====== 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.
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[[Resistance]] of high-grade [[tumor]]s 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 pathway]]s. 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 [[method]]s 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 [[volume]]s 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 [[protocol]]s for future [[research]] efforts that marry revolutionary bio-information technologies, growing access to increased [[computation]]al capability, and powerful statistical [[classification]] techniques to guide rational treatment selection
((Parker JG, Servati M, Diller EE, Cao S, Ho C, Lober R, Cohen-Gadol A. [[Target]]ing intra-[[tumor]]al [[heterogeneity]] of human [[brain tumor]]s with [[in vivo]] [[imaging]]: A [[roadmap]] for imaging [[genomics]] from [[multiparametric]] MR signals. Med Phys. 2022 Nov 13. doi: 10.1002/mp.16059. Epub ahead of print. PMID: 36371678.)).

[[B cell targeted therapy]]