Framework humanization optimizes potency of anti-CD72 nanobody CAR-T cells for B-cell malignancies.

BACKGROUND: Approximately 50% of patients who receive anti-CD19 CAR-T cells relapse, and new immunotherapeutic targets are urgently needed. We recently described CD72 as a promising target in B-cell malignancies and developed nanobody-based CAR-T cells (nanoCARs) against it. This cellular therapy design is understudied compared with scFv-based CAR-T cells, but has recently become of significant interest given the first regulatory approval of a nanoCAR in multiple myeloma. METHODS: We humanized our previous nanobody framework regions, derived from llama, to generate a series of humanized anti-CD72 nanobodies. These nanobody binders were inserted into second-generation CD72 CAR-T cells and were evaluated against preclinical models of B cell acute lymphoblastic leukemia and B cell non-Hodgkin's lymphoma in vitro and in vivo. Humanized CD72 nanoCARs were compared with parental ("NbD4") CD72 nanoCARs and the clinically approved CD19-directed CAR-T construct tisangenlecleucel. RNA-sequencing, flow cytometry, and cytokine secretion profiling were used to determine differences between the different CAR constructs. We then used affinity maturation on the parental NbD4 construct to generate high affinity binders against CD72 to test if higher affinity to CD72 improved antitumor potency. RESULTS: Toward clinical translation, here we humanize our previous nanobody framework regions, derived from llama, and surprisingly discover a clone ("H24") with enhanced potency against B-cell tumors, including patient-derived samples after CD19 CAR-T relapse. Potentially underpinning improved potency, H24 has moderately higher binding affinity to CD72 compared with a fully llama framework. However, further affinity maturation (KD<1 nM) did not lead to improvement in cytotoxicity. After treatment with H24 nanoCARs, in vivo relapse was accompanied by CD72 antigen downregulation which was partially reversible. The H24 nanobody clone was found to have no off-target binding and is therefore designated as a true clinical candidate. CONCLUSION: This work supports translation of H24 CD72 nanoCARs for refractory B-cell malignancies, reveals potential mechanisms of resistance, and unexpectedly demonstrates that nanoCAR potency can be improved by framework alterations alone. These findings may have implications for future engineering of nanobody-based cellular therapies.

Pre-and post-HSCT use of TKI therapy for fusion-driven B-ALL: A case series of five pediatric, adolescent and young adult patients.

BACKGROUND: The development of tyrosine kinase inhibitors (TKIs) has significantly improved survival rates among patients with Philadelphia chromosome (Ph+) B cell acute lymphoblastic leukemia (B-ALL). Ph-like B-ALL patients lack the BCR::ABL1 translocation but share gene expression profiles with Ph+ B-ALL. The role of TKIs for Ph-like patients pre- and post-hematopoietic stem cell transplantation (HSCT) is not yet clear. CASE: Here we present five cases of pediatric, adolescent, and young adult patients who presented with Ph-like B-ALL or CML in B-ALL blast phase who were treated with personalized TKI regimens pre- and post-HSCT. CONCLUSION: This report describes several novel Ph-like fusions as well as combinations of TKIs with chemotherapy or immunotherapy not yet reported in the pediatric population. This case series provides real-world experience highlighting the potential application of pre- and post-HSCT use of TKIs in a subset of patients with targetable fusions.

Structural surfaceomics reveals an AML-specific conformation of integrin ß2 as a CAR T cellular therapy target.

Safely expanding indications for cellular therapies has been challenging given a lack of highly cancer-specific surface markers. Here we explore the hypothesis that tumor cells express cancer-specific surface protein conformations that are invisible to standard target discovery pipelines evaluating gene or protein expression, and these conformations can be identified and immunotherapeutically targeted. We term this strategy integrating cross-linking mass spectrometry with glycoprotein surface capture 'structural surfaceomics'. As a proof of principle, we apply this technology to acute myeloid leukemia (AML), a hematologic malignancy with dismal outcomes and no known optimal immunotherapy target. We identify the activated conformation of integrin ß2 as a structurally defined, widely expressed AML-specific target. We develop and characterize recombinant antibodies to this protein conformation and show that chimeric antigen receptor T cells eliminate AML cells and patient-derived xenografts without notable toxicity toward normal hematopoietic cells. Our findings validate an AML conformation-specific target antigen and demonstrate a tool kit for applying these strategies more broadly.

Diagnosis and management of lymphoblastic lymphoma in children, adolescents and young adults.

Lymphoblastic lymphoma (LBL) is the second most common type of non-Hodgkin Lymphoma (NHL) in children, adolescents, and young adults (CAYA), accounting for 25-35% of all cases. T-lymphoblastic lymphoma (T-LBL) comprises 70-80% of cases, while precursor B-lymphoblastic lymphoma (pB-LBL) makes up the remaining 20-25% of cases. Event-free and overall survival (EFS and OS) for paediatric LBL patients both exceed 80% with current therapies. Treatment regimens, especially in T-LBL with large mediastinal tumours, are complex with significant toxicity and long-term complications. Though prognosis overall is good for T-LBL and pB-LBL with upfront therapy, outcomes for patients with relapsed or refractory (r/r) disease remain dismal. Here, we review new understanding about the pathogenesis and biology of LBL, recent clinical results and future directions for therapy, and remaining obstacles to improve outcomes while reducing toxicity.

Incorporating Radiomics into Machine Learning Models to Predict Outcomes of Neuroblastoma.

Neuroblastoma is one of the most common pediatric cancers. This study used machine learning (ML) to predict the mortality and a few other investigated intermediate outcomes of neuroblastoma patients non-invasively from CT images. Performances of multiple ML algorithms over retrospective CT images of 65 neuroblastoma patients are analyzed. An artificial neural network (ANN) is used on tumor radiomic features extracted from 3D CT images. A pre-trained 2D convolutional neural network (CNN) is used on slices of the same images. ML models are trained for various pathologically investigated outcomes of these patients. A subspecialty-trained pediatric radiologist independently reviewed the manually segmented primary tumors. Pyradiomics library is used to extract 105 radiomic features. Six ML algorithms are compared to predict the following outcomes: mortality, presence or absence of metastases, neuroblastoma differentiation, mitosis-karyorrhexis index (MKI), presence or absence of MYCN gene amplification, and presence of image-defined risk factors (IDRF). The prediction ranges over multiple experiments are measured using the area under the receiver operating characteristic (ROC-AUC) for comparison. Our results show that the radiomics-based ANN method slightly outperforms the other algorithms in predicting all outcomes except classification of the grade of neuroblastic differentiation, for which the elastic regression model performed the best. Contributions of the article are twofold: (1) noninvasive models for the prognosis from CT images of neuroblastoma, and (2) comparison of relevant ML models on this medical imaging problem.

Association of image-defined risk factors with clinical features, histopathology, and outcomes in neuroblastoma.

BACKGROUND: Clinical, molecular, and histopathologic features guide treatment for neuroblastoma, but obtaining tumor tissue may cause complications and is subject to sampling error due to tumor heterogeneity. We hypothesized that image-defined risk factors (IDRFs) would reflect molecular features, histopathology, and clinical outcomes in neuroblastoma. METHODS: We performed a retrospective cohort study of 76 patients with neuroblastoma or ganglioneuroblastoma. Diagnostic CT scans were reviewed for 20 IDRFs, which were consolidated into five IDRF groups (involvement of multiple body compartments, vascular encasement, tumor infiltration of adjacent organs/structures, airway compression, or intraspinal extension). IDRF groups were analyzed for association with clinical, molecular, and histopathologic features of neuroblastoma. RESULTS: Patients with more IDRF groups had a higher risk of surgical complications (OR = 3.1, p = 0.001). Tumor vascular encasement was associated with increased risk of surgical complications (OR = 5.40, p = 0.009) and increased risk of undifferentiated/poorly differentiated histologic grade (OR = 11.11, p = 0.013). Tumor infiltration of adjacent organs and structures was associated with decreased survival (HR = 8.90, p = 0.007), MYCN amplification (OR = 9.91, p = 0.001), high MKI (OR = 6.20, p = 0.003), and increased risk of International Neuroblastoma Staging System stage 4 disease (OR = 8.96, p < 0.001). CONCLUSIONS: The presence of IDRFs at diagnosis was associated with high-risk clinical, molecular, and histopathologic features of neuroblastoma. The IDRF group tumor infiltration into adjacent organs and structures was associated with decreased survival. Collectively, these findings may assist surgical planning and medical management for neuroblastoma patients.

Maternal High-Protein and Low-Protein Diets Perturb Hypothalamus and Liver Transcriptome and Metabolic Homeostasis in Adult Mouse Offspring.

Early life nutritional imbalances are risk factors for metabolic dysfunctions in adulthood, but the long term effects of perinatal exposure to high versus low protein diets are not completely understood. We exposed C57BL/6J offspring to a high protein/low carbohydrate (HP/LC) or low protein/high carbohydrate (LP/HC) diet during gestation and lactation, and measured metabolic phenotypes between birth and 10 months of age in male offspring. Perinatal HP/LC and LP/HC exposures resulted in a decreased ability to clear glucose in the offspring, with reduced baseline insulin and glucose concentrations in the LP/HC group and a reduced insulin response post-glucose challenge in the HP/LC group. The LP/HC diet group also showed reduced birth and weanling weights, whereas the HP/LC offspring displayed increased weanling weight with increased adiposity beyond 5 months of age. Gene expression profiling of hypothalamus and liver revealed alterations in diverse molecular pathways by both diets. Specifically, hypothalamic transcriptome and pathway analyses demonstrated perturbations of MAPK and hedgehog signaling, processes associated with neural restructuring and transmission, and phosphate metabolism by perinatal protein imbalances. Liver transcriptomics revealed changes in purine and phosphate metabolism, hedgehog signaling, and circadian rhythm pathways. Our results indicate maternal protein imbalances perturbing molecular pathways in central and peripheral metabolic tissues, thereby predisposing the male offspring to metabolic dysfunctions.