Targeted Therapy
Targeted therapy is one of the major modalities of medical treatment (pharmacotherapy) for cancer treatment, the other being hormone therapy and cytotoxic chemotherapy. As a form of molecular medicine, targeted therapy blocks the growth of cancer cells by interfering with specific targeted molecules needed for carcinogenesis and tumor growth, rather than by simply interfering with all rapidly dividing cells (e.g. with traditional chemotherapy). Because most agents for targeted therapy are biopharmaceuticals, the term biologic therapy is sometimes synonymous with targeted therapy when used in the context of cancer therapy (and thus distinguished from chemotherapy, that is, cytotoxic therapy). However, the modalities can be combined; antibody-drug conjugates combine biological and cytotoxic mechanisms into one targeted therapy.
Resistance of high-grade tumors to treatment involves cancer stem cell features, deregulated cell division, acceleration of genomic errors, and the emergence of cellular variants that rely upon diverse signaling pathways. This heterogeneous tumor landscape limits the utility of the focal sampling provided by invasive biopsy when designing strategies for targeted therapy. In a roadmap review paper, Parker et al. proposed and developed methods for enabling the mapping of cellular and molecular features in vivo to inform and optimize cancer treatment strategies in the brain. This approach leverages 1) the spatial and temporal advantages of in vivo imaging compared with surgical biopsy, 2) the rapid expansion of meaningful anatomical and functional MR signals, 3) widespread access to cellular and molecular information enabled by next-generation sequencing, and 4) the enhanced accuracy and computational efficiency of deep learning techniques. As multiple cellular variants may be present within volumes below the resolution of imaging, they described a mapping process to decode micro- and even nano-scale properties from the macro-scale data by simultaneously utilizing complimentary multiparametric image signals acquired in routine clinical practice. They outlined design protocols for future research efforts that marry revolutionary bio-information technologies, growing access to increased computational capability, and powerful statistical classification techniques to guide rational treatment selection 1).