Recent Advances in Cancer Therapy (2020–2025): Evolving Therapies, Biomarkers, and Diagnostic Technologies

Abstract

Cancer is one of the major causes of morbidity and mortality globally, and treatment resistance and disease heterogeneity are ongoing problems. Over the past five years, cancer treatment has undergone a substantial transformation thanks to precision medicine, molecular profiling, and the application of artificial intelligence (AI) in diagnostics. Next-generation immune checkpoint inhibitors, CAR T-cell treatments targeting solid tumours, and bispecific antibodies are examples of advances in immunotherapy. RNA-based treatments, oncolytic viruses, and tailored cancer vaccinations all made a big difference. The discovery of novel biomarkers, including ctDNA, tumour mutational burden (TMB), and spatial transcriptomic signatures, has enhanced real-time monitoring, patient stratification, and resistance prediction. Early intervention and flexible treatment adjustments are now possible thanks to developments in single-cell sequencing, liquid biopsy, and AI-assisted imaging. The assessment of minimal residual disease (MRD) and the detection of non-invasive cancer have also changed as a result. However, due to issues such as tumour heterogeneity, unequal access to state-of-the-art technology, insufficient biomarker validation, and implementation costs, these developments are not widely adopted in clinical practice. Moreover, immune-related side effects and the emergence of resistance mechanisms continue to hinder treatment efficacy. To improve reproducibility and worldwide applicability, future work will focus on standardizing biomarker validation, employing adaptive clinical trial designs, and integrating multi-omic data. Enhancing collaboration between genomics, computational biology, and immuno-oncology will be crucial to accelerating the shift to personalized, accurate, and accessible cancer care.