title: Impact of tissue sampling on accuracy of Ki67 immunohistochemistry evaluation in breast cancer.
abstract: BACKGROUND
  Gene expression studies have identified molecular subtypes of breast cancer with implications to chemotherapy recommendations. For distinction of these types, a combination of immunohistochemistry (IHC) markers, including proliferative activity of tumor cells, estimated by Ki67 labeling index is used. Clinical studies are frequently based on IHC performed on tissue microarrays (TMA) with variable tissue sampling. This raises the need for evidence-based sampling criteria for individual IHC biomarker studies. We present a novel tissue sampling simulation model and demonstrate its application on Ki67 assessment in breast cancer tissue taking intratumoral heterogeneity into account.
  
  
  METHODS
  Whole slide images (WSI) of 297 breast cancer sections, immunohistochemically stained for Ki67, were subjected to digital image analysis (DIA). Percentage of tumor cells stained for Ki67 was computed for hexagonal tiles super-imposed on the WSI. From this, intratumoral Ki67 heterogeneity indicators (Haralick's entropy values) were extracted and used to dichotomize the tumors into homogeneous and heterogeneous subsets. Simulations with random selection of hexagons, equivalent to 0.75 mm circular diameter TMA cores, were performed. The tissue sampling requirements were investigated in relation to tumor heterogeneity using linear regression and extended error analysis.
  
  
  RESULTS
  The sampling requirements were dependent on the heterogeneity of the biomarker expression. To achieve a coefficient error of 10 %, 5-6 cores were needed for homogeneous cases, 11-12 cores for heterogeneous cases; in mixed tumor population 8 TMA cores were required. Similarly, to achieve the same accuracy, approximately 4,000 nuclei must be counted when the intratumor heterogeneity is mixed/unknown. Tumors of low proliferative activity would require larger sampling (10-12 TMA cores, or 6,250 nuclei) to achieve the same error measurement results as for highly proliferative tumors.
  
  
  CONCLUSIONS
  Our data show that optimal tissue sampling for IHC biomarker evaluation is dependent on the heterogeneity of the tissue under study and needs to be determined on a per use basis. We propose a method that can be applied to determine the sampling strategy for specific biomarkers, tissues and study targets. In addition, our findings highlight the benefit of high-capacity computer-based IHC measurement techniques to improve accuracy of the testing.
authors: Faculty of Medicine, Vilnius University, M.K.Ciurlionio 21, Vilnius, LT-03101, Lithuania. justinas.besusparis@vpc.lt.|National Center of Pathology, affiliate of Vilnius University Hospital Santariskiu Clinics, P. Baublio 5, Vilnius, LT-08406, Lithuania. justinas.besusparis@vpc.lt.
authors: Justinas
authors: J
authors: Besusparis
authors: PathImage/BioTICLA, Inserm (UMR 1199), University Caen Normandy, Cancer Center F. Baclesse, Caen, France.
authors: Benoit
authors: B
authors: Plancoulaine
authors: National Center of Pathology, affiliate of Vilnius University Hospital Santariskiu Clinics, P. Baublio 5, Vilnius, LT-08406, Lithuania.
authors: Allan
authors: A
authors: Rasmusson
authors: Faculty of Medicine, Vilnius University, M.K.Ciurlionio 21, Vilnius, LT-03101, Lithuania.|National Center of Pathology, affiliate of Vilnius University Hospital Santariskiu Clinics, P. Baublio 5, Vilnius, LT-08406, Lithuania.
authors: Renaldas
authors: R
authors: Augulis
authors: Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
authors: Andrew R
authors: AR
authors: Green
authors: Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.|Histopathology, Nottingham City Hospital University of Nottingham, Nottingham, UK.
authors: Ian O
authors: IO
authors: Ellis
authors: Faculty of Medicine, Vilnius University, M.K.Ciurlionio 21, Vilnius, LT-03101, Lithuania.|National Center of Pathology, affiliate of Vilnius University Hospital Santariskiu Clinics, P. Baublio 5, Vilnius, LT-08406, Lithuania.
authors: Aida
authors: A
authors: Laurinaviciene
authors: Faculty of Medicine, Vilnius University, M.K.Ciurlionio 21, Vilnius, LT-03101, Lithuania.
authors: Paulette
authors: P
authors: Herlin
authors: Faculty of Medicine, Vilnius University, M.K.Ciurlionio 21, Vilnius, LT-03101, Lithuania.|National Center of Pathology, affiliate of Vilnius University Hospital Santariskiu Clinics, P. Baublio 5, Vilnius, LT-08406, Lithuania.
authors: Arvydas
authors: A
authors: Laurinavicius
mesh_terms: D000465:Algorithms; D001706:Biopsy; D001943:Breast Neoplasms / Q000737:chemistry* / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000737:chemistry* / Q000473:pathology; D049109:Cell Proliferation; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007150:Immunohistochemistry; D019394:Ki-67 Antigen / Q000032:analysis*; D016014:Linear Models; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D046888:Tissue Array Analysis
chemical_list: D019394:Ki-67 Antigen
keywords: Breast cancer; Digital image analysis; Ki67; TMA; Tissue microarrays; Tissue sampling; Tumor heterogeneity