Off-target activity of TNF-alpha inhibitors characterized by protein biochips

Predicting monoclonal antibody binding sequences from a sparse sampling of all possible sequences

Previous work has shown that binding of target proteins to a sparse, unbiased sample of all possible peptide sequences is sufficient to train a machine learning model that can then predict, with statistically high accuracy, target binding to any possible peptide sequence of similar length. Here, highly sequence-specific molecular recognition is explored by measuring binding of 8 monoclonal antibodies (mAbs) with specific linear cognate epitopes to an array containing 121,715 near-random sequences about 10 residues in length. Network models trained on resulting sequence-binding values are used to predict the binding of each mAb to its cognate sequence and to an in silico generated one million random sequences. The model always ranks the binding of the cognate sequence in the top 100 sequences, and for 6 of the 8 mAbs, the cognate sequence ranks in the top ten. Practically, this approach has potential utility in selecting highly specific mAbs for therapeutics or diagnostics. More fundamentally, this demonstrates that very sparse random sampling of a large amino acid sequence spaces is sufficient to generate comprehensive models predictive of highly specific molecular recognition.

A Novel Etanercept-loaded Nano-emulsion for Targeted Treatment of Inflammatory Arthritis via Draining Lymph Node

BACKGROUND

Rheumatoid arthritis (RA) is a systemic autoimmune disease (AD), and the global incidence rate is 0.5 ~ 1%. Existing medications might reduce symptoms, however, there is no known cure for this illness. Etanercept (EN) can competitively inhibit TNF-α binding to the TNF receptor on the cell surface to treat RA. However, subcutaneous injection of free EN predisposes to systemic distribution and induces immune system hypofunction. Draining lymph nodes (LNs) play a significant role in the onset, maintenance, and progression of RA as they are the primary sites of aberrant immune response and inflammatory cytokine production.

AIM

The purpose of this study was to successfully treat RA with etanercept by encapsulating it in nanoemulsions (NEs/EN) and then delivering it specifically to draining LNs. The EN-loaded NEs were prepared by high-pressure homogenization method and modified with DSPE-mPEG2000 and Ca(OH)2.

METHODS

A novel nano-emulsion (NE) was constructed to deliver EN (NE/EN) to RA-draining LNs. To decrease aggregation and load EN, DSPE-mPEG2000 and Ca(OH)2 were successively decorated on the surface of the lipid injectable emulsions. The hydrodynamic diameter and morphology of NEs/EN were investigated by using a laser particle size analyzer and transmission electron microscopy, respectively. The in vivo fluorescence imaging system was used to study the in vivo LN targeting ability of the formulation. In the therapeutic experiment, NEs/EN was subcutaneously administrated to inhibit the development of the mouse arthritis model.

RESULTS

Circular dichroism spectrum and L929 cell experiment confirmed that NEs encapsulation had no impact on the biological activity of EN. In vivo investigation on collagen-induced arthritis (CIA) mouse model showed that NEs/EN have good inguinal lymph node targeting capabilities, as well as, anti-inflammatory effect against RA. Compared with the free group, the paw thickness and arthritic score in NEs/EN group were significantly alleviated. Moreover, the concentration of pro-inflammatory cytokines TNF-α and IL-1β in NEs/EN-treated mice was lower than that in free EN.

CONCLUSION

NEs/EN effectively improve the effectiveness of EN in the treatment of RA. Our work provides an experimental foundation for expanding the clinical application of EN.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics

Developability refers to the likelihood that an antibody candidate will become a manufacturable, safe and efficacious drug. Although the safety and efficacy of a drug candidate will be well considered by sponsors and regulatory agencies, developability in the narrow sense can be defined as the likelihood that an antibody candidate will go smoothly through the chemistry, manufacturing and control (CMC) process at a reasonable cost and within a reasonable timeline. Developability in this sense is the focus of this review. To lower the risk that an antibody candidate with poor developability will move to the CMC stage, the candidate's developability-related properties should be screened, assessed and optimized as early as possible. Assessment of developability at the early discovery stage should be performed in a rapid and high-throughput manner while consuming small amounts of testing materials. In addition to monoclonal antibodies, bispecific antibodies, multispecific antibodies and antibody-drug conjugates, as the derivatives of monoclonal antibodies, should also be assessed for developability. Moreover, we propose that the criterion of developability is relative: expected clinical indication, and the dosage and administration route of the antibody could affect this criterion. We also recommend a general screening process during the early discovery stage of antibody-derived therapeutics. With the advance of artificial intelligence-aided prediction of protein structures and features, computational tools can be used to predict, screen and optimize the developability of antibody candidates and greatly reduce the risk of moving a suboptimal candidate to the development stage.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

The Efficacy and Evidence-Based Use of Biologics in Children and Adolescents: Using Monoclonal Antibodies and Fusion Proteins as Treatments

BACKGROUND

Monoclonal antibodies (mAb) and fusion proteins (FP) are increasingly being used in children and adolescents. In this review, we analyze the evidence for their safety and efficacy in the treatment of the most common chronic inflammatory diseases.

METHODS

We systematically searched PubMed, AWMF.org, and other databases for high-quality trials (i.e., randomized controlled trials with clinical primary endpoints) and guidelines published at any time up to 10 December 2018 that dealt with mAb and FP that are approved for pediatric use. The search term was "monoclonal anti- body/fusion protein [e. g. adalimumab] AND children."

RESULTS

The 620 hits included 25 high-quality trials (20 of them manufacturer- sponsored) on 9 mAb/FP (omalizumab, adalimumab, etanercept, ustekinumab, infliximab, golimumab, anakinra, canakinumab, tocilizumab, and abatacept), as well as 6 guidelines (3 each of levels S3 and S2k) on the treatment of bronchial asthma, psoriasis, juvenile idopathic arthritis, and chronic inflammatory bowel diseases. For none of these conditions are mAb and FP the drugs of first choice. Adverse drug effects are rare but sometimes severe (infection, immune dysregulation, tumors).

CONCLUSION

The retrieved trials have deficiencies that make it difficult to reliably evaluate the efficacy, safety, and utility of mAb/FP for children and adolescents with chronic inflammatory diseases. mAb/FP nonetheless represent a treatment option to be considered in case conventional immune-modulating drugs are ineffective. Researcher-initiated, high-quality trials and manufacturer-independent, systematic long-term evaluations of adverse effects (e.g., tumors) are sorely needed.

A spatial similarity of stereochemical environments formed by amino acid residues defines a common epitope of two non-homologous proteins

It is critical for development of high-quality antibodies in research and diagnostics to predict accurately their cross-reactivities with "off-target" molecules, which potentially induce false results. Herein, we report a good example of such a cross-reactivity for an off-target due to a stereochemical environment of epitopes, which does not simply depend on amino acid sequences. We found that significant subpopulation of a polyclonal peptide antibody against Bcnt (Bucentaur) (anti-BCNT-C antibody) cross-reacted with a completely different protein, glutamine synthetase (GS), and identified four amino acids, GYFE, in its C-terminal region as the core amino acids for the cross-reaction. Consistent with this finding, the anti-BCNT-C antibody strongly recognized endogenously and exogenously expressed GS in tissues and cultured cells by Western blotting and immunohistochemistry. Furthermore, we elucidated that the cross-reaction is caused by a spatial similarity between the stereochemical environments formed by amino acid residues, including the GYFE of GS and the GYIE of Bcnt, rather than by their primary sequences. These results suggest it is critical to comprehensively analyze antibody interactions with target molecules including off-targets with special attention to the physicochemical environments of epitope-paratope interfaces to decrease the risk of false interpretations of results using antibodies in science and clinical applications.

Sustained stimulation of β2- and β3-adrenergic receptors leads to persistent functional pain and neuroinflammation

Functional pain syndromes, such as fibromyalgia and temporomandibular disorder, are associated with enhanced catecholamine tone and decreased levels of catechol-O-methyltransferase (COMT; an enzyme that metabolizes catecholamines). Consistent with clinical syndromes, our lab has shown that sustained 14-day delivery of the COMT inhibitor OR486 in rodents results in pain at multiple body sites and pain-related volitional behaviors. The onset of COMT-dependent functional pain is mediated by peripheral β2- and β3-adrenergic receptors (β2- and β3ARs) through the release of the pro-inflammatory cytokines tumor necrosis factor α (TNFα), interleukin-1β (IL-1β), and interleukin-6 (IL-6). Here, we first sought to investigate the role of β2- and β3ARs and downstream mediators in the maintenance of persistent functional pain. We then aimed to characterize the resulting persistent inflammation in neural tissues (neuroinflammation), characterized by activated glial cells and phosphorylation of the mitogen-activated protein kinases (MAPKs) p38 and extracellular signal-regulated kinase (ERK). Separate groups of rats were implanted with subcutaneous osmotic mini-pumps to deliver OR486 (15 mg/kg/day) or vehicle for 14 days. The β2AR antagonist ICI118551 and β3AR antagonist SR59230A were co-administrated subcutaneously with OR486 or vehicle either on day 0 or day 7. The TNFα inhibitor Etanercept, the p38 inhibitor SB203580, or the ERK inhibitor U0126 were delivered intrathecally following OR486 cessation on day 14. Behavioral responses, pro-inflammatory cytokine levels, glial cell activation, and MAPK phosphorylation were measured over the course of 35 days. Our results demonstrate that systemic delivery of OR486 leads to mechanical hypersensitivity that persists for at least 3 weeks after OR486 cessation. Corresponding increases in spinal TNFα, IL-1β, and IL-6 levels, microglia and astrocyte activation, and neuronal p38 and ERK phosphorylation were observed on days 14-35. Persistent functional pain was alleviated by systemic delivery of ICI118551 and SR59230A beginning on day 0, but not day 7, and by spinal delivery of Etanercept or SB203580 beginning on day 14. These results suggest that peripheral β2- and β3ARs drive persistent COMT-dependent functional pain via increased activation of immune cells and production of pro-inflammatory cytokines, which promote neuroinflammation and nociceptor activation. Thus, therapies that resolve neuroinflammation may prove useful in the management of functional pain syndromes.

Targeting microenvironment in cancer therapeutics

During development of a novel treatment for cancer patients, the tumor microenvironment and its interaction with the tumor cells must be considered. Aspects such as the extracellular matrix (ECM), the epithelial-mesenchymal transition (EMT), secreted factors, cancer-associated fibroblasts (CAFs), the host immune response, and tumor-associated microphages (TAM) are critical for cancer progression and metastasis. Additionally, signaling pathways such as the nuclear factor κB (NF-κB), transforming growth factor β (TGFβ), and tumor necrosis factor α (TNFα) can promote further cytokine release in the tumor environment, and impact tumor progression greatly. Importantly, cytokine overexpression has been linked to drug resistance in cancers and is therefore an attractive target for combinational therapies. Specific inhibitors of cytokines involved in signaling between tumor cells and the microenvironment have not been studied in depth and have great potential for use in personalized medicines. Together, the interactions between the microenvironment and tumors are critical for tumor growth and promotion and should be taken into serious consideration for future novel therapeutic approaches.

Pharmacokinetics of monoclonal antibodies and Fc-fusion proteins

There are many factors that can influence the pharmacokinetics (PK) of a mAb or Fc-fusion molecule with the primary determinant being FcRn-mediated recycling. Through Fab or Fc engineering, IgG-FcRn interaction can be used to generate a variety of therapeutic antibodies with significantly enhanced half-life or ability to remove unwanted antigen from circulation. Glycosylation of a mAb or Fc-fusion protein can have a significant impact on the PK of these molecules. mAb charge can be important and variants with pI values of 1-2 unit difference are likely to impact PK with lower pI values being favorable for a longer half-life. Most mAbs display target mediated drug disposition (TMDD), which can have significant consequences on the study designs of preclinical and clinical studies. The PK of mAb can also be influenced by anti-drug antibody (ADA) response and off-target binding, which require careful consideration during the discovery stage. mAbs are primarily absorbed through the lymphatics via convection and can be conveniently administered by the subcutaneous (sc) route in large doses/volumes with co-formulation of hyaluronidase. The human PK of a mAb can be reasonably estimated using cynomolgus monkey data and allometric scaling methods.

Antibody-siRNA conjugates: drugging the undruggable for anti-leukemic therapy

INTRODUCTION

Generating effective RNAi-based therapies with the potential to achieve leukemia remission remains critical unmet need. Despite a growing number of leukemia clinical trials, tissue specific delivery of therapeutic siRNA is a major roadblock in translating its clinical potential. The most recent reports in the antibody-siRNA-conjugates (ARCs) field add new dimensions to leukemic therapy, where a covalently ligated therapeutic antisense-RNA with the potential to repress the oncogenic transcript is selectively delivered into the cancer cells. Despite ARC localization to leukemic cells due to high affinity antigen-antibody interactions, multiple challenges exist to unlock the therapeutic potential of siRNA targeting. Areas covered: This review focuses on antibody and siRNA-based therapies for leukemia as well as potential antibody engineering-based strategies to generate an optimal ARC platform. Expert opinion: In vitro and clinical results have revealed that non-targeted delivery and inefficient cellular internalization of therapeutic siRNA are major contributing factors for the lack of efficacy in leukemia patients. Rational antibody design and selective protein engineering with the potential to neutralize siRNA charge, stabilize ARC complex, restrict off-targeted delivery, optimize endosomal escape, and extend serum half-life will generate clinically relevant leukemic therapies that are safe, selective, and effective.

Engineering the surface properties of a human monoclonal antibody prevents self-association and rapid clearance in vivo

Uncontrolled self-association is a major challenge in the exploitation of proteins as therapeutics. Here we describe the development of a structural proteomics approach to identify the amino acids responsible for aberrant self-association of monoclonal antibodies and the design of a variant with reduced aggregation and increased serum persistence in vivo. We show that the human monoclonal antibody, MEDI1912, selected against nerve growth factor binds with picomolar affinity, but undergoes reversible self-association and has a poor pharmacokinetic profile in both rat and cynomolgus monkeys. Using hydrogen/deuterium exchange and cross-linking-mass spectrometry we map the residues responsible for self-association of MEDI1912 and show that disruption of the self-interaction interface by three mutations enhances its biophysical properties and serum persistence, whilst maintaining high affinity and potency. Immunohistochemistry suggests that this is achieved via reduction of non-specific tissue binding. The strategy developed represents a powerful and generic approach to improve the properties of therapeutic proteins.

An automated immunoassay for early specificity profiling of antibodies

Antibody-based therapeutics are of great value for the treatment of human diseases. In addition to functional activity, affinity or physico-chemical properties, antibody specificity is considered to be one of the most crucial attributes for safety and efficacy. Consequently, appropriate studies are required before entering clinical trials. High content protein arrays are widely applied to assess antibody specificity, but this commercial solution can only be applied to final therapeutic antibody candidates because such arrays are expensive and their throughput is limited. A flexible, high-throughput and economical assay that allows specificity testing of IgG or Fab molecules during early discovery is described here. The 384-well microtiter plate assay contains a comprehensive panel of 32 test proteins and uses electrochemiluminescence as readout. The Protein Panel Profiling ( 3P) was used to analyze marketed therapeutic antibodies that all showed highly specific binding profiles. Subsequently, 3P was applied to antibody candidates from early discovery and the results compared well with those obtained with a commercially available high content protein chip. Our results suggest that 3P can be applied as an additional filter for lead selection, allowing the identification of favorable antibody candidates in early discovery and thereby increasing the speed and possibility of success in drug development.

Serum-autoantibodies for discovery of prostate cancer specific biomarkers

BACKGROUND

The currently used prostate cancer serum marker has a low cancer specificity and improved diagnostics are needed. Here we evaluated whether autoantibodies are present in sera of prostate cancer patients and whether they are useful diagnostic markers for prostate cancer.

METHODS

Sera from 20 prostate cancer patients and 20 healthy controls were incubated on expression clone arrays containing more than 37,000 recombinant human proteins. Functional annotation clustering of the identified autoantigens was performed using the DAVID database. Autoantigens identified in the prostate cancer group were validated on microarrays using sera of 40 prostate cancer patients, 40 patients with elevated PSA levels but prostate cancer negative biopsies (benign disease), and 40 healthy controls.

RESULTS

We detected autoantibodies against 408 different antigens in sera of prostate cancer patients. One hundred seventy-four of these were exclusively detected in the cancer group compared to the healthy control group. Functional annotation clustering revealed an enrichment of RNA-associated, cytoskeleton, and nuclear proteins. The autoantibody panel was validated in serum samples of independent prostate cancer patients. Autoantibody profiles discriminated between prostate cancer patients and benign disease patients with an ROC curve AUC of 0.71. TTLL12, a protein recently described to be over-expressed in prostate cancer, was the highest ranked discrimination autoantigen.

CONCLUSION

A variety of autoantibodies were identified in sera of prostate cancer patients and provide a first step towards autoantibody diagnostics. Serum autoantibodies reflect the disease and represent valuable tools not only for prostate cancer, but also for other diseases affecting the immune response.

A novel method of transcriptional response analysis to facilitate drug repositioning for cancer therapy

Little research has been done to address the huge opportunities that may exist to reposition existing approved or generic drugs for alternate uses in cancer therapy. In addition, there has been little work on strategies to reposition experimental cancer agents for testing in alternate settings that could shorten their clinical development time. Progress in each area has lagged, in part, because of the lack of systematic methods to define drug off-target effects (OTE) that might affect important cancer cell signaling pathways. In this study, we addressed this critical gap by developing an OTE-based method to repurpose drugs for cancer therapeutics, based on transcriptional responses made in cells before and after drug treatment. Specifically, we defined a new network component called cancer-signaling bridges (CSB) and integrated it with a Bayesian factor regression model (BFRM) to form a new hybrid method termed CSB-BFRM. Proof-of-concept studies were conducted in breast and prostate cancer cells and in promyelocytic leukemia cells. In each system, CSB-BFRM analysis could accurately predict clinical responses to more than 90% of drugs approved by the U.S. Food and Drug Administration and more than 75% of experimental clinical drugs that were tested. Mechanistic investigation of OTEs for several high-ranking drug-dose pairs suggested repositioning opportunities for cancer therapy, based on the ability to enforce retinoblastoma-dependent repression of important E2F-dependent cell-cycle genes. Together, our findings establish new methods to identify opportunities for drug repositioning or to elucidate the mechanisms of action of repositioned drugs.

Highly specific off-target binding identified and eliminated during the humanization of an antibody against FGF receptor 4

Off-target binding can significantly affect the pharmacokinetics (PK), tissue distribution, efficacy and toxicity of a therapeutic antibody. Herein we describe the development of a humanized anti- fibroblast growth factor receptor 4 (FGFR4) antibody as a potential therapeutic for hepatocellular carcinoma (HCC). A chimeric anti FGFR4 monoclonal antibody (chLD1) was previously shown to block ligand binding and to inhibit FGFR4 mediated signaling as well as tumor growth in vivo. A humanized version of chLD1, hLD1.vB, had similar binding affinity and in vitro blocking activity, but it exhibited rapid clearance, poor target tissue biodistribution and limited efficacy when compared to chLD1 in a HUH7 human HCC xenograft mouse model. These problems were traced to instability of the molecule in rodent serum. Size exclusion high performance liquid chromatography, immunoprecipitation and mass spectral sequencing identified a specific interaction between hLD1.vB and mouse complement component 3 (C3). A PK study in C3 knock-out mice further confirmed this specific interaction. Subsequently, an affinity-matured variant derived from hLD1.vB (hLD1.v22), specifically selected for its lack of binding to mouse C3 was demonstrated to have a PK profile and in vivo efficacy similar to that of chLD1 in mice. Although reports of non-specific off-target binding have been observed for other antibodies, this represents the first report identifying a specific off-target interaction that affected disposition and biological activity. Screens developed to identify general non-specific interactions are likely to miss the rare and highly specific cross-reactivity identified in this study, thus highlighting the importance of animal models as a proxy for avoiding unexpected clinical outcomes.

Tumor necrosis factor-alpha antagonist-induced sarcoidosis

Sarcoidosis is a multisystem granulomatous disease of unknown etiology. Tumor necrosis factor (TNF)-alpha is an important player in granuloma formation, and recent clinical trials have investigated the efficacy of TNF-alpha inhibitors in sarcoidosis. Paradoxically, there are several case reports in the medical literature describing the development of sarcoidosis in patients treated with TNF-alpha inhibitors. We describe 3 cases of TNF-alpha antagonist-induced sarcoidosis: 1 case of pulmonary, ocular and cutaneous sarcoidosis developing in a patient receiving infliximab for erosive rheumatoid arthritis, 1 case of etanercept-induced sarcoidosis in a patient with seronegative rheumatoid arthritis, and 1 case of sarcoidosis developing in a patient receiving etanercept for erosive rheumatoid arthritis. We also provide a brief discussion on the role of TNF alpha in granuloma formation and implications in the use of TNF-alpha antagonists in autoimmune disease.

Toward a Successful Clinical Neuroproteomics The 11th HUPO Brain Proteome Project Workshop 3 March, 2009, Kolymbari, Greece

The HUPO Brain Proteome Project (HUPO BPP) held its 11th workshop in Kolymbari on March 3, 2009. The principal aim of this project is to obtain a better understanding of neurodiseases and ageing, with the ultimate objective of discovering prognostic and diagnostic biomarkers, in addition to the development of novel diagnostic techniques and new medications. The attendees came together to discuss sub-project progress in the clinical neuroproteomics of human or mouse models of Alzheimer's and Parkinson's disease, and to define the needs and guidelines required for more advanced proteomics approaches. With the election of new steering committees, the members of the HUPO BPP elaborated an actual plan promoting activities, outcomes, and future directions of the HUPO BPP to acquire new funding and new participants.

Determination and validation of off-target activities of anti-CD44 variant 6 antibodies using protein biochips and tissue microarrays

We describe a novel procedure for determination and validation of off-target activities of anti-cluster designation antigen identity 44 (CD44) variant 6 recombinant antibodies by combining two complementary technology platforms; namely UNIchip AV-400, containing a printed serial dilution of CD44 variant 6 and approximately 400 different human proteins, and TISSOMICS, enabling human tissue microarray analysis in high-throughput mode. We have analyzed the performance of two human monoclonal recombinant antibodies directed against CD44 variant 6 protein, BMS 116 and BMS 125, in a blinded study. The antibodies exhibit a clear differentiation with regard to their binding profiles in the two systems. BMS 116 shows a low degree of specificity in the normal human Food and Drug Administration (FDA) tissue panel, which was confirmed by binding to more than 206 proteins on the protein biochip. In contrast, BMS 125 gives a highly selective membranous staining on selected human epithelial tissue components with no off-target activities observed on the protein biochip. Additionally, antibody BMS 125 shows a higher sensitivity to its antigen CD44 variant 6 than antibody BMS 116 as determined by the protein biochip.