The DOI matches its Crossref record; 172 of the 172 references it cites were found in a registry or an index.
Combinatorial drug therapy for cancer in the post-genomic era
Abstract
Over the past decade, whole genome sequencing and other 'omics' technologies have defined pathogenic driver mutations to which tumor cells are addicted. Such addictions, synthetic lethalities and other tumor vulnerabilities have yielded novel targets for a new generation of cancer drugs to treat discrete, genetically defined patient subgroups. This personalized cancer medicine strategy could eventually replace the conventional one-size-fits-all cytotoxic chemotherapy approach. However, the extraordinary intratumor genetic heterogeneity in cancers revealed by deep sequencing explains why de novo and acquired resistance arise with molecularly targeted drugs and cytotoxic chemotherapy, limiting their utility. One solution to the enduring challenge of polygenic cancer drug resistance is rational combinatorial targeted therapy.
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“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 In Vivo Combination Studies Using Mouse Tumor Models (2023) · cites this paper as [1]
In the citing paper
“combinations of inhibitors targeting multiple effector and/or feedback pathways have shown impressive activity in KRAS mutant model systems”
From A Landscape of Therapeutic Cooperativity in KRAS Mutant Cancers Reveals Principles for Controlling Tumor Evolution (2017) · cites this paper as Al-Lazikani et al., 2012
In the citing paper
“The activity of single agent therapies targeting individual RAS effector pathways is limited”
From A Landscape of Therapeutic Cooperativity in KRAS Mutant Cancers Reveals Principles for Controlling Tumor Evolution (2017) · cites this paper as Al-Lazikani et al., 2012
In the citing paper
“To minimize the emergence of resistant clones and to achieve maximal therapeutic response, combinations of different classes of therapeutic agents123 are commonly used.”
From MDM2, MDMX and p53 in oncogenesis and cancer therapy (2013) · cites this paper as [123]
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Metadata
- Authors
- Al-Lazikani, B., Banerji, U., & Workman, P.
- Affiliations
- Royal Marsden NHS Foundation Trust (GB)
- Institute of Cancer Research (GB)
- Corresponding author
- Banerji, Udai
- Workman, Paul
- Venue
- Nature Biotechnology
- Published
- 2012-07
- Volume
- 30
- Issue
- 7
- Pages
- 679-692
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2061061337
- Cited by
- 1,070
- References
- 172
- Citations by year
- 2026: 63 · 2025: 80 · 2024: 71 · 2023: 73 · 2022: 87 · 2021: 73 · 2020: 80 · 2019: 91 · 2018: 81 · 2017: 76 · 2016: 83 · 2015: 90 · 2014: 69 · 2013: 46 · 2012: 6
- FWCI
- 5.04
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- NIHR Biomedical Research Centre, Royal Marsden NHS Foundation Trust/Institute of Cancer Research
- Cancer Research UK (C309/8992, 11566, C309/A8274)
- National Institute for Health and Care Research
- National Institutes of Health
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Keywords
- combination therapy, targeted cancer therapy, driver mutations, synthetic lethality, tumor vulnerability, precision oncology, acquired drug resistance, de novo resistance, polygenic resistance, cytotoxic chemotherapy
- MeSH terms
- Antineoplastic Combined Chemotherapy Protocols, Clinical Trials as Topic, Combined Modality Therapy, Humans, Neoplasms, Drug Design, Genome, Human, Genetic Heterogeneity, Metabolic Networks and Pathways, Precision Medicine, Molecular Targeted Therapy, High-Throughput Nucleotide Sequencing
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