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Nix, M. A.

Publications and source records attributed to Nix, M. A..

6 recordsLinked to original sources

Affinity-matured CD72-targeting Nanobody CAR T-cells Enhance Elimination of Antigen-Low B-cell Malignancies

BackgroundChimeric antigen receptor (CAR) T-cell therapies are highly efficacious for several different hematologic cancers. However, for most CAR T targets it is observed that low surface antigen density on tumors can significantly reduce therapeutic efficacy. Here, we explore this dynamic in the context of CD72, a surface antigen we recently found as a promising target for refractory B-cell cancers, but for which CD72 low antigen density can lead to therapeutic resistance in preclinical models. MethodsPrimary samples were accessed via institutional review board-approved protocols. Affinity-matured and humanized nanobody clones were previously described in Temple et al.1 CAR T-cells were generated via lentiviral transduction. In vitro cytotoxicity assays were performed using luciferase-labeled cell lines. In vivo studies were performed using cell line- or patient-derived xenografts implanted in NOD scid gamma (NSG) mice. ResultsWe first confirmed ubiquitous CD72 expression across a range of primary B-cell non-Hodgkin lymphomas. We further found that after resistance to CD19-directed therapies, across both B-cell acute lymphoblastic leukemia (B-ALL) models and primary tumor samples, surface CD72 expression was largely preserved while CD22 expression was significantly diminished. Affinity maturation of a nanobody targeting CD72, when incorporated into chimeric antigen receptor (CAR) T-cells, led to more effective elimination in vitro of isogenic models of CD72 low-expressing tumors. These results suggested that nanobody-based CAR T-cells (nanoCARs) may exhibit a similar relationship between binder affinity, antigen expression, and efficacy as previously demonstrated only for scFv-based CAR T-cells. Surprisingly, however, this significantly improved in vitro efficacy only translated to modest in vivo survival benefit. As a parallel strategy to enhance CAR T function, we found that the small molecule bryostatin could also significantly increase CD72 surface antigen density on B-cell malignancy models. Structural modeling and biochemical analysis identified critical residues improving CD72 antigen recognition of our lead affinity-matured nanobody. ConclusionsTogether, these findings support affinity-matured CD72 nanoCARs as a potential immunotherapy product for CD19-refractory B-cell cancers. Our results also suggest that for B-ALL in particular, CD72 may be a preferable second-line immunotherapy target over CD22. What is already known on this topicPrevious work using single chain variable fragment (scFv) based CAR Ts has suggested that improving affinity for target antigen could potentially help mitigate tumor resistance mediated by antigen downregulation, or baseline low antigen density. However, it is unknown whether this same dynamic holds for CAR T-cells that utilize different antigen recognition elements, such as nanobodies. What this study addsHere we show that affinity maturation of nanobody-based CAR T-cells (nanoCARs) targeting CD72 can improve their in vitro efficacy versus CD72-low tumors; however, in vivo efficacy differences are more modest. Furthermore, we show that for refractory B-cell malignancies, surface CD72 appears preserved after CD19 resistance even in situations where CD22 is strongly downregulated. How this study might affect research, practice or policyCD72 warrants further investigation as a preferred immunotherapy target in the context of CD19-refractory B-cell cancers, though nanobody affinity maturation is not a universal solution to the challenge of low tumor surface antigen density.

immunology↗

Structural surfaceomics reveals an AML-specific conformation of Integrin-β2 as a CAR-T 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, invisible to standard target discovery pipelines evaluating gene or protein expression, that can be identified and immunotherapeutically targeted. We term this strategy, integrating cross-linking mass spectrometry (XL-MS) with glycoprotein surface capture, "structural surfaceomics". As a proof of principle, we apply this technology to acute myeloid leukemia, a hematologic malignancy with dismal outcomes and no known optimal immunotherapy target. We identify the activated conformation of integrin-{beta}2 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 (CAR) T-cells eliminate AML cells and patient-derived xenografts without notable toxicity versus normal hematopoietic cells. Our findings validate an AML conformation-specific target antigen while demonstrating a toolkit for applying these strategies more broadly.

cancer biology↗

Defining the cell surface proteomic landscape of multiple myeloma reveals immunotherapeutic strategies and biomarkers of drug resistance

The myeloma cell surface proteome ("surfaceome") not only determines tumor interaction with the microenvironment but serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to first define surface markers most-enriched on myeloma when compared to B-cell malignancy models, revealing unexpected biological signatures unique to malignant plasma cells. We next integrate our proteomic dataset with existing transcriptome databases, nominating CCR10 and TXNDC11 as possible monotherapeutic targets and CD48 as a promising co-target for increasing avidity of BCMA-directed cellular therapies. We further identify potential biomarkers of resistance to both proteasome inhibitors and lenalidomide including changes in CD53, EVI2B, CD10, and CD33. Comparison of short-term treatment with chronic resistance delineates large differences in surface proteome profile under each type of drug exposure. Finally, we develop a miniaturized version of the surface proteomics protocol and present the first surface proteomic profile of a primary myeloma patient plasma cell sample. Our dataset provides a unique resource to advance the biological, therapeutic, and diagnostic understanding of myeloma.

cancer biology↗

Engineered ACE2 receptor traps potently neutralize SARS-CoV-2

An essential mechanism for SARS-CoV-1 and -2 infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human Fc domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2 pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50) in the 10-100 ng/ml range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-utilizing coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be pre-designed for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated or generated from convalescent patients.

bioengineering↗

Signaling input from divergent pathways subverts malignant B-cell transformation

Malignant transformation typically involves multiple genetic lesions whose combined activity gives rise to cancer1. Our analysis of 1,148 patient-derived B-cell leukemia (B-ALL) samples revealed that individual mutations did not promote leukemogenesis unless they converged on one single oncogenic pathway characteristic for the differentiation status of these transformed B cells. Specifically, we show here the JAK/STAT5 signaling pathway supports the developmental stage-specific expansion of pro-B ALL whereas the ERK-pathway that of pre-B ALL. Mutations that were not aligned with the central oncogenic driver would activate divergent pathways and subvert malignant transformation. Oncogenic lesions in B-ALL frequently mimic survival and proliferation signals downstream of cytokine receptors (through activation of STAT5)2-7 or the pre-B cell receptor (through activation of ERK)8-13. STAT5- (372 cases) and ERK- (386 cases) activating lesions were frequently found but only co-occurred in [~]3% (37) of cases (P=2.2E-16). Single-cell mutation and phosphoprotein analyses revealed that even in these rare cases, oncogenic STAT5- or ERK-activation were mutually exclusive and segregated to competing clones. STAT5 and ERK engaged opposing biochemical and transcriptional programs orchestrated by MYC and BCL6, respectively. Genetic reactivation of the divergent (suppressed) pathway came at the expense of the principal oncogenic driver and reversed malignant transformation. Conversely, Cre-mediated deletion of divergent pathway components triggered leukemia-initiation and accelerated development of fatal disease. Thus, persistence of divergent signaling pathways represents a powerful barrier to malignant transformation while convergence on one principal driver defines a key event during leukemia-initiation. Proof-of-concept studies in patient-derived B-ALL cells revealed that pharmacological reactivation of suppressed divergent circuits strongly synergized with direct inhibition of the principal oncogenic driver. Hence, pharmacological reactivation of divergent pathways can be leveraged as a previously unrecognized strategy to deepen treatment responses and to overcome drug-resistance. Current treatment approaches for drug-resistant cancer are focused on drug-combinations to suppress the central oncogenic driver and multiple alternative pathways14-17. Here, we introduce a concept based on inhibition of the principal driver combined with pharmacological reactivation of divergent pathways.

cancer biology↗

Evaluating the efficacy of multiple myeloma cell lines as models for patient tumors via transcriptomic correlation analysis

Multiple myeloma (MM) cell lines are routinely used to model the disease. However, a long-standing question is how well these cell lines truly represent tumor cells in patients. Here, we employ a recently-described method of transcriptional correlation profiling to compare similarity of 66 MM cell lines to 779 newly-diagnosed MM patient tumors. We found that individual MM lines differ significantly with respect to patient tumor representation, with median R ranging from 0.35-0.54. ANBL-6 was the "best" line, markedly exceeding all others (p < 2.2e-16). Notably, some widely-used cell lines (RPMI-8226, U-266) scored poorly in our patient similarity ranking (48 and 52 of 66, respectively). Lines cultured with interleukin-6 showed significantly improved correlations with patient tumor (p = 9.5e-4). When common MM genomic features were matched between cell lines and patients, only t(4;14) and t(14;16) led to increased transcriptional correlation. To demonstrate utility of our top-ranked line for preclinical studies, we showed that intravenously-implanted ANBL-6 proliferates in hematopoietic organs in immunocompromised mice. Overall, our large-scale quantitative correlation analysis, utilizing emerging datasets, provides a resource informing the MM community of cell lines that may be most reliable for modeling patient disease while also elucidating biological differences between cell lines and tumors.

cancer biology↗