Precision oncology aims to tailor cancer treatment to the individual characteristics of each patient and their tumor, especially genetic alterations. Instead of relying only on the tumor’s location and microscopic appearance, this approach uses molecular diagnostics to identify mutations, gene fusions, copy number changes, epigenetic modifications and other biomarkers that can guide therapy.

A major focus is on creating and validating predictive biomarkers that indicate whether a patient is likely to benefit from a specific drug, such as targeted inhibitors or immunotherapies. Large scale sequencing efforts have revealed that many tumors share actionable mutations across different cancer types, enabling “tumor agnostic” therapies. At the same time, the heterogeneity and evolution of tumors, including acquired resistance mutations and clonal diversity, create major challenges for durable responses.

Research in precision oncology spans multiple levels. Genomic profiling of tumors is now complemented by transcriptomic, proteomic and epigenomic data to build a more complete molecular picture. Functional assays, such as patient derived organoids and xenografts, are used to test drug sensitivity in systems that better mimic the patient’s cancer. Computational models integrate clinical and molecular data to predict treatment outcomes and prioritize therapeutic options.

Clinical implementation requires robust diagnostic platforms, standardized bioinformatics pipelines and carefully designed trials that match patients to therapies based on molecular criteria. Adaptive and basket trial designs help evaluate drugs across different tumor types sharing a common biomarker. Ongoing work seeks to expand the range of targetable alterations, refine combination therapies to overcome resistance and ensure that precision oncology benefits more patients in real world clinical practice.