Cross-platform comparison of immune-related gene expression to assess intratumor immune responses following cancer immunotherapy

J Immunol Methods. 2021 Jul;494:113041. doi: 10.1016/j.jim.2021.113041. Epub 2021 Mar 19.

Abstract

Neoadjuvant immunotherapy can induce immune responses within the tumor microenvironment. Gene expression can be used to assess responses with limited amounts of conventionally-fixed patient-derived samples. We aim to assess the cross-platform concordance of immune-related gene expression data. We performed comparisons across three panels in two platforms: Nanostring nCounter® PanCancer Immune Profiling Panel (nS), HTG EdgeSeq Oncology Biomarker Panel (HTG OBP) and Precision Immuno-Oncology Panel (HTG PIP). All tissue samples of 14 neoadjuvant GM-CSF treated, 14 neoadjuvant Provenge treated, and 12 untreated prostate cancer patients were radical prostatectomy (RP) tissues, while 6 prostatitis patients and 6 non-prostatitis subjects were biopsies. For all 52 patients, more than 90% of the common genes were significantly correlated (p < 0.05) and more than 76% of the common genes were highly correlated (r > 0.5) between any two panels. Co-inertia analysis also demonstrated high overall dataset structure similarity (correlation>0.84). Although both dimensionality reduction visualization analysis and unsupervised hierarchical cluster analysis for highly correlated common genes (r > 0.9) suggested a high-level of consistency across the panels, there were subsets of genes that were differentially expressed across the panels. In addition, while the effect size of the differential testing for neoadjuvant treated vs. untreated localized prostate cancer patients across the panels were significantly correlated, some genes were only differentially expressed in the HTG panels. Finally, the HTG PIP panel had the best classification performance among the 3 panels. These differences detected may be a result of the different panels or platforms due to their technical setting and focus. Thus, researchers should be aware of those potential differences when deciding which platform and panel to use.

Keywords: Classification performance; Gene expression profiling; HTG EdgeSeq; Nanostring platform; Neoadjuvant immunotherapy; Prostate cancer.

Publication types

  • Clinical Trial, Phase I
  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • Datasets as Topic
  • Gene Expression Profiling
  • Granulocyte-Macrophage Colony-Stimulating Factor / therapeutic use*
  • Humans
  • Immunity, Cellular / genetics
  • Immunotherapy / methods*
  • Lymphocytes, Tumor-Infiltrating / physiology*
  • Male
  • Nanostructures
  • Neoadjuvant Therapy / methods*
  • Prostate / metabolism*
  • Prostate / pathology
  • Prostatectomy
  • Prostatic Neoplasms / therapy*
  • Transcriptome

Substances

  • Granulocyte-Macrophage Colony-Stimulating Factor