Nanoparticles have gained considerable attention as important platforms in pharmaceutical and biomedical research due to their size, morphology, surface chemistry, and colloidal behavior, which can affect drug delivery, antimicrobial activity, diagnostics, imaging, and therapeutic performance. However, conventional chemical and physical synthesis routes may require hazardous reagents, high energy demands, and procedures that raise environmental, safety, and scalability concerns. In this context, biologically mediated synthesis has emerged as an approach in which plants, microorganisms, including fungi and algae, and isolated biomolecules contribute to nanoparticle formation by acting as reducing, capping, and stabilizing agents. This narrative review evaluates these routes as potential green strategies, covering formation principles, biological sources, nanoparticle classes, characterization challenges, pharmaceutical applications, comparison with conventional synthesis, and limitations. The reviewed evidence indicates that the composition of biological sources and reaction conditions can shape nanoparticle size, morphology, surface chemistry, stability, and biological activity, highlighting green synthesis as a design-dependent process rather than a simple substitute for chemical reducing agents. Integrated characterization using optical, spectroscopic, diffraction, microscopic, and colloidal techniques is essential for interpreting nanoparticle identity and reproducibility. Biologically mediated nanoparticles show experimental and preclinical potential in drug delivery, antimicrobial therapy, anticancer research, biosensing, imaging, and diagnostics; however, most evidence remains preclinical and model-dependent. Translation remains limited by source variability, batch inconsistency, scale-up and purification challenges, stability, incomplete safety evidence, and regulatory uncertainty. Progress will require standardized process control, comparative life cycle and techno-economic assessment, scalable manufacturing, and rigorous pharmacokinetic, biodistribution, toxicological, and regulatory validation.

Metals and metalloids play essential roles in cancer biology, influencing redox balance, epigenetic regulation, immune responses, and cell death throughout tumour development, progression, and resistance to therapy. Despite this broad biological relevance, the systematic clinical integration of metallomics into oncology remains in its early stages. This review introduces the Cancer Metallome Continuum (CMC), a framework illustrating how metallomic reprogramming evolves from cancer initiation through progression to therapy-resistant states, and evaluates the analytical, systems-level, and translational approaches needed to test it. In early stages of cancer, toxic metals such as As, Cd, hexavalent chromium [Cr(VI)], and Ni induce oxidative stress, epigenetic modifications, and DNA repair defects. During progression, dyshomeostasis of essential metals creates tumour-specific dependencies. For example, Fe accumulation can support tumour growth, while tumour cells concurrently engage anti-ferroptotic programs; Cu contributes to angiogenesis and kinase signalling, and Zn transporter networks regulate apoptosis and immune responses. Under treatment pressure, tumours adapt by rewiring metal transporters, upregulating metallothionein buffering, and suppressing metal-dependent cell death pathways, including ferroptosis and cuproptosis. Translational advances include selenium-based prognostic panels with replicated evidence in breast cancer (SCAN-B) and colorectal cancer (CORSA), Cu-chelation trials, and spatially resolved metallodrug imaging. The strongest human evidence currently supports Se-based prognostic panels (replicated across breast and colorectal cancer cohorts) and the feasibility of biomarker-guided Cu depletion (a Phase II single-arm trial), while spatial integration and artificial intelligence/machine learning (AI/ML) applications remain at the proof-of-concept or emerging stages. Clinical translation will require tighter control of preanalytical variability, prospective multicentre validation, and standardized reporting.