Hotspot enumeration of CD8+ tumor-infiltrating lymphocytes using digital image analysis in triple-negative breast cancer yields consistent results Academic Article uri icon

Overview

MeSH Major

  • Hemoperfusion
  • Kidney Diseases
  • Liver Diseases
  • Renal Dialysis

abstract

  • © 2018 Elsevier Inc. Tumor-infiltrating lymphocytes (TILs) have emerged as prognostic in triple-negative breast cancer (TNBC). We aimed to assess the consistency of hotspot placement and TIL enumeration among multiple pathologists. Additionally, we assessed hotspot TIL count consistency by comparing hotspot counts in 3 separate locations within a single whole-tissue section. Anti-CD8 immunohistochemistry was performed on a representative section from 66 cases of primary TNBC, which were then scanned as whole-slide images. Quantification of the tissue area and combined stromal and intratumoral CD8+ TILs was performed using digital image analysis (DIA) within 2.2 mm–diameter circle hotspots. TIL counts were quantified as absolute counts and densities (absolute count/tissue area in micrometers 2 ). For each case, 6 pathologists placed a single hotspot, defined as an area with the subjectively highest CD8+ immunoreactivity, within the tumor bed. Separately for each case, a single pathologist placed hotspots in 3 different locations within a single tumor section. Intraclass correlation coefficients (ICCs) were generated following TIL enumeration via DIA. ICCs for single hotspot placement by 6 pathologists were 0.96 for density and 0.97 for absolute counts, respectively. In 32% of cases (21/66), all the hotspots placed by the 6 pathologists were in the same location. When evaluating hotspots in 3 different locations within a tumor, the ICC was 0.95 for both density and absolute counts. Hotspot evaluation by DIA is a reproducible method for CD8+ TIL quantification, and the use of hotspots may reduce TIL count variation caused by intratumoral TIL heterogeneity.

publication date

  • March 2019

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1016/j.humpath.2018.10.014

Additional Document Info

start page

  • 27

end page

  • 32

volume

  • 85