Expanding the repertoire of Antibody Drug Conjugate (ADC) targets with improved tumor selectivity and range of potent payloads through in-silico analysis
Umesh Kathad, Neha Biyani, Raniero L. Peru y Colón De Portugal, Jianli Zhou, Harry Kochat, Kishor Bhatia
Abstract
Antibody-Drug Conjugates (ADCs) have emerged as a promising class of targeted cancer therapeutics. Further refinements are essential to unlock their full potential, which is currently limited by a lack of validated targets and payloads. Essential aspects of developing effective ADCs involve the identification of surface antigens, ideally distinguishing target tumor cells from healthy types, uniformly expressed, accompanied by a high potency payload capable of selective targeting. In this study, we integrated transcriptomics, proteomics, immunohistochemistry and cell surface membrane datasets from Human Protein Atlas, Xenabrowser and Gene Expression Omnibus utilizing Lantern Pharma’s proprietary AI platform Response Algorithm for Drug positioning and Rescue (RADR®).
Introduction
Antibody-drug conjugates (ADCs) offer a promising approach towards targeted cancer treatments. The approval of 12 ADCs for treatment of hematological and solid tumors, along with more than 170 novel ADCs in clinical development, serves as compelling evidence of the growing acceptance of this therapeutic approach in treating cancers [1].
Materials and method
In this section, the data acquisition and processing steps are described in detail.
Identification of potential ADC target candidates
All protein coding genes (n = 20,090) were queried using the Human Protein Atlas (HPA) database version 22.0 with the goal to identify the membrane protein coding genes (n = 5543) as an initial filter (https://v22.proteinatlas.org/search/protein_class:Predicted+membrane+proteins). Subsequently, we utilized the HPA annotation to further narrow down the genes list.
Results
Identification of potential ADC target candidates
Derived from methods used by Razzaghdoust et al. [14] and delineated in the methods section, and in Fig 1, we initially identified 5543 membrane protein coding genes out of a total of 20,090 genes using HPA database version 22.0. For further analysis, 4875 genes based on evidence at protein level were retained. It is worth mentioning that the same gene, which has a membrane protein annotation, may also have the intracellular localization for it`s isoforms. This is seen for many clinically validated target antigens, such as CD276 and ERBB2, which carry two annotations-membrane protein and intracellular in the protein atlas database. Such antigens are retained in our approach. By relying on annotation used in the protein atlas database, we have exclusively filtered out proteins which lacked any membrane annotations for further evaluation.
Discussion
Through our thorough analysis, we pinpointed a set of 82 prioritized ADC targets and 290 target indication combinations for precise targeting of tumors. Among these, 22 ADC targets have already undergone evaluation in clinical trials or preclinical contexts, including ERBB2 and NECTIN4 demonstrating the validity of our approach. We have identified 60 additional novel targets that meet our filtering criteria and have not yet been investigated for ADC development. One of the novel targets identified by our approach is OSMR-receptor for Oncostatin M (OSMR), which exhibited overexpression across 10 cancer indications.
Acknowledgments
We would like to thank Dr. Norbert Sewald and Dr. Harald Kolmar for discussion and critical reading of the manuscript.
Citation: Kathad U, Biyani N, Peru y Colón De Portugal RL, Zhou J, Kochat H, Bhatia K (2024) Expanding the repertoire of Antibody Drug Conjugate (ADC) targets with improved tumor selectivity and range of potent payloads through in-silico analysis. PLoS ONE 19(8): e0308604.
https://doi.org/10.1371/journal.pone.0308604
Editor: Satish Rojekar, Icahn School of Medicine at Mount Sinai Department of Pharmacological Sciences, UNITED STATES OF AMERICA
Received: February 7, 2024; Accepted: July 28, 2024; Published: August 26, 2024
Copyright: © 2024 Kathad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The datasets generated and/or analyzed during the current study are available in the below public repositories and other files are provided in Supporting information files. 1) https://v22.proteinatlas.org/about/download 2) https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42519 3) https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443 4) https://discover.nci.nih.gov/cellminercdb/ 5) http://wlab.ethz.ch/surfaceome.
Funding: U.K., N.B., R.P., J.Z., H.K. and K.B. have been salaried employees of or consultants to the pharmaceutical company Lantern Pharma Inc. The research reported on in this manuscript was funded by Lantern Pharma Inc. Employees, consultants and contractors of Lantern Pharma Inc. were involved in writing this manuscript and in the design of the research and the collection, analysis, and interpretation of data reported on herein. The specific roles of these authors are articulated in the 'author contributions' section.
Competing interests: U.K., N.B., R.P., J.Z., H.K. and K.B. have been salaried employees of or consultants to the pharmaceutical company Lantern Pharma Inc. U.K., N.B., J.Z., R.P. and K.B. hold common stock and/or options to purchase common stock of Lantern Pharma Inc. U.K., N.B., K.B., J.Z., and H.K. are included as inventors on patent applications and/or patents owned by Lantern Pharma Inc. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products associated with this research to declare.
Abbreviations: ADC, Antibody Drug Conjugate; NCI, National Cancer Institute; RADR®, Response Algorithm for Drug positioning and Rescue; DTP, Developmental Therapeutics Program; IHC, Immunohistochemistry; HSC, Hematopoietic Stem Cells; MPP, Multipotent Progenitor Cells; GEO, Gene Expression Omnibus; TCGA, The Cancer Genome Atlas.
