The DOI matches its Crossref record; 86 of the 86 references it cites were found in a registry or an index.
Generation of peptides using phage display technology for cancer diagnosis and molecular imaging
Open accessAbstract
Cancer is one of the leading causes of mortality worldwide; nearly 10 million people died from it in 2020. The high mortality rate results from the lack of effective screening approaches where early detection cannot be achieved, reducing the chance of early intervention to prevent cancer development. Non-invasive and deep-tissue imaging is useful in cancer diagnosis, contributing to a visual presentation of anatomy and physiology in a rapid and safe manner. Its sensitivity and specificity can be enhanced with the application of targeting ligands with the conjugation of imaging probes. Phage display is a powerful technology to identify antibody- or peptide-based ligands with effective binding specificity against their target receptor. Tumour-targeting peptides exhibit promising results in molecular imaging, but the application is limited to animals only. Modern nanotechnology facilitates the combination of peptides with various nanoparticles due to their superior characteristics, rendering novel strategies in designing more potent imaging probes for cancer diagnosis and targeting therapy. In the end, a myriad of peptide candidates that aimed for different cancers diagnosis and imaging in various forms of research were reviewed.
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“Two-dimensional (2D) monolayer cultures of human or murine cancer cell lines serve as preliminary models to evaluate phage targeting, transduction efficiency, and cytotoxic effects [93,95,104,105]”
From Phage therapy in oncology: opportunities for cancer prevention and treatment (2026) · cites this paper as [104]
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Cites
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Siegel, R. L., Miller, K. D., & Jemal, A. (2016) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21332 · Cited by 16,003
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Smith, G. P. (1985) · Science · doi:10.1126/science.4001944 · Cited by 4,143
A matrix metalloproteinase expressed on the surface of invasive tumour cells
Sato, H., Takino, T., Okada, Y., Cao, J. P., Shinagawa, A., Yamamoto, E., & Seiki, M. (1994) · Nature · doi:10.1038/370061a0 · Cited by 2,547
Searching for Peptide Ligands with an Epitope Library
Scott, J. K., & Smith, G. P. (1990) · Science · doi:10.1126/science.1696028 · Cited by 2,095
Non-small-cell lung cancers: a heterogeneous set of diseases
Chen, Z., Brainson, C. F., Hammerman, P. S., Kim, C. F., & Wong, K. (2014) · Nature reviews. Cancer · doi:10.1038/nrc3775 · Cited by 1,982
Recent advances in iron oxide nanocrystal technology for medical imaging☆
Corot, C., Robert, P., Idée, J., & Port, M. (2006) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2006.09.013 · Cited by 1,498
Organ targeting In vivo using phage display peptide libraries
Pasqualini, R., & Ruoslahti, E. I. (1996) · Nature · doi:10.1038/380364a0 · Cited by 1,234
Application of Nanomaterials in Biomedical Imaging and Cancer Therapy
Siddique, S., & Chow, J. C. L. (2020) · Nanomaterials · doi:10.3390/nano10091700 · Cited by 411
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Phage therapy in oncology: opportunities for cancer prevention and treatment
Mutalik, V. K., Inman, J. L., Chang, H., Arkin, A., & Mao, J.-H. (2026) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2026.02.001 · Cited by 7
Metadata
- Authors
- Pung, H. S., Tye, G. J., Leow, C. H., Ng, W. K., & Lai, N. S.
- Affiliations
- Universiti Sains Malaysia (MY)
- AIMST University (MY)
- Corresponding author
- Lai, Ngit Shin
- Venue
- Molecular Biology Reports
- Published
- 2023-04-04
- Volume
- 50
- Issue
- 5
- Pages
- 4653-4664
- ISSN
- 0301-4851 (ISSN-L)
- 1573-4978
- PMC
- PMC10072011
- OpenAlex
- W4362523162
- Cited by
- 30
- References
- 86
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 9 · 2023: 6
- FWCI
- 0.67
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Molecular Biology Reports (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HiCoE (311/CIPPM/44001005)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Nanoplatforms for cancer theranostics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiopharmaceutical Chemistry and Applications
- Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
- Keywords
- phage display, cancer diagnosis, molecular imaging, imaging agents, targeting ligands, peptide-nanoparticle conjugates, early cancer detection, deep tissue imaging
- MeSH terms
- Animals, Bacteriophages, Neoplasms, Peptides, Technology, Peptide Library, Molecular Imaging
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