Prognostic significance of extensive microsatellite instability in sporadic clinicopathological stage C colorectal cancer

Br J Surg. 2000 Sep;87(9):1197-202. doi: 10.1046/j.1365-2168.2000.01508.x.


Background: Colorectal cancers exhibiting microsatellite instability (MSI) appear to have unique biological behaviour. This study analyses the association between extensive MSI (MSI-H), clinicopathological features and survival in an unselected group of patients with sporadic Australian Clinico-Pathological Stage (ACPS) C (tumour node metastasis stage III) colorectal cancer.

Methods: Some 255 patients who underwent resection for sporadic ACPS C colorectal cancer between 1986 and 1992 were studied. No patient had received chemotherapy. Minimum follow-up for all patients was 5 years. Archival normal and tumour DNA was extracted and amplified by polymerase chain reaction using a radioactive labelling technique. MSI-H was defined as instability in 40 per cent or more of seven markers.

Results: Twenty-one patients showed MSI-H. No association was found between MSI and age or sex. Tumours exhibiting MSI-H were more commonly right sided (P<0.00001), larger (P = 0.002) and more likely to be high grade (P = 0.049). After adjustment for age, sex and other pathological variables, patients whose cancers exhibited MSI-H had improved survival (P = 0.015).

Conclusion: Recognition of MSI-H in sporadic ACPS C tumours identifies a subset of cancers with improved prognosis. Such stratification should be considered in trials of adjuvant therapy and may be relevant to therapeutic decision making.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Colorectal Neoplasms / genetics*
  • Colorectal Neoplasms / pathology
  • Colorectal Neoplasms / surgery
  • Female
  • Humans
  • Male
  • Microsatellite Repeats / genetics*
  • Middle Aged
  • Multivariate Analysis
  • Neoplasm Staging / methods
  • Polymerase Chain Reaction
  • Prognosis
  • Proportional Hazards Models
  • Regression Analysis
  • Survival Analysis