Rational combinations of targeted cancer therapies: background, advances and challenges
Abstract
Over the past two decades, elucidation of the genetic defects that underlie cancer has resulted in a plethora of novel targeted cancer drugs. Although these agents can initially be highly effective, resistance to single-agent therapies remains a major challenge. Combining drugs can help avoid resistance, but the number of possible drug combinations vastly exceeds what can be tested clinically, both financially and in terms of patient availability. Rational drug combinations based on a deep understanding of the underlying molecular mechanisms associated with therapy resistance are potentially powerful in the treatment of cancer. Here, we discuss the mechanisms of resistance to targeted therapies and how effective drug combinations can be identified to combat resistance. The challenges in clinically developing these combinations and future perspectives are considered.
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Combination therapies using two or more therapeutic agents can be superior to single-agent therapies in the treatment of cancers.
“Combination therapies using two or more therapeutic agents can be superior to single-agent therapies in the treatment of cancers (1–3).”
From Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models (2023) · cites this paper as [3]
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- Authors
- Jin, H., Wang, L., & Bernards, R.
- Affiliations
- Shanghai Jiao Tong University (CN)
- The Netherlands Cancer Institute (NL)
- Corresponding author
- Jin, Haojie
- Wang, Liqin
- Bernards, René
- Venue
- Nature Reviews Drug Discovery
- Published
- 2022-12-12
- Volume
- 22
- Issue
- 3
- Pages
- 213-234
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W4311247426
- Cited by
- 503
- References
- 70
- Citations by year
- 2026: 125 · 2025: 187 · 2024: 136 · 2023: 54 · 2022: 1
- FWCI
- 16.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Nature Reviews Drug Discovery (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pathology and Forensic Medicine › Cancer Mechanisms and Therapy
- Keywords
- targeted cancer therapy, combination therapy, drug resistance, resistance mechanisms, monotherapy, cancer genomics
- MeSH terms
- Antineoplastic Agents, Antineoplastic Combined Chemotherapy Protocols, Humans, Neoplasms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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