title: Assessment of tumor cell cohesion in vivo using pattern interpretation by cellular automata.
abstract: OBJECTIVE
  There is abundant evidence that patterning in life sciences may be closely related to the functional properties of the constitutive elements. In order to estimate some of these functional properties by examining the static pattern evolved, pattern interpretation by cellular automata (PICA) was introduced and applied to the mechanisms of tumor growth. Previously it was shown that the estimates concerning tumor cell proliferation and motility were consistent with those obtained by other methods.
  
  
  METHODS
  Morphologic patterns obtained by growing two variants of the C4 cervical carcinoma cell lines with different in vitro adhesive properties in the hamster cheek pouch were evaluated by PICA.
  
  
  RESULTS
  PICA estimates of tumor cell cohesion turned out to be significantly higher in tumors derived from the C4-I cell line (0.73 +/- 0.02 SD) with high in vitro cohesiveness than in tumors derived from the less adhesive C4-II cell line (0.32 +/- 0.04 SD; t test, P = .001).
  
  
  CONCLUSIONS
  These results indicate that functional estimates concerning tumor cell cohesion obtained by PICA may be in good agreement with in vitro observations of the same cellular property and further underscore that PICA may be a useful tool for the functional interpretation of static histologic patterns.
authors.affiliation: Department of Dermatology, University of Graz, Austria.
authors.forename: J
authors.initials: J
authors.lastname: Smolle
authors.forename: R
authors.initials: R
authors.lastname: Hofmann-Wellenhof
authors.forename: R
authors.initials: R
authors.lastname: Fink-Puches
authors.forename: N
authors.initials: N
authors.lastname: Auersperg
mesh_terms: D000818:Animals; D002448:Cell Adhesion; D002452:Cell Count; D002455:Cell Division / Q000502:physiology; D006224:Cricetinae; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008938:Mitosis / Q000502:physiology; D010363:Pattern Recognition, Automated; D014407:Tumor Cells, Cultured / Q000166:cytology; D002583:Uterine Cervical Neoplasms / Q000473:pathology*