Cancer represents a diverse group of diseases distinguished by uncontrolled cellular growth, genomic instability, and metastatic potential. Despite major advances in understanding its molecular and cellular mechanisms, effective treatment remains a major clinical challenge. Conventional therapies such as chemotherapy and radiotherapy often lack specificity, causing damage to healthy tissues and leading to significant side effects. Moreover, cancer cells frequently develop resistance to treatments through genetic mutations, altered signaling pathways, or adaptive metabolic changes, which cause many treatments to be ineffective over time and contribute to recurrence.

In order to evaluate recent innovations in cancer therapeutics, this literature review focuses on studies published within the past two years and investigates novel therapeutic techniques, which we divided into three main categories: small molecules, antibody-based modalities, and gene-editing technologies. AI has rapidly improved the identification of small molecules and produced more potent inhibitors by enhancing virtual screening, structural prediction, and optimization procedures. Advances in antibody engineering, including the development of antibody-drug conjugates and AI-assisted antibody design, have contributed to efficient tumor targeting while reducing off-target toxicity.

Meanwhile, precise modulation of oncogenic pathways and immune cell stimulations has been made possible by gene-editing technologies like CRISPR-Cas9, TALENs, and zinc finger nucleases. Together, these approaches show how cancer treatment is transitioning toward mechanism-driven treatments. The intersection of genetic engineering, molecular biology, and AI offers new opportunities to overcome treatment resistance and improve long-term patient outcomes. Continued integration of these interdisciplinary technologies is set to define the next generation of precision cancer medicine.

Saerin Nam is affiliated to Philips Exeter Academy in USA