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  5. Targeting the ribosome to treat multiple myeloma

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Preprint
en
2023

Targeting the ribosome to treat multiple myeloma

0 Datasets

0 Files

en
2023
DOI: 10.21203/rs.3.rs-3582717/v1

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Elaine Sanij
Elaine Sanij

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Kylee Maclachlan
Kezia Gitareja
Jian Kang
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Abstract

<title>Abstract</title> The high rates of protein synthesis and processing render multiple myeloma (MM) cells vulnerable to perturbations in protein homeostasis. The induction of proteotoxic stress by targeting protein degradation with proteasome inhibitors (PI) has revolutionized the treatment of MM. However, resistance to PI is inevitable and represents an ongoing clinical challenge. Our first-in-human study of the selective inhibitor of RNA polymerase I transcription of ribosomal RNA genes, CX-5461 has demonstrated a potential signal for anti-tumor activity in three of six heavily pre-treated MM patients. Here we show that CX-5461 has potent antimyeloma activity in PI-resistant MM preclinical models in vitro and in vivo. In addition to inhibiting ribosome biogenesis, CX-5461 causes topoisomerase II trapping and replication-dependent DNA damage, leading to G2/M cell cycle arrest and apoptotic cell death. Surprisingly, the addition of PI does not enhance the therapeutic benefit of CX-5461. In contrast, CX-5461 shows synergistic interaction with the histone deacetylase inhibitor panobinostat in both the Vk*MYC and the 5T33-KaLwRij mouse models of MM by targeting ribosome biogenesis and protein synthesis through distinct mechanisms. Our findings thus provide strong evidence to facilitate the clinical development of targeting the ribosome to treat relapsed and refractory MM.

How to cite this publication

Kylee Maclachlan, Kezia Gitareja, Jian Kang, Andrew Cuddihy, Yuxi Cao, Nadine Hein, Carleen Cullinane, Ching‐Seng Ang, Natalie Brajanovski, Richard B. Pearson, Amit Khot, Elaine Sanij, Ross D. Hannan, Gretchen Poortinga, Simon J. Harrison (2023). Targeting the ribosome to treat multiple myeloma. , DOI: https://doi.org/10.21203/rs.3.rs-3582717/v1.

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Publication Details

Type

Preprint

Year

2023

Authors

15

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.21203/rs.3.rs-3582717/v1

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