Phenotype of TPBG Gene Replacement in the Mouse and Impact on the Pharmacokinetics of an Antibody–Drug Conjugate

The use of predictive preclinical models in drug discovery is critical for compound selection, optimization, preclinical to clinical translation, and strategic decision-making. Trophoblast glycoprotein (TPBG), also known as 5T4, is the therapeutic target of several anticancer agents currently in clinical development, largely due to its high expression in tumors and low expression in normal adult tissues. In this study, mice were engineered to express human TPBG under endogenous regulatory sequences by replacement of the murine Tpbg coding sequence. The gene replacement was considered functional since the hTPBG knockin (hTPBG-KI) mice did not exhibit clinical observations or histopathological phenotypes that are associated with Tpbg gene deletion, except in rare instances. The expression of hTPBG in certain epithelial cell types and in different microregions of the brain and spinal cord was consistent with previously reported phenotypes and expression patterns. In pharmacokinetic studies, the exposure of a clinical-stage anti-TPBG antibody–drug conjugate (ADC), A1mcMMAF, was lower in hTPBG-KI versus wild-type animals, which was evidence of target-related increased clearance in hTPBG-KI mice. Thus, the hTPBG-KI mice constitute an improved system for pharmacology studies with current and future TPBG-targeted therapies and can generate more precise pharmacokinetic and pharmacodynamic data. In general the strategy of employing gene replacement to improve pharmacokinetic assessments should be broadly applicable to the discovery and development of ADCs and other biotherapeutics

Preclinical Development of an anti-5T4 Antibody–Drug Conjugate: Pharmacokinetics in Mice, Rats, and NHP and Tumor/Tissue Distribution in Mice

The pharmacokinetics of an antibody (huA1)–drug (auristatin microtubule disrupting MMAF) conjugate, targeting 5T4-expressing cells, were characterized during the discovery and development phases in female nu/nu mice and cynomolgus monkeys after a single dose and in S-D rats and cynomolgus monkeys from multidose toxicity studies. Plasma/serum samples were analyzed using an ELISA-based method for antibody and conjugate (ADC) as well as for the released payload using an LC-MS/MS method. In addition, the distribution of the Ab, ADC, and released payload (cys-mcMMAF) was determined in a number of tissues (tumor, lung, liver, kidney, and heart) in two tumor mouse models (H1975 and MDA-MB-361-DYT2 models) using similar LBA and LC-MS/MS methods. Tissue distribution studies revealed preferential tumor distribution of cys-mcMMAF and its relative specificity to the 5T4 target containing tissue (tumor). Single dose studies suggests lower CL values at the higher doses in mice, although a linear relationship was seen in cynomolgus monkeys at doses from 0.3 to 10 mg/kg with no evidence of TMDD. Evaluation of DAR (drug–antibody ratio) in cynomolgus monkeys (at 3 mg/kg) indicated that at least half of the payload was still on the ADC 1 to 2 weeks after IV dosing. After multiple doses, the huA1 and conjugate data in rats and monkeys indicate that exposure (AUC) increases with increasing dose in a linear fashion. Systemic exposure (as assessed by <i>C</i>_max and AUC) of the released payload increased with increasing dose, although exposure was very low and its pharmacokinetics appeared to be formation rate limited. The incidence of ADA was generally low in rats and monkeys. We will discuss cross species comparison, relationships between the Ab, ADC, and released payload exposure after multiple dosing, and insights into the distribution of this ADC with a focus on experimental design as a way to address or bypass apparent obstacles and its integration into predictive models

Potency of hinge-cysteine thailanstatin trastuzumab ADC.

<p>(A) Structure of iodoacetamide derivatized non-cleavable thailanstatin linker-payloads (LPs). (B) <i>In vitro</i> cytotoxicity of hinge-cysteine thailanstatin trastuzumab ADCs against cancer cell lines expressing various levels of Her2, reported in half-maximal inhibitory concentration (IC₅₀) values of conjugated payload in nM. Data are the mean of multiple experiments. (C) <i>In vivo</i> efficacy of hinge-cysteine thailanstatin trastuzumab <b>ADC1</b> in an N87 gastric cancer xenograft model dosed at 3 mg/kg (q4d x 4). Arrows indicate the day(s) on which intravenous dosing was carried out. DAR = Drug Antibody Ratio; 361 = MDA-MB-361-DYT2; 468 = MDA-MB-468.</p

In vitro cytotoxicity of single-cysteine mutant thailanstatin trastuzumab ADCs against various levels of Her2 expressing cancer cell lines, reported in Mean IC₅₀ values of conjugated payload in nM.

<p>In vitro cytotoxicity of single-cysteine mutant thailanstatin trastuzumab ADCs against various levels of Her2 expressing cancer cell lines, reported in Mean IC₅₀ values of conjugated payload in nM.</p

Generation of site-specific multiple-payload carrying peptidic linker (MPP) ADC delivering MMAD.

<p>(A) Schematic showing generation of a double-MMAD carrying peptidic linker ADC generated on trastuzumab A114C. (B) <i>In vitro</i> cytotoxicity of peptidic linked MMAD trastuzumab A114C ADC against various levels of Her2 expressing cancer cell lines, reported in Mean IC₅₀ values of conjugated payload in nM. Data are the mean of multiple experiments. MAL = malemide; DBCO = Dibenzocyclooctyne.</p

Double-cysteine mutant thailanstatin trastuzumab ADCs.

<p>(A) <i>In vitro</i> cytotoxicity of double-cysteine mutant thailanstatin trastuzumab ADCs against various levels of Her2 expressing cancer cell lines, reported in Mean IC₅₀ values of conjugated payload in nM. Data are the mean of multiple experiments. (B) <i>In vivo</i> efficacy of double-cysteine mutant thailanstatin trastuzumab <b>ADC16</b> in N87 gastric cancer xenograft model dosed at 0.5, 1.56 and 3 mg/kg (q4d x 4). (C) <i>In vitro</i> cytotoxicity of double-cysteine mutant thailanstatin trastuzumab <b>ADC16</b> against T-DM1 resistant N87 (N87-TDM1) and 361 (361-TDM1) as well as MDR1 overexpressing N87 (N87-MDR1-CL3) cancer cell lines, reported in IC₅₀ values of conjugated payload in nM.</p

Natural Product Splicing Inhibitors: A New Class of Antibody–Drug Conjugate (ADC) Payloads

There is a considerable ongoing work to identify new cytotoxic payloads that are appropriate for antibody-based delivery, acting via mechanisms beyond DNA damage and microtubule disruption, highlighting their importance to the field of cancer therapeutics. New modes of action will allow a more diverse set of tumor types to be targeted and will allow for possible mechanisms to evade the drug resistance that will invariably develop to existing payloads. Spliceosome inhibitors are known to be potent antiproliferative agents capable of targeting both actively dividing and quiescent cells. A series of thailanstatin–antibody conjugates were prepared in order to evaluate their potential utility in the treatment of cancer. After exploring a variety of linkers, we found that the most potent antibody–drug conjugates (ADCs) were derived from direct conjugation of the carboxylic acid-containing payload to surface lysines of the antibody (a “linker-less” conjugate). Activity of these lysine conjugates was correlated to drug-loading, a feature not typically observed for other payload classes. The thailanstatin-conjugates were potent in high target expressing cells, including multidrug-resistant lines, and inactive in nontarget expressing cells. Moreover, these ADCs were shown to promote altered splicing products in N87 cells in vitro, consistent with their putative mechanism of action. In addition, the exposure of the ADCs was sufficient to result in excellent potency in a gastric cancer xenograft model at doses as low as 1.5 mg/kg that was superior to the clinically approved ADC T-DM1. The results presented herein therefore open the door to further exploring splicing inhibition as a potential new mode-of-action for novel ADCs