Hypoxia-activated prodrug derivatives of anti-cancer drugs: a patent review 2006 – 2021

ABSTRACT

Introduction

The hypoxic tumor microenvironment represents a persistent obstacle in the treatment of most solid tumors. In the past years, significant efforts have been made to improve the efficacy of anti-cancer drugs. Therefore, hypoxia-activated prodrugs (HAPs) of chemotherapeutic compounds have attracted widespread interest as a therapeutic means to treat hypoxic tumors.

Areas covered

This updated review paper covers key patents published between 2006 and 2021 on the developments of HAP derivatives of anti-cancer compounds.

Expert opinion

Despite significant achievements in the development of HAP derivatives of anti-cancer compounds and although many clinical trials have been performed or are ongoing both as monotherapies and as part of combination therapies, there has currently no HAP anti-cancer agent been commercialized into the market. Unsuccessful clinical translation is partly due to the lack of patient stratification based on reliable biomarkers that are predictive of a positive response to hypoxia-targeted therapy.

KEYWORDS:

• Hypoxia
• tumor
• anti-cancer compounds
• hypoxia-activated prodrug
• bioreductive prodrug

Article highlights

• Hypoxia is a common feature of most solid tumors and has been associated with poor patient outcome and aggressive metastatic phenotypes

• Hypoxia-activated prodrugs (HAPs) of chemotherapeutic agents are based on the selective release of toxic species upon reduction by reductases under hypoxia.

• HAPs with tumor targeting properties have a better safety profile and antitumor activity.

• Failure of HAPs in clinical trials is due to the lack of reliable biomarkers that are predictive of the hypoxia-status of the tumor.

• In line with a personalized medicine approach, hypoxia-based biomarkers for patient selection are needed for translation from bench to bedside.

Declaration of interest

P Lambin reports, within the submitted work, minority shares in the company Convert pharmaceuticals and three non-issues, non-licensed patents on Deep Learning-Radiomics and LSRT (N2024482, N2024889, N2024889). L Dubois reports within the submitted work, minority shares in the company Convert Pharmaceuticals and a non-issued, non-licensed patent on LSRT (N2024889). P Lambin and L Dubois confirm that the above entities was not involved in the preparation of this paper. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was financially supported by the ERC advanced grant HYPOXIMMUMO (ERC-ADG-2015, n° 694812) and by the French-Dutch Hubert Curien Partnership (PHC Van Gogh 42528YH)