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With the integration of nanotechnology into the medical field at large, great strides have been made in the development of nanomedicines for tackling different diseases, including cancers. To date, various cancer nanomedicines have demonstrated success in preclinical studies, improving therapeutic outcomes, prolonging survival, and/or decreasing side effects. However, the translation from bench to bedside remains challenging. While a number of nanomedicines have entered clinical trials, only a few have been approved for clinical applications. In this review, we highlight the most recent progress in cancer nanomedicine, discuss current clinical advances and challenges for the translation of cancer nanomedicines, and provide our viewpoints on accelerating clinical translation. We expect this review to benefit the future development of cancer nanotherapeutics specifically from the clinical perspective.

Significance Deep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle–protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

We have developed a scalable system that leverages protein-nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Introducing proprietary engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle-protein interface, driven by the relationship between protein-NP affinity and protein abundance. Here we demonstrate the importance of tuning the protein to NP-surface ratio (P/NP), which determines the competition between proteins for binding. We demonstrate how optimized P/NP ratio affects protein corona composition, ultimately enhancing performance of a fully automated NP-based deep proteomic workflow (Proteograph). By limiting the available binding surface of NPs and increasing the binding competition, we identify 1.2 – 1.7x more proteins with only 1% false discovery rate on the surface of each NP, and up to 3x compared to a standard neat plasma proteomics workflow. Moreover, increased competition means proteins are more consistently identified and quantified across replicates, yielding precise quantification and improved coverage of the plasma proteome when using multiple physicochemically distinct NPs. In summary, by optimizing NPs and assay conditions, we capture a larger and more diverse set of proteins, enabling deep proteomic studies at scale.

Nanoparticles exposed to biological fluids such as blood, quickly interact with their surrounding milieu resulting in a biological coating that results in large part as a function of the physicochemical properties of the nanomaterial. The large nanoparticle surface area-to-volume ratio further augments binding of biological molecules and the resulting biomolecular or protein corona, once thought of as problematic biofouling, is now viewed as a rich source of biological information that can guide the development of nanomedicines. This review gives an overview of the utility of the protein corona in proteomic profiling and discusses how a better understanding of nano-bio interactions can accelerate the clinical translation of nanomedicines and facilitate the identification of disease-specific biomarkers. With the FDA requirement of the protein corona analysis of nanoparticles in place, it is envisaged that analyzing the protein corona of nanoparticles on a case-by-case basis can provide highly valuable nano-bio interface information that can aid and improve their clinical translation.