Peptide Therapeutics for Solid Tumors: Functional Classes, AI-Enhanced Discovery and Clinical Advances.
Peptide therapeutics show potential in treating solid tumors, with AI enhancing their design and discovery.
Where it sits
this study against the rest of the leuprorelin corpusSummary and findings
This review discusses advancements in peptide-based therapeutics for solid tumors from 2020 to 2025. It categorizes peptide agents into five functional classes and highlights the role of AI in peptide design. Clinical trial outcomes of peptide drugs in solid tumors are also discussed.
Abstract
Solid tumors, the most prevalent form of malignancy, pose therapeutic challenges distinct from hematologic malignancies due to their complex biology, including high tumor heterogeneity, a dense extracellular matrix (ECM), an immunosuppressive tumor microenvironment (TME), and multifaceted drug resistance. Peptide drugs have emerged as a focal point in precision oncology, combining the deep tissue penetration of small molecules with the high target specificity, low immunogenicity, and sequence designability of antibodies. This review systematically summarizes advancements in peptide-based therapeutics for solid tumors from 2020 to 2025. These agents are categorized by function into five classes: tumor-homing peptides, surface receptor antagonist/inhibitory peptides, interfering peptides, peptide vaccines, and cell-penetrating peptides as delivery tools. We also highlight the transformative role of artificial intelligence (AI) in peptide design and discovery. Finally, we discuss outcomes from clinical trials of peptide drugs in solid tumors, underscoring their potential as multifunctional agents in this setting.
Background
Solid tumors are the most common form of cancer and present unique therapeutic challenges due to their complex biology, including high heterogeneity and drug resistance. Peptide therapeutics have emerged as a promising approach in precision oncology, offering advantages such as deep tissue penetration and high specificity. This review is significant as it compiles recent advancements in peptide-based treatments for solid tumors, providing insights into their potential roles in oncology.
Methods
This is a review article that systematically summarizes advancements in peptide-based therapeutics for solid tumors from 2020 to 2025. It categorizes peptide agents into five functional classes and discusses the role of AI in peptide design. The review also highlights outcomes from clinical trials of peptide drugs in this context.
Results
Not reported in abstract.
Interpretation
The review suggests that peptide therapeutics hold promise for treating solid tumors due to their multifunctional capabilities and specificity. However, the absence of specific quantitative data limits the ability to assess the clinical significance of these advancements. The role of AI in enhancing peptide design is noted as a significant development, potentially accelerating the discovery of effective treatments.
Key findings
- Solid tumors present distinct therapeutic challenges due to complex biology.
- Peptide drugs combine deep tissue penetration with high target specificity.
- Five functional classes of peptide agents are identified.
- AI plays a transformative role in peptide design and discovery.
- Clinical trials underscore the potential of peptide drugs in solid tumors.
Limitations
- Review article, no new experimental data.
- Lacks specific quantitative outcomes.
- Focuses on advancements rather than detailed trial results.
- Potential publication bias in selected studies.