The estimation of tumor cell percentage for molecular testing by pathologists is not accurate

Mod Pathol. 2014 Feb;27(2):168-74. doi: 10.1038/modpathol.2013.134. Epub 2013 Jul 26.


Molecular pathology is becoming more and more important in present day pathology. A major challenge for any molecular test is its ability to reliably detect mutations in samples consisting of mixtures of tumor cells and normal cells, especially when the tumor content is low. The minimum percentage of tumor cells required to detect genetic abnormalities is a major variable. Information on tumor cell percentage is essential for a correct interpretation of the result. In daily practice, the percentage of tumor cells is estimated by pathologists on hematoxylin and eosin (H&E)-stained slides, the reliability of which has been questioned. This study aimed to determine the reliability of estimated tumor cell percentages in tissue samples by pathologists. On 47 H&E-stained slides of lung tumors a tumor area was marked. The percentage of tumor cells within this area was estimated independently by nine pathologists, using categories of 0-5%, 6-10%, 11-20%, 21-30%, and so on, until 91-100%. As gold standard, the percentage of tumor cells was counted manually. On average, the range between the lowest and the highest estimate per sample was 6.3 categories. In 33% of estimates, the deviation from the gold standard was at least three categories. The mean absolute deviation was 2.0 categories (range between observers 1.5-3.1 categories). There was a significant difference between the observers (P<0.001). If 20% of tumor cells were considered the lower limit to detect a mutation, samples with an insufficient tumor cell percentage (<20%) would have been estimated to contain enough tumor cells in 27/72 (38%) observations, possibly causing false negative results. In conclusion, estimates of tumor cell percentages on H&E-stained slides are not accurate, which could result in misinterpretation of test results. Reliability could possibly be improved by using a training set with feedback.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Molecular Biology / standards*
  • Neoplasms / genetics*
  • Neoplasms / pathology*
  • Pathology, Clinical / standards*
  • Reproducibility of Results