How do I name a binding antibody? “Binding antibody to”, “binding antibody against”, or “anti-[antigen] binding antibody”?

How do I name a binding antibody? “Binding antibody to”, “binding antibody against”, or “anti-[antigen] binding antibody”?

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I'm translating a text that describes how an immunogenicity of a drug is measured by assaying the levels of binding antibodies to the drug. Or is it "against the drug"? I'm wondering how to name these antibodies. Let's say the drug is cetuximab, and I'm writing the title of a document section:

  1. Assay of binding antibodies against cetuximab in serum.
  2. Assay of binding antibodies to cetuximab in serum.
  3. Assay of anti-cetuximab binding antibodies in serum.

I googled for "binding antibodies to" and "binding antibodies against" and got only several dozen results for each of the two options. Therefore I came up with "anti-[name of the antigen] binding antibodies", but don't know how to google for it, hence my question here. Would option 3 look nice to a native speaker?

P.S. Alas, it is exactly "binding antibodies to" in my Russian text. I cannot omit the adjective "binding" before "antibodies"…

Связывающие антитела к цетуксимабу.

I quote from the Wikipedia page on neutralizing antibodies:

Most antibodies work by binding to an antigen, signaling to a white blood cell that this antigen has been targeted, after which the antigen is processed and consequently destroyed. The difference between neutralizing antibodies and binding antibodies is that neutralizing antibodies neutralize the biological effects of the antigen, while binding antibodies flag antigens.

My authors use the adjective "binding" to distinguish binding antibodies from neutralizing antibodies, just like in this paper, for instance: BAbs and NAbs. Another section in my document gives the results of an assay of NAbs against the same antigen.

Explanation of the difference between binding and neutralizing antibodies from the FDA:

(ADA: anti-drug antibodies)

The adjective “binding” is not used to qualify “antibody” in English scientific usage because linguistically it is thought to belong with the antigen the antibody binds.

Generally it is omitted if the prefix “anti” is used, e.g.

anti-cetuximab antibody

(e.g. “two or more anti-hapten antibodies” here)

However if you wish to refer to the particular small portion of the antigen that is recognized (the epitope), you might write, e.g.

tyrosine-binding antibody

(e.g. “Hapten‐binding antibodies… ” here)

As far as the use of prepositions is concerned, “to” is used with binding, although it is optional. However generally with the antigen, e g.

cetuximab binds to the antibody

(e.g. “Antigen binds to the antibody on the B-cell membrane.” here)


the antibody binds cetuximab

(e.g. “An additional VNAR, Help6, which binds Hepatitis B precore protein” here.)

Completely illogical, I know, and this distinction is not universal.

However, “against” is used in relation to preparing or raising antibodies, e.g.

We raised an antibody against cetuximab…

(See the legend to Fig 1. in this paper.)

So in general one would write:

  1. Assay of anti-cetuximab antibodies in serum

Addendum: Binding antibodies v. Neutralizing antibodies

The revised question makes it clear that the authors are referring to “binding antibodies” as a specific contrast to “neutralizing antibodies”. This expression was not known to me (I am not an immunologist), and, although the poster documents it, its use would appear to be limited, perhaps because the topic is or was controversial.

The question remains, how to express this idea in a clear and unambiguous manner, with the specific problem that the poster is a translator, not an editor. I would still try to avoid the use of the word “binding” in the expression. I have two suggestions:

  1. I believe that an alternative expression would be “non-neutralizing antibody” (the paper just quoted does not hyphenate this term, but others do, and I would). If this belief is correct, one could write:
  1. Assay of non-neutralizing anti-cetuximab antibodies in serum
  1. Alternatively one could use the abbreviation, “BAb”, from the paper cited by the poster, although this would have to be defined somewhere.
  1. Assay of anti-cetuximab BAbs in serum

In English, you say that antibodies bind to something (X), not against something. You can use the phrases "X-binding antibodies," "X-specific antibodies," "X binders" (when referring to the antibodies that you've previously introduced in the text), to name a few. You can use "antibodies binding to X," but not "binding antibodies to X," people will misinterpret the latter, because it means something else is binding to the antibodies or you are trying to bind something to the antibodies.

/>Antibody Plasmid Collection

Antibodies are produced by the immune system to help defend against invaders such as bacteria, viruses, or even perceived threats such as proteins in peanuts or plant pollen. They are large proteins that bind to an antigen, a particular part of a foreign substance. In addition to being useful for our bodies to fight off intruders, antibodies are also extremely useful to researchers in a lab. When an antibody binds tightly to a specific antigen, scientists can use it to pull out a protein of choice from a mix of other proteins, visualize a protein under a microscope, or detect when the protein is present in a sample--just to name a few.

A standard antibody is made up of 4 protein chains: two large heavy chains and two small light chains. These four domains come together to form a “Y” shape, as shown in the picture to the right. The two arms of the Y structure are responsible for binding the antigen, and are called the antigen binding fragments (Fab). The tips of the Fab fragments contain highly variable regions, shown in light blue and orange, that bind to a specific antigen, triggering an immune response. The other part of the antibody is the constant region, shown in dark blue and orange, which is the same within each class of antibody. Antibodies are divided into five major classes, IgM, IgG, IgA, IgD, and IgE, based on their constant region structure and immune function.

Traditional sources of antibodies for research purposes include animals or hybridoma cells, but are difficult to generate due to expense and time. An alternative approach is to use synthetically produced recombinant antibodies, created by cloning antibody components into plasmids and expressing these in bacteria, mammalian cells, yeast, plants, or insect cells. Benefits include consistency between lots and the ability to optimize the antibody’s antigen binding sequence to improve binding and reproducibility.

Some scientists choose to work with full length recombinant monoclonal antibodies (R-mAbs) expressed in mammalian cells. Monoclonal antibodies are derived from an individual clone targeting a single antigen. Examples of R-mAbs are the monoclonal antibodies (NeuroMabs) extensively validated for neuroscience research applications from the NeuroMab/Trimmer Lab Recombinant mAb Plasmid Collection. Once the plasmids are transiently transfected into mammalian tissue culture cells, the R-mAbs are secreted into the culture media and can be collected for use.

Other scientists may choose to work with a smaller fragment of an antibody, which could offer increased stability and ease of production due to their small size. These recombinant antibody fragments can be used in experiments such as immunoprecipitation and super-resolution microscopy. Two commonly used plasmid-based antibody fragments are described below:

ScFvs (single-chain variable fragment) include parts of the variable regions of heavy (VH) and light chains (VL) fused together to form a single polypeptide. Unlike full length antibodies, which are often produced in mammalian cell cultures, scFvs are often produced in bacterial cell cultures such as E. coli. While full-length antibodies generally do not fold properly in the cytoplasm, soluble scFv antibodies have been successfully expressed. The Vale lab has created several scFv fragments which bind to the GCN4 peptide, from the SunTag system, fused to sfGFP for imaging.

Nanobodies are small single chain antibodies that are derived from an unusual type of IgG antibody called a heavy chain antibody (HCab), which are unique to camels, llamas, alpacas and other camelids. In terms of structure, HCabs are like a pared down version of a standard IgG antibody. Their small size also allows better tissue penetration and decreases the distance between a fluorescent tag and the target antigen, which can lead to higher resolution for super-resolution microscopy. Examples include secondary antibodies from the Gorlich lab and GFP nanobodies from the Cepko lab.

WO2016000813A1 - Anti-tnfa antibodies with ph-dependent antigen binding - Google Patents

38.5% share within the biologies market. Sales of -$24.6 billion manifest the role of therapeutic antibodies as highest earning category of all biologies (Aggarwal, 2009, Aggarwal, 2014). For therapeutic antibodies different biological outcomes are determined by the interaction profiles with four classes of naturally occurring interaction partners: antigen, neonatal Fc- receptor (FcRn), Fc-receptors (FcyRs), and factors of the complement system (Chan and Carter, 2010). Several strategies have been reported to optimize antibodies that aim for additional or improved functions and specificities. (Beck et al, 2010). Within antibodies there are two structural features that can be addressed for engineering. First, the variable fragment (Fv) that mediates interaction with the antigen, second the constant fragment (Fc) that is involved in antibody recycling or mediates interactions with immune cells.

10 12 ) isolated variants showed KDs between 35-91 nM at pH 7.4 and a

10'fold decrease in binding affinity at pH 5.4 (Murtaugh et al. 2011).

Clinical applications and market for therapeutic antibodies

Therapeutic antibodies currently approved as disease treatments

The mAb market enjoys a healthy pipeline and is expected to grow at an increasing pace, with a current valuation of $115.2 billion in 2018 [44]. Despite this high growth potential, new companies are unlikely to take over large shares of the market, which is currently dominated by seven companies: Genentech (30.8%), Abbvie (20.0%), Johnson & Johnson (13.6%), Bristol-Myers Squibb (6.5%), Merck Sharp & Dohme (5.6%), Novartis (5.5%), Amgen (4.9%), with other companies comprising the remaining 13% [44].

Many mAbs products achieved annual sales of over US$3 billion in 2018 (Fig. 1), while six (adalimumab, nivolumab, pembrolizumab, trastuzumab, bevacizumab, rituximab) had sales of more than $6 billion (Table 2). Adalimumab (Humira) had the highest sales figure ever recorded for a biopharmaceutical product, nearly $19.9 billion. The top ten selling mAb products in 2018 are listed in Table 2. Top-selling mAb drugs were ranked based on sales or revenue reported by biological or pharmacological companies in press announcements, conference calls, annual reports or investor materials throughout 2018. For each drug, the name, sponsors, disease indications, and 2018 sales are shown.

mAbs are increasingly used for a broad range of targets oncology, immunology, and hematology remain the most prevalent medical applications [45]. Most mAbs have multiple disease indications and at least one that is cancer-related (lymphoma, myeloma, melanoma, glioblastoma, neuroblastoma, sarcoma, colorectal, lung, breast, ovarian, head and neck cancers). As such, oncological diseases are the medical specialty most accessible to mAb treatments [45]. Moreover, the number of target proteins known to function as either stimulatory or inhibitory checkpoints of the immune system has dramatically expanded, and numerous antibody therapeutics targeting programmed cell death protein 1 (PD-1, cemiplimab, nivolumab, pembrolizumab), its ligand programmed death-ligand 1 (PD-L1, durvalumab, avelumab, atezolizumab) or cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4, ipilimumab) have been granted marketing approvals [46].

Adalimumab (Humira) was the world’s best-selling drug in 2018. Adalimumab is a subcutaneously administered biological disease modifier used for the treatment of rheumatoid arthritis and other TNFα-mediated chronic debilitating diseases. It was originally launched by Abbvie in the United States after gaining approval from the US FDA in 2002. It has been shown that Adalimumab reduces the signs and symptoms of moderate to severe rheumatoid arthritis in adults, and it is also used to treat psoriatic arthritis, ankylosing spondylitis, Crohn's disease, ulcerative colitis, psoriasis, hidradenitis suppurativa, uveitis, and juvenile idiopathic arthritis [47, 48]. It may be used alone or in combination with disease-modifying anti-rheumatic drugs [49].

Immune checkpoints are important for maintaining self-tolerance and tempering physiologic immune responses in peripheral tissues. Therefore, the molecules underlying checkpoints have recently drawn considerable interest in cancer immunotherapy [50]. Both nivolumab (Opdivo) and pembrolizumab (Keytruda) are anti-PD-1 mAbs and were the second and third best-selling mAb drugs in 2018 (Table 2). Nivolumab is a human antibody, which blocks a signal that normally prevents activated T cells from attacking cancer cells. The target for nivolumab is the PD-1 receptor, and the antibody blocks the interaction of PD-1 with its ligands, PD-L1 and PD-L2, releasing PD-1 pathway-mediated immune inhibition [51, 52]. Pembrolizumab is a humanized antibody used in cancer immunotherapy to treat melanoma, lung cancer, head and neck cancer, Hodgkin’s lymphoma, and stomach cancer [53,54,55]. Pembrolizumab is a first-line treatment for NSCLC if cancer cells overexpresse PD-L1 and have no mutations in EGFR or in anaplastic lymphoma kinase [56, 57]. Large randomized clinical trials indicated that NSCLC patients treated with nivolumab and pembrolizumab (both approved by the US FDA in 2014) showed increased overall survival compared with docetaxel, the standard second-line treatment [58].

A total of 12 new mAbs were approved in the US during 2018. The majority of these products were approved for non-cancer indications, perhaps reflecting the higher approval success rate for antibodies as treatments for other diseases. Three antibodies (erenumab, galcanezumab, and fremaezumab) were approved for migraine prevention, and one (Ibalizumab) is used for human immunodeficiency virus (HIV) infection. The three migraine-preventing drugs, Erenumab (Aimovig), galcanezumab (Emgality), and fremaezumab (Ajovy), are mAbs that block the activity of calcitonin gene-related peptide (CGRP) receptor in migraine etiology [59]. CGRP acts through a heteromeric receptor, which is composed of a G protein-coupled receptor(calcitonin receptor-like receptor: CALCRL) and receptor activity-modifying protein 1 (RAMP1) [60, 61]. Both galcanezumab and fremaezumab bind to CGRP and block its binding to the receptor. However, erenumab is the only one of the three antibodies to target the extracellular domains of human G protein-coupled receptors CALCRL and RAMP1,interfering with the CGRP binding pocket [62].

Many mAbs are under development for treatment of infectious diseases, currently only four have been approved by the US FDA: raxibacumab and obiltoxaximab for treatment of inhalational anthrax [63], palivizumab for prevention of respiratory syncytial virus in high-risk infants [64], and ibalizumab for treatment of HIV infection patients [65]. Ibalizumab (Trogarzo) is a humanized IgG4 mAb that is used as a CD4 domain 2-directed post-attachment HIV-1 inhibitor. The US FDA approved ibalizumab for adult patients infected with HIV who were previously treated and are resistant to currently available therapies.

Therapeutic antibodies currently in clinical trials

Companies are currently sponsoring clinical studies for more than 570 mAbs. Of these, approximately 90% are early-stage studies designed to assess safety (Phase I) or safety and preliminary efficacy (Phase I/II or Phase II) in patient populations. Most of the mAbs in Phase I (

70%) are for cancer treatment, and the proportions of mAbs intended to treat cancer are similar for those currently in Phase II and late-stage clinical studies (pivotal Phase II, Phase II/III or Phase III) [2].

Twenty-nine novel antibody therapeutics were in late-stage clinical studies for non-cancer indications in 2018. Among the trials for these mAbs, no single therapeutic area predominated, but 40% were for immune-mediated disorders, which comprised the largest group. From this group of potential treatments, leronlimab and brolucizumab entered regulatory review by the end of 2018, and five mAbs (eptinezumab, teprotumumab, crizanlizumab, satralizumab, and tanezumab) may enter regulatory review in 2019. In comparison, there were 33 novel antibody therapeutics in late-stage clinical studies for cancer indications in 2018. Antibody therapeutics for solid tumors clearly predominated, with less than 20% of the candidates intended solely for hematological malignancies. Five mAbs (isatuximab, spartalizumab, tafasitamab, dostarlimab, and ublituximab) license applications were submitted to the US FDA in 2019 [2].

Isatuximab is an anti-CD38 IgG1 chimeric mAb under evaluation as a treatment for patients with multiple myeloma (MM). Combinations of isatuximab and different chemotherapies are being tested in three Phase III studies (ICARIA, IKEMA, and IMROZ) on MM patients. The ICARIA study (NCT02990338) is evaluating the effects of isatuximab in combination with pomalidomide and dexamethasone compared to chemotherapy only in patients with refractory or relapsed MM. Pivotal Phase III ICARIA-MM trial results demonstrated that isatuximab combination therapy showed statistically significant improvements compared to pomalidomide and dexamethasone alone in patients with relapsed or refractory MM in 2019. The US FDA has accepted for review the biologics license application for isatuximab for the treatment relapsed or refractory MM patients. The target action date for the FDA decision is April 2020 [66]. The IKEMA (NCT03275285) and IMROZ (NCT03319667) studies are evaluating the isatuximab with other chemotherapeautic combinations in MM patients [67].

Spartalizumab is a humanized IgG4 mAb that binds PD-1 with sub-nanomolar affinity and blocks its interaction with PD-L1/PD-L2, preventing PD-1-mediated inhibitory signaling and leading to T-cell activation. Clinical study of Spartalizumab is underway with a randomized, double-blind, placebo-controlled Phase III COMBI-i study (NCT02967692), which is evaluating the safety and efficacy of dabrafenib and trametinib in combination with spartalizumab compared to matching placebo in previously untreated patients with BRAF V600-mutant unresectable or metastatic melanoma. The primary endpoints of the study are an assessment of dose-limiting toxicities, changes in PD-L1 levels and CD8+ cells in the tumor microenvironment, and progression-free survival. Key secondary endpoints are overall survival, overall response rate and duration of response. The estimated primary completion date of the study is September 2019 [68].

Dostarlimab is an anti-PD-1 mAb that may be useful as a treatment for several types of cancers. GlaxoSmithKline announced results from a Phase I dose escalation and cohort expansion study (GARNET NCT02715284) in 2018, which is expected to support a biologics license application submission to the US FDA in 2019. Dostarlimab is being assessed in patients with advanced solid tumors who have limited available treatment options in the GARNET study. The drug is administered at a dose of 500 mg every 3 weeks for the first 4 cycles, and 1000 mg every 6 weeks thereafter in four patient cohorts: microsatellite instability high (MSI-H) endometrial cancer, MSI-H non-endometrial cancer, microsatellite-stable endometrial cancer, and non-small cell lung cancer. Dostarlimab is also being evaluated in another Phase III study (NCT03602859), which is comparing platinum-based therapy with dostarlimab and niraparib versus standard of care platinum-based therapy as first-line treatment of Stage III or IV non-mucinous epithelial ovarian cancer [69].

Ublituximab is a glyco-engineered anti-CD20 antibody currently under clinical investigation in five late-stage clinical studies for different cancers (chronic lymphocytic leukemia, CLL, non-Hodgkin’s lymphoma) and non-cancer (multiple sclerosis) indications. Three Phase III studies are exploring the efficacy of ublituximab in combination with other anti-cancer agents. Among these studies, the UNITY-CLL Phase III study (NCT02612311) is evaluating the combination of ublituximab and TGR-1202, a PI3K delta inhibitor, compared to anti-CD20 obinutuzumab plus chlorambucil in untreated and previously treated CLL patients. Two other Phase III studies (ULTIMATE 1, NCT03277261 and ULTIMATE 2, NCT03277248) are evaluating the efficacy and safety of ublituximab compared to teriflunomide in 440 patients with relapsing multiple sclerosis [70].

These authors contributed equally: Quan-Xin Long, Bai-Zhong Liu, Hai-Jun Deng, Gui-Cheng Wu, Kun Deng, Yao-Kai Chen.


Key Laboratory of Molecular Biology on Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing, China

Quan-Xin Long, Hai-Jun Deng, Yong Lin, Xue-Fei Cai, De-Qiang Wang, Yuan Hu, Ji-Hua Ren, Ni Tang, Jun Yuan, Jie-Li Hu, Juan Chen & Ai-Long Huang

Yongchuan Hospital Affiliated to Chongqing Medical University, Chongqing, China

Bai-Zhong Liu, Yin-Yin Xu, Li-Hua Yu, Zhan Mo, Fang Gong, Xiao-Li Zhang, Wen-Guang Tian & Li Hu

Chongqing University Three Gorges Hospital, Chongqing, China

Gui-Cheng Wu, Xian-Xiang Zhang, Jiang-Lin Xiang, Hong-Xin Du, Hua-Wen Liu, Chun-Hui Lang, Xiao-He Luo, Shao-Bo Wu, Xiao-Ping Cui & Zheng Zhou

Chongqing Three Gorges Central Hospital, Chongqing, China

Gui-Cheng Wu, Xian-Xiang Zhang, Jiang-Lin Xiang, Hong-Xin Du, Hua-Wen Liu, Chun-Hui Lang, Xiao-He Luo, Shao-Bo Wu, Xiao-Ping Cui & Zheng Zhou

The Third Hospital Affiliated to Chongqing Medical University, Chongqing, China

Division of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing, China

Yao-Kai Chen, Jing Wang, Cheng-Jun Xue, Xiao-Feng Li & Li Wang

Laboratory Department, Chongqing People’s Hospital, Chongqing, China

Pu Liao, Zhi-Jie Li, Kun Wang, Chang-Chun Niu & Qing-Jun Yang

School of Public Health and Management, Chongqing Medical University, Chongqing, China

Jing-Fu Qiu, Xiao-Jun Tang & Yong Zhang

The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China

Wanzhou People’s Hospital, Chongqing, China

BioScience Co. Ltd, Chongqing, China

Chongqing Center for Disease Control and Prevention, Chongqing, China

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Conceptualization was provided by A.-L.H. The methodology was developed by X.-F.C., D.-Q.W., P. Liu, Q.-X.L., K.D. and M.-M.Z. Investigations were carried out by Q.-X.L., H.-J.D., J.C., J.-L.H., B.-Z.L., G.-C.W., K.D., Y.-K.C. and Y.H. The original draft of the manuscript was written by Q.-X.L., H.-J.D., J.C. and J.-L.H. Review and editing of the manuscript were carried out by Q.-X.L., H.-J.D., J.C., J.-L.H., Y.L. and A.-L.H. Funding acquisition was performed by A.-L.H. and J.-L.H. Resources were provided by P. Liao, Y.-Y.X., L.-H.Y., Z.M., F.G., X.-M.L., X.-X.Z., Z.-J.L., K.W., X.-L.Z., W.-G.T., C.-C.N., Q.-J.Y., J.-L.X., H.-X.D., H.-W.L., C.-H.L., X.-H.L., .S.-B.W., X.-P.C., Z.Z., J.W., C.-J.X., X.-F.L., L.W., X.-J.T., Y.Z., J.-F.Q., X.-M.L., L.H., J.-J.L., D.-C.Z., F.Z., J.-H.R., N.T., J.Y. and Q.L. A.-L.H. provided supervision.

Corresponding authors



Reagent or resourceSourceIdentifier
Goat anti-Human IgG (H+L) secondary antibody, HRPThermo Fisher ScientificCat#31410 RRID: AB_228269
Mouse anti-human IgG Fab antibody (HRP)GenScriptCat#A01855-200
Mouse anti-human CD20-PECy7BD PharMingenCat#560735 RRID: AB_399985
APC Mouse anti-human CD19BD PharMingenCat#555415
Anti-CD27-PEBD BiosciencesCat#555441 RRID: AB_395834
Anti-hCD32BD PharMingenCat#557333
Anti-HBs H004Wang etਊl., 2020bN/A
CR3022ter Meulen etਊl., 2006N/A
Anti-N polyclonal antibodyGu etਊl., 2020N/A
Bacterial and virus strains
E.਌oli Trans5α chemically Competent CellsTransGen BiotechCat#CD201-01
Authentic SARS-CoV-2 virus, nCoV-SH01 (GenBank: <"type":"entrez-nucleotide","attrs":<"text":"MT121215.1","term_id":"1819735426","term_text":"MT121215.1">> MT121215.1)Wu etਊl., 2020bN/A
Chemicals, peptides, and recombinant proteins
Streptavidin HRPBD BiosciencesCat#554066
Streptavidin APCBD BiosciencesCat#554067 RRID: AB_10050396
Streptavidin PEeBioscienceCat#12-4317-87
Human BD Fc BlockBD PharMingenCat#564220
SARS-CoV-2 S protein (RBD)GenScriptCat#Z03479
SARS-CoV-2 S1 proteinGenScriptCat#Z03501
Recombinant 2019-nCoV S2 protein (C-Fc)NovoproteinCat#DRA48
SARS-CoV-2 Spike protein (ECD, His & Flag tag)GenScriptCat#Z03481
Insect-C-His NPGenScriptCat#Z03480
Recombinant 2019 nCoV Spike S (amino acid 14-1212)Kactus BiosystemsCat#COV-VM5SS
Recombinant 2019 nCoV Spike RBDKactus BiosystemsCat#COV-VM4BD
RNAsin Plus RNase inhibitorPromegaCat#N2615
4 × dNTPS (100 mM)Solarbio Life SciencesCat#PC2300
DNase/RNase-Free waterSolarbio Life SciencesCat#R1600
PBS (10 × ), pH 7.2-7.4Solarbio Life SciencesCat#P1022
1 M Tris-HCl, pH 9.0Solarbio Life SciencesCat#T1160
IGEPAL CA-630SigmaCat#I8896
Dimethyl SulfoxideSigmaCat#2650
Bovine Serum AlbuminWeiAo Biotech, ShanghaiCat#WH3044
Fetal Bovine SerumGEMINICat#900-108
UltraPure SucroseMacklin BiochemicalCat#S824459
Cresol Red sodium saltMacklin BiochemicalCat#C806031
ABTS Chromogen / substrate solution for ELISAThermo Fisher ScientificCat#00-2024
UltraPure 0.5M EDTA, pH 8.0InvitrogenCat#15575-038
Hank’s Balanced Salt Mixture (D-Hanks)Solarbio Life SciencesCat#H1045-500
EZ TransLife iLAB Bio Technology, ShanghaiCat#AC04L082
TRIzol LS ReagentThermo Fisher ScientificCat# 10296010
Critical commercial assays
LS magnetic columnsMiltenyi BiotechCat#130-042-401
CD19 MicroBeads, humanMiltenyi BiotechCat#130-097-055
EZ-Link Sulfo-NHS-LC Biotin, No weight formatThermo Fisher ScientificCat#39257
BirA Biotin-Protein Ligase KitAvidityCat#BIRA500
Zeba Spin Desalting Columns, 7K MWCOThermo Fisher ScientificCat#89889
Superscript III Reverse TranscriptaseThermo Fisher ScientificCat#18080044
HotStarTaq DNA PolymeraseQIAGENCat#203209
Protein G Sepharose 4 Fast FlowGE HealthcareCat#17061805
Pierce™ IgG Elution bufferThermo Fisher ScientificCat#21004
AgeI-HFNew England BioLabsCat#R3552L
BsiwI-HFNew England BioLabsCat#R3553L
XhoINew England BioLabsCat#R0146L
SalI-HFNew England BioLabsCat#R3138S
T4 DNA polymeraseNew England BioLabsCat#M0203L
One Step PrimeScript RT-PCR KitTakaraCat#RR064B
Luciferase Assay SystemPromegaCat#E1501
Experimental models: cell lines
HEK293F cell line( Wu etਊl., 2020b N/A
HEK293T cell line( Xia etਊl., 2020a N/A
Expi293 Expression SystemThermo Fisher ScientificCat#A14635
Huh-7 cell line( Xia etਊl., 2020a N/A
Vero-E6 cell line( Xia etਊl., 2020a N/A
Raji cell line( Jaume etਊl., 2011 N/A
Random PrimersThermo Fisher ScientificCat#48190011
Recombinant DNA
IG㬱 expression vectorvon Boehmer etਊl., 2016N/A
IGκ expression vectorvon Boehmer etਊl., 2016N/A
IGλ expression vectorvon Boehmer etਊl., 2016N/A
pNL4-3.luc.REXia etਊl., 2020aN/A
pcDNA3.1-SARS-CoV-1-SXia etਊl., 2020aN/A
pcDNA3.1-SARS-COV-2-SXia etਊl., 2020aN/A
IG㬱-GRLR expression vectorRobbiani etਊl., 2019N/A
Software and algorithms
IgBlastYe etਊl., 2013
IMGT/V-QUESTBrochet etਊl., 2008
Sterile 50 ml Disposable Vacuum Filtration SystemMillipore SigmaCat#SCGP00525
Amicon Ultra-4 Centrifugal Filters Ultracel-30KMerck Millipore Ltd.Cat#UFC803096
Ultrafree-MC Centrifugal filter units, 0.22uM GV DURAPOREMerck Millipore Ltd.Cat#UFC30GV0S
Pipet-Lite Multi Pipette L12-20XLS+RAININCat#17013808
General Long-Term Storage Cryogenic TubesNalgeneCat#5000-1020
SimpliAmp Thermal CyclerThermo Fisher ScientificCat# <"type":"entrez-protein","attrs":<"text":"A24812","term_id":"80001","term_text":"pir||A24812">> A24812
500 mL Bottle Top Vacuum Filter, 0.20 μm PoreThermo Fisher ScientificCat#566-0020
ACCUSPIN Tubes Sterile, 50ml CapacitySigmaCat#A2055-10EA

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Qiao Wang ([email protected]).

Materials availability

All unique reagents generated in this study are available from the Lead Contact with a completed Materials Transfer Agreement. Sharing of antibodies with academic researchers may require a payment to cover the cost of generation and a completed Material Transfer Agreement.

Data and code availability

The published article includes all datasets generated or analyzed during this study. Original data have been deposited Mendeley data:

Experimental model and subject details

Human subjects

Volunteer recruitment and blood draws were performed at the Zhoushan Hospital under a protocol approved by the Zhoushan Hospital Research Ethics Committee (2020-003). Experiments related to all human samples were performed at the School of Basic Medical Sciences, Fudan University under a protocol approved by the institutional Ethics Committee (2020-C007). Study participants, 16 convalescent donors, whose infections have been confirmed by PCR, and 8 unexposed naive donors. All donors ranged in age from 7-67 with a mean of 37, and the female:male ratio was 14:10 (Figure S1B).

Cell lines

Human embryonic kidney 293T (HEK293T) cells, human hepatoma Huh-7 cells and African green monkey kidney Vero-E6 cells ( Xia etਊl., 2020a ) were maintained in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% heat-inactivated fetal bovine serum (FBS), 100 U/ml penicillin, and 100 mg/ml streptomycin. Raji cells (human Burkitt’s lymphoma B lymphoblast) ( Jaume etਊl., 2011 ), were maintained in RPMI 1640 supplemented with 10% FBS, 100 U/ml penicillin, and 100 mg/ml streptomycin. All cell lines were cultured at 37ଌ in 5% CO2. Human embryonic kidney 293F (HEK293F) suspension cells were cultured using HEK293 serum-free OPM-293-CD05 medium (OPM Biosciences) at 37ଌ in 5% CO2 with shaking at 100 rpm.


The authentic SARS-CoV-2 virus, nCoV-SH01 (GenBank: <"type":"entrez-nucleotide","attrs":<"text":"MT121215.1","term_id":"1819735426","term_text":"MT121215.1">> MT121215.1) used in this study was isolated from infected patients at the Biosafety Level 3 (BSL-3) laboratory at the Shanghai Medical College, Fudan University ( Wu etਊl., 2020b ). The SARS-CoV-2 virus was propagated in Vero-E6 cells. Concentrated virus stock was aliquoted and stored at liquid nitrogen. One aliquot of cell line-passaged authentic SARS-CoV-2 virus, originally launched from patient serum and stored at �ଌ, was thawed for in vitro cell infection experiments.


E.਌oli Trans5α (TransGen Biotech) were cultured at 37ଌ with shaking at 230 rpm.

Method details

Collection of human samples

Samples of peripheral blood were collected from SARS-CoV-2 patients at the Zhoushan Hospital in Zhejiang province. Serum samples were heat inactivated for 60 minutes at 56ଌ, separated by centrifugation of coagulated whole blood, and aliquoted for storage at �ଌ. After a 400 mL blood draw from donor #16, human peripheral blood mononuclear cells (PBMCs) were isolated using a cell separation tube with frit barrier. The isolated PBMCs were resuspended in 90% heat-inactivated FBS supplemented with 10% dimethylsulfoxide (DMSO) and cryopreserved in liquid nitrogen.


All the cloned human monoclonal antibodies, their GRLR version, and the previously reported monoclonal antibody CR3022 ( ter Meulen etਊl., 2006 ) were prepared by transient transfection of mammalian HEK293F cells as previously reported ( Wu etਊl., 2020b ).


The ELISA binding of serum samples or purified IgG antibody fractions from serum samples or recombinant IgG antibodies against SARS-CoV-2 proteins, including S-ECD-, RBD-, S1-, S2-, and N-proteins (see details in Key resources table) was measured as previously reported ( Wang etਊl., 2020b ). Briefly, ELISA plates were first coated with 10 μg/ml of antigen in phosphate buffered saline (PBS) overnight at 4ଌ, and then blocked with 2% bovine serum albumin (BSA) in PBS. The serum or 1 st antibody was serially diluted 1:3 in PBS (maximum concentration, 1:10 for serum, 10 μg/ml for monoclonals) for eight dilutions in total, and added for incubation for one hour at room temperature. Visualization was with HRP-conjugated goat anti-human IgG (Thermo Fisher Scientific) or HRP-conjugated mouse anti-human IgG Fab (GenScript). The area under the curve (AUC) was calculated for each antibody by analysis using PRISM software to evaluate the antigen-binding capacity. ELISA assays using RBD mutants was performed as described above except coating RBD-Fc at a concentration of 2 μg/ml, and using wild-type RBD as a reference for normalization.

Competition ELISA

Competition ELISAs were performed as described previously ( Wang etਊl., 2020b ). Briefly, plates were coated with 2 μg/ml SARS-CoV-2 RBD or 2 μg/ml SARS-CoV-2 S-ECD and incubated with 15 μg/ml 1 st blocking antibody/proteins (60 μg/ml for antibody CR3022) for two hours. Biotinylated 2 nd antibodies/proteins (0.25 μg/ml) (15 μg/ml for antibody CR3022) were directly added for 30 minutes at room temperature. Detection was performed with streptavidin-HRP (BD Biosciences). PBS buffer substituted for the 1 st blocking antibody was used as a reference for normalization, while the anti-HBs antibody H004 ( Wang etਊl., 2020b ), which could not block the binding of the 2 nd antibodies, served as a negative control.

Preparation of SARS-CoV-2 and SARS-CoV-1 pseudotyped virus

The pseudotyped viruses were produced as previously reported ( Xia etਊl., 2020a ). Briefly, plasmids pNL4-3.luc.RE (the luciferase reporter-expressing HIV-1 backbone) and pcDNA3.1-SARS-CoV-1-S/pcDNA3.1-SARS-CoV-2-S (encoding for the S-protein of SARS-CoV-1 or SARS-CoV-2) were co-transfected into HEK293T cells using the transfection reagent VigoFect (Vigorous Biotechnology, Beijing). The supernatant containing the released pseudotyped particles was harvested at 72 hours post-transfection. After centrifugation, the supernatant was collected, aliquoted, and frozen at �ଌ. The production of the SARS-CoV-2 pseudovirus mutants was performed as described above except using the plasmids of pcDNA3.1-SARS-CoV-2 with the corresponding mutations (V341I, F342L, V367F, R408I, A435S, G476S, and V483A) in the S-protein ( Ou etਊl., 2020 ). These plasmids were constructed using the plasmid of pcDNA3.1-SARS-CoV-2-S as a template by a site-directed mutation kit (Yeasen Biotech, Shanghai).

In vitro neutralization assay by pseudotyped SARS-CoV-1 and 𢄢 viruses

In vitro SARS-CoV-1 and SARS-CoV-2 pseudovirus infection was performed as previously described ( Xia etਊl., 2020a ). Briefly, 1 × 10 4 /well Huh-7 cells were seeded in 96-well plates in DMEM supplemented with 10% FBS. The seeded cells were cultured for an additional eight hours before infection. To quantitate the neutralization capacity, the human serum (maximum concentration, 1:20), polyclonal antibodies purified from human serum (maximum concentration, 50 μg/ml), or monoclonal antibodies (maximum concentration, 10 or 1 or 0.625 μg/ml) was serially diluted 1:2 in DMEM medium for nine dilutions in total. Subsequently, the diluted antibodies or serum samples were incubated with SARS-CoV-1 or 𢄢 pseudoviruses for 30 minutes at 37ଌ before added onto Huh-7 cells for infection. For the neutralization blocking experiments, different antigens (RBD, S1, S2 or S-ECD proteins) were incubated at different concentrations, respectively, with 5 μg/ml purified IgG from donor #16 for one hour at 37ଌ before incubation with SARS-CoV-2 pseudovirus. After incubation for half an hour, the mixture was finally added to the Huh-7 cells for infection. After incubation for 12 hours, the supernatant was replaced with fresh DMEM medium supplemented with 2% FBS. The cell supernatant was removed after culture for further 48 hours, and the cells were lysed for luciferase activity measurement using a Firefly Luciferase Assay Kit (Promega) and luminometer according to the manufacturer’s instructions.

The absolute luciferase values were measured and the relative values were calculated by normalizing to the virus-only control well in the same lane. For example, the absolute luciferase value in a pseudovirus-only control well (considered as reference) was 5 × 10 4 , while adding one neutralizing serum sample might reduce this to 1 × 10 4 . Therefore, the normalized luciferase values were calculated as 100% in the pseudovirus-only control and 20% for this neutralizing serum. Since many aspects, such as pseudovirus concentration, cultured cell concentration, status of the cells, immunofluorescence reading, and etc., varied dramatically between different plates and different tests, normalization is necessary for combining data for comparison. For the serum neutralization assays ( Figures 1 F and 1G), the reciprocal of the serum dilution that resulted in 50% inhibition compared with pseudovirus alone was reported as the 50% neutralization titer (NT50).

In vitro neutralization assay by authentic SARS-CoV-2 virus

In vitro authentic SARS-CoV-2 neutralization assay was performed using Vero-E6 as previously reported ( Chi etਊl., 2020 ). Briefly, 1 × 10 4 /well Vero-E6 cells were seeded in 96-well plates. After culture for 24 hours, the 1:4 serially diluted antibodies (maximum concentration, 5 μg/ml) were mixed with 0.1 MOI (multiplicity of infection) authentic SARS-CoV-2 virus and incubated at 37ଌ for 30 minutes. This mixture was subsequently added into the cultured Vero-E6 cells. The supernatants were collected after further culture for two days for quantitative reverse transcription PCR and the cells were analyzed by immunofluorescence.

For immunofluorescence, the cells were fixed in 4% paraformaldehyde in PBS for 20 minutes, washed with PBS and permeabilized with 0.1% Triton X-100 in PBS at room temperature. After blocking with 3% BSA, the cells were incubated with anti-N polyclonal antibody ( Gu etਊl., 2020 ) at a dilution of 1:1000 overnight at 4ଌ and visualized with donkey anti-mouse IgG Alexa Fluor 488 (Thermo Fisher Scientific). Nuclei were stained with DAPI. Cells were imaged using an Eclipse Ti-S inverted fluorescence microscopy (Nikon).

For quantitative reverse transcription PCR, the viral RNA was extracted from the collected supernatant using Trizol LS (Thermo Fisher Scientific) and used as templates for quantitative PCR analysis by One-Step PrimeScrip RT-PCR Kit (Takara) following the manufacturer’s instructions. The primers and probe used were listed in Table S2. The PCR amplicon by SARS-CoV-2-N-F and SARS-CoV-2-N-R primers was inserted into pUC57 plasmid for standard curve generation. The program of the quantitative reverse transcription PCR was performed using the Mastercycler ep realplex Real-time PCR System (Eppendorf) as followed: 95ଌ 5 minutes 40 cycles of 95ଌ 10 s, 50ଌ 30 s, 72ଌ 30 s.

In vitro assay to detect antibody-dependent viral entry

In vitro SARS-CoV-2 pseudovirus ADE assays was performed using Raji cells as previously reported ( Jaume etਊl., 2011 ). Briefly, 3 × 10 4 Raji cells were seeded in each well of 96-well plates coated with 0.01% poly-L-lysine in PBS and cultured for 24 hours. The antibodies were serially diluted 1:2 (maximum concentration, 100 μg/ml) in RPMI 1640 for nine dilutions in total, and were incubated with the SARS-CoV-2 pseudovirus for 30 minutes. The mixture was applied onto the Raji cells and cultured for 60 hours. The measurement of luciferase activity was performed as described above using a Firefly Luciferase Assay Kit (Promega). The absolute luciferase activity values from all the wells were normalized to the luciferase activity value obtained with 2 μg/ml of antibody XG043 and expressed as the fold change in luciferase activity. Two replicates of XG043 (2 μg/ml) were performed on each plate and the average luciferase activity value of these two replicates was considered as reference (100% relative luciferase activity, the dotted lines in Figures 6 A, 6D, and 6E Figure S6B). Since many factors (virus concentration, cell concentration, immunofluorescence reading, etc.) vary between different plates or different rounds of experiments, normalization is necessary for comparing the luciferase activity values from different plates. The reason for choosing XG043 as the reference is simply because that XG043 was the first identified to induce ADE in our studies.

For the experiment to block the antibody-dependent viral entry, different concentrations of anti-hCD32 (BD PharMingen) were incubated with the Raji cells for 30 minutes at 37ଌ. Then, the mixture of 2 μg/ml antibody XG005 and SARS-CoV-2 pseudovirus was added to the treated Raji cells. The plates were incubated at 37ଌ for 60 hours before the measurement of luciferase activities as described above.

For in vitro Raji cell-dependent ADE assays using authentic SARS-CoV-2 virus, cultured Raji cells were incubated with the mixture of authentic SARS-CoV-2 virus and monoclonal antibodies (final concentration 4 μg/ml), XG038, XG016 and XG005, respectively. After 6, 24 or 48 hours incubation, the Raji cells were collected for RNA extraction and quantitative reverse transcription PCR analysis. SARS-CoV-2 N-protein RNA copy numbers were calculated using a standard curve composed of seven prepared N-protein DNA samples with 10-fold serial dilutions.

Protein production

The codon optimized wild-type cDNA of SARS-CoV-2 receptor-binding domain (RBD) (amino acid 330�) together with an Avi tag (GLNDIFEAQKIEWHE) was synthesized (GENEWIZ), and cloned into pACgp67 vector with a C-terminal 8 × His tag for purification. The SARS-CoV-2 RBD was expressed using the Bac-to-Bac baculovirus system. Extracted bacmid DNA was then transfected into Sf9 cells using Cellfectin II Reagent (Invitrogen). The low-titer viruses were harvested and then amplified to generate high-titer virus stock. The supernatant containing the secreted RBD without glycosylation was harvested 72 hours after infection and the RBD protein was captured by Ni-NTA resin (GE Healthcare) and purified. SDS-PAGE analysis revealed over 95% purity of the purified recombinant protein.

For the site-directed mutagenesis and expression of RBD mutants, SARS-CoV-2 RBD fragment (residue 319-541) and its mutants were synthesized (GenScript), fused with the human IgG1 Fc fragment, and cloned into mammal expression vector pSecTag. The plasmid was transfected into HEK Expi293 cells and incubated at 37ଌ for four days. Supernatant was harvest for further purification by Protein G resin according to the manufacturer’s protocol.

Single cell sorting of RBD- or S-ECD-binding memory B cells

S-ECD protein (GenScript) expressed and purified from recombinant baculovirus-infected insect Sf9 cells was chemically biotinylated using EZ-Link Sulfo-NHS-LC-Biotin kit (Thermo Fisher Scientific) as manufacturer’s instructions. Avi-tagged RBD expressed in baculovirus-infected insect Sf9 cells and Avi-tagged S-ECD expressed in mammalian HEK293T cells (Kactus Biosystems) were biotinylated using BirA Biotin-Protein Ligase kit (Avidity). The excess of unbound biotin was removed by using Zeba Spin Desalting column (Thermo Fisher Scientific). For each sample, the bait protein-PE and bait protein-APC were prepared by incubating 3 μg of biotinylated RBD or 25 μg of biotinylated S-ECD proteins with streptavidin-PE (eBioscience) or streptavidin-APC (BD Biosciences), respectively.

Purification of B cells, two-fluorescent-dye labeling of bait protein-binding B cells and single cell sorting experiments were performed as previously described ( Escolano etਊl., 2019 Robbiani etਊl., 2017 Wang etਊl., 2020b ). Briefly, PBMCs thawed and washed with RPMI medium were incubated with CD19 MicroBeads (Miltenyi Biotec) for positive selection of B lymphocytes. Sequential incubation at 4ଌ with human Fc block (BD Biosciences), bait protein-PE/APC (10 μg/ml for RBD, 60 μg/ml for S-ECD), and anti-CD20-PECy7 (BD Biosciences) was performed, followed by the single-cell sorting of CD20-PECy7 + bait protein-PE + bait protein-APC + memory B cells into 96-well plates using a FACSAria II (BD Biosciences). The single-cell sorted B cells were stored at �ଌ.

Antibody cloning, sequencing and production

Antibody cloning from the sorted single cells and the production of monoclonal antibodies were done as previously reported ( Robbiani etਊl., 2017 Wang etਊl., 2020b ). The sequences of primers for the 1 st / 2 nd round of nested PCR were listed in Table S2. Amplified PCR products from each single cell were loaded onto 2% agarose gel for electrophoresis and purified for Sanger sequencing. All the sequencing result of heavy and kappa/lambda light chains were analyzed by IMGT/V-QUEST ( Brochet etਊl., 2008 ) and IgBlast ( Ye etਊl., 2013 ), and the V(D)J gene segment and CDR3 sequences of each antibody were determined. The selected antibodies were subjected to vector construction and antibody expression as previously described ( von Boehmer etਊl., 2016 ).

Clustering analysis

Relative luciferase activities measured in neutralization or ADE assays or both were used for unsupervised hierarchical clustering analysis with the statistical scripting language R, using log-transformed data, Euclidean correlation coefficients for a distance metric, and ward.D2 clustering. A heatmap and cluster dendrogram tree were created using the Pretty Heatmaps (pheatmap and hclust) R packages.

Quantification and statistical analysis

The detailed results of statistical analysis are shown in the Result and Figure Legends. The Shapiro-Wilk test and Fisher’s F test were employed to check for normality and homogeneity of variances, respectively, prior to performing the comparison. Student’s t test was performed for RBD ELISA ( Figureਁ A), while Wilcoxon Rank Sum test was used for other ELISAs ( Figures 1 B�) and comparisons of ADE AUC ( Figureਇ E) due to their non-normal distribution. In order to determine whether there is a statistically significant difference of the ADE AUC and IC50 values of Cluster-X, -Y, and -Z antibodies, the nonparametric test (Dunn’s Kruskal-Wallis multiple comparison) was performed ( Figures 7 B and 7C). Fisher’s exact test was performed to assess the statistical significance based on the exact distribution of the frequencies of RBD Group-IV antibodies in three antibody clusters ( Figureਇ D). Correlation was evaluated by Spearman’s rank correlation method (Figures S6E–S6G). The area under the ELISA curves (ELISA AUC) ( Figures 1 A� and ​ and3A�), 3 A�), the half-maximal neutralizing titer (NT50) for serum neutralization assays ( Figures 1 F𠄱H), the 50% inhibitory concentration (IC50) values calculated for antibody neutralization capacities ( Figures 4 A, 4F, and ​ and5C), 5 C), the area under the ADE curve (ADE AUC) ( Figureਆ C), and enhancing power values (Figure S6D) were calculated in PRISM software as previously reported ( Bardina etਊl., 2017 Robbiani etਊl., 2019 Wang etਊl., 2020b ).


1. An antibody which binds to AXL (SEQ ID NO: 130) and comprises a heavy chain variable (VH) region and a light chain variable (VL) region, wherein the VH region comprises the CDR1, CDR2, and CDR3 sequences set forth in SEQ ID NOs: 36, 37, and 38, respectively, and the VL region comprises the CDR1, CDR2, and CDR3 sequences set forth in SEQ ID NO: 39, GAS, and SEQ ID NO: 40, respectively.

2. The antibody of claim 1, wherein the VH and VL regions comprise the amino acid sequences set forth in SEQ ID NOs: 1 and 2, respectively.

3. The antibody of claim 1, wherein said antibody comprises a heavy chain of an isotype selected from the group consisting of IgG1, IgG2, IgG3, and IgG4.

4. The antibody of claim 1, which is a full-length monoclonal antibody.

5. The antibody of claim 1, wherein said antibody is a monovalent antibody.

6. The antibody of claim 1, wherein said antibody is a single-chain antibody.

7. An immunoconjugate comprising the antibody of claim 1, and a therapeutic moiety.

8. The immunoconjugate of claim 7, wherein the therapeutic moiety is a cytotoxic agent.

9. The immunoconjugate of claim 8, wherein said cytotoxic agent is linked to said antibody with a cleavable linker.

10. The immunoconjugate of claim 9, wherein said linker is mc-vc-PAB and the cytotoxic agent is MMAE or the linker is SSP and the cytotoxic agent is DM1.

11. A pharmaceutical composition comprising the immunoconjugate of claim 7, and a pharmaceutical acceptable carrier.

12. A pharmaceutical composition comprising the antibody of claim 1, and a pharmaceutical acceptable carrier.

13. A kit for detecting the presence of AXL antigen, or a cell expressing AXL, in a sample, wherein the kit comprises the antibody of claim 1.

14. A bispecific antibody comprising (a) a first binding region which binds to AXL (SEQ ID NO: 130) and comprises a heavy chain variable (VH) region and a light chain variable (VL) region, wherein the VH region comprises the CDR1, CDR2, and CDR3 sequences set forth in SEQ ID NOs: 36, 37, and 38, respectively, and the VL region comprises the CDR1, CDR2, and CDR3 sequences set forth in SEQ ID NO: 39, GAS, and SEQ ID NO: 40, respectively, and (b) a second binding region which binds a different target or epitope than said first binding region.

15. The bispecific antibody of claim 14, wherein said bispecific antibody comprises a first and a second heavy chain, each of said first and second heavy chain comprises at least a hinge region, a CH2 and CH3 region, wherein in said first heavy chain at least one of the amino acids in the positions corresponding to positions selected from the group consisting of K409, T366, L368, K370, D399, F405, and Y407 in a human IgG1 heavy chain has been substituted, and in said second heavy chain at least one of the amino acids in the positions corresponding to a position selected from the group consisting of F405, T366, L368, K370, D399, Y407, and K409 in a human IgG1 heavy chain has been substituted, wherein said substitutions of said first and said second heavy chains are not in the same positions, and wherein the numbering is according to the EU Index as set forth in Kabat.

16. The bispecific antibody of claim 14, wherein the amino acid in the position corresponding to K409 in a human IgG1 heavy chain is R in said first heavy chain, and the amino acid in the position corresponding to F405 in a human IgG1 heavy chain is L in said second heavy chain, or vice versa, wherein the numbering is according to the EU Index as set forth in Kabat.

17. An immunoconjugate comprising the bispecific antibody of claim 14, and a therapeutic moiety.

18. A pharmaceutical composition comprising the bispecific antibody of claim 14, and a pharmaceutical acceptable carrier.

19. An antibody which binds to AXL (SEQ ID NO: 130) and comprises a heavy chain variable (VH) region and a light chain variable (VL) region, wherein the VH region comprises the amino acid sequence set forth in SEQ ID NO: 1, and the VL region comprises the amino acid sequence set forth in SEQ ID NO: 2.

20. The antibody of claim 19, wherein said antibody comprises a heavy chain of an isotype selected from the group consisting of IgG1, IgG2, IgG3, and IgG4.

21. The antibody of claim 19, which is a full-length monoclonal antibody.

22. The antibody of claim 19, wherein said antibody is a monovalent antibody.

23. The antibody of claim 19, wherein said antibody is a single-chain antibody.

24. An immunoconjugate comprising the antibody of claim 19, and a therapeutic moiety.

25. The immunoconjugate of claim 24, wherein the therapeutic moiety is a cytotoxic agent.

26. A pharmaceutical composition comprising the antibody of claim 19, and a pharmaceutical acceptable carrier.

27. A kit for detecting the presence of AXL antigen, or a cell expressing AXL, in a sample wherein the kit comprises the antibody of claim 19.

28. A bispecific antibody comprising (a) a first binding region which binds to AXL (SEQ ID NO: 130) and comprises a heavy chain variable (VH) region and a light chain variable (VL) region, wherein the VH region comprises the amino acid sequence set forth in SEQ ID NO: 1, and the VL region comprises the amino acid sequence set forth in SEQ ID NO: 2, and (b) a second binding region which binds a different target or epitope than said first binding region.


As discussed in the early section, format diversity is essential to serve the plethora of applications of bsAbs defined by TPPs. Variances in affinity, valency, epitope, and geometry of their binding domains, linkers, as well as in size- and Fc-mediated distribution and pharmacokinetic properties to fulfill a particular clinical application define a bsAb format. In practice, many variances or attributes for selecting an optimal format are intertwined and must be addressed for selecting the right molecule. Therefore, we will discuss these attributes below.

Antigen-binding affinity and valency


Even though one of the advantages of using antibody-based therapeutics is that they may interact with their antigens with substantially high affinities, higher affinity does not always translate into better efficacy. Unlike antagonistic molecule, whose potency is usually associated with its affinity, agonistic molecule is more difficult to predict and to optimize its potency by increasing the binding affinity. Based on different modes the receptor uses for activation, different binding kinetics of the agonistic bsAb to reach optimal receptor activation are required. For receptors depending on clustering to activate, fast-on fast-off binding kinetics is preferred to ensure efficient recruitment of receptors [136, 137]. On the contrary, for receptors activated by ligand binding-induced conformational change, the slow off binding kinetics would endorse more durable activating efficacy [138]. Furthermore, there are evidences that the affinity to CD3 may significantly affect the function and safety profile for TRBAs. It has been suggested that T cells require lower threshold for mediating cytotoxic killing than for cytokine production perhaps due to different number of ITAM motifs of TCR complex being phosphorylated, it may be possible to dissociate TRBAs’ potency from toxicity by modulating the CD3 affinity of the bsAbs. As shown by Leong et al., by lowering the affinity to CD3, the CD3 ×਌LL1 bsAb with low affinity to CD3 exhibited better safety profile and retained equivalent in vivo efficacy, as compared to the ones with high affinity to CD3 [139] when net impact on T cell activation, receptor internalization, and PK all combined. Similar results were also shown by Zuch de Zafra et al. By comparing a series of CD38 ×򠳓 bsAbs with different affinities to CD3, they found that lowering the affinity to CD3 can dramatically decrease the cytokine release, but still maintain potency in mediating cytotoxic killing [140]. In November 2019, AMG-424, the final lead from the aforementioned study, was granted with orphan drug designation for multiple myeloma by the FDA.

As for the affinities of TRBAs to TAAs, due to the different expression profile of the TAAs in normal tissues versus in tumors, and the tolerability and the ability of regeneration of TAA-positive cell populations in normal tissues, the TRBAs targeting different TAAs may require different binding kinetics. For low-expression, tumor-specific antigens, a TRBA with high affinity to the antigen would be required to elicit efficient tumor cell killing. However, for TAA with low expression on essential normal tissues/organs, to spare the normal cells and avoid on-target off-tumor toxicity, low-affinity high-avidity TRBAs would be preferred, which can be achieved by modulating the valency (see below).

Moreover, for a bsAb, difference in affinities of two different antigen-binding specificities may determine which arm drives tissue distribution, tissue penetration, and retention of a therapeutic molecule at the site of MOA. For examples, high affinity to TAA and low affinity to CD3 may enable the preferential binding of TRBAs to the target cells and implement serial killing of the target cells by a single T cell [141] and as mentioned above, APLP2 × Her2 bispecific ADC with high affinity to Her2 and low affinity to APLP2 preferentially binds to Her2-positive cells and then bridges APLP2 on the cell surface to mediate efficient endocytosis to avoid the toxicity associated with the pan expression of APLP2.

For BBB crossing bsAbs, along with other considerations, careful selection of the transport receptor and selection of a molecule with appropriate binding kinetics to the transport receptor is critical for success of this strategy. As reported by the scientists from Genentech, to ensure the effectiveness of the transcytosis, the “Trojan horse” antibody using the TfR pathway needs to have low affinity to TfR [142]. Later, another study by the University of Wisconsin-Madison showed that TfR bsAb with high binding affinity to TfR at pHਇ.4 but low affinity at pHਅ.5 can effectually release the bsAbs from BBB into the brain and avoid the degradation of bsAb in the endosome [143].


The valency for each target can dramatically affect the function of the bsAbs. For the TRBAs, monovalency of anti-CD3 arms may help to avoid non-specific activation of the T cells without engagement of tumor cells, as shown by Bardwell et al. [144]. Interestingly, Y-mAb and Abpro have CD3 scFv fused to the C-terminus of the light chain. Even though the format ends up with two binding sites for CD3, both companies claimed that this format was actually functional monovalent toward CD3. Additionally, Aptevo and Affimed also developed TRBAs using bivalency to CD3. Preclinical evidence has suggested that the adoption of the ADAPTIR format can induce potent T cell activation and target cell killing, but low levels of cytokine release [145]. AFM-11 (CD19 ×򠳓) also showed more potent T cell activation than BiTE control and strict CD19-dependent T cell activation preclinically [146]. However, due to one death and two life-threatening events in clinical trial, AFM-11 was placed on clinical hold.

The valence for the TAA may vary based on the properties of the TAA, such as tumor specificity, antigen size, expression level on the tumor versus normal tissue, and the tolerance of complete elimination of TAA-positive cells. In the case of some types of hematopoietic tumors, the depletion of both normal and malignant cells expressing TAAs, such as CD19 and/or CD20, can be tolerated. However, for most of the other TAAs, the expression levels may be low on normal tissues, but the killing of these low-expression normal cells can lead to deleterious consequences. To distinguish the target high tumor cells from the target low normal tissue, RG7802 (CEA ×򠳓) was optimized to have low-affinity high-avidity 2 +ਁ format in appropriate geometry to facilitate the selection of CEA high cells with a threshold of

10򠀀 CEA-binding sites/cell [105].

Based on the lessons learned from the initial mAb development for cMET treatment, bivalency to cMET may elicit agonistic, instead of antagonistic, effect resulting from the mAb-mediated dimerization of cMET. Though monovalent binding to cMET can function as an antagonist, it can only block the HGF-mediated cMET activation. Later, Wang et al. demonstrated that ABT-700, a truly antagonistic mAb against cMET, can bind to a unique epitope on cMET. The bivalency to cMET of ABT-700 and stringent hinge region was essential to inhibit both HGF-dependent and HGF-independent activation of cMET and induce cMET downregulation [147]. Interestingly, half of the cMET bsAb programs are using monovalency against cMET to avoid agonistic effect, while the other half choose bivalency. EMB-01 (EGFR ×਌MET) has two binding sites for cMET, and has no obvious cMET activation in the absence of ligands. Furthermore, it can effectively induce EGFR and cMET degradation, therefore preventing the cMET activation [62].

Epitope, geometry, and distance between different antigen-binding domains


In respect of antagonistic bsAb, the binding epitope of the corresponding binding units are required to prevent the receptor/ligand engagement, or the receptor signal complex formation, or any step that is crucial for the initiation or passage of signaling cascade into the cells to play its biological function.

In general, the receptor-binding epitope for agonistic molecules is not as predictive as it is for antagonistic molecules. However, there is evidence to suggest that the binding epitopes do contribute significantly to the bsAb efficacy. It was found that anti-CD3 binding arms recognizing different epitopes on CD3-activated T cell differently. TeneoBio, therefore, identified a dozen of anti-CD3 antibodies with different binding epitopes and different binding kinetics to CD3 molecules to disassociate the capabilities of TRBAs in inducing cytotoxic killing from promoting cytokine production post T cell activation. They identified a clone (F2B) that recognizes a unique epitope on CD3δε, but not CD3 γε, at a low affinity (34 nM). By comparing to another clone (F1F), which binds to both CD3δε and CD3 γε with high affinity (ρ pM), they found that BCMA ×򠳓 bsAb using F2B arm (CD3_F2BxBCMA) can induce moderate levels of cell killing but very weak cytokine production, as compared to the one using F1F arm (CD3_F1FxBCMA) in vitro. Moreover, the in vivo efficacy study showed that CD3_F2BxBCMA exhibited antitumor activity in a wide dose range (0.01� μg), while CD3_F1FxBCMA completely lost its therapeutic efficacy at the high dose (10 μg) [148].

As we mentioned above, to effectively redirect T cell killing, the TRBAs must be able to induce the IS formation between the T cells and target tumor cells. Besides the format of the TRBAs, the tumor antigen selection, the size of the antigen, antigen surface density, as well as the distance between the TRBAs binding epitope to target cell membrane, all can influence the formation of the IS. Comparing to large antigens or antigens with protruding structure, the small antigens or antigens with structure close to the cell membrane can more effectively promote the IS formation [106]. When the selected tumor antigen is large in size, such as melanoma chondroitin sulfate proteoglycan (MCSP) [149] and FcRH5 [150], the membrane-proximal epitope is desired. For cell surface targets that can be shed into the bloodstream, to avoid antigen sink, the bsAbs should recognize the membrane-bound but not the soluble form of the antigen [151].


Besides the distance between the epitope to the target cell membrane, the distance between the two targets engaged by TRBAs also plays a crucial role in determining whether it can effectively promote IS formation and T cell activation. Considering the distances between the TAA and CD3 epitopes to target cell and T cell, respectively, the format of the TRBAs needs to bring TAA and CD3 to a close proximity much less than 14 nm. Moreover, the whole molecule has to be able to physically fit into the small junction between the two cells in a density to effectively form a cluster with several engaged target pairs to initiate TCR signaling. Despite its short serum half-life, the small size of BiTE format with two binding units locating in opposite sides is extremely potent in redirecting T cell cytotoxicity by inducing serial killing of tumor cells at an effector-to-target ratio as low as 1:5 [141]. In another case, Aptevo fused the scFvs against the TAA and CD3 at the N- and C-terminus of Fc (scFv + scFv with Fc, 2 +ਂ), which ended up with longer distances between the two binding domains. The in vitro studies showed that this molecule had more potent target cell killing, but less cytokine release, as compared to the BiTE format [145]. Unfortunately, the clinical development for this molecule was discontinued due to high frequency of anti-drug antibody development.

The same situation also applies to T cell co-stimulatory and co-inhibitory receptors, which co-cluster with TCR during IS formation and regulate T cell activation. PD-1 and PD-L1 interaction leads to the accumulation of PD-1 microclusters at cSMAC and destabilizes the IS. When the extracellular domain of PD-1 was elongated by inserting extra Ig domains, the inhibitory role of PD-1 decreased along with the increase of the number of Ig domains inserted [152]. Though current anti-PD-1 molecules all block the PD-1 signaling by inhibiting the PD-1/PD-L1 interaction, in theory, the designs that can prevent the PD-1 colocalization to cSMAC should also be able to diminish the inhibitory role of PD-1 in T cell responses. On the contrary, bsAbs to activate the co-stimulatory receptor such as 4-1BB must exert its function at the site of IS [93] therefore, a format that can meet these criteria is necessary. As reported by Pieris, the geometry of the 4-1BB anticalin attachment significantly affected the function of the Her2 ×਄-1BB bispecific anticalins. PRS-343 with 4-1BB anticalin attached at the C-terminus of the heavy chain showed the most effective T cell activation, as compared to other formats. One possible explanation is that the binding sites for Her2 and 4-1BB are approximately 15 nm apart, which is close to the distance of the IS. However, after measuring the distances from the binding epitopes to the cell membrane, the distance between the target cell and the effector cell might be much longer than 15 nm. On the other hand, ND-021 (PD-L1 ×਄-1BB × HSA) is an Fc-lacking scFv-VHH-based molecule. With its small size and flexible structure, it may have better potential in colocalizing at cSMAC and enhance TCR signaling. It will be interesting to see how it will perform in the clinical trials.

Cases are also shown in bsAbs programs developed for other conditions. For example, when the scientists at MedImmune tested their Psl × PcrV bsAbs, they examined several different formats with varying intramolecular distances between the two binding components. After comparison of these formats in both in vitro and in vivo efficacy studies, BiS4aPa, with an intermediate distance, exhibited the most effective protection against P. aeruginosa infection and therefore was selected as the final therapeutic candidate format [132].

Linker design

As reviewed by Brinkmann and Kontermann, various connecting linkers have been explored [3]. Similar to the hinge region of the IgG subclass, the length, flexibility, and amino acid composition of the linkers used to connect the building blocks (scFv, Fab, etc.) may determine the correct formation, functionality, and developability of the resulting bispecific molecules, as shown by Le Gall et al. [153] and DiGiammarino et al. [154].

The bsAbs have made significant impact on hematologic malignancy treatments. However, the therapeutic benefits delivered by bsAb for solid tumor are still waiting to be unveiled. One of the concerns using bsAbs for solid tumor treatment is how to increase the drug tumor penetration and accumulation. Though molecules with smaller size would have better chance entering the tumor site by increased tumor penetration, the molecules with size smaller than the threshold of renal clearance of proteins are rapidly cleared from the blood and therefore have decreased flux into the tumor [155]. Using a compartmental model, Schmidt and Wittrup predicted that molecules with the size of 150 kDa would have the best tumor localization, whereas molecules with the size of 25 kDa would have the worst tumor uptake [156]. However, due to their large size, molecules at the size of

150 kDa have decreased extravasation and normally take days to reach maximum tumor uptake. On the other hand, molecules of smaller size reach the maximum tumor uptake within a short period of time. The fast tumor penetration and systemic clearance of small-sized molecule therefore lead to high tumor/blood localization ratio, which is preferred for some applications, such as imaging [157], as well as safety management to decrease the systemic drug exposure-associated toxicity.

To improve the serum half-life, while still retaining the fast extravasation property, Harpoon developed the TriTAC platform, which targets TAA, CD3, as well as human albumin for extended half-life with a total size of

50 kDa. It is believed that with its improved drug exposure and small size, TriTAC would enable faster and better tumor penetration, compared to large-sized bsAbs.

Fc region

The Fc region can substantially influence the bsAbs’ function. It was found that the properties of IgG subclass hinge region, such as length, sequences, flexibility, and disulfide bond structures, can influence the variable region presentation and thereby affect the functionality of an antibody [158]. While it is not always desired, the format with Fc can prolong the bsAb serum half-life through FcRn-mediated recycling and may provide Fc effector function through the interaction with FcγRs.

IgG subclass

Recently, Kapelski et al. reported the influence of the IgG subclass on TRBAs. They found that due to its short and rigid hinge region, IgG2 cannot effectively promote the IS formation. However, by replacing the hinge region of the IgG2 with the hinge region of IgG4 or IgG1, the function of IgG2 chimeric bsAb can effectively induce IS formation and redirect T cell killing [159].

Similarly, the Fc region also showed significant influence on the factor VIII-mimetic activity of emicizumab. After comparison between different IgG subclasses, interchain disulfide bonds, and mutations in hinge region and CH2 domain, IgG4 was selected as it presented with the most potent factor VIII-mimetic activity [160].

Fc effector function

As mentioned above, several strategies have been developed to enhance the binding between Fc and FcγRs to increase the Fc effector function. This could be important for bsAbs against TAAs for effective killing tumor cells or for bsAbs against infectious agents for pathogen uptake and clearance. However, the Fc effector function and FcγR binding are usually abrogated for TRBAs and some other agonistic bsAbs to avoid the FcγR-mediated cross-linking, which may cause non-specific activation of T cells and the targeted receptors, respectively. Advances in Fc engineering allow tailored modification of Fc effector functions for specific need. For example, Xencor developed a series of TRBAs using the XmAb platforms, including AMG-424 (CD38 ×򠳓, Fab + scFv with Fc, 1 +ਁ), and used a combination of mutations (E233P/L234V/L235A/G236del/S267K) to completely eliminate the binding of IgG1 Fc to FcγRs [55].

Because IgG4 only binds to FcγR1 with high affinity and mediates weaker effector function than IgG1, it is commonly used for antagonistic antibodies targeting immune cells, to avoid Fc effector function-mediated cell elimination. However, the research by Zhang et al. showed that the anti-PD-1/IgG4 antibody can induce the phagocytosis of PD-1 + T cells by activating FcγRI + macrophages. By introducing five additional mutations (E233P/F234VL235A/D265A/R409K), BGB-A317 showed no binding to FcγR1, and more efficient preclinical antitumor activity, as compared to the anti-PD-1/IgG4 control [161]. The recently reported results of the pivotal study of BGB-A317 also exhibited its superior antitumor efficacy in patients with relapsed/refractory classical Hodgkin lymphoma, with an overall response rate (ORR) of 87% and 63% complete response rate (CRR).

As we discussed above, the format contains many components that can be tweaked, their final impact on pharmacological properties of a bsAb is intertwined, and here we only mentioned some of them. The fine-tuned parts work in concert with each other to determine the success of bsAbs. To obtain the optimal therapeutic candidate, the selection of any component in the final format should be carefully evaluated for specific target pairs and the matched format will not only facilitate the bsAbs to elicit biological function but also may enable a molecule for further product development, which otherwise may not be suitable for clinical application.


Cocaine Toxicity in the Rat.

Rats pretreated with mAb 15A10 showed a significant (P < 0.001) dose-dependent increase in survival after an LD90 cocaine infusion (Fig. 2). Four of five animals receiving 15 mg/kg antibody, and all of five receiving 50 mg/kg antibody, survived. In contrast, all eight untreated rats expired before the cocaine infusion was complete. In the animals not treated with mAb 15A10, the mean cocaine dose at death was 7.5 ± 0.6 mg/kg, whereas the five treated with antibody at 5 mg/kg expired at a mean cocaine dose of 8.2 ± 1.0 mg/kg and the single nonsurvivor in the group treated with antibody at 15 mg/kg expired at 15.9 mg/kg of cocaine.

Log dose-response relationship for mAb 15A10 on rats’ survival after infusion of an LD90 (16 mg/kg) cocaine. The effect of mAb 15A10 on survival was significant by a χ 2 test (P < 0.001).

To quantify further the protective effect of the catalytic antibody, we infused catecholamines and cocaine continuously to the experimental (mAb 15A10, 100 mg/kg) and control (saline) groups until all animals expired (Fig. 3A). The dose of cocaine at seizure averaged 9.48 mg/kg for saline controls and 32.5 mg/kg for animals treated with mAb 15A10 (P < 0.01). The mean lethal dose of cocaine was also increased >3-fold, from 11.5 mg/kg of cocaine for controls to 37.0 mg/kg for the mAb 15A10 group (P < 0.01).

Saturation of mAb 15A10 with cocaine. Mean cocaine dose at seizure and at death (A). Plasma concentration of ecgonine methyl ester (EME) and cocaine at death (B). A significant difference between the saline control group and the 15A10 group was determined using the Mann–Whitney U test for unpaired samples.

Simple binding was an unlikely explanation for the effectiveness of mAb 15A10 because stoichiometric binding of cocaine would be expected to shift the dose-response to cocaine by <1 mg/kg. However, to exclude this possibility, we tested the action of a binding antibody, mAb 1C1, at the same dose. mAb 1C1 was elicited by immunization with TSA-I but the antibody is not catalytically active because it binds free TSA and cocaine with comparable affinity. As expected mAb 1C1, despite its greater affinity for cocaine compared with mAb 15A10, was ineffective in blocking cocaine-induced convulsions or death (Fig. 3A).

To demonstrate in vivo catalysis, we measured the plasma concentrations of cocaine hydrolysis products in the 15A10 and control groups by our previously developed HPLC method (17). The mAb 15A10 group showed a >10-fold increase in ecgonine methyl ester compared with either the saline (P < 0.001) or the mAb 1C1 (P < 0.01) control groups (Fig. 3B). As expected, based on its rapid metabolism (13), plasma benzoic acid concentrations were not significantly elevated in the 15A10 group (3.85 ± 0.89 μM) compared with the saline control group (2.36 ± 1.05 μM) [data not shown]. Consistent with specific catalysis at the benzoyl ester, the plasma concentration of the methyl ester hydrolysis product, benzoyl ecgonine, was not significantly increased in the mAb 15A10 group (7.68 ± 1.07 μM) compared with saline control (5.47 ± 1.01 μM) [data not shown].

We measured plasma cocaine concentrations at death using HPLC (17) in control rats and those receiving mAb 15A10 to confirm that mAb 15A10 conferred resistance to cocaine toxicity through a prereceptor mechanism. A marked elevation of plasma cocaine at death would be expected if mAb 15A10 blocked toxicity by acting at or after the binding of cocaine to its receptors. In contrast, plasma cocaine concentrations at death were not significantly different between 15A10 and control groups (Fig. 3B) despite the administration of >3-fold higher dose of cocaine to the mAb 15A10 group (Fig. 3A). This result for mAb 15A10 was as expected for a prereceptor effect and consistent with protection from toxicity through catalyzed degradation of cocaine.

Rat Self-Administration.

In this evaluation, the rats were prepared with chronic indwelling intravenous catheters and trained to press on levers and receive intravenous injections of 0.3 mg/kg/inj cocaine during 1-hr daily sessions. Cocaine maintained regular patterns of lever-pressing when saline was substituted for cocaine, lever-pressing decreased rapidly during a session (Fig. 4 A and B). mAb 15A10 blocked completely the reinforcing effects of intravenous cocaine in the rat both number of cocaine injections and pattern of responding were similar to those after saline substitution (Figs. 4 C and 5). The pattern of cocaine self-administration produced a half-life that averaged 23.8 min for the five rats, indicating that half of the total responses were made in the first 23.8 min of the 60-min session. An average of 24.2 injections of cocaine were taken under control conditions. The response half-life when saline was available was 7.8 min of the session, reflecting the rapid decrease in saline-maintained responding 11.2 injections of saline were taken on average. When cocaine was available to the rats 24 hr after administration of 9–12 mg of mAb 15A10, the pattern and amount of cocaine self-administration was much like that produced by saline substitution. The average half-life value was 12.7 min and the average number of injections was 11.6 (Fig. 5). These values were significantly different from those for cocaine in the absence of antibody administration [ANOVA, F(2, 12) 27.1, P < 0.001 Tukey post hoc test, P < 0.001]. The half-life of the mouse monoclonal in rat was <24 hr by ELISA 12 [data not shown] and the ability of the antibody to prevent the reinforcing effects of cocaine was correspondingly short lasting all animals recovered normal cocaine-like patterns of behavior by 48 hr after the test with mAb 15A10.

Pattern of intravenous cocaine (A), saline (B), or cocaine + mAb 15A10 (C) self-administration in a single rat. Each vertical line within the panels indicates a single injection, obtained on a fixed ratio 5 time-out 10 sec schedule of cocaine delivery. The three panels show infusion patterns from three consecutive sessions.

Comparison of the number of injections and response half-live (time required for 50% of the total injections to be taken) for responding maintained by cocaine, saline, or cocaine after administration of mAb 15A10. An asterisk indicates a significant difference from cocaine (P < 0.001 Tukey post hoc test).

Because a saline-like pattern of behavior may have been generated if mAb 15A10 simply disrupted behavior in general, its effect was tested in four rats that were maintained on sweetened condensed milk reinforcement. This milk produced a very regular pattern of responding. As expected, administration of mAb 15A10 did not alter this pattern (Fig. 6A) or the number of milk reinforcers earned.

Comparison of the response half-lives for milk reinforcer and milk reinforcer after administration of mAb 15A10 (A) and for responding maintained by bupropion, saline, or bupropion after administration of mAb 15A10 (B). ANOVA indicated a significant difference [F(2, 9) 70.28, P < 0.00001]. An asterisk indicates a significant difference from saline (P < 0.0001 Tukey post hoc test).

The possibility remained that the action of mAb 15A10 was due to a nonspecific effect on the dopaminergic reward pathway. To test this possibility, we evaluated the ability of 9–12 mg mAb 15A10 to modify self-administration of the dopamine reuptake inhibitor bupropion. This stimulant maintained a pattern of responding that was much like that maintained by cocaine, and substitution of saline led to a rapid change in patterns of responding. In contrast, administration of mAb 15A10 did not alter the pattern (Fig. 6B) or amount of bupropion self-administered by the rats.

In summary, the catalytic antibody was extremely selective in blocking behavior maintained by cocaine. Because catalytic antibodies act outside the central nervous system, this approach to cocaine pharmacotherapy will not be complicated by the cocaine-like side effects expected with agonist-based treatments, or the neuroleptic side effects as might be expected with a dopamine antagonist-based treatment of cocaine abuse.

Example 29: Activity of Anti-TIGIT Antagonistic Antibody on γδ T Cells

γδ (gamma-delta, or g/d)T cells are a population of unconventional T cells with described antitumor activity (Zhao et al. 2018. J Transl Med. 16:122) and antiviral activity (e.g. CMV infection) and also have been implicated in autoimmune diseases (Malik S et al. 2016. Front Immunol. 7:14).

Flow cytometry analyses were performed to assess the expression of TIGIT on 78 T cells on PBMC freshly isolated from healthy individuals with a seronegative or seropositive status for Cytomegalovirus (CMV) (CMV status was assessed by the EFS Nouvelle Aquitaine, Bordeaux, France). Cells were stained per manufacturer's instruction using filtered FACS buffer (PBS+2 mM EDTA+0.1% BSA). Acquisition was performed on a FACS Fortessa (BD Biosciences) and analyzed with BD FACS DIVA software (BD Biosciences). Cells were gated on Forward and Side scatter and viability. □□T cells were gated as follows: CD3+ TCR□□D+V□2− (V□2− □□T cells) using the following antibodies: anti-TCR□□APC, clone REA591 #130-109-280 from Miltenyi anti-TCR V□2-PE-Vio 770, clone REA771, #130-111-012 from Miltenyi BV421 mouse anti-human CD3, clone UCHT1, #560365 from BD Biosciences Zombie Aqua Fixable viable kit, #423101 from Biolegend.

Similar to conventional αβ T cells, non-conventional Vδ2− γδ T cells express TIGIT in both CMV negative and positive human populations (anti-TIGIT, clone MBSA43, #12-98500-42 from eBioscience) (FIG. 34A). To characterize the functional consequence of blocking TIGIT receptor on this cell population, magnetically isolated Vδ1+γδ T cells (anti-TCR Vd1-FITC, clone REA173 #130-100-532 and anti-FITC Microbeads #130-048-701 both from Miltenyi) or total PBMC from CMV positive donors were activated with anti-V□1 (10 ug/ml) (clone R9.1, #IM1761 from Beckman Coulter) and IL-15 (20 ng/ml), #200-15-50UG from Peprotech), IL-2 (100 U/ml, #200-02-1MG Peprotech) was additionally added to isolated VD 1+□□□QT cells, in presence or absence of TIGIT-ligand CD155 (#9174-CD-050 from R&D Systems). FIG. 34B shows a dose-dependent decrease in IFNγ secretion (ELISA kit, #3420-1 h-20 from Mabtech) mediated by the addition of TIGIT-ligand CD155 (0, 0.1, 1 and 10 ug/ml) with a maximal inhibition reached at 1 ug/ml of CD155. The addition of anti-TIGIT Ab clone 31282 (10 ug/ml) fully restores IFNγ production to level equal or higher to the condition without CD155 ligand while human IgG1 isotype control has very limited effect. FIG. 34C demonstrates similar inhibitory effect mediated by CD155 (101 μg/ml) after anti-Vδ1 activation of total PBMC and a total restoration of IFNγ secretion when a-TIGIT clone 31282 is added to the mix. These data demonstrate that, similar to αβ T cells, activity of γδ T cells can be impaired by ligation of CD155 to TIGIT and that anti-TIGIT antibodies fully prevent this inhibition.