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Review Article, J Clin Exp Oncol Vol: 7 Issue: 4

Screening of Monoclonal Antibodies for Cancer Treatment

Peifeng Tang1,2, Shaoyan Liang1, Jianlin Xu3, Shaoxiong Wang1, Lijun Wang4 and Shijie Liu2*

1Department of Process Development, Mab-Venture Biopharm Co. Ltd., Shanghai, China

2Department of Paper and Bioprocess Engineering, State University of New York-College of Environmental Science and Forestry, Syracuse, New York, USA

3Biologics Process Development, Global Manufacturing and Supply, Bristol- Myers Squibb Company, Devens, Massachusetts, USA

4College of Light Industry and Food Engineering, Guangxi University, Nanning, China

*Corresponding Author : Shijie Liu
Department of Paper and Bioprocess Engineering, State University of New York-College of Environmental Science and Forestry, Syracuse, New York, USA
Tel: (315) 470-6885/470-6501
E-mail:
[email protected]; [email protected]

Received: August 01, 2017 Accepted: January 23, 2018 Published: January 31, 2018

Citation: Tang P, Liang S, Xu J, Wang S, Wang L, et al. (2018) Screening of Monoclonal Antibodies for Cancer Treatment. J Clin Exp Oncol 7:4. doi: 10.4172/2324-9110.1000225

Abstract

With the rapid development of cancer treatment using monoclonal antibodies (mAbs), the screening process of suitable biologics and indications attracts much attention. A general definition of ‘screening’ in the biopharmaceutical industry includes three aspects: the appropriate biologics for the specific cancers, the appropriate indications for the specific biologics and the promising biologic candidates from the pool at the pre-clinical drug discovery stage. Effective screening strategies in the biopharmaceutical industry are crucial to accelerate the drug commercialization process and select the effective biologics for patients. The current status of commercial mAbs and the global pharmaceutical market was briefly reviewed. The mechanism of commercial mAbs and the indications, as well as the current technologies for mAbs screening in the new drug discovery and cell line development stages were systematically reviewed, with an aim as a beneficial reference for screening highquality mAbs, appropriate indications with efficient technologies.

Keywords: Screening; Cancer treatment; Biomarker; Monoclonal antibodies

Abbreviations

ADC: Antibody Drug Conjugate; BLA: Biologic License Application; CMC: Chemistry Manufacturing and Control; ELISA: Enzyme-Linked Immunosorbent Assay; FMAT: Fluorometric Microvolume Assay; FACS: Fluorescence-Activated Cell Sorting; MAb: Monoclonal Antibody; M-M: Michaelis-Menten; MWC: Monod-Wyman-Changeux; QbD: Quality by Design

Introduction

Cancer is the global leading cause of death [1]. It is featured as unregulated cell division and growth [2]. Caused by genic mutation or gene expression disorder, abnormal metabolism can be observed within cells [3]. While gene therapy is still away from well accepted by FDA, monoclonal antibodies (mAbs), as one of the major parts of biologics, are currently widely recognized drugs for conservative cancer treatment. The mAbs are antibodies made by identical cells, which are all derived from a unique parent immune cell [4,5]. The history of mAbs can be traced back to 1975 when recombinant DNA technology was applied to antibody design [6]. The first mAb approved by FDA was OKT3 in 1986 [7] though it took almost three decades to the current ‘golden age’ of cancer therapies using mAbs [8]. Currently, around one hundred commercial mAbs are available in the global market.

The biopharmaceutical industry is regarded, as a matter of fact, a high risk and high revenue industry. On average, it takes $1.2 to $4 billion and 10 to 12 years for a biologic candidate to be approved and enter the market from the discovery stage. From the risk point of view, less than 0.1 % of the biologic candidates before CMC stages are able to enter into Phase I. Among those biologics, 60 % fail to pass Phase Ⅱ, while there’s another 50% failure risk at Phase Ⅲ the clinical stage. In addition, there are significantly higher risks at earlier new drug discovery stages. Thus, the efficient and successful screening of mAb candidates and corresponding indications is crucial. The word “screening” in the biopharmaceutical industry refers to three aspects:

Screening of drug or biologic candidates for specific diseases;

Screening the potential indications for specific drugs or biologics; and

Screening of promising drug or biologic candidates from the pool in the pre-clinical stage.

Undoubtedly, all the aspects are definitive for the destiny of one biologic candidate.

In this work, the current commercial mAbs and the recognized biomarkers were systematically reviewed. The principles, criteria, modeling and detection methods of biologics screening were presented and compared. This review aims at providing comprehensive screening information for cancer treatment, which is potentially beneficial for research institutes, pharmaceutical companies and patients.

Mechanism

It is known that one distinctive characteristics of cancer from other diseases is that immune cells have difficulties to distinguish tumor cells from normal cells [5]. Therefore, a process that can either assist the immune cells to identify the tumor cells, or stimulate the immune cells to be more active should exhibit potential for cancer treatment. MAbs, which are designed for distinguishing the biomarkers abnormally expressed on tumor cells or specifically expressed by immune cells, are recognized as promising biologics to annihilate tumor cells. Though the exact metabolic details of how mAbs work is awaiting better understanding, the general mechanism typically falls into two categories:

mAbs distinguish and bind the biomarkers abnormally expressed by the tumor cells, helping the immune cells to target these cells. For example, trastuzumab, which was designed to target the biomarkers HER2, is a representative commercial mAb for breast cancer.

The immune cells are activated by mAbs to attack the tumor cells. Successful commercialized examples, such as nivolumab and pembrolizumab which target PD-1 and PD-L1 biomarkers; respectively, were designed based on such mechanism.

Owing to limited understanding of mammalian cell metabolism, limited biomarkers have been detected and only with parts of them have been used for mAbs design. Table 1 listed 43 recognized biomarkers that have been successfully used for commercial mAb design. Indications that exhibited abnormal expression of these biomarkers have been well studied. The one-to-one correspondence shown in the table aims to help narrow down the screening scope of the mAbs and indications, as well as predict the clinical results and control the quality of the designed protein therapeutics, which is in compliance with the Quality by Design (QbD) principles. This information may help biopharmaceutical industry to make decisions on biologics design at early discovery stage or on indication selection at clinical stages

Antigen Biomarkers Indications References
α-4 integrin Multiple sclerosis [39]
BLyS Systemic lupus erythematosus [40]
CCR4 Relapsed or refractory adult T-cell leukemia/lymphoma [41]
CD3 Transplant rejection, organ [42]
CD6 Psoriasis, Arthritis, rheumatoid [43]
CD19 Precursor B-cell acute lymphoblastic leukemia [44]
CD20 Relapsed or refractory low-grade, follicular, or transformed B-cell non-Hodgkin's lymphoma, chronic lymphocytic leukemia, and multiple sclerosis [45]
CD30 Hodgkin lymphoma, and anaplastic large-cell lymphoma [46,47]
CD38 Multiple myeloma [48]
CD52 B-cell chronic lymphocytic leukemia [49]
Clostridium difficile toxin B Prevent recurrence of Clostridium difficile infection [50]
Complement component 5 Paroxysmal nocturnal hemoglobinuria [51]
CTLA-4 Metastatic melanoma [52]
Dabigatran Emergency reversal of anticoagulant dabigatran [53]
EGFR Metastatic colorectal carcinoma, and metastatic squamous non-small cell lung carcinoma [54,55]
EpCAM Malignant ascites, multiple cancers [56]
F protein of RSV Respiratory syncytial virus [57]
Ganglionside P3 Multiple cancers [58]
GD2 Pediatric high-risk neuroblastoma [59]
GPIIb/IIIa Percutaneous coronary intervention [60]
HER2 Metastatic breast cancer [61]
IgE Moderate to severe persistent asthma [62]
IL12 Plaque psoriasis [63]
IL23 Psoriatic arthritis, plaque psoriasis, and crohn's disease [63,64]
IL17A / IL17RA Plaque psoriasis [65]
IL1B Cryopyrin-associated periodic syndrome [66]
IL2R Multiple sclerosis [67]
IL2RA Prophylaxis of acute organ rejection in renal transplant [68]
IL4RA Atopic dermatitis [69]
IL5 Severe asthma [70]
IL6 Multicentric Castleman's disease [71]
IL6R Rheumatoid arthritis, and systemic juvenile idiopathic arthritis [72]
IL8 Psoriasis [73]
integrin receptor Ulcerative colitis, crohn's disease [74]
PCSK9 Heterozygous familial hypercholesterolemia, and refractory hypercholesterolemia [75]
PD-1 Metastatic melanoma, and metastatic squamous non-small cell lung carcinoma [76-78]
PD-L1 Urothelial carcinoma, metastatic non-small cell lung cancer, and metastatic Merkel cell carcinoma [79,80]
PDGFRA Soft tissue sarcoma [81]
Protective antigen of Bacillus anthracis / Anthrax toxin Inhalational anthrax [82]
PSMA Diagnostic imaging agent in newly diagnosed prostate cancer or post-prostatectomy [83]
RANKL Postmenopausal women with osteoporosis [84]
SLAMF7 Multiple myeloma [85]
TNF Rheumatoid arthritis, juvenile idiopathic arthritis, psoriatic arthritis, ankylosing spondylitis, crohn's disease, ulcerative colitis, and plaque psoriasis [86,87]
TNF α Crohn's disease [86]
VEGF Metastatic colorectal cancer [88,89]
VEGFR1 Wet age-related macular degeneration [90]
VEGFR2 Wet age-related macular degeneration, and gastric cancer [89,91]

Table 1: The recognized biomarkers for biologics and the approved indications.

Design Technologies Selection

Unlike small molecule drugs that can directly enter the cells and interrupt the metabolism with poor capacity of discernment, mAbs are mild and impact indirectly on the metabolic pathways with good targeting ability on tumor cells. To improve the efficacy as well as avoid patent dispute, several advanced design technologies have been applied to improve mAb performance. The characteristics of different biologic design technologies are briefly summarized in Table 2, which were further discussed as follows:

Design Technology Characteristics
Manufacturing Cost Expression
(g/L)
Purification Recovery
(%)
Efficacy
Conventional * 2-10 60-80 Normal
ADC ** 0.4-5 50-70 Small and Large Molecule
Bi-specific ** 0.5-3 <20 Tumor and Immune Cells (Synergistic)
Combined Medication *** Depends Depends Synergistic Effect

Table 2: Different biologic design technologies with their characteristics.

Antibody drug conjugate

Antibody drug conjugate (ADC) technology is one improvement strategy, which allows small molecules conjugated on an antibody molecule [9]. Via the excellent targeting ability of the protein therapeutics, the small molecule is able to directly interrupt the metabolic pathways of tumor cells with significantly improved capacity of discernment [10]. Nevertheless, challenges that ADC faces in manufacturing include:

Unstable expression level due to the variety of the link structure, especially, when the link consists of unnatural amino acids.

Low downstream yield due to the added purification steps after the conjugation of the small molecule drug to the protein molecule.

Bi-specific

Bi-specific antibody technology is another option for better biologics design. It allows one biologic molecule to recognize two biomarkers simultaneously. Theoretically, the combination of the two biomarkers should fall into one of the three types: both on tumor cells, both on immune cells and one on tumor cell and one on immune cell. Nevertheless, the third design is the major preference in the industry. By this design, the immune cells can be effectively activated, then rapidly and adequately attack the tumor cells in situ [11]. This makes the protein therapeutics exhibit synergistic effect compared to using two or more independent mAbs. This technology has the potential to enhance the efficacy while reducing the biologics dosage and side effects. However, bi-specific molecules also have their drawbacks in manufacturing, such as:

Low expression level during cell culture due to the high risks of chain mispairing and protein aggregation

Low downstream separation efficiency because of the similar physicochemical properties of the mis-pairing molecules.

Combined medication

Combined medication technology is an alternative choice to improve the efficacy. The joint usage of two or more biologics or biologics with small molecule drugs has the potential to exhibit synergistic effect on tumor cells, because different biologics and/or drugs may impact on different metabolic pathways. This technology provides one strategy to screen new indications for existing mAbs avoiding huge investment for new drug design and application. This strategy, however, has some disadvantages for commercialization, including:

Significantly high cost in manufacturing, factory operation, storage and supply chain management for different products/ molecules;

Difficulties in maintaining acceptable stability of different biologics and/or drugs if in one formulation;

Inconvenience and high cost in drug delivery if different formulations were used for different biologics/drugs.

Commercial mAbs

With increasing attention focused on mAbs, large amounts of investment have been attracted into the biopharmaceutical industry aiming at biologics commercialization. The study of the current commercial mAbs can benefit the biopharmaceutical industry, especially those start-up companies focusing on biosimilars, to rapidly follow up the recent trends and successfully screen the promising molecules. Figure 1 lists the top 10 best-selling mAbs in 2016 and their global annual sales in the recent three years. The data were obtained from the annual reports of these enterprises. Little ranking change was observed in Figure 1, except Opdivo was regarded as a dark-horse in the recent years due to the excellent performance of this anti-PD-1 mAb. Humira, Remicade and Rituxan kept the top three best-selling for the recent three years (Figure 1), bringing considerable revenue to Abbvie, Johnson & Johnson and Roche, respectively. In 2016, the total sales of these 10 mAbs were $ 61.2 billion, which is almost 70% of the whole global antibody market. The global oligopolistic market landscape may not be broken in the next few years due to limited number of validated biomarkers and long period of time for one biologic product to be commercialized. A list of biomarkers with corresponding commercial mAbs and patent holders were shown in Table 3. The mAbs and patent information was filtered manually from an open source tool called ‘Citeline Service’ before July 16th, 2017. Most of the biosimilars currently in research were designed based on these listed mAbs. This table also includes the major biomarkers for ADC and bi-specific antibodies, which is a trend for biologic design in the next few years.

Antigen Biomarkers Biologics Patent Holders BLA Approved
α-4 integrin Tysabri Biogen Idec 11/23/2004
BLyS Benlysta Human Genome Sciences 03/09/2011
CCR4 Poteligeo Amgen 03/30/2012, Japan
CD6 Alzumab Center of Molecular Immunology 01/07/2013, India
CD19 Blincyto Amgen 12/03/2014
CD20 Zevalin Spectrum Pharmaceuticals 02/19/2002
Gazyva Genentech 11/01/2013
Ocrevus 03/28/2017
Rituxan 10/26/2009
Arzerra Glaxo Grp 11/26/1997
CD30 Adcentris Seattle Genetics 09/19/2011
CD38 Darzalex Janssen Biotech 11/16/2015
CD52 Campath Genzyme 05/07/2001
Lemtrada
Clostridium difficile toxin B Zinplava Merck 10/21/2016
Complement component 5 Soliris Alexion 03/16/2007
CTLA-4 Yervoy Bristol-Myers Squibb 03/25/2011
dabigatran Praxbind Boehringer Ingelheim 10/16/2015
EGFR Erbitux ImClone Systems 02/12/2004
Portrazza Eli Lilly 11/24/2015
Vectibix Amgen 09/27/2006
BIOMAB EGFR Biocon 11/12/2007, India
Theraloc Oncoscience 11/12/2003, EMEA
CIMAher Center of Molecular Immunology 11/18/1994, Cuba
CD3 Ior-t3a Center of Molecular Immunology 05/15/1996, Cuba
Removab Fresenius, Swedish Orphan Biovitrum, Neovii Biotech 01/27/2011, EMEA
EpCAM
F protein of RSV Synagis Med-Immune 06/19/1998
Ganglionside P3 Vaxira Recombio, Laboratorio Elea, Innogene Kalbiotech 12/31/2012, Cuba
GD2 Unituxin United Therapeutics 03/10/2015
GPIIb/IIIa ReoPro Centocor 12/22/1994
HER2 Kadcyla Genentech 02/22/2013
Perjeta 06/08/2012
Herceptin 09/25/1998
IgE Xolair 06/20/2003
IL12
IL23
Stelara Centocor 09/25/2009
Janssen Biotech 09/23/2016
IL17A Taltz Eli Lilly 03/22/2016
Cosentyx Novartis 01/21/2015
IL17RA Siliq Valeant 02/15/2017
IL1B Ilaris Novartis 06/17/2009
IL2R Zinbryta Biogen 05/27/2016
IL2RA Simulect Novartis 05/12/1998
Zenapax Roche 12/10/1997
IL4RA Dupixent Regeneron 03/28/2017
IL5 Nucala GlaxoSmithKline 11/04/2015
Cinqair Teva 03/23/2016
IL6 Sylvant Janssen Biotech 04/23/2014
IL6R Actemra Genentech 01/08/2010
10/21/2013
Kevzara Sanofi 02/01/2017, Canada
IL8 ABCreama Yes Biotech 07/13/2004, China
Integrin receptor Entyvio Takeda 05/20/2014
PCSK9 Praluent Sanofi Aventis 07/24/2015
Repatha Amgen 08/27/2015
PD-1 Opdivo Bristol-Myers Squibb 12/22/2014
03/04/2015
Keytruda Merck 09/04/2014
PD-L1 Tecentriq Genentech 05/18/2016
10/18/2016
Bavencio EMD Serono 03/23/2017
Imfinzi AstraZeneca 05/01/2017
PDGFRA Lartruvo Eli Lilly 10/19/2016
Protective antigen of Bacillus anthracis Raxibacumab Human Genome Sciences 12/24/2012
Protective antigen of the Anthrax toxin Anthem Elusys Therapeutics 03/18/2016
PSMA ProstaScint Cytogen 10/28/1996
RANKL Prolia Amgen 06/01/2010
Xgeva
SLAMF7 Empliciti Bristol-Myers Squibb 11/30/2015
TNF Humira Abbvie 12/31/2002
Amjevita Amgen 09/23/2016
Cimzia UCB (company) 04/22/2008
Simponi Centocor 04/24/2009
Simponi Aria Janssen Biotech 07/18/2013
Renflexis Samsung Bioepis 04/21/2017
Inflectra Celltrion Healthcare 04/05/2016
TNFα Remicade Centocor 08/24/1998
VEGF Avastin Genentech 02/26/2004
VEGFR1 Lucentis 06/30/2006
VEGFR2
Cyramza Eli Lilly 04/21/2014

Table 3: Commercial biologics and the corresponding antigen biomarkers, patent holders and the biologic license application (BLA) approved dates.

Figure 1: Top 10 best-selling mAbs in 2016 and their global annual sales in the recent three years. Different colors refer to the selling data in different years.

mAbs Screening Methods

Screening criteria

After the designing of the mAbs based on the mechanisms discussed above, there could still be thousands of candidates available. This will be followed by two major screening processes to obtain best performed antigen-specific antibodies from the pool, which are:

Binding screening including specificity [12] and affinity [13]

Functional screening including cell growth, proliferation, apoptosis, endothelial tube formation, etc. [14]

While the functional assays are based on different disease models, the binding screening assays are universal in biopharmaceutical industry.

Specificity is the ability of the antibody binding to its cognate antigen and not to other targets. Affinity is the characteristic of antibody-antigen binding strength. These two criteria are crucial to ensure the efficacy, while good specificity can minimize the side-effects and good affinity is well preferred to reduce the drug dosage.

Functional activities are often the most significant characteristics of an antibody, including ability to deliver a toxin, antagonist activity, partial and full agonist activity, etc. These activities are often related to the protein allostery via the antigen-antibody specific binding [15,16].

Screening models

To quantitatively evaluate the above criteria, kinetic modeling strategies are usually applied [17]. Known models include Michaelis– Menten (M-M) model [18], Hill Equation [19-22], different types of Binding Models [23-25], Morpheein Model, Monod–Wyman– Changeux (MWC) model [26], Mechanistic kinetic description strategy [27] and empirical models derived from software such as JMP [28]. Nevertheless, different models have their advantages and drawbacks and none is appropriate in all situations.

M-M Equation has been the preferred modeling strategy in many enzyme kinetic studies due to its convenience for calculation [20,29]. M-M equation is only applicable for single domain enzymes or noninteractive oligomeric enzymes. However, most of the enzymes involved in metabolism are oligomeric. By introducing the Hill Coefficient, better simulation results can usually be generated than those using the M-M Equation [30]. However, kinetic parameters lose their mechanistic information due to the forcible introduction of the empirical Hill Coefficient. This shortcoming makes the Hill Equation more appropriate for empirical data manipulation in industry instead of mechanism research.

The Binding Models are extensions of the M-M and Hill Equations when there are more than two, typically three, molecules involved in one reaction. They were derived based on the ordered/ random molecule collision process and the second order elementary reaction mechanism [31]. These models considered multiple reaction processes simultaneously. In addition, the substrate-enzyme binding during the subsequent coenzyme and substrate binding processes for oligomeric enzymes with more than two active subunits can be important [24,31].

Morpheein Model, MWC model and Mechanistic kinetic description strategy are three modeling methods to mechanistically illustrate the molecular kinetic process by taking the interactive nature of one molecule with substrate and/or inhibitors into consideration [27,32]. More parameters are involved in the modeling which typically requires much more experimental data to support. Thus, these time- and cost-consuming methods are not the first choice in most commercial activities.

Table 4 presented a summary of the above models with their typical mathematic formula and applicable scopes. In the current biopharmaceutical researches, M-M Model and Hill Equation are the favored modeling strategies for biologics screening, due to their simplicity. While Morpheein Model, MWC Model and Mechanistic kinetic description strategy are able to well describe the kinetic properties of the molecular interactions, if the kinetic mechanism is critical to understand the biologics. Different types of Binding Models can be applied for multiple molecules involved reactions, such as bi-specific antibody involved reactions. Different strategies are selectively used based on the study purposes and research limitations.

Type Formula Parameter number Applicable Scope References
M-M Model image 2 non-interactive oligomeric or mono- molecular interactions [18,23]
Hill Equation image 3 Data manipulation for all molecular interactions [22,92]
MWC model image 5 Oligomeric molecular interactions [32,93]
Morpheein Model image 5 Oligomeric molecular interactions [94]
Random Binding Model image 3 Three molecule involved interactions [25,95]
Ordered Binding Model image 3 Three molecule involved interactions [25,96]
Mechanistic Kinetic Description image 5 Oligomeric molecular interactions [27,94]

Table 4: Reported kinetic modeling strategies for molecular interaction study.

Binding screening assays

Enzyme-linked Immunosorbent assay (ELISA) is one of the most popular platform technologies to identify antigen-antibody complex and both qualitatively and quantitatively evaluate the binding strength. The basic principle of ELISA based on radioimmunoassay techniques dates back top 1941 [33] and the exact method was created in 1971 [34]. Currently, it is a major detection method for biologics screening, because it is simple, quick, sensitive, specific and highthroughput [35]. Another screening technology is surface Plasmon resonance (SPR) biosensor [36]. As a gold standard for real-time and label-free monitoring technology of bimolecular interactions, it is able to determine the thermodynamic and kinetic properties of specific molecular interactions [37].

While ELISA and SPR are the common techniques for extracellular or cell-free antigen-antibody binding detection, fluorometric micro volume assay (FMAT) and fluorescence-activated cell sorting (FACS) are well-developed methods for on-cell or native binding screening [38]. The working principle based on antibodies binding to the antigen expressed on cell surface and the immunoglobulin constant region of the antibodies is detected by a fluorescently conjugated secondary antibody. As a high-throughput cell-based assay in the hybridoma screening, FMAT and FACS based technologies has significantly improved the screening efficiency and success probability.

Conclusion

Though cancers are not incurable disease due to the rapid technology development, they are still a leading threat for human health. In this paper, the recent trends and technologies of mAb development are comprehensively reviewed. The information of biomarkers, indications, commercial mAbs and the pattern status were systematically reviewed, which is beneficial for biopharmaceutical industry, research institutes and patients to make decisions. This review aims at providing a comprehensive understanding of the biomarker, indication and mAb screening strategies, which may promote further advancements in new drug discovery, novel indications of exiting drugs, as well as joint usage of mAbs and other cancer treatment methods.

Acknowledgement

The authors thank Mr. Boyuan Yin from General Electric Company, Mr. Pan Tian, Ms. Jing Zhao and Mr. Qing Dai from Mab-Venture Biopharm Co. Ltd. for their kind comments on this work.

Declaration of Interest

The authors declare no financial or commercial conflict of interest.

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