Targeted chemotherapy via HER2-based chimeric antigen receptor (CAR) engineered T-cell membrane coated polymeric nanoparticles.

Cell membrane-derived nanoparticles (NPs) have recently gained popularity due to their desirable features in drug delivery such as mimicking properties of native cells, impeding systemic clearance, and altering foreign body responses. Besides NP technology, adoptive immunotherapy has emerged due to its promise in cancer specificity and therapeutic efficacy. In this research, we developed a biomimetic drug carrier based on chimeric antigen receptor (CAR) transduced T-cell membranes. For that purpose, anti-HER2 CAR-T cells were engineered via lentiviral transduction of anti-HER2 CAR coding lentiviral plasmids. Anti-HER2 CAR-T cells were characterized by their specific activities against the HER2 antigen and used for cell membrane extraction. Anti-cancer drug Cisplatin-loaded poly (D, l-lactide-co-glycolic acid) (PLGA) NPs were coated with anti-human epidermal growth factor receptor 2 (HER2)-specific CAR engineered T-cell membranes. Anti-HER2 CAR-T-cell membrane-coated PLGA NPs (CAR-T-MNPs) were characterized and confirmed via fluorescent microscopy and flow cytometry. Membrane-coated NPs showed a sustained drug release over the course of 21 days in physiological conditions. Cisplatin-loaded CAR-T-MNPs also inhibited the growth of multiple HER2+ cancer cells in vitro. In addition, in vitro uptake studies revealed that CAR-T-MNPs showed an increased uptake by A549 cells. These results were also confirmed via in vivo biodistribution and therapeutic studies using a subcutaneous lung cancer model in nude mice. CAR-T-MNPs localized preferentially at tumor areas compared to those of other studied groups and consisted of a significant reduction in tumor growth in tumor-bearing mice. In Conclusion, the new CAR modified cell membrane-coated NP drug-delivery platform has demonstrated its efficacy both in vitro and in vivo. Therefore, CAR engineered membrane-coated NP system could be a promising cell-mimicking drug carrier that could improve therapeutic outcomes of lung cancer treatments.

The MHC-E peptide ligands for checkpoint CD94/NKG2A are governed by inflammatory signals, whereas LILRB1/2 receptors are peptide indifferent.

The immune checkpoint NKG2A/CD94 is a promising target for cancer immunotherapy, and its ligand major histocompatibility complex E (MHC-E) is frequently upregulated in cancer. NKG2A/CD94-mediated inhibition of lymphocytes depends on the presence of specific leader peptides in MHC-E, but when and where they are presented in situ is unknown. We apply a nanobody specific for the Qdm/Qa-1b complex, the NKG2A/CD94 ligand in mouse, and find that presentation of Qdm peptide depends on every member of the endoplasmic reticulum-resident peptide loading complex. With a turnover rate of 30 min, the Qdm peptide reflects antigen processing capacity in real time. Remarkably, Qdm/Qa-1b complexes require inflammatory signals for surface expression in situ, despite the broad presence of Qa-1b molecules in homeostasis. Furthermore, we identify LILRB1 as a functional inhibition receptor for MHC-E in steady state. These data provide a molecular understanding of NKG2A blockade in immunotherapy and assign MHC-E as a convergent ligand for multiple immune checkpoints.

Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology.

The development of tools for the annotation of genes from newly sequenced species has not evolved much from homologous alignment to prior annotated species. While the quality of gene annotations continues to decline as we sequence and assemble more evolutionary distant gut microbiome species, machine learning presents a high quality alternative to traditional techniques. In this study, we investigate the relative performance of common classical and nonclassical machine learning algorithms in the problem of gene annotation using human microbiome-associated species genes from the KEGG database. The majority of the ensemble, clustering, and deep learning algorithms that we investigated showed higher prediction accuracy than CD-Hit in predicting partial KEGG function. Motif-based, machine-learning methods of annotation in new species were faster and had higher precision-recall than methods of homologous alignment or orthologous gene clustering. Gradient boosted ensemble methods and neural networks also predicted higher connectivity in reconstructed KEGG pathways, finding twice as many new pathway interactions than blast alignment. The use of motif-based, machine-learning algorithms in annotation software will allow researchers to develop powerful tools to interact with bacterial microbiomes in ways previously unachievable through homologous sequence alignment alone.

A Single-Domain TCR-like Antibody Selective for the Qa-1b/Qdm Peptide Complex Enhances Tumoricidal Activity of NK Cells via Blocking the NKG2A Immune Checkpoint.

The NKG2A/HLA-E axis is an immune checkpoint that suppresses immune effector activity in the tumor microenvironment. In mice, the ligand for the NKG2A/CD94 inhibitory receptor is the nonclassical MHC molecule Qa-1b, the HLA-E ortholog, which presents the peptide AMAPRTLLL, referred to as Qdm (for Qa-1 determinant modifier). This dominant peptide is derived from the leader sequences of murine classical MHC class I encoded by the H-2D and -L loci. To broaden our understanding of Qa-1b/Qdm peptide complex biology and its tumor protective role, we identified a TCR-like Ab from a single domain VHH library using yeast surface display. The TCR-like Ab (EXX-1) binds only to the Qa-1b/Qdm peptide complex and not to Qa-1b alone or Qa-1b loaded with control peptides. Conversely, currently available Abs to Qa-1b bind independent of peptide loaded. Flow cytometric results revealed that EXX-1 selectively bound to Qa-1b/Qdm-positive B16F10, RMA, and TC-1 mouse tumor cells but only after pretreatment with IFN-γ; no binding was observed following genetic knockdown of Qa-1b or Qdm peptide. Furthermore, EXX-1 Ab blockade promoted NK cell-mediated tumor cell lysis in vitro. Our findings show that EXX-1 has exquisite binding specificity for the Qa-1b/Qdm peptide complex, making it a valuable research tool for further investigation of the Qa-1b/Qdm peptide complex expression and regulation in healthy and diseased cells and for evaluation as an immune checkpoint blocking Ab in syngeneic mouse tumor models.

Self-Induced Back-Action Actuated Nanopore Electrophoresis (SANE) Sensor for Label-Free Detection of Cancer Immunotherapy-Relevant Antibody-Ligand Interactions.

We fabricated a novel single molecule nanosensor by integrating a solid-state nanopore and a double nanohole nanoaperture. The nanosensor employs Self-Induced Back-Action (SIBA) for optical trapping and enables SIBA-Actuated Nanopore Electrophoresis (SANE) for concurrent acquisition of bimodal optical and electrical signatures of molecular interactions. This work describes how to fabricate and use the SANE sensor to quantify antibody-ligand interactions. We describe how to analyze the bimodal optical-electrical data to improve upon the discrimination of antibody and ligand versus bound complex compared to electrical measurements alone. Example results for specific interaction detection are described for T-cell receptor-like antibodies (TCRmAbs) engineered to target peptide-presenting Major Histocompatibility Complex (pMHC) ligands, representing a model of target ligands presented on the surface of cancer cells. We also describe how to analyze the bimodal optical-electrical data to discriminate between specific and non-specific interactions between antibodies and ligands. Example results for non-specific interactions are shown for cancer-irrelevant TCRmAbs targeting the same pMHCs, as a control. These example results demonstrate the utility of the SANE sensor as a potential screening tool for ligand targets in cancer immunotherapy, though we believe that its potential uses are much broader.

Quantification of low affinity binding interactions between natural killer cell inhibitory receptors and targeting ligands with a self-induced back-action actuated nanopore electrophoresis (SANE) sensor.

A plasmonic nanopore sensor enabling detection of bimodal optical and electrical molecular signatures was fabricated and tested for its ability to characterize low affinity ligand-receptor interactions. This plasmonic nanosensor uses self-induced back-action (SIBA) for optical trapping to enable SIBA-actuated nanopore electrophoresis (SANE) through a nanopore located immediately below the optical trap volume. A natural killer (NK) cell inhibitory receptor heterodimer molecule CD94/NKG2A was synthesized to target a specific peptide-presenting Qa-1b Qdm ligand as a simplified model of low-affinity interactions between immune cells and peptide-presenting cancer cells that occurs during cancer immunotherapy. A cancer-irrelevant Qa-1b GroEL ligand was also targeted by the same receptor as a control experiment to test for non-specific binding. The analysis of different pairs of bimodal SANE sensor signatures enabled discrimination of ligand, receptor and their complexes and enabled differentiating between specific and non-specific ligand interactions. We were able to detect ligand-receptor complex binding at concentrations over 500 times lower than the free solution equilibrium binding constant (K D ). Additionally, SANE sensor measurements enabled estimation of the fast dissociation rate (k off) for this low-affinity specific ligand-receptor system, previously shown to be challenging to quantify with commercial technologies. The k off value of targeted peptide-presenting ligands is known to correlate with the subsequent activation of immune cells in vivo, suggesting the potential utility of the SANE senor as a screening tool in cancer immunotherapy.

Melanoma Peptide MHC Specific TCR Expressing T-Cell Membrane Camouflaged PLGA Nanoparticles for Treatment of Melanoma Skin Cancer.

Melanoma is one of the most aggressive skin cancers, and the American Cancer Society reports that every hour, one person dies from melanoma. While there are a number of treatments currently available for melanoma (e.g., surgery, chemotherapy, immunotherapy, and radiation therapy), they face several problems including inadequate response rates, high toxicity, severe side effects due to non-specific targeting of anti-cancer drugs, and the development of multidrug resistance during prolonged treatment. To improve chemo-drug therapeutic efficiency and overcome these mentioned limitations, a multifunctional nanoparticle has been developed to effectively target and treat melanoma. Specifically, poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) were coated with a cellular membrane derived from the T cell hybridoma, 19LF6 endowed with a melanoma-specific anti-gp100/HLA-A2 T-cell receptor (TCR) and loaded with an FDA-approved melanoma chemotherapeutic drug Trametinib. T-cell membrane camouflaged Trametinib loaded PLGA NPs displayed high stability, hemo- and cyto-compatibility. They also demonstrated membrane coating dependent drug release profiles with the most sustained release from the NPs proportional with the highest amount of membrane used. 19LF6 membrane-coated NPs produced a threefold increase in cellular uptake toward the melanoma cell line in vitro compared to that of the bare nanoparticle. Moreover, the binding kinetics and cellular uptake of these particles were shown to be membrane/TCR concentration-dependent. The in vitro cancer killing efficiencies of these NPs were significantly higher compared to other NP groups and aligned with binding and uptake characteristics. Particles with the higher membrane content (greater anti-gp100 TCR content) were shown to be more effective when compared to the free drug and negative controls. In vivo biodistribution studies displayed the theragnostic capabilities of these NPs with more than a twofold increase in the tumor retention compared to the uncoated and non-specific membrane coated groups. Based on these studies, these T-cell membrane coated NPs emerge as a potential theragnostic carrier for imaging and therapy applications associated with melanoma.

Detection of specific antibody-ligand interactions with a self-induced back-action actuated nanopore electrophoresis sensor.

Recent advances in plasmonic nanopore technologies have enabled the use of concurrently acquired bimodal optical-electrical data for improved quantification of molecular interactions. This work presents the use of a new plasmonic nanosensor employing self-induced back-action (SIBA) for optical trapping to enable SIBA-actuated nanopore electrophoresis (SANE) for quantifying antibody-ligand interactions. T-cell receptor-like antibodies (TCRmAbs) engineered to target peptide-presenting major histocompatibility complex (pMHC) ligands, representing a model of target ligands presented on the surface of cancer cells, were used to test the SANE sensor's ability to identify specific antibody-ligand binding. Cancer-irrelevant TCRmAbs targeting the same pMHCs were also tested as a control. It was found that the sensor could provide bimodal molecular signatures that could differentiate between antibody, ligand and the complexes that they formed, as well as distinguish between specific and non-specific interactions. Furthermore, the results suggested an interesting phenomenon of increased antibody-ligand complex bound fraction detected by the SANE sensor compared to that expected for corresponding bulk solution concentrations. A possible physical mechanism and potential advantages for the sensor's ability to augment complex formation near its active sensing volume at concentrations lower than the free solution equilibrium binding constant (K D ) are discussed.

MicroRNA dysregulational synergistic network: discovering microRNA dysregulatory modules across subtypes in non-small cell lung cancers.

BACKGROUND: The majority of cancer-related deaths are due to lung cancer, and there is a need for reliable diagnostic biomarkers to predict stages in non-small cell lung cancer cases. Recently, microRNAs were found to have potential as both biomarkers and therapeutic targets for lung cancer. However, some of the microRNA's functions are unknown, and their roles in cancer stage progression have been mostly undiscovered in this clinically and genetically heterogeneous disease. As evidence suggests that microRNA dysregulations are implicated in many diseases, it is essential to consider the changes in microRNA-target regulation across different lung cancer subtypes. RESULTS: We proposed a pipeline to identify microRNA synergistic modules with similar dysregulation patterns across multiple subtypes by constructing the MicroRNA Dysregulational Synergistic Network. From the network, we extracted microRNA modules and incorporated them as prior knowledge to the Sparse Group Lasso classifier. This leads to a more relevant selection of microRNA biomarkers, thereby improving the cancer stage classification accuracy. We applied our method to the TCGA Lung Adenocarcinoma and the Lung Squamous Cell Carcinoma datasets. In cross-validation tests, the area under ROC curve rate for the cancer stages prediction has increased considerably when incorporating the learned microRNA dysregulation modules. The extracted modules from multiple independent subtypes differential analyses were found to have high agreement with microRNA family annotations, and they can also be used to identify mutual biomarkers between different subtypes. Among the top-ranked candidate microRNAs selected by the model, 87% were reported to be related to Lung Adenocarcinoma. The overall result demonstrates that clustering microRNAs from the dysregulation pattern between microRNAs and their targets leads to biomarkers with high precision and recall rate to known differentially expressed disease-associated microRNAs. CONCLUSIONS: The results indicated that our method improves microRNA biomarker selection by detecting similar microRNA dysregulational synergistic patterns across the multiple subtypes. Since microRNA-target dysregulations are implicated in many cancers, we believe this tool can have broad applications for discovery of novel microRNA biomarkers in heterogeneous cancer diseases.

Improved microRNA biomarkers for pathological stages in lung adenocarcinoma via clustering of dysregulated microRNA-target associations.

Most of cancer-related deaths are due to lung cancer, and there is a need for reliable prognosis biomarkers to predict stages in lung adenocarcinoma cases. Recently, microRNAs are found to have potential as both biomarkers and therapeutic targets for lung cancer. As evidence suggests microRNA dysregulations are implicated in many cancer malignancies, it is important to consider the changes in miRNA-target associations among different lung cancer biological states. We proposed a novel clustering strategy to identify groups of miRNAs with similar dysregulated targets. Then, we incorporated the learned clusters of miRNA as prior knowledge to a Sparse Group Lasso classifier to improve classification results, thereby leading to more relevant selection of microRNA biomarkers. We apply the method to the TCGA Lung Adenocarcinoma dataset. In cross-validation tests, the AUC rate for each stages is 1.0, 0.71, 0.68, 0.64, and 0.90 for normal, Stage I, Stage II, Stage III, and Stage IV, respectively. Among the candidate miRNAs selected in the model, 87% are reported to be related to Lung Adenocarcinoma. Further result demonstrates that clustering miRNAs by considering the dysregulation between miRNAs and mRNA targets leads to biomarkers with higher precision and recall rate to known lung adenocarcinoma miRNAs.

TCR-like antibody drug conjugates mediate killing of tumor cells with low peptide/HLA targets.

The currently marketed antibody-drug conjugates (ADC) destabilize microtubule assembly in cancer cells and initiate apoptosis in patients. However, few tumor antigens (TA) are expressed at high densities on cancer lesions, potentially minimizing the therapeutic index of current ADC regimens. The peptide/human leukocyte antigen (HLA) complex can be specifically targeted by therapeutic antibodies (designated T cell receptor [TCR]-like antibodies) and adequately distinguish malignant cells, but has not been the focus of ADC development. We analyzed the killing potential of TCR-like ADCs when cross-linked to the DNA alkylating compound duocarmycin. Our data comprise proof-of-principle results that TCR-like ADCs mediate potent tumor cytotoxicity, particularly under common scenarios of low TA/HLA density, and support their continued development alongside agents that disrupt DNA replication. Additionally, TCR-like antibody ligand binding appears to play an important role in ADC functionality and should be addressed during therapy development to avoid binding patterns that negate ADC killing efficacy.

Immunodominant West Nile Virus T Cell Epitopes Are Fewer in Number and Fashionably Late.

Class I HLA molecules mark infected cells for immune targeting by presenting pathogen-encoded peptides on the cell surface. Characterization of viral peptides unique to infected cells is important for understanding CD8(+) T cell responses and for the development of T cell-based immunotherapies. Having previously reported a series of West Nile virus (WNV) epitopes that are naturally presented by HLA-A*02:01, in this study we generated TCR mimic (TCRm) mAbs to three of these peptide/HLA complexes-the immunodominant SVG9 (E protein), the subdominant SLF9 (NS4B protein), and the immunorecessive YTM9 (NS3 protein)-and used these TCRm mAbs to stain WNV-infected cell lines and primary APCs. TCRm staining of WNV-infected cells demonstrated that the immunorecessive YTM9 appeared several hours earlier and at 5- to 10-fold greater density than the more immunogenic SLF9 and SVG9 ligands, respectively. Moreover, staining following inhibition of the TAP demonstrated that all three viral ligands were presented in a TAP-dependent manner despite originating from different cellular compartments. To our knowledge, this study represents the first use of TCRm mAbs to define the kinetics and magnitude of HLA presentation for a series of epitopes encoded by one virus, and the results depict a pattern whereby individual epitopes differ considerably in abundance and availability. The observations that immunodominant ligands can be found at lower levels and at later time points after infection suggest that a reevaluation of the factors that combine to shape T cell reactivity may be warranted.

Human Leukocyte Antigen-Presented Macrophage Migration Inhibitory Factor Is a Surface Biomarker and Potential Therapeutic Target for Ovarian Cancer.

T cells recognize cancer cells via HLA/peptide complexes, and when disease overtakes these immune mechanisms, immunotherapy can exogenously target these same HLA/peptide surface markers. We previously identified an HLA-A2-presented peptide derived from macrophage migration inhibitory factor (MIF) and generated antibody RL21A against this HLA-A2/MIF complex. The objective of the current study was to assess the potential for targeting the HLA-A2/MIF complex in ovarian cancer. First, MIF peptide FLSELTQQL was eluted from the HLA-A2 of the human cancerous ovarian cell lines SKOV3, A2780, OV90, and FHIOSE118hi and detected by mass spectrometry. By flow cytometry, RL21A was shown to specifically stain these four cell lines in the context of HLA-A2. Next, partially matched HLA-A*02:01+ ovarian cancer (n = 27) and normal fallopian tube (n = 24) tissues were stained with RL21A by immunohistochemistry to assess differential HLA-A2/MIF complex expression. Ovarian tumor tissues revealed significantly increased RL21A staining compared with normal fallopian tube epithelium (P < 0.0001), with minimal staining of normal stroma and blood vessels (P < 0.0001 and P < 0.001 compared with tumor cells) suggesting a therapeutic window. We then demonstrated the anticancer activity of toxin-bound RL21A via the dose-dependent killing of ovarian cancer cells. In summary, MIF-derived peptide FLSELTQQL is HLA-A2-presented and recognized by RL21A on ovarian cancer cell lines and patient tumor tissues, and targeting of this HLA-A2/MIF complex with toxin-bound RL21A can induce ovarian cancer cell death. These results suggest that the HLA-A2/MIF complex should be further explored as a cell-surface target for ovarian cancer immunotherapy.

Detection of human leukocyte antigen biomarkers in breast cancer utilizing label-free biosensor technology.

According to the American Cancer Society, more than 200,000 women will be diagnosed with invasive breast cancer each year and approximately 40,000 will die from the disease. The human leukocyte antigen (HLA) class I samples peptides derived from proteasomal degradation of cellular proteins and presents these fragments on the cell surface for interrogation by circulating cytotoxic T lymphocytes (CTL). Generation of T-cell receptor mimic (TCRm) monoclonal antibodies (mAbs) which recognize breast cancer specific peptide/HLA-A*02:01 complexes such as those derived from macrophage migration inhibitory factor (MIF19-27) and NY-ESO-1157-165 enable detection and destruction of breast cancer cells in the absence of an effective anti-tumor CTL response. Intact class I HLA/peptide complexes are shed by breast cancer cells and represent potentially relevant cancer biomarkers. In this work, a breakthrough biomarker screening system for cancer diagnostics incorporating T-cell receptor mimic monoclonal antibodies combined with a novel, label-free biosensor utilizing guided-mode resonance (GMR) sensor technology is presented. Detection of shed MIF/HLA-A*02:01 complexes in MDA-MB-231 cell supernatants, spiked human serum, and patient plasma is demonstrated. The impact of this work could revolutionize personalized medicine through development of companion disease diagnostics for targeted immunotherapies.

A novel T-cell receptor mimic defines dendritic cells that present an immunodominant West Nile virus epitope in mice.

We used a newly generated T-cell receptor mimic monoclonal antibody (TCRm MAb) that recognizes a known nonself immunodominant peptide epitope from West Nile virus (WNV) NS4B protein to investigate epitope presentation after virus infection in C57BL/6 mice. Previous studies suggested that peptides of different length, either SSVWNATTAI (10-mer) or SSVWNATTA (9-mer) in complex with class I MHC antigen H-2D(b) , were immunodominant after WNV infection. Our data establish that both peptides are presented on the cell surface after WNV infection and that CD8(+) T cells can detect 10- and 9-mer length variants similarly. This result varies from the idea that a given T-cell receptor (TCR) prefers a single peptide length bound to its cognate class I MHC. In separate WNV infection studies with the TCRm MAb, we show that in vivo the 10-mer was presented on the surface of uninfected and infected CD8α(+) CD11c(+) dendritic cells, which suggests the use of direct and cross-presentation pathways. In contrast, CD11b(+) CD11c(-) cells bound the TCRm MAb only when they were infected. Our study demonstrates that TCR recognition of peptides is not limited to certain peptide lengths and that TCRm MAbs can be used to dissect the cell-type specific mechanisms of antigen presentation in vivo.

Antitumor activity of a monoclonal antibody targeting major histocompatibility complex class I-Her2 peptide complexes.

BACKGROUND: Applications of trastuzumab are limited to breast cancer patients with high Her2-expressing tumors. We developed a T-cell receptor mimic (TCRm) monoclonal antibody (hereafter called RL1B) that targets the Her2-E75 peptide (residues 369-377)-HLA-A2 complex and examined its effects in Her2-expressing cancer cells. METHODS: RL1B binding affinity was determined by surface plasmon resonance and specificity was demonstrated using Her2 antigen-positive and negative tumor cell lines. Immunohistochemistry was used to assess binding to frozen sections of human carcinomas (n = 3). Antitumor activity mediated by RL1B and trastuzumab against Her2(+) tumor cell lines was evaluated using the WST-1 cell viability assay and caspase-3 and poly(ADP-ribose) polymerase cleavage assays. A xenograft mouse model (n = 6 per group) was used to assess RL1B antitumor activity. Mechanisms of RL1B-mediated cytotoxicity were evaluated with confocal microscopy, flow cytometry, and histology. All statistical tests were two-sided. RESULTS: RL1B bound with high specificity and affinity to the E75 peptide-HLA-A2 complex in all Her2(+) and HLA-A2(+) cancer cell lines and human carcinomas. Compared with control antibody, RL1B suppressed growth of low Her2-expressing breast tumors in mice (mean volume, RL1B vs control = 241 mm(3) vs 1531 mm(3); P = .0109) and statistically significantly increased mouse survival (P = .0098). It reduced viability compared to control monoclonal antibody-treated cells and statistically significantly increased caspase 3 activation of all Her2(+) carcinoma cell lines tested, whereas trastuzumab induced apoptosis only in high Her2-expressing cancer cells. Mechanisms of RL1B cytotoxicity were associated with antibody internalization and intracellular signaling. CONCLUSION: The TCRm RL1B could be a new approach to immunotherapy of Her2-expressing malignancies.

TCR-like biomolecules target peptide/MHC Class I complexes on the surface of infected and cancerous cells.

The human leukocyte antigen (HLA; also called major histocompatibility, or MHC) class I system presents peptides that distinguish healthy from diseased cells. Therefore, the discovery of peptide/MHC class I markers can provide highly specific targets for immunotherapy. Over the course of almost two decades, various strategies have been used, with mixed success, to produce antibodies that have recognition specificity for unique peptide/MHC class I complexes that mark infected and cancerous cells. Using these antibody reagents, novel peptide/MHC class I targets have been directly validated on diseased cells and new insight has been gained into the mechanisms of antigen presentation. More recently, these antibodies have shown promise for clinical applications such as therapeutic targeting of cancerous and infected cells and diagnosis and imaging of diseased cells. In this review, the authors comprehensively describe the methods used to identify disease-specific peptide/MHC class I epitopes and generate antibodies to these markers. Finally, they offer several examples that illustrate the promise of using these antibodies as anti-cancer agents.

Expanding the targets available to therapeutic antibodies via novel disease-specific markers.

The development of immunotherapies offers significant promise for clinical applications in cancer and infectious diseases. Here the authors describe a novel, integrated approach to immunotherapy that combines novel technologies to discover and target disease-specific peptide/HLA class I complexes. This unique class of markers makes the entire proteome accessible to antibody reagents and offers unsurpassed specificity for targeting cancerous and infected cells. Arm one of the three-armed approach uses an innovative technology for the efficient, direct discovery of new peptide/HLA class I markers. Arm two applies a powerful and inventive strategy to generate T-cell receptor mimics (TCRms), which are antibodies with exquisite binding specificity for peptide/HLA class I markers, and uses TCRms to validate the specific expression of markers on cancerous and infected cells. The third arm uses TCRms to target and kill diseased cells with high sensitivity and specificity. In summary, the combination of two pioneering technologies expands the repertoire of disease-specific markers that can be targeted by therapeutic antibodies and enables a powerful, integrated approach to HLA-based immunotherapy.

An HLA-presented fragment of macrophage migration inhibitory factor is a therapeutic target for invasive breast cancer.

This report describes a novel HLA/peptide complex with potential prognostic and therapeutic roles for invasive breast cancer. Macrophage migration inhibitory factor (MIF) mediates inflammation and immunity, and MIF overexpression is observed in breast cancer. We hypothesized that the HLA class I of cancerous breast epithelial cells would present MIF-derived peptides. Consistent with this hypothesis, the peptide FLSELTQQL (MIF(19-27)) was eluted from the HLA-A*0201 (HLA-A2) of breast cancer cell lines. We posited that if this MIF(19-27)/HLA-A2 complex was exclusively found in invasive breast cancer, it could be a useful prognostic indicator. To assess the presentation of MIF peptides by the HLA of various cells and tissues, mice were immunized with the MIF(19-27)/HLA-A2 complex. The resulting mAb (RL21A) stained invasive ductal carcinoma (IDC) but not ductal carcinoma in situ, fibroadenoma, or normal breast tissues. RL21A did not stain WBCs (total WBCs) or normal tissues from deceased HLA-A2 donors, substantiating the tumor-specific nature of this MIF/HLA complex. As this MIF/HLA complex appeared specific to the surface of IDC, RL21A was tested as an immunotherapeutic for breast cancer in vitro and in vivo. In vitro, RL21A killed the MDA-MB-231 cell line via complement and induction of apoptosis. In an in vivo orthotopic mouse model, administration of RL21A reduced MDA-MB-231 and BT-20 tumor burden by 5-fold and by >2-fold, respectively. In summary, HLA-presented MIF peptides show promise as prognostic cell surface indicators for IDC and as targets for immunotherapeutic intervention.