/2021. Included study participants were adults with glioblastoma having undergone standard treatment (maximal resection, radiotherapy with concomitant and adjuvant temozolomide), and follow-up imaging to determine treatment response status (specifically, distinguishing progression/recurrence from progression/recurrence mimics, the target condition). Using Quality Assessment of Diagnostic Accuracy Studies Two/Checklist for Artificial Intelligence in Medical Imaging, we assessed bias risk and applicability concerns. We determined test set performance accuracy (sensitivity, specificity, precision, F1-score, balanced accuracy). We used a bivariate random-effect model to determine pooled sensitivity, specificity, area-under the receiver operator characteristic curve (ROC-AUC). Pooled measures of balanced accuracy, positive/negative likelihood ratios (PLR/NLR) and diagnostic odds ratio (DOR) were calculated. PROSPERO registered (CRD42021261965).

RESULTS

Eighteen studies were included (1335/384 patients for training/testing respectively). Small patient numbers, high bias risk, applicability concerns (particularly confounding in reference standard and patient selection) and low level of evidence, allow limited conclusions from studies. Ten studies (10/18, 56%) included in meta-analysis gave 0.769 (0.649-0.858) sensitivity [pooled (95% CI)]; 0.648 (0.749-0.532) specificity; 0.706 (0.623-0.779) balanced accuracy; 2.220 (1.560-3.140) PLR; 0.366 (0.213-0.572) NLR; 6.670 (2.800-13.500) DOR; 0.765 ROC-AUC.

CONCLUSION

ML models using MRI features to distinguish between progression and mimics appear to demonstrate good diagnostic performance. However, study quality and design require improvement.

Exosomal miRNA profiles of triple-negative breast cancer in neoadjuvant treatment

Triple-negative breast cancer (TNBC) is characterized by aggressive clinicopathological features and is associated with a poor prognosis. Identifying patients that are non-responsive to chemotherapy remains a critical goal for effective personalized therapies. In the present study, the predictive value of exosomal microRNAs (miRNAs) was investigated in patients with TNBC. Exosomes were isolated from patients with TNBC undergoing neoadjuvant chemotherapy. Microarray-based miRNA profiles were compared between patients with pathological complete response (pCR; n=12) and non-pCR (n=12). Furthermore, the miRNA profiles of non-pCR patients with breast cancer recurrence were compared with those with no recurrence. A total of 16 differentially expressed exosomal miRNAs were identified between the patients with pCR and non-pCR by microarray analysis. Of these, a combined signature of four miRNAs (miR-4448, miR-2392, miR-2467-3p and miR-4800-3p) could be used to discriminate between pCR and non-pCR patients with TNBC with an area under the curve value of 0.7652. Furthermore, this study found 43 differentially expressed miRNAs between the patients with non-pCR and recurrence and non-pCR patients without recurrence. In network analysis, 'pathway in cancer', 'focal adhesion' and 'cell cycle' were identified as the crucial pathways in patients with non-pCR who also developed recurrence. Several exosomal miRNAs may be useful biomarkers to predict treatment efficacy for TNBC. The present study identified patients who were resistant to standard chemotherapy and therefore more likely to develop breast cancer recurrence.

The Role of the Immune Response in Brain Metastases: Novel Imaging Biomarkers for Immunotherapy

Brain metastases are a major clinical problem, and immunotherapy offers a novel treatment paradigm with the potential to synergize with existing focal therapies like surgery and radiosurgery or even replace them in future. The brain is a unique microenvironment structurally and immunologically. The immune response is likely to be crucial to the adaptation of systemic immune modulating agents against this disease. Imaging is frequently employed in the clinical diagnosis and management of brain metastasis, so it is logical that brain imaging techniques are investigated as a source of biomarkers of the immune response in these tumors. Current imaging techniques in clinical use include structural MRI (post-contrast T1W sequences, T2, and FLAIR), physiological sequences (perfusion- and diffusion-weighted imaging), and molecular imaging (MR spectroscopy and PET). These are reviewed for their application to predicting and measuring the response to immunotherapy in brain metastases.

Multiparametric MRI assessment of response to convection-enhanced intratumoral delivery of MDNA55, an interleukin-4 receptor targeted immunotherapy, for recurrent glioblastoma

Background

Glioblastoma (GBM) is the most common malignant brain tumor and carries a dismal prognosis. Attempts to develop biologically targeted therapies are challenging as the blood-brain barrier can limit drugs from reaching their target when administered through conventional (intravenous or oral) routes. Furthermore, systemic toxicity of drugs often limits their therapeutic potential. To circumvent these problems, convection-enhanced delivery (CED) provides direct, targeted, intralesional therapy with a secondary objective to alter the tumor microenvironment from an immunologically "cold" (nonresponsive) to an "inflamed" (immunoresponsive) tumor.

Case Description

We report a patient with right occipital recurrent GBM harboring poor prognostic genotypes who was treated with MRI-guided CED of a fusion protein MDNA55 (a targeted toxin directed toward the interleukin-4 receptor). The patient underwent serial anatomical, diffusion, and perfusion MRI scans before initiation of targeted therapy and at 1, 3-month posttherapy. Increased mean diffusivity along with decreased fractional anisotropy and maximum relative cerebral blood volume was noted at follow-up periods relative to baseline.

Conclusion

Our findings suggest that diffusion and perfusion MRI techniques may be useful in evaluating early response to CED of MDNA55 in recurrent GBM patients.

Anti-tumor effects of vascular endothelial growth factor/vascular endothelial growth factor receptor binding domain-modified chimeric antigen receptor T cells

BACKGROUND AIMS

The vascular endothelial growth factor (VEGF)/vascular endothelial growth factor receptor (VEGFR) signaling pathway plays an important role in angiogenesis and lymphangiogenesis, which are closely related to tumor cell growth, survival, tissue infiltration and metastasis. Blocking/interfering with the interaction between VEGF and VEGFR to inhibit angiogenesis/lymphangiogenesis has become an important means of tumor therapy.

METHODS

Here the authors designed a novel chimeric antigen receptor (CAR) lentiviral vector expressing the VEGF-C domain targeting both VEGFR-2 and VEGFR-3 (VEGFR-2/3 CAR) and then transduced CD3-positive T cells with VEGFR-2/3 CAR lentivirus.

RESULTS

After co-culturing with target cells, VEGFR-2/3 CAR T cells showed potent cytotoxicity against both VEGFR-2- and VEGFR-3-positive breast cancer cells, with increased simultaneous secretion of interferon gamma, tumor necrosis factor alpha and interleukin-2 cytokines. Moreover, CAR T cells were able to destroy the tubular structures formed by human umbilical vein endothelial cells and significantly inhibit the growth, infiltration and metastasis of orthotopic mammary xenograft tumors in a female BALB/c nude mice model.

CONCLUSIONS

The authors' results indicate that VEGFR-2/3 CAR T cells targeting both VEGFR-2 and VEGFR-3 have significant anti-tumor activity, which expands the application of conventional CAR T-cell therapy.

Physiological Imaging Methods for Evaluating Response to Immunotherapies in Glioblastomas

Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive multi-modal therapy. Immunotherapy is currently being evaluated as an alternate treatment modality for recurrent GBMs in clinical trials. These immunotherapeutic approaches harness the patient's immune response to fight and eliminate tumor cells. Standard MR imaging is not adequate for response assessment to immunotherapy in GBM patients even after using refined response assessment criteria secondary to amplified immune response. Thus, there is an urgent need for the development of effective and alternative neuroimaging techniques for accurate response assessment. To this end, some groups have reported the potential of diffusion and perfusion MR imaging and amino acid-based positron emission tomography techniques in evaluating treatment response to different immunotherapeutic regimens in GBMs. The main goal of these techniques is to provide definitive metrics of treatment response at earlier time points for making informed decisions on future therapeutic interventions. This review provides an overview of available immunotherapeutic approaches used to treat GBMs. It discusses the limitations of conventional imaging and potential utilities of physiologic imaging techniques in the response assessment to immunotherapies. It also describes challenges associated with these imaging methods and potential solutions to avoid them.

Assessing Immunotherapy with Functional and Molecular Imaging and Radiomics

Immunotherapy is changing the treatment paradigm for cancer and has introduced new challenges in medical imaging. Because not all patients benefit from immunotherapy, pretreatment imaging should be performed to identify not only prognostic factors but also factors that allow prediction of response to immunotherapy. Follow-up studies must allow detection of nonresponders, without confusion of pseudoprogression with real progression to prevent premature discontinuation of treatment that can benefit the patient. Conventional imaging techniques and classic tumor response criteria are limited for the evaluation of the unusual patterns of response that arise from the specific mechanisms of action of immunotherapy, so advanced imaging methods must be developed to overcome these shortcomings. The authors present the fundamentals of the tumor immune microenvironment and immunotherapy and how they influence imaging findings. They also discuss advances in functional and molecular imaging techniques for the assessment of immunotherapy in clinical practice, including their use to characterize immune phenotypes, assess patient prognosis and response to therapy, and evaluate immune-related adverse events. Finally, the development of radiomics and radiogenomics in these therapies and the future role of imaging biomarkers for immunotherapy are discussed. Online supplemental material is available for this article. ^©RSNA, 2020.

Emerging MRI Techniques to Redefine Treatment Response in Patients With Glioblastoma

Glioblastoma is the most common and most malignant primary brain tumor. Despite aggressive multimodal treatment, its prognosis remains poor. Even with continuous developments in MRI, which has provided us with newer insights into the diagnosis and understanding of tumor biology, response assessment in the posttherapy setting remains challenging. We believe that the integration of additional information from advanced neuroimaging techniques can further improve the diagnostic accuracy of conventional MRI. In this article, we review the utility of advanced neuroimaging techniques such as diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, proton magnetic resonance spectroscopy, and chemical exchange saturation transfer in characterizing and evaluating treatment response in patients with glioblastoma. We will also discuss the existing challenges and limitations of using these techniques in clinical settings and possible solutions to avoiding pitfalls in study design, data acquisition, and analysis for future studies. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3 J. Magn. Reson. Imaging 2020;52:978-997.

Cell Tracking in Cancer Immunotherapy

The impressive development of cancer immunotherapy in the last few years originates from a more precise understanding of control mechanisms in the immune system leading to the discovery of new targets and new therapeutic tools. Since different stages of disease progression elicit different local and systemic inflammatory responses, the ability to longitudinally interrogate the migration and expansion of immune cells throughout the whole body will greatly facilitate disease characterization and guide selection of appropriate treatment regiments. While using radiolabeled white blood cells to detect inflammatory lesions has been a classical nuclear medicine technique for years, new non-invasive methods for monitoring the distribution and migration of biologically active cells in living organisms have emerged. They are designed to improve detection sensitivity and allow for a better preservation of cell activity and integrity. These methods include the monitoring of therapeutic cells but also of all cells related to a specific disease or therapeutic approach. Labeling of therapeutic cells for imaging may be performed in vitro, with some limitations on sensitivity and duration of observation. Alternatively, in vivo cell tracking may be performed by genetically engineering cells or mice so that may be revealed through imaging. In addition, SPECT or PET imaging based on monoclonal antibodies has been used to detect tumors in the human body for years. They may be used to detect and quantify the presence of specific cells within cancer lesions. These methods have been the object of several recent reviews that have concentrated on technical aspects, stressing the differences between direct and indirect labeling. They are briefly described here by distinguishing ex vivo (labeling cells with paramagnetic, radioactive, or fluorescent tracers) and in vivo (in vivo capture of injected radioactive, fluorescent or luminescent tracers, or by using labeled antibodies, ligands, or pre-targeted clickable substrates) imaging methods. This review focuses on cell tracking in specific therapeutic applications, namely cell therapy, and particularly CAR (Chimeric Antigen Receptor) T-cell therapy, which is a fast-growing research field with various therapeutic indications. The potential impact of imaging on the progress of these new therapeutic modalities is discussed.

Molecular imaging and advanced MRI findings following immunotherapy in patients with brain tumors

Introduction: Currently, immunotherapy using vaccination strategies or oncolytic virus approaches, cell-based immunotherapy, and the blockade of immune checkpoints are under evaluation in patients with brain cancer. Here we summarize clinically significant imaging findings such as treatment-related changes detected by advanced neuroimaging techniques following the most suitable immunotherapy options currently used in neuro-oncology. We, furthermore, provide an overview of how these advanced imaging techniques may help to overcome shortcomings of standard MRI in the assessment and follow-up of patients with brain cancer.Areas covered: The current literature on neuroimaging for immunotherapy in the field of brain tumors, with a focus on gliomas and brain metastases is summarized.Expert commentary: Data suggest that imaging parameters primarily derived from amino acid PET, diffusion- and perfusion-weighted MRI, or MR spectroscopy are particularly helpful for the evaluation of treatment response and provide valuable information for the differentiation of treatment-induced changes from actual brain tumor progression following various immunotherapy approaches.