Omics-Based Functional Fingerprinting of Nanoparticles in Cancer: Toward Predictive Nanomedicine

TL;DR

This paper introduces a new approach to study how nanoparticles affect cancer cells by combining multiple layers of biological data.

Contribution

The novel concept of 'omics-based functional fingerprinting' is proposed to better understand nanoparticle behavior in cancer contexts.

Findings

Nanoparticles induce complex biological responses that depend on delivery context and cellular environment.

Omics data can reveal non-additive effects of nanocarriers and payloads on cellular pathways.

Functional fingerprinting helps distinguish between carrier, payload, and combined effects in nanoparticle biology.

Abstract

Nanoparticles are widely explored in oncology as delivery platforms for cytotoxic drugs and molecularly defined therapeutic agents, including immunomodulators. While advances in nanomaterial engineering have enabled precise control over physicochemical properties, biological responses to nanoparticles remain difficult to predict and often diverge across experimental systems. Recent omics studies reveal that nanoparticle exposure induces coordinated cellular programs that extend beyond overt toxicity and are strongly shaped by delivery context, cellular state, and microenvironmental conditions. Importantly, these responses cannot be attributed solely to the payload, as nanocarriers themselves frequently engage stress, metabolic, and immune-related pathways, giving rise to non-additive and context-dependent effects. This Perspective proposes omics-based functional fingerprinting as a conceptual framework to interpret nanoparticle biology in cancer. Functional fingerprints are defined as integrated biological response states arising from nanocarrier–payload systems and resolving through transcriptomic, proteomic, metabolomic, and emerging single-cell or spatial approaches. By explicitly distinguishing carrier-dependent, payload-induced, and composite response programs, functional fingerprinting provides a means to reconcile heterogeneous observations and move beyond material-centered classification. Incorporating biological resolution and context awareness into nanoparticle profiling is expected to improve mechanistic interpretation, safety assessment, and the rational design of more predictive nanomedicine strategies.

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