title: Determination of the optimal tubulin isotype target as a method for the development of individualized cancer chemotherapy.
abstract: BACKGROUND
  As microtubules are essential for cell growth and division, its constituent protein β-tubulin has been a popular target for various treatments, including cancer chemotherapy. There are several isotypes of human β-tubulin and each type of cell expresses its characteristic distribution of these isotypes. Moreover, each tubulin-binding drug has its own distribution of binding affinities over the various isotypes, which further complicates identifying the optimal drug selection. An ideal drug would preferentially bind only the tubulin isotypes expressed abundantly by the cancer cells, but not those in the healthy cells. Unfortunately, as the distributions of the tubulin isotypes in cancer cells overlap with those of healthy cells, this ideal scenario is clearly not possible. We can, however, seek a drug that interferes significantly with the isotype distribution of the cancer cell, but has only minor interactions with those of the healthy cells.
  
  
  METHODS
  We describe a quantitative methodology for identifying this optimal tubulin isotype profile for an ideal cancer drug, given the isotype distribution of a specific cancer type, as well as the isotype distributions in various healthy tissues, and the physiological importance of each such tissue.
  
  
  RESULTS
  We report the optimal isotype profiles for different types of cancer with various routes of delivery.
  
  
  CONCLUSIONS
  Our algorithm, which defines the best profile for each type of cancer (given the drug delivery route and some specified patient characteristics), will help to personalize the design of pharmaceuticals for individual patients. This paper is an attempt to explicitly consider the effects of the tubulin isotype distributions in both cancer and normal cell types, for rational chemotherapy design aimed at optimizing the drug's efficacy with minimal side effects.
authors: Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada.
authors: Siamak
authors: S
authors: Ravanbakhsh
authors: Melissa
authors: M
authors: Gajewski
authors: Russell
authors: R
authors: Greiner
authors: Jack A
authors: JA
authors: Tuszynski
mesh_terms: D000465:Algorithms; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D006801:Humans; D008958:Models, Molecular; D009369:Neoplasms / Q000188:drug therapy*; D014404:Tubulin / Q000737:chemistry / Q000378:metabolism*
chemical_list: D000970:Antineoplastic Agents; D014404:Tubulin
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