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170 Identifying novel targets for antibody-drug conjugates in sarcomas using RNA sequencing
  1. Vladimir Kushnarev1,
  2. Aleksei E Shevkoplias1,
  3. Kirill Kryukov1,
  4. Alexander Bagaev1,
  5. Jochen K Lennerz1,
  6. Nikita Kotlov1,
  7. Gregory M Cote2,
  8. Sudha Yalamanchili3,
  9. Neeta Somaiah3,
  10. Dejka M Araujo3,
  11. Juliana Thomas3,
  12. Anthony P Conley3,
  13. Evan Rosenbaum4,
  14. Vinod Ravi3,
  15. Konstantin Chernyshov1 and
  16. Sant P Chawla5
  1. 1BostonGene, Corp., Waltham, MA, USA
  2. 2Massachusetts General Hospital, Boston, MA, USA
  3. 3The University of Texas MD Anderson Cancer Center, Houston, TX, USA
  4. 4Memorial Sloan Kettering Cancer Center, New York, NY, USA
  5. 5Sarcoma Oncology Center, Santa Monica, CA, USA
  • Journal for ImmunoTherapy of Cancer (JITC) preprint. The copyright holder for this preprint are the authors/funders, who have granted JITC permission to display the preprint. All rights reserved. No reuse allowed without permission.

Abstract

Background Antibody-drug conjugates (ADCs) targeting precise surface antigens are pivotal to advancing targeted cancer therapies. Here, we analyzed transcriptomic data from sarcoma samples to identify novel cell surface protein candidates for designing new and highly specific ADCs with potential minimal side effects.

Methods We processed 826 FFPE samples (soft tissue or bone tumors) by whole-exome and RNA sequencing as described previously.1 To study target expression in carcinomas and normal tissues, we utilized TCGA datasets and normal samples from the Adult GTEx project dataset,2 retrospectively. Information on 82 ADC targets and relevant clinical trials (until January 2024) was extracted from ClinicalTrials.gov.3 4 We employed the Mann-Whitney U-test (with false discovery rate correction) to compare ADC target expression in a given sarcoma diagnosis against all others, highlighting genes highly expressed (≥4 log2 transcripts per million (TPM)) in sarcomas but lowly expressed (<2 log2 TPM) in normal tissues. Additionally, we examined the expression profiles of tertiary lymphoid structure (TLS)- and immune checkpoint (IC)-associated genes as previously described.5

Results Heatmap of RNA expression in (figure 1) depicts 20 ADC targets currently prioritized for clinical trial investigation. Table 1 lists the top 10 potential ADC targets based on expression level. Table 2 lists potential ADC targets with low expression in normal tissues but high expression in certain sarcomas, along with highly expressed TLS- and IC-associated genes. Combined expression of ADC targets, TLS markers, IC molecules indicates complex immune landscapes among different sarcoma subtypes that may benefit from combination therapies involving ADCs. Interestingly, only 4 genes from both tables 1 and 2 overlap with the 20 prioritized targets in (figure 1). Therefore, the expression profiles we uncovered also unveil new potential ADC targets that warrant further investigation.

Conclusions This study uncovered the expression landscape of potential ADC targets in sarcomas, particularly those lowly expressed in normal tissues. Expression profiles of TLS and IC gene signatures combined with ADC target expression characterize the immune landscape of sarcomas and can guide the development of immunotherapy approaches. Existing ADC clinical trials preclude many of these genes, underscoring the need for new trials that investigate these candidates. Our findings support the advancement of precision oncology in sarcoma therapies that prioritize safety and efficacy to improve patient outcomes.

References

  1. Kotlov N, Shaposhnikov K, Tazearslan C, Chasse M, Baisangurov A, Podsvirova S, Fernandez D, Abdou M, Kaneunyenye L, Morgan K, et al. Procrustes is a machine-learning approach that removes cross-platform batch effects from clinical RNA sequencing data. Commun. Biol. 2024;7:1–14. https://doi.org/10.1038/s42003-024-06020-z.

  2. GTEx Portal https://gtexportal.org/home/.

  3. Home | ClinicalTrials.gov https://clinicaltrials.gov/.

  4. Fang J, Guo L, Zhang Y, Guo Q, Wang M, and Wang X. The target atlas for antibody-drug conjugates across solid cancers. Cancer Gene Ther. 2024;31:273–284. https://doi.org/10.1038/s41417-023-00701-3.

  5. Bagaev A, Kotlov N, Nomie K, Svekolkin V, Gafurov A, Isaeva O, Osokin N, Kozlov I, Frenkel F, Gancharova O, et al. Conserved pan-cancer microenvironment subtypes predict response to immunotherapy. Cancer Cell 2021;39:845-865.e7. https://doi.org/10.1016/j.ccell.2021.04.014.

Ethics Approval The use of clinical samples was conducted in accordance with the Declaration of Helsinki and has been granted exemption from ethics approval by the Biomedical Research Alliance of New York (BRANY) Institutional Review Board (BRANY study #22-12-938-853).

Abstract 170 Figure 1

RNA Expression Profiles (log2 TPM) of 20 ADC Targets Prioritized for Clinical Investigation, Based on ClinicalTrials.gov (total n = 82 targets)

Abstract 170 Table 1

Top 10 genes of potential ADC targets and where they are primarily overexpressed. Asterisks mark the genes that are prioritized for clinical investigation, based on ClinicalTrials.gov

Abstract 170 Table 2

Connection Between High expression of TLS markers, immune checkpoint molecules, and ADC Targets in Sarcoma Subtypes. Asterisks mark the genes that are prioritized for clinical investigation, based on ClinicalTrials.gov

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