Impact of tumor heterogeneity and tissue sampling for genetic mutation testing: a systematic review and post hoc analysis

J Clin Epidemiol. 2020 Oct:126:45-55. doi: 10.1016/j.jclinepi.2020.06.010. Epub 2020 Jun 12.

Abstract

Objective: The objective of the study was to identify guidelines to assist systematic reviewers or clinical researchers in identifying sampling bias due to tumor heterogeneity (TH) in solid cancers assayed for somatic mutations. We also assessed current reporting standards to determine the impact of TH on sample bias.

Study design and setting: We conducted a systematic review searching 13 databases (to January 2019) to identify guidelines. A post hoc analysis was performed using 12 prostate tumor somatic mutation data sets from a previous systematic review to assess reporting on TH.

Results: Searches identified 2,085 records. No formal guidelines were identified. Forty publications contained incidental recommendations across five major themes: using multiple tumor samples (n = 29), sample purity thresholds (n = 14), using specific sequencing methods (n = 8), using liquid biopsies (n = 4), and microdissection (n = 4). In post hoc analyses, 50% (6 of 12) clearly reported pathology methods. Forty-two percent (5 of 12) did not report pathology results. Forty-two percent (5 of 12) confirmed the pathology of the sample by direct diagnosis rather than inference. Forty-two percent (5 of 12) used multiple samples per patient. Fifty-eight percent (7 of 12) reported on tumor purity (reported ranges 10% to 100%).

Conclusions: As precision medicine progresses to the clinic, guidelines are required to help evidence-based decision makers understand how TH may impact sample bias. Authors need to clearly report pathology methods and results and tumor purity methods and results.

Keywords: Guidelines; Intratumour heterogeneity; Recommendations; Somatic; Systematic review; Tissue sample bias.

Publication types

  • Systematic Review

MeSH terms

  • Data Management / statistics & numerical data
  • Decision Making / ethics
  • Female
  • Genetic Heterogeneity / drug effects
  • Genetic Testing / standards
  • Guidelines as Topic
  • Humans
  • Knowledge
  • Male
  • Mutation / genetics*
  • Neoplasms / genetics*
  • Neoplasms / pathology
  • Precision Medicine / standards
  • Publications / statistics & numerical data
  • Research Personnel / education
  • Research Personnel / statistics & numerical data*
  • Sample Size
  • Selection Bias