Modulating AntibodyâDrug Conjugate Payload Metabolism by

Subscriber access provided by Karolinska Institutet, University Library

Article

Modulating ADC payload metabolism by conjugation site and linker modification Dian Su, Katherine Kozak, Jack Sadowsky, Shang-Fan Yu, Aimee Fourie-O’Donohue, Christopher Nelson, Richard Vandlen, Rachana Ohri, Luna Liu, Carl Ng, Jintang He, Helen Davis, Jeff Lau, Geoffrey Del Rosario, Ely Cosino, Josefa dela Cruz-Chuh, Yong Ma, Donglu Zhang, Martine Darwish, Wenwen Cai, Chunjiao Chen, Hongxiang Zhou, Jiawei Lu, Yichin Liu, Surinder Kaur, Keyang Xu, and Thomas Pillow Bioconjugate Chem., Just Accepted Manuscript • DOI: 10.1021/acs.bioconjchem.7b00785 • Publication Date (Web): 26 Feb 2018 Downloaded from http://pubs.acs.org on February 27, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Bioconjugate Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Bioconjugate Chemistry

Modulating ADC payload metabolism by conjugation site and linker modification Dian Su1*#, Katherine R. Kozak1#, Jack Sadowsky1, Shang-Fan Yu1, Aimee Fourie-O’Donohue1, Christopher Nelson1, Richard Vandlen1, Rachana Ohri1, Luna Liu1, Carl Ng1, Jintang He1, Helen Davis1, Jeff Lau1, Geoffrey Del Rosario1, Ely Cosino1, Josefa dela Cruz-Chuh1, Yong Ma1, Donglu Zhang1, Martine Darwish1, Wenwen Cai2, Chunjiao Chen2, Hongxiang Zhou2, Jiawei Lu2, Yichin Liu1, Surinder Kaur1, Keyang Xu1 and Thomas H. Pillow1 1 2

Genentech, Inc., 1 DNA Way, South San Francisco, California 94080, United States Wuxi Biologics, 288 Fute Zhong Road, Waigaoqiao Free Trade Zone, Shanghai 200131, China

#

Co-first authors *Corresponding Author: Email: [email protected]. Phone: +1 650-467-6442. Fax: +1 650-467-3487.

Abstract Previous investigations on antibody-drug conjugate (ADC) stability have focused on drug release by linker-deconjugation on ADC stability due to the relatively stable payloads such as maytansines. Recent development of ADCs has been focused on exploring technologies to produce homogenous ADCs and new classes of payloads to expand the mechanisms of action of the delivered drugs. Certain new ADC payloads could undergo metabolism in circulation while attached to antibodies and thus affect ADC stability, pharmacokinetics and, efficacy and toxicity profiles. Herein, we investigate payload stability specifically and seek general guidelines to address payload metabolism and therefore increase the overall ADC stability. Investigation was performed on various payloads with different functionalities (e.g. PNU-159682, tubulysin, cryptophycin, and taxoid) using different conjugation sites (HC-A118C, LC-K149C and HC-A140C) on THIOMABTM antibodies. We were able to reduce metabolism and inactivation of a broad range of payloads of THIOMABTM antibody-drug conjugates by employing optimal conjugation sites (LC-K149C and HC-A140C). Additionally, further payload stability was achieved by optimizing the linkers. Coupling relatively stable sites with optimized linkers provided optimal stability and reduction of payloads metabolism in circulation in vivo.

1 ACS Paragon Plus Environment

Bioconjugate Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Introduction Antibody-drug conjugates (ADCs) are designed to specifically deliver cytotoxic drugs to cancer cells and therefore improve the associated therapeutic index.1-4 Recent efforts have focused on site-specific conjugation and produced homogeneous ADCs, such as THIOMABTM antibody drug conjugates (TDCs).5-7 Both Adcetris®8 and Kadcyla®9 use tubulin-binders as cytotoxic payloads. The recently approved ADCs Besponsa® and Mylotarg® utilize calicheamicin,10-12 a DNA damaging agent, as the cytotoxic payload. Next generation ADCs employ additional tubulin-binders such as tubulysin 13, 14 and other DNA damaging reagents, such as, pyrrolobenzodiazepine (PBD) dimers,15-21 anthracyclines,22-24 and cyclopropabenzindolone (CBI) dimers25 as well as new linker chemistries, which should diversify the platform and provide new treatment opportunities.26, 27 An ideal ADC would remain intact in circulation prior to internalization and efficiently release its cytoxic payload in the target cell for maximum efficacy and minimum toxicity. However, biotransformations including undesirable drug release or inactivation via deconjugation and/or payload metabolism can occur while the ADC is in circulation and therefore may compromise ADC efficacy and safety (Figure 1).28, 29 Deconjugation via chemical decoupling of the covalent linker and enzymatic cleavage of the linker are common mechanisms of drug release in plasma.30-34 In addition, biotransformations such as adduct formation between the unconjugated drug and the free thiols in cysteine (Cys), glutathione (GSH) and albumin, cytotoxic drug or payload metabolism, or generation of peptide fragments or linker-drug fragments can also lead to increased complexity of total ADCs in circulation.30, 35, 36 In particular, enzymatic metabolism (e.g., ester- and amidebond hydrolysis) can occur with certain payloads in circulation and thus affect ADC PK, efficacy and toxicity profiles. In contrast to deconjugation, which always leads to deactivation or loss of payload, payload metabolism could result in either active or inactive payloads. Historically, the drug-antibody-ratio (DAR) was defined to monitor the payloads retained on the antibody, which were usually metabolically stable. The term, aDAR, referring to active DAR, is thereby defined specifically for active payloads (intact or metabolized) attached to antibodies to differentiate them from the inactive payloads 2 ACS Paragon Plus Environment

Page 2 of 29

Page 3 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


that result from metabolism (Figure 1). The values of aDAR and DAR are the same when there is no payload deactivation following metabolism. However, aDAR is reduced relative to DAR when the payload is deactivated due to payload metabolism. For example, ester hydrolysis was observed with a thailanstatin ADC37 and a tubulysin ADC (Figure 2).38 The labile acetate was not required for the activity of thailanstatin and the ester hydrolysis therefore did not cause loss of ADC potency. However, acetate cleavage in tubulysin38 and amide hydrolysis in monomethyl auristatin D (MMAD)39 of sitespecific conjugates resulted in a significant loss of potency. Deactiviting metabolism of the macrocycle was also observed in cryptophycin C52 (LY355703)-ADC in mice in circulation via amide and ester hydrolysis (Figure 2).40, 41 Payload metabolism of these cryptophycin conjugates was found to be species-dependent and observed in mice but not in non-rodent species.

Figure 1. Possible ADC/TDC biotransformations due to linker deconjugation and payload metabolism in circulation in vivo. Deconjugation (pathway 1) leads to deactivation/loss of the payload and possible formation of antibody-Cys/GSH adduct. Payload metabolism (pathway 2) results in either active (in red) or inactive (in black) payload corresponding to different changes to aDAR. The payload portion cleaved from the ADC/TDC due to metabolism is in blue.



Figure 2. Examples of payload metabolism. The payload portion cleaved from the ADC/TDC due to metabolism is in blue and the portion retained on the ADC is in red (active) or black (inactive).

Previously, we demonstrated that conjugation site modulates linker deconjugation properties and thus the in vivo stability and efficacy of ADCs.30 Our results indicated that the electrostatic and/or steric environment of the conjugation site can influence ADC PK and efficacy by modulating the stability of the antibody-linker connection. Others also demonstrated that site of conjugation modulates the linker stability and thus the PK profiles of ADCs.42 Recently, we found that another major contributor to linker deconjugation is the pKa of the cysteine residues at selected sites.43 In contrast, there have been fewer in-depth investigations done on payload metabolism and its relationship to ADC performance. In one recent example, Tumey et al. recently demonstrated that sites of conjugation could also modulate the payload metabolism of tubulysin-containing ADCs.38 To pursue general guidance for modulating payload metabolism, we explored a broad range of ADC payloads and established approaches to modulating payload metabolism in addition to linker decongjugation to improve the overall stability of ADCs.

Like linker deconjugation, payload metabolism could be modulated by multiple parameters such as chemical and structural environment and species impact. However, we speculated that among various possibilities solvent accessibility or steric hindrance could play a critical role in regulating payload metabolism. These parameters in turn could be impacted by the selection of each component of the ADC: antibody, linker and payload. Our interest was to utilize antibody steric shielding to modulate the metabolism 4 ACS Paragon Plus Environment

Page 4 of 29

Page 5 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


of a broad range of payloads by employing different conjugation sites and maleimide and disulfide linkers of varying structures. The investigations were conducted using TDCs containing various payloads with different functionalities (e.g. PNU-159682, tubulysin, cryptophycin, and others) and metabolic liabilities (Figure 2). We evaluated conjugation sites including HC-A118C, LC-K149C and HC-A140C (according to EU numbering), which were selected through our high-throughput screening efforts that identified relatively stable sites.44 We also investigated linkers with different lengths using both disulfide and maleimide conjugation to find an alternative or complementary strategy to address payload metabolism. Payload stability of these conjugates was evaluated via whole blood in vitro assessments and was confirmed in plasma in vivo for the selected conjugates by affinity capture LC-MS.45-47 The described conjugation site and linker modification can be used independently or simultaneously in the case of more labile payloads. Below we describe the outcomes of these explorations.

Results & Discussion To compare the TDC biotransformations across conjugates with different conjugation sites and linkers, the normalized percentage of aDAR (active drug-to-antibody ratio) was calculated relative to the starting material. Metabolism products were assigned based on mass changes relative to the starting TDC DAR2 species. As described above, the aDAR parameters can be impacted by either deconjugation or payload metabolism. In the cases where deconjugation was much slower than payload metabolism events, the aDAR change/reduction is expected to be mainly influenced by biotransformation due to metabolism. Modulating payload metabolism by site of conjugation. A PNU-159682 analog payload was conjugated to sites HC-A118C and LC-K149C of anti-HER2 THIOMABTM antibody via a non-cleavable maleimide linker (Figure 3A). In vitro stability was tested in whole blood from different species. After a 24 h incubation in vitro (Figure 3B), the deactivating payload metabolism (deglycosidation), indicated by the percentage of the conjugate that was converted to the deglycosylated form, was 5 ACS Paragon Plus Environment


observed at 17% for cyno and 6% for mouse for HC-A118C conjugates and 7% and 6% for LC-K149C conjugates, respectively. Deglycosidation was not significantly different between the two sites after 24 h in vitro (Figure 3B) or in vivo (Figure 3C) likely due to the relative slower metabolism rate compared to some other case studies included in this work. The in vivo stability and antitumor activity of these two conjugates was tested in a HER2+ Fo5 mammary tumor transplant mouse model. At day 4 post-dose in mice (Figure 3C), significant deconjugation was observed with the HC-A118C conjugate but not the LC-K149C conjugate indicating that conjugation to the LC-K149C site protected the linker from deconjugation. In addition, payload metabolism i.e., deglycosidation,48 was observed to a lesser degree in the LC-K149C conjugates indicating the PNU-159682 analog was better protected by this site. Deglycosidation resulted in the loss of sugar moiety containing the reactive site (- 243 Da), leading to the loss of activity of the payload. Therefore, the aDAR values of TDC species with sugar loss (-Gly) were reduced accordingly relative to unmetabolized conjugates. As a result, the average aDAR was reduced from 1.9 to 1.3 for the HC-A118C conjugate and from 1.9 to 1.8 for the LCK149C TDC after 4 days in mice due to the stability differences mentioned above. These changes were due to a combination of both sugar loss and deconjugation for the HCA118C conjugate, but only payload metabolism for the LC-K149C entity (Figure 3C). Thus, an overall improvement in stability was achieved by reducing both deconjugation and payload metabolism in the LC-K149C conjugate, resulting in 95% of the unmetabolized conjugated PNU-159682 analog being retained at day 7 post-dose compared to about 70% retained in the HC-A118C conjugate (Figure 3D). Consistent with the in vivo stability results, the more stable K149C conjugate was also more efficacious when dosed at 1 mg/kg in a HER2 allograft tumor model relative to the A118 TDC (Figure 3E).


Page 6 of 29

Page 7 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 3. In vitro and vivo stability and efficacy results of NMS-048 TDCs with the payload PNU-159682 analog conjugated to antiHER2 THIOMABTM antibody via a maleimide linker at sites HC-A118C and LC-K149C, respectively. (A) Representative structure of NMS-048 TDCs or PNU-159682 analog conjugates. The payload portion cleaved from the TDC due to metabolism is in blue and the portion retained on the TDC is in black. The linker (in green) length was estimated using the molecule operation environment (MOE) software. (B) Bar graphs of percentage of payload metabolism after 24 h incubation in cynomolgus monkey and mouse whole blood in vitro. (C) MS spectra on day 4 and (D) aDAR change profile of the in vivo TDC stability. TDC biotransformations due to decongjuation and payload metabolism, i.e. deglycosidation resulting in loss of the sugar moiety (-Gly), were identified by MS (A-C). MS peaks labeled with * represent the glycated TDC species of the corresponding (color coded) aDAR value.49, 50 (E) Efficacy profile of TDCs at 1 mg/kg (25 ug/m2 drug dose) in nu/nu mice bearing HER2+ Fo5 mammary tumors.

Site LC-K149C provides good protection of maleimide-based linkers from deconjugation and certain payload metabolism such as deglycosidation of PNU-159682 analog (Figure 3). However, not every linker-drug examined had improved metabolic stability when conjugated to the LC-K149C site. When cryptophycin was conjugated to site LC-K149C 7 ACS Paragon Plus Environment


on THIOMABTM antibodies via the cleavable maleimidocaproyl-valine-citrulline-paminobenzoyloxycarbonyl (MC-vc-PAB) linker, the payload was not well protected from metabolism in mouse. Amide hydrolysis resulting from the addition of water was followed by cleavage of portion A due to further hydrolysis (Figure 4A and B). Such payload metabolism was not observed in cynomolgus monkey (Figure 4B) likely due to absence/low-abundance of the hydrolase. As observed in a mouse stability study in vitro (Figure 4B), the cryptophycin LC-K149C conjugate displayed significant metabolic instability that was similar to the behavior of the corresponding HC-A118C conjugate. After 24 h incubation in vitro more than 40% of the payload present in both conjugates experienced significant metabolic degradation. We therefore explored whether alternative sites would afford enhanced protection of the payload from enzymatic metabolism compared to the LC-K149C location. Site HC-A140C was subsequently discovered to provide better protection of MC-vc-PAB-cryptophycin from metabolism in mouse compared to sites HC-A118C and LC-K149C in vitro (Figure 4B). The results were confirmed by in vivo stability studies (Figure 4C). In particular, hydrolysis of the payload attached to the HC-A140C site at day 1 in mice was significantly slower that that observed for the HC-A118C conjugate (Figure 4D). Interestingly, by day 1 post-dose in mice only the relatively more susceptible payload present in the DAR2 HC-A140C conjugate underwent significant metabolism and the resulting conjugate retained an aDAR value of 0.9 (Figure 4C). In contrast, both payloads present in the corresponding HC-A118C DAR2 conjugate experienced significant metabolism by day 1 in mice, resulting in an aDAR value of 0 at that time point. The improved stability of the HCA140C conjugate resulted in increased efficacy (Figure 4E).


Page 8 of 29

Page 9 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4. In vitro and in vivo stability and efficacy results of cryptophycin TDCs with the payload conjugated to anti-CD22 THIOMABTM antibody via the MC-vc-PAB linker at sites HC-A118C and HC-A140C, respectively. (A) Representative structure of cryptophycin TDCs and proposed payload metabolic pathways. The payload portion cleaved from the TDC due to metabolism is in blue and the portion retained on the TDC is in black. The linker (in green) length was estimated using the MOE software. (B) Bar graphs of percentage of payload metabolism after 24 h incubation in cynomolgus monkey and mouse whole blood in the in vitro stability study. (C) MS spectra on day 1 and (D) aDAR change profile of the in vivo TDC stability in SCID mice overtime. MS peaks labeled with * represent the glycated TDC species of the corresponding (color coded) aDAR value49, 50 (E) Efficacy profile of TDCs at 3 mg/kg (67-77 ug/m2 drug dose) in SCID mice bearing BJAB-luc human Burkitt’s lymphoma. Tumor-bearing animals were randomized into groups of n=8 with an average tumor size of 223 mm3 and administered a single IV dose (day 0) of vehicle or antiCD22 TDCs at 3 mg/kg (66-77 ug/m2 drug dose). Mean tumor volumes (±SEM) are plotted over time (days post dose).



For subsequent experiments, we focused on comparing TDCs generated using two distinct conjugation sites HC-A140C and LC-K149C. The ability to generate stable linkages (e.g. minimal deconjugation) on these two sites allowed us to examine how different sites of conjugation influence payload metabolism and thus efficacy profiles. Our further investigation with a variety of linker-drugs suggested that HC-A140C provides better protection from payload metabolism than LC-K149C for the same linkerdrug. For example, as was observed for cryptophycin above, when tubulysin was conjugated to THIOMABTM antibodies via the MC-vc-PAB linker (Figure 5A), the payload underwent slower metabolism/hydrolysis on the HC-A140C site than LC-K149C both in vitro (Figure 5B) and in vivo (Figure 5C) in mice with no significant hydrolysis observed in cynomolgus monkey (Figure 5B). The observed deacetylation due to ester hydrolysis resulted in loss of activity of the payload.38 Therefore, aDARs of the corresponding deacetylated TDC species were reduced accordingly. As illustrated in the figure, the aDAR changes were mainly due to the payload metabolism (Figure 5C). At day 1 post-dose in mice, the aDAR value dropped from 1.9 to 0.6 on LC-K149C and from 1.9 to 1.4 on HC-A140C, respectively (Figure 5C). In particular, at the earlier time point on day 1, payload metabolism (e.g., deacetylation), was only observed with the more susceptible payload in the HC-A140C TDC while both payloads were susceptible to metabolism in the LC-K149C TDC. As expected, the superior stability of the HCA140C tubulysin TDC (Figure 5D) translated into better efficacy in mouse xenograft experiments relative to the LC-K149C conjugate (Figure 5E). Similarly, when conjugated via the MC-vc-PAB linker using a potentially labile carbonate moiety, a taxoid derivative (Figure S1A) underwent slower payload release on the HC-A140C site relative to LCK149C in whole blood in vitro (Figure S1B). In mice, the LC-K149C taxoid conjugate was susceptible to rapid and complete drug release by day 1 (aDAR=0) due to carbonate hydrolysis in the linker (Figure S1C). Conjugation to site HC-A140C resulted in significantly reduced carbonate hydrolysis by day 1 (aDAR=1.6, Figure S1C and S1D). The HC-A140C location thus provides better protection from payload metabolism than LC-K149C for both tubulysin and taxoid TDCs that employ with the MC-vc-PAB linker. 10 ACS Paragon Plus Environment

Page 10 of 29

Page 11 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


TM

Figure 5. In vitro and vivo stability and efficacy results of tubulysin TDCs with the payload conjugated to anti-CD22 THIOMAB antibody via the MC-vc-PAB linker at sites LC-K149C and HC-A140C, respectively. (A) Structure of tubulysin TDCs. The payload portion cleaved from the TDC due to metabolism is in blue and the portion retained on the TDC is in black. The linker (in green) length was estimated using the MOE software. (B) Bar graphs of percentage of payload metabolism after 24 h incubation in cynomolgus monkey and mouse whole blood in vitro. (C) MS spectra on day 1 and (D) aDAR change profile of the in vivo TDC stability in SCID mice overtime. MS peaks labeled with * represent the glycated TDC species of the corresponding (color coded) aDAR value.49, 50 (E) Efficacy profile of TDCs at 1 mg/kg (28-29 ug/m2 drug dose) in SCID mice bearing BJAB-luc human Burkitt’s lymphoma..

Taken together, our results suggested that the general ranking of metabolic protection at various sites is: HC-A140C > LC-K149C > HC-A118C. When mapped using the crystal structure of the humanized anti-HER2 Fab fragment 4D5 (pdb: 1FVD) HC-A118 is located on the antibody surface with minimal steric hindrance while LC-K149 and HCA140 are more deeply buried in the mAb structure (Figure 6A). Moreover, site HC-A118 11 ACS Paragon Plus Environment


is located on an unstructured loop, whereas LC-K149 and HC-A140 are located in more structured β-sheets (Figure 6B). The fractional solvent accessibility (FSA) values could be used to estimate the accessibility of solvent to the amino acid residue in a given polypeptide. An FSA value close to zero is indicative of a residue that is predicted to be inaccessible to solvent.5 The FSA values for the HC-A118, LC-K149 and HC-A140 mAb residues were calculated using the available crystal structure information (pdb: 1FVC, 1FVD and 1FVE)51 by the SOLV module of XSAE (personal communication from C. Broger, F. Hoffman-LaRoche, Basel) and are expressed as percentages (33.0, 15.5 and 8.9, respectively).5 The results suggested that HC-A140 was the least solvent accessible. The solvent accessibility data and 3D-antibody structure suggested that HC-A140C is the least solvent accessible, followed by LC-K149C and then HC-A118C. These data help explain the observed ranking of linker-drug metabolic protection by the conjugation site (HC-A140C >LC-K149C > HC-A118C). They also extend our previously published determinations regarding the impact of conjugation site on ADC/TDC stability and efficacy.30

Figure 6. Visualization of conjugation sites HC-A118 (red), LC-K149 (blue), and HC-A140 (green) mapped to the crystal structure of humanized anti-HER2 Fab fragment 4D5 (pdb: 1FVD).51 The surface (A) and cartoon (B) formats of the antibody depict solvent accessibility and structure of the three sites, respectively.

Modulating payload metabolism by linker modification.


Page 12 of 29

Page 13 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


As described above, both cryptophycin and tubulysin were susceptible to hydrolysis at day 1 post-dose in mice when conjugated to the less solvent-accessible LC-K149C and HC-A140C sites via the MC-vc-PAB linker (Figures 4 and 5). However, the PNU159682 analog was well protected from deglycosidation at day 1 post-dose by site LCK149C when conjugated to a THIOMABTM antibody via a shorter maleimide linker (Figure 3). We speculated that this difference in payload metabolism was at least partially due to the different linker lengths associated with the various conjugates. To explore this possibility, we investigated a broader range of conjugates in which PNU-159682 (analog) was connected to the antibodies at site LC-K149C using various linkers with different linker length, mAb connection chemistry (maleimide or disulfide) and steric hindrance (Figure 7A). A higher percentage of payload metabolism was observed for conjugates with 16Å linkers than those with 6-8Å linkers in cynomolgus monkey (Figure 7B) and mouse (Figure 7C) whole blood. The data suggested that linker length may play a role in regulating payload metabolism. Interestingly, the in vitro stability differences across the different linkers were observed to be less dramatic in mouse relative to monkey (Figure 7A and 7B). The observed species-dependent deglycosidation is likely due to the different levels of metabolic enzymes in mouse versus in monkey, leading to the different impact of species on different compounds. Overall, linker-dependent deglycosidation was observed in mouse and monkey.



Figure 7. In vitro stability results of PNU-159682 (analog) conjugates with different linkers (A) assessed by affinity capture LC-MS after incubation 24 h in cynomolgus monkey (B) or mouse (C) whole blood. Linker-drug NMS-048 was connected to anti-HER2 THIOMABTM antibody. Linker-drug NMS-829 was connected to anti-CLL1 THIOMABTM antibody. The other linker-drugs were connected to anti-CD22 THIOMABTM antibody. The linker (in green) lengths were estimated using the MOE software.

We therefore explored the potential of using short linkers to address payload metabolism of labile linker-drugs that could not be fully protected by the optimal conjugation sites. Tubulysin and cryptophycin were conjugated to sites LC-K149C and HC-A140C, respectively, via a shorter mono-methyl pyridyl disulfide (mm-PDS) linker (Figure 8A and S2). As shown in Figure S2B, conjugates prepared using the shorter linker displayed improved metabolic stability in mouse whole blood relative to those constructed from the longer moieties. Minimal deconjugation was observed with tubulysin TDCs at day 1 post-dose in vivo and aDAR reduction mainly resulted from payload metabolism (e.g., deacetylation) (Figure 8B). As expected based on the in vitro results, better protection of payload by the shorter mm-PDS linker was observed in vivo for both the LC-K149C and HC-A140C sites compared to the longer MC-vc-PAB linker. The shorter mm-PDS linker 14 ACS Paragon Plus Environment

Page 14 of 29

Page 15 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


improved the average aDAR from 0.6 to 1.1 at site LC-K149C and from 1.4 to 1.8 at site HC-A140C with the starting aDARs of 1.9, respectively, at day 1 post-dose (Figure 8B). Similar linker-derived stability improvements were observed for cryptophycin conjugates that employed the mm-PDS linker with the payload conjugated to anti-CD22 THIOMABTM antibody at sites LC-K149C and HC-140C, respectively (Figure S2). The shorter linker resulted in better payload stability and enabled determination of a stepwise hydrolysis mechanism of cryptophycin (Figure S2A). First, amide hydrolysis occurred at location 1 (addition of water), followed by ester hydrolysis at location 2 (loss of portion B) and then another ester hydrolysis at location 3 (loss of portion C). The final payload metabolite resulted from the addition of water and loss of portion A. Slower payload metabolism was observed for the disulfide-containing conjugates in stability studies both in vitro (Figure S2B) and in vivo (Figure S2C). In particular, at day 1 post-dose in mice, the shorter mm-PDS linker improved the aDAR of cryptophycin TDCs relative to MCvc-PAB conjugates from 0.3 to 0.8 at site LC-K149C and from 0.9 to 1.8 at site HCA140C, respectively.

TM

Figure 8. In vivo stability results of tubulysin TDCs with the payload conjugated to anti-CD22 THIOMAB antibody at sites LCK149C and HC-A140C, respectively, via a longer MC-vc-PAB linker (left) and a shorter mm-PDS linker (right). (A) Structures of tubulysin TDCs. The payload portion cleaved from the TDC due to metabolism is in blue and the portion retained on the TDC is in black. The linker (in green) lengths were estimated using the MOE software. (B) MS spectra of TDCs on day 1 of the in vivo stability. MS peaks labeled with * represent the glycated TDC species of the corresponding (color coded) aDAR value.49, 50 The linker lengths were estimated with the distances from the thiol of antibody to amine of drug using the molecule operation environment (MOE) software. In vivo stability was assessed in the SCID mice dosed intravenously with 5 mg/kg (151-155 ug/m2 drug dose) of anti-CD22



TDCs. At the indicated time points, blood was drawn for determination of the average aDAR normalized to day 0 using the affinity capture LC-MS F(ab')2 assay.

Our proof-of-concept stability testing, both in vitro and in vivo, suggested that payload metabolism is indeed modulated by the linker in addition to the site of attachment. Therefore, selection of an optimal linker, such as a shorter linker, could be used as an alternative or complementary approach to site modulation to address payload metabolism and thus improve payload stability. Coupling the conjugation site and linker modification for optimal ADC payload stability. Analysis of our collective data revealed that the favorable impact of site, e.g. the improvement in payload metabolism by using a less solvent-accessible mAb attachment location, appeared to be more pronounced (e.g., larger increase in % average aDAR change) for conjugates that employed a short linker (Figure 9A). In turn, the impact of linker, e.g., the improvement in payload metabolism by the shorter mm-PDS linker, appeared to be more pronounced (e.g., larger increase in % average aDAR change) with a less solvent-accessible site (Figure 9B). ADC stability is maximized upon the combination of a less solvent-accessible site and a shorter linker, e.g., the hydrolysis of tubulysin and cryptopycin was not observed at day 1 post-dose when the payloads were conjugated to the least solvent-accessible site HC-A140C via a short mm-PDS linker (Figures 8 and S2).


Page 16 of 29

Page 17 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 9. Impact of site (A) and linker (B) payload protection. Exemplary stability results of tubulysin TDC variants (conjugates shown in Figure 8) were plotted in groups of MC-vc-PAB vs. mm-PDS linkers (A) and LC-K149C vs. HC-A140C sites (B) to determine the site- and linker-impact ), respectively. In vivo stability was assessed in the SCID mice dosed intravenously with 5 mg/kg (151-155 ug/m2 drug dose) of anti-CD22 TDC site variants with the mm-PDS linker and 1 mg/kg (28-29 ug/m2 drug dose) of antiCD22 TDC site variants with the MC-vc-PAB linker. At the indicated time points, blood was drawn for determination of the average aDAR normalized to day 0 using the affinity capture LC-MS F(ab')2 assay.

Payload metabolism was hypothesized to depend on not only site but also linker, which influences the associated structural environment and thereby the solvent accessibility. To test the hypotheses, we conducted serial comparative experiments on TDCs with different sites, linkers and payloads. For maximal throughput and efficiency, in vitro whole blood stability was performed to predict and guide the stability assessment of TDCs in animals. In summary, the primary protection of payloads from undesired (inactivating) metabolism was provided by the steric shield around the conjugation site in the local structure of the antibody. For example, when a payload is in close proximity to a more sterically hindered or less solvent-accessible Ab attachment site, it can be more sterically shielded or less accessible to solvent and enzymes (Figure 10). Secondary protection of payloads from metabolism is achieved by using optimized linkers. For example, a shorter linker may position the payload further inside the steric shield associated with a given conjugation site and thereby can afford improved protection (Figure 10).



Figure 10. Hypothetic model to illustrate regulation of ADC payload metabolism by conjugation site and linker modification.

Conclusion We previously hypothesized that solvent accessibility and steric hindrance, due to structural environment, plays a critical role in modulating ADC stability.30 Herein, we show that payload metabolism, also influenced by the structural environment, is modulated by the steric shield from the antibody, which acts as a carrier as well as a protector of the payload in circulation in vivo. The steric hindrance of the antibody in proximity modulates the solvent accessibility of payloads and protects or shields the payload from metabolism. The steric shield from the antibody that protects payloads can be modulated by both conjugation site and linker. The combination of a sterically hindered site and an optimized linker such as a short linker could provide optimum protection of the payload from metabolism. We first demonstrated the impact of conjugation site on ADC deconjugation in 2012.30 Pfizer recently showed that payload metabolism such as deacetylation in tubulysin38 and amide hydrolysis in MMAD39 was also impacted by conjugation sites. Herein we explored generic strategies of using conjugation site and/or linker to modulate payload metabolism, which were supported by proof-of concept testing on a variety of TDCs. The investigated TDCs consist of different conjugation sites and linker-drugs with different 18 ACS Paragon Plus Environment

Page 18 of 29

Page 19 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


types of linker chemistry (maleimide and disulfide linkage) and payload functionality (PNU-159682, cryptophycin, tubulysin and others). To our knowledge, this is the first time it has been demonstrated that ADC payload metabolism can be modulated by coupling conjugation site and linker modification for a variety of payloads with different functionalities. There are multiple factors that could impact payload metabolism such as steric shield, electrostatic environment and species-specific metabolic enzymes. Taking advantage of the steric shield from the antibody, we have identified a novel conjugation site HC-A140C to protect payload from metabolism in addition to the previously reported LC-K149C site that protected linker attachment.33, 43, 52 In addition, we have demonstrated that payload metabolism could also be modulated by linker optimization (e.g., shorter length). Experimental Procedures Materials. Lithium heparin treated whole blood was purchased from BioreclamationIVT (New York, USA). Streptavidin-coated Dynabeads M-280 were purchased from Invitrogen (CA, USA). IdeS, FabRICATOR®, was purchased from Genovis, Inc. (Cambridge, MA). Other reagents included HBS-EP buffer containing 0.01 M HEPES, pH 7.4, 0.15 M NaCl, 3 mM EDTA, 0.005% Polysorbate 20 (GE Healthcare; Little Chalfont, UK) and the peptide N-glycosidase F (PNGase F) (New England Biolabs (MA, USA) ). All TDCs and specific ADC capture reagents, e.g., extracellular domain (ECD), were produced at Genentech (South San Francisco, CA, USA). Briefly, ECD was biotinylated with a 10 (HER2) or 4 (CD22) molar equivalent of Sulfo-NHS-LC-biotin (Pierce/Thermo Fisher Scientific, Rockford, IL, USA) to ECD for 60 min at room temperature in 10 mM sodium phosphate/150 mM NaCl, pH 7.8. Excess unbound biotin was removed using ZebaTM spin desalting column (Pierce/Thermo Fisher Scientific), as per the manufacturer’s protocol. Biotinylated ECD concentration was determined spectrophotometrically by measuring the absorbance at 280 nm using GeneQuantTM 1300 (GE Healthcare). Preparation of linker-drugs. 19 ACS Paragon Plus Environment


The PNU-159682 (analog) linker-drugs were prepared as described previously.53-55 Preparation of ADCs. THIOMAB™ antibodies were prepared for conjugation as previously described. Conjugation was then performed with activated nitro-pyridyl disulfide analogs of linkerdrugs or maleimides as previously described.52, 54, 55 In vitro stability assessment. In vitro stability assessment was conducted by utilizing a whole blood (WB) assay where conjugates were incubated in mouse (CB17 SCID), rat (Sprague-Dawley), cynomolgus monkey and human whole blood as well as buffer. Briefly, whole blood was collected by BioreclamationIVT (NY), shipped cold overnight and used in the WB assay upon arrival. Conjugates were prediluted to 1mg/mL in buffer (1X PBS, 0.5% BSA, 15PPM Proclin), followed by a 10-fold dilution with blood or buffer (100 µg/mL final concentration). Once mixed, two aliquots were generated and incubated for either 0 or 24 hours at 37⁰C while shaking and stored frozen at -80⁰C until analysis. In vivo efficacy and stability studies. All animal studies were carried out in compliance with National Institutes of Health guidelines for the care and use of laboratory animals and were approved by the Institutional Animal Care and Use Committee at Genentech, Inc. The efficacy of the anti-HER2 TDCs was investigated in a mouse allograft model of MMTV-HER2 Founder #5 murine mammary tumor. The MMTV-HER2 Founder #5 (Fo5) model (developed at Genentech) is a transgenic mouse model in which the human HER2 gene, under transcriptional regulation of the murine mammary tumor virus promoter (MMTV-HER2), is overexpressed in mammary epithelium which leads to spontaneous development of mammary tumors. To set up the model, the Fo5 transgenic mammary tumor was surgically transplanted into the thoracic mammary fat pads of female nu/nu mice (Charles River Laboratories) as tumor fragments of approximately 2mm x 2mm in size. 20 ACS Paragon Plus Environment

Page 20 of 29

Page 21 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


The efficacy of anti-CD22 TDCs was evaluated in a mouse xenograft model of BJAB-luc human Burkitt’s lymphoma. The BJAB-luc cell line was obtained from Genentech cell line repository. Cells were maintained in RPMI 1640 supplemented with 10% FBS (Sigma) and 1% L-glutamine. This cell line was authenticated by short tandem repeat (STR) profiling using the Promega PowerPlex 16 System and compared with external STR profiles of cell lines to determine cell line ancestry. To set up the model, tumor cells (20 million cells in 0.2mL Hank’s Balanced Salt Solution; Hyclone) were inoculated subcutaneously into the flanks of female CB17 SCID mice (Charles Rivers Laboratories). For all efficacy studies, when mean tumor size reached the desired volume (150-250 mm3), animals were divided into groups of n=8 with similar mean tumor size and received a single intravenous injection of antibody drug conjugates through the tail vein. Tumors were measured in two dimensions (length and width) using calipers and the tumor volume was calculated using the formula: Tumor size (mm3) = 0.5 x (length x width x width). The results were plotted as mean tumor volume ± SEM of each group over time. Blood samples were collected via retro-orbital bleeds from animals (n=1-2/ time point) at 1, 3 or 4, and 7 days post dose for in vivo TDC stability assessments. All blood samples were collected into tubes containing lithium heparin and were allowed to sit on wet ice until centrifugation (within 15 minutes of collection). Samples were centrifuged at 10,000 rpm for 5 minutes at 4⁰C. Plasma was then collected, placed on dry ice, and stored in a freezer set at -70⁰C until analysis. Affinity capture LC-MS intact antibody and F(ab')2 assays for in vitro and vivo stability assessment. ADC biotransformation characterization and stability assessment were conducted by affinity capture LC-MS intact antibody or F(ab')2 assay depending on the need of MS resolution for confident structural elucidation as previously described.45, 47 In brief, 100 µL of streptavidin paramagnetic beads was added to a 96-deep well plate containing an excess of biotinylated specific capture reagents, e.g., extracellular domain (ECD), in HBS-EP buffer and incubated with agitation at room temperature (RT) for 1 h. TDCcontaining whole blood or plasma samples were then added (a maximum of 2 µg or 250 21 ACS Paragon Plus Environment


(µL, whichever is smaller) to the above ECD-immobilized beads after washes, and incubated with agitation at RT for 1.5 h. A KingFisher 96 magnetic particle processor (Thermo Electron) was used to mix, wash, gather, and transfer the paramagnetic beads for all the affinity capture steps through elution. For the in vitro stability assessment of non-tubulysin containing TDCs, affinity captured TDCs were washed and deglycosylated in HBS-EP buffer using peptide N-glycosidase F (PNGase F) (New England Biolabs) at 37⁰C overnight.47 After extensive washing of the beads with HBS-EP, water and 10% acetonitrile, the ADC analytes were eluted using 50 µL of 30% acetonitrile with 0.1%formic acid. For the following LC-MS analysis, 10 µL of eluted TDC samples were injected and loaded onto a Thermo Scientific PepSwift RP monolithic column (500 µm × 5 cm) maintained at 65 ⁰C. The TDC was separated on the column using a Waters NanoAcquity UPLC system at a flow rate of 20 µL/min with the following gradient: 20% B (95% acetonitrile + 0.1% formic acid) at 0-2 min; 35% B at 2.5 min; 65% B at 5 min; 95% B at 5.5 min; 5% B at 6 min. The column was directly coupled for online detection with a Waters Synapt G2-S Q-ToF mass spectrometer (Synapt-G2S, Waters, Milford, MA) operated in positive ESI mode with an acquisition range from m/z 500 to 5000. Deconvolution of the raw mass spectra within a selected TDC chromatographic elution time window was implemented with Waters BiopharmaLynx 1.3.3 software. Peak labeling was performed with a custom Vortex script (Dotmatics, Bishops Stortford, United Kingdom). TDC metabolites were identified according to the corresponding mass shifts from the starting TDC material. Relative ratios of individual TDC species were obtained based on their peak intensity in the deconvoluted mass spectra. In vitro stability assessment of tubulysin (Figure 5B) was performed by the affinity capture LC-MS F(ab')2 assay (described below) to obtain higher MS resolution for confident identification of peaks due to payload metabolismdeacetylation.45 For the in vivo stability assessment that required higher MS resolution, captured TDCs were digested by addition of IdeS (FabRICATOR, 40 units) in HBS-EP buffer at 37⁰C for 1 h.45 PNU-159682 (analog) containing TDCs,were deglycosylated using PNGase F to obtain intact analytes (~150 kDa), which required lower MS resolution due to the 22 ACS Paragon Plus Environment

Page 22 of 29

Page 23 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


relatively larger mass changes resulting from deglycosidation.47 After extensive washing of the beads with HBS-EP, water and 10% acetonitrile, the resulted F(ab')2 fragments (~ 100 kDa)with the same linker-drugs were eluted using 50 µL of 30% acetonitrile in water with 1% formic acid. An aliquot of 5 µL of F(ab')2 elution was subjected to LC-MS analysis. Capillary LC-MS was performed on a TripleTOF 5600 mass spectrometer coupled to a Waters nanoACQUITY UPLC system. Online desalting and preconcentration were conducted on a PS-DVB monolithic column (500-µm i.d. × 50 mm, Thermo Fisher Scientific, Waltham, MA) at 65°C using a 15-min gradient with mobile phases A, 0.1% formic acid and B, acetonitrile with 0.1% FA at a flow rate of 15 µL/min. Mass spectra were acquired in the intact protein mode, using Analyst® TF 1.6. Deconvolution was performed with BioAnalystTM 1.5.1. Relative ratios of individual TDC species were obtained based on their peak areas in the deconvoluted mass spectra. For in vivo stability studies, aDAR, which represents the active drug-antibody ratio following possible payload metabolism, was estimated as below and plotted over time to establish the stability profile in vivo. Average aDAR=Σ (%peak area × number of conjugated active payloads/metabolites)/100 ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: Additional experimental details and spectroscopic data as noted in the text (PDF)

AUTHOR INFORMATION Corresponding Author * E-mail: [email protected]. Phone: +1 650-467-6442. Fax: +1 650-467-3487.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors would like to thank Rebecca Rowntree, Genee Lee, Binqing Wei and Douglas Leipold for their help in the work. We thank Peter Dragovich, Susan Spencer, Hans Erickson, An Song, Patty Siguenza, Cyrus Khojasteh-Bakht and Cornelis Hop for their support. We also thank Peter Dragovich, Hans Erickson, Ben-Quan Shen and Amrita Kamath for their helpful discussion on the manuscript. ABBREVIATIONS



ADC

antibody–drug conjugate

TDC

THIOMABTM antibody–drug conjugate

Cys

cysteine

GSH

glutathione

aDAR

active drug-to-antibody ratio

HC

heavy chain

LC

light chain

MC-vc-PAB maleimidocaproyl-valine-citrulline-p-aminobenzoyloxycarbonyl mm-PDS

mono-methyl pyridyl disulfide

REFERENCES

(1) (2)

(3) (4) (5)

(6)

(7) (8)

(9)

(10)

Strebhardt, K., and Ullrich, A. (2008) Paul Ehrlich's magic bullet concept: 100 years of progress. Nat. Rev. Cancer 8, 473-480. Shen, W.-C. (2015) Antibody-Drug Conjugates: A Historical Review. Antibody-Drug Conjugates: The 21st Century Magic Bullets for Cancer (Wang, J., Shen, W.-C., Zaro, J. L. Eds.) pp 3–7, Chapter 1, Springer, New York. Peters, C., and Brown, S. (2015) Antibody–drug conjugates as novel anticancer chemotherapeutics. Biosci. Rep. 35, e00225. Polakis, P. (2016) Antibody Drug Conjugates for Cancer Therapy. Pharmacol. Rev. 68, 3-19. Junutula, J. R., Bhakta, S., Raab, H., Ervin, K. E., Eigenbrot, C., Vandlen, R., Scheller, R. H., and Lowman, H. B. (2008) Rapid identification of reactive cysteine residues for site-specific labeling of antibody-Fabs. J. Immunol. Methods 332, 41-52. Junutula, J. R., Raab, H., Clark, S., Bhakta, S., Leipold, D. D., Weir, S., Chen, Y., Simpson, M., Tsai, S. P., Dennis, M. S., et al. (2008) Site-specific conjugation of a cytotoxic drug to an antibody improves the therapeutic index. Nat. Biotechnol. 26, 925-932. Bhakta, S., Erickson,H., Junutula, J. R., Kozak, K. R., Ohri, R., Pillow, T. H. (2016) WO 2016040856 A2. Senter, P. D., and Sievers, E. L. (2012) The discovery and development of brentuximab vedotin for use in relapsed Hodgkin lymphoma and systemic anaplastic large cell lymphoma. Nat. Biotechnol. 30, 631-637. Lambert, J. M., and Chari, R. V. (2014) Ado-trastuzumab Emtansine (T-DM1): an antibody-drug conjugate (ADC) for HER2-positive breast cancer. J. Med. Chem. 57, 6949-664. Ricart, A. D. (2011) Antibody-drug conjugates of calicheamicin derivative: gemtuzumab ozogamicin and inotuzumab ozogamicin. Clin. Cancer Res. 17, 6417-6427.


Page 24 of 29

Page 25 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(11)

(12) (13)

(14)

(15) (16)

(17)

(18)

(19)

(20)

(21)

(22)

Shor, B., Gerber, H. P., and Sapra, P. (2015) Preclinical and clinical development of inotuzumab-ozogamicin in hematological malignancies. Mol. Immunol. 67, 107-116. Godwin, C. D., Gale, R. P., and Walter, R. B. (2017) Gemtuzumab ozogamicin in acute myeloid leukemia. Leukemia 31, 1855-1868. Cohen, R., Vugts, D. J., Visser, G. W., Stigter-van Walsum, M., Bolijn, M., Spiga, M., Lazzari, P., Shankar, S., Sani, M., Zanda, M., et al. (2014) Development of novel ADCs: conjugation of tubulysin analogues to trastuzumab monitored by dual radiolabeling. Cancer Res. 74, 5700-5710. Leverett, C. A., Sukuru, S. C., Vetelino, B. C., Musto, S., Parris, K., Pandit, J., Loganzo, F., Varghese, A. H., Bai, G., Liu, B., et al. (2016) Design, Synthesis, and Cytotoxic Evaluation of Novel Tubulysin Analogues as ADC Payloads. ACS Med. Chem. Lett. 7, 999-1004. Hartley, J. A. (2011) The development of pyrrolobenzodiazepines as antitumour agents. Expert Opin. Investig. Drugs 20, 733-744. Jeffrey, S. C., Burke, P. J., Lyon, R. P., Meyer, D. W., Sussman, D., Anderson, M., Hunter, J. H., Leiske, C. I., Miyamoto, J. B., Nicholas, N.D., et al. (2013) A potent anti-CD70 antibody-drug conjugate combining a dimeric pyrrolobenzodiazepine drug with site-specific conjugation technology. Bioconjugate Chem. 24, 1256-1263. Kung Sutherland, M.S., Walter, R.B., Jeffrey, S.C., Burke, P.J., Yu, C., Kostner, H., Stone, I., Ryan, M.C., Sussman, D., Lyon, R.P., et al. (2013) SGN-CD33A: a novel CD33-targeting antibody-drug conjugate using a pyrrolobenzodiazepine dimer is active in models of drug-resistant AML. Blood 122, 1455-63. Flynn, M. J., Zammarchi, F., Tyrer, P. C., Akarca, A. U., Janghra, N., Britten, C. E., Havenith, C. E., Levy, J. N., Tiberghien, A., Masterson, L. A., Barry, C., et al. (2016) ADCT-301, a Pyrrolobenzodiazepine (PBD) Dimer-Containing Antibody-Drug Conjugate (ADC) Targeting CD25-Expressing Hematological Malignancies. Mol. Cancer Ther. 15, 2709-2721. Zhang, D., Yu, S. F., Ma, Y., Xu, K., Dragovich, P. S., Pillow, T. H., Liu, L., Del Rosario, G., He, J., Pei, Z., et al. (2016) Chemical Structure and Concentration of Intratumor Catabolites Determine Efficacy of Antibody Drug Conjugates. Drug Metab. Dispos. 44, 1517-1523. Mantaj, J., Jackson, P. J., Rahman, K. M., and Thurston, D. E. (2017) From Anthramycin to Pyrrolobenzodiazepine (PBD)-Containing Antibody-Drug Conjugates (ADCs). Angew. Chem. Int. Ed. Engl. 56, 462-488. Pillow, T. H., Schutten, M., Yu, S. F., Ohri, R., Sadowsky, J., Poon, K. A., Solis, W., Zhong, F., Del Rosario, G., Go, M. A. T., et al. (2017) Modulating Therapeutic Activity and Toxicity of Pyrrolobenzodiazepine Antibody-Drug Conjugates with Self-Immolative Disulfide Linkers. Mol. Cancer Ther. 16, 871-878. Junttila, M. R., Mao, W., Wang, X., Wang, B. E., Pham, T., Flygare, J., Yu, S. F., Yee, S., Goldenberg, D., Fields, C., et al. (2015) Targeting LGR5+ cells with an antibody-drug conjugate for the treatment of colon cancer. Sci. Transl. Med. 7, 314ra186. 25 ACS Paragon Plus Environment


(23)

(24)

(25)

(26) (27)

(28)

(29) (30)

(31)

(32)

(33)

(34)

(35)

Minotti, G., Menna, P., Salvatorelli, E., Cairo, G., and Gianni, L. (2004) Anthracyclines: molecular advances and pharmacologic developments in antitumor activity and cardiotoxicity. Pharmacol. Rev. 56, 185-229. Yu, S. F., Zheng, B., Go, M., Lau, J., Spencer, S., Raab, H., Soriano, R., Jhunjhunwala, S., Cohen, R., Caruso, M., et al. (2015) A Novel Anti-CD22 Anthracycline-Based Antibody-Drug Conjugate (ADC) That Overcomes Resistance to Auristatin-Based ADCs. Clin. Cancer. Res. 21, 3298-3306. Flygare, J. A., Pillow, T. H., Safina, B., Verma, V., Wei, B., Denny, W., Giddens, A., Lee, H., Lu, G.-L., Miller, C., Rewcastle, G., Tercel, M., Bonnet, M. (2015) WO 2015023355 A1. Flygare, J. A., Pillow, T. H., and Aristoff, P. (2013) Antibody-drug conjugates for the treatment of cancer. Chem. Biol. Drug Des. 81, 113-121. Perez, H. L., Cardarelli, P. M., Deshpande, S., Gangwar, S., Schroeder, G. M., Vite, G. D., and Borzilleri, R. M. (2014) Antibody-drug conjugates: current status and future directions. Drug Discov. Today 19, 869-881. Kaur, S., Xu, K., Saad, O. M., Dere, R. C., and Carrasco-Triguero, M. (2013) Bioanalytical assay strategies for the development of antibody-drug conjugate biotherapeutics. Bioanalysis 5, 201-226. Tumey, L. N., Rago, B., and Han, X. (2015) In vivo biotransformations of antibody-drug conjugates. Bioanalysis 7, 1649-1664. Shen, B. Q., Xu, K., Liu, L., Raab, H., Bhakta, S., Kenrick, M., Parsons-Reponte, K. L., Tien, J., Yu, S. F., Mai, E., Li, D., et al. (2012) Conjugation site modulates the in vivo stability and therapeutic activity of antibody-drug conjugates. Nat. Biotechnol. 30, 184-189. Hengel, S. M., Sanderson, R., Valliere-Douglass, J., Nicholas, N., Leiske, C., and Alley, S. C. (2014) Measurement of in vivo drug load distribution of cysteinelinked antibody-drug conjugates using microscale liquid chromatography mass spectrometry. Anal. Chem. 86, 3420-3425. Kellogg, B. A., Garrett, L., Kovtun, Y., Lai, K. C., Leece, B., Miller, M., Payne, G., Steeves, R., Whiteman, K. R., Widdison, W., et al. (2011) Disulfide-linked antibody-maytansinoid conjugates: optimization of in vivo activity by varying the steric hindrance at carbon atoms adjacent to the disulfide linkage. Bioconjugate Chem. 22, 717-727. Pillow, T. H., Sadowsky, J. D., Zhang, D., Yu, S. F., Del Rosario, G., Xu, K., He, J., Bhakta, S., Ohri, R., Kozak, K. R., et al. (2017) Decoupling stability and release in disulfide bonds with antibody-small molecule conjugates. Chem. Sci. 8, 366-370. Zhang, D., Pillow, T. H., Ma, Y., Cruz-Chuh, J. D., Kozak, K. R., Sadowsky, J. D., Lewis Phillips, G. D., Guo, J., Darwish, M., Fan, P., et al. (2016) Linker Immolation Determines Cell Killing Activity of Disulfide-Linked Pyrrolobenzodiazepine Antibody-Drug Conjugates. ACS Med. Chem. Lett. 7, 988-993. Alley, S. C., Benjamin, D. R., Jeffrey, S. C., Okeley, N. M., Meyer, D. L., Sanderson, R. J., and Senter, P. D. (2008) Contribution of linker stability to the activities of anticancer immunoconjugates. Bioconjugate Chem. 19, 759-765. 26 ACS Paragon Plus Environment

Page 26 of 29

Page 27 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(36)

(37)

(38)

(39)

(40) (41)

(42)

(43)

(44)

(45)

(46) (47)

Jackson, D., Atkinson, J., Guevara, C. I., Zhang, C., Kery, V., Moon, S. J., Virata, C., Yang, P., Lowe, C., Pinkstaff, J., et al. (2014) In vitro and in vivo evaluation of cysteine and site specific conjugated herceptin antibody-drug conjugates. PLoS One 9, e83865. Puthenveetil, S., Loganzo, F., He, H., Dirico, K., Green, M., Teske, J., Musto, S., Clark, T., Rago, B., Koehn, F., et al. (2016) Natural Product Splicing Inhibitors: A New Class of Antibody-Drug Conjugate (ADC) Payloads. Bioconjugate Chem. 27, 1880-1888. Tumey, L. N., Leverett, C. A., Vetelino, B., Li, F., Rago, B., Han, X., Loganzo, F., Musto, S., Bai, G., Sukuru, S. C., et al. (2016) Optimization of Tubulysin Antibody−Drug Conjugates: A Case Study in Addressing ADC Metabolism. ACS Med. Chem. Lett. 7 (11), 977−982. Dorywalska, M., Strop, P., Melton-Witt, J. A., Hasa-Moreno, A., Farias, S. E., Galindo Casas, M., Delaria, K., Lui, V., Poulsen, K., Sutton, J., Bolton, G., et al. (2015) Site-Dependent Degradation of a Non-Cleavable Auristatin-Based Linker-Payload in Rodent Plasma and Its Effect on ADC Efficacy. PLoS One 10, e0132282. Bouchard, H. (2016) 7th World ADC, San Diego. Brun, M.-P., Bouchard, H., Clerc, F., Zhang, J., Abecassis, P.-Y., Amara, C., Beys, E., Efremenko, F., Nicolazzi, C., Pascual, M.-H., et al. (2016) Abstract LB-053: Towards new cryptophycins as promising payloads for ADC. Cancer Res. 76, LB-053-LB-053. Strop, P., Liu, S. H., Dorywalska, M., Delaria, K., Dushin, R. G., Tran, T. T., Ho, W. H., Farias, S., Casas, M. G., Abdiche, Y., et al. (2013) Location matters: site of conjugation modulates stability and pharmacokinetics of antibody drug conjugates. Chem. Biol. 20, 161-167. Vollmar, B. S., Wei, B., Ohri, R., Zhou, J., He, J., Yu, S. F., Leipold, D., Cosino, E., Yee, S., Fourie-O'Donohue, A., et al. (2017) Attachment Site Cysteine Thiol pKa Is a Key Driver for Site-Dependent Stability of THIOMAB Antibody-Drug Conjugates. Bioconjugate Chem. 28, 2538-2548. Ohri, R., Bhakta, S., Fourie-O’Donohue, A., dela Cruz-Chuh, J., Tsai, S. P., Cook, R., Wei, B., Ng, C., Wong, A. W., Bos, A. B., et al. (2018) High-Throughput Cysteine Scanning To Identify Stable Antibody Conjugation Sites for Maleimide- and Disulfide-Based Linkers. Bioconjugate Chem. 29, 473-485 Su, D., Ng, C., Khosraviani, M., Yu, S. F., Cosino, E., Kaur, S., and Xu, K. (2016) Custom-Designed Affinity Capture LC-MS F(ab')2 Assay for Biotransformation Assessment of Site-Specific Antibody Drug Conjugates. Anal. Chem. 88, 11340-11346. Kaur, S., Saad, O., and Xu, K. (2013) US8541178. Xu, K., Liu, L., Saad, O. M., Baudys, J., Williams, L., Leipold, D., Shen, B., Raab, H., Junutula, J. R., Kim, A., et al. (2011) Characterization of intact antibody-drug conjugates from plasma/serum in vivo by affinity capture capillary liquid chromatography-mass spectrometry. Anal. Biochem. 412, 56-66.



(48)

(49)

(50)

(51)

(52)

(53) (54)

(55)

Edwardson, D. W., Narendrula, R., Chewchuk, S., Mispel-Beyer, K., Mapletoft, J. P., and Parissenti, A. M. (2015) Role of Drug Metabolism in the Cytotoxicity and Clinical Efficacy of Anthracyclines. Curr. Drug Metab. 16, 412-426. Miller, A. K., Hambly, D. M., Kerwin, B. A., Treuheit, M. J., and Gadgil, H. S. (2011) Characterization of site-specific glycation during process development of a human therapeutic monoclonal antibody. J. Pharm. Sci. 100, 2543-2550. Quan, C., Alcala, E., Petkovska, I., Matthews, D., Canova-Davis, E., Taticek, R., and Ma, S. (2008) A study in glycation of a therapeutic recombinant humanized monoclonal antibody: where it is, how it got there, and how it affects charge-based behavior. Anal. Biochem. 373, 179-191. Eigenbrot, C., Randal, M., Presta, L., Carter, P., and Kossiakoff, A. A. (1993) Xray structures of the antigen-binding domains from three variants of humanized anti-p185HER2 antibody 4D5 and comparison with molecular modeling. J. Mol. Biol. 229, 969-995. Sadowsky, J. D., Pillow, T. H., Chen, J., Fan, F., He, C., Wang, Y., Yan, G., Yao, H., Xu, Z., Martin, S., et al. (2017) Development of Efficient Chemistry to Generate Site-Specific Disulfide-Linked Protein- and Peptide-Payload Conjugates: Application to THIOMAB Antibody-Drug Conjugates. Bioconjugate Chem. 28, 2086-2098. Beria, I., Caruso, M., Flygare, J. A., Lupi, V., Perego, R., Polakis, P., Polson, A., Salsa, M., Spencer, S. D., and Valsasina, B. (2014) US14528142. Staben, L. R., Koenig, S. G., Lehar, S. M., Vandlen, R., Zhang, D., Chuh, J., Yu, S. F., Ng, C., Guo, J., Liu, Y., Fourie-O'Donohue, A., et al. (2016) Targeted drug delivery through the traceless release of tertiary and heteroaryl amines from antibody-drug conjugates. Nat. Chem. 8, 1112-1119. Verma, V. A., Pillow, T. H., DePalatis, L., Li, G., Phillips, G. L., Polson, A. G., Raab, H. E., Spencer, S., and Zheng, B. (2015) The cryptophycins as potent payloads for antibody drug conjugates. Bioorg. Med. Chem. Lett. 25, 864-868.


Page 28 of 29

Page 29 of 29 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table of Contents Graphic


Modulating AntibodyâDrug Conjugate Payload Metabolism by

Recommend Documents

Modulating AntibodyâDrug Conjugate Payload Metabolism by