Cancer is the leading cause of mortality worldwide, requiring continuous advancements in diagnosis
and treatment. Traditional methods often lack sensitivity and specificity, leading to the need for new methods.
3D printing has emerged as a transformative tool in cancer diagnosis, offering the potential for precise
and customizable nanosensors. These advancements are critical in cancer research, aiming to improve early detection
and monitoring of tumors. In current times, the usage of the 3D printing technique has been more prevalent
as a flexible medium for the production of accurate and adaptable nanosensors characterized by exceptional
sensitivity and specificity. The study aims to enhance early cancer diagnosis and prognosis by developing
advanced 3D-printed nanosensors using 3D printing technology. The research explores various 3D printing
techniques, design strategies, and functionalization strategies for cancer-specific biomarkers. The integration
of these nanosensors with detection modalities like fluorescence, electrochemical, and surface-enhanced Raman
spectroscopy is also evaluated. The study explores the use of inkjet printing, stereolithography, and fused
deposition modeling to create nanostructures with enhanced performance. It also discusses the design and functionalization
methods for targeting cancer indicators. The integration of 3D-printed nanosensors with multiple
detection modalities, including fluorescence, electrochemical, and surface-enhanced Raman spectroscopy, enables
rapid and reliable cancer diagnosis. The results show improved sensitivity and specificity for cancer biomarkers,
enabling early detection of tumor indicators and circulating cells. The study highlights the potential
of 3D-printed nanosensors to transform cancer diagnosis by enabling highly sensitive and specific detection of
tumor biomarkers. It signifies a pivotal step forward in cancer diagnostics, showcasing the capacity of 3D
printing technology to produce advanced nanosensors that can significantly improve early cancer detection
and patient outcomes.