Theranostic A New Approaches For Colorectal Cancer Treatment: Molecular Biomarkers, Challenges And Future Directions

Abstract

Colorectal cancer (CRC) presents a significant global health challenge, being one of the most prevalent malignancies and a leading cause of cancer-related mortality worldwide. Despite advances in screening initiatives and therapeutic interventions, CRC incidence persists, particularly among younger demographics and in transitioning regions. The multifaceted etiology of CRC involves a complex interplay of genetic predisposition, environmental influences, and lifestyle factors, contributing to its heterogeneous nature. Understanding the traditional adenoma-carcinoma sequence provides a framework for comprehending the stepwise progression of CRC, characterized by the accumulation of genetic and epigenetic alterations driving tumorigenesis. This review delves into the emerging paradigm of theranostics in CRC, which integrates targeted therapies with diagnostic tools to tailor treatment strategies based on individual molecular profiles. Theranostics revolutionizes CRC care by enhancing precision through early detection, guided therapy selection, and real-time monitoring of treatment responses. By ident[1]ifying specific biomarkers and employing personalized therapeutic agents, theranostics minimizes unnecessary exposure to ineffective treatments and their associated toxicities, while optimizing therapeutic outcomes. Various theranostic strategies are explored, including the utilization of nanomaterials such as iron oxide nanoparticles, quantum dots, dendrimers, carbon nanotubes, and liposomes, along with the assessment of epigenetic markers such as CpG island methylator phenotype and microRNAs. Additionally, novel potential markers for CRC, such as phosphatidylinositide-3-kinases (PI3K), PTEN, TP53, and IGFR-1R, are investigated, alongside the expression of protein markers like carcinoembryonic antigen (CEA) and heat shock proteins (HSP). Furthermore, the review elucidates the role of molecular imaging biomarkers in CRC management, encompassing techniques such as computed tomographic colonography, dual-energy spectral CT, diffusion-weighted imaging, and positron emission tomography. The integration of machine learning algorithms enhances the predictive accuracy of imaging modalities, facilitating early detection and precise treatment planning. Personalized treatment strategies in CRC are discussed, focusing on biomarker-driven targeted therapies such as RAS mutations, BRAF V600E mutation, microsatellite instability (MSI), and deficiency in mismatch repair (dMMR). Moreover, the emergence of immunotherapy and immune checkpoint inhibitors, including PD-1/PD-L1 pathway inhibitors and CTLA-4 blockade, represents a promising frontier in CRC treatment, offering improved outcomes and prolonged survival for patients