Assessments of leukocyte populations in the context of cancer tissues are typically determined by staining for one or more leukocyte marker in formalin-fixed tissues. Evaluation of more than one leukocyte marker in a tissue, especially in the clinical setting, can be challenging due to technical constraints on the number of markers possible with chromogenic multiplexing or the complexity of the wet chemistry, image acquisition, and scoring for fluorescent multiplexing. Approaches which rely on widely adopted chromogenic immunohistochemistry (IHC) staining are preferred in the clinical laboratory setting, but the number of assayable markers is typically limited to 1-2 markers. Furthermore, limited clinical tissue material may be available for evaluation with multiple assays, and staining of archived samples may not be possible if tissue material has been exhausted during previous studies.
In order to provide an additional evaluation of the inflammatory landscape in tissues without requiring added wet assay complexity or additional staining, Flagship Biosciences has developed an approach for deriving the complex endpoints often necessary in immuno-oncology studies which rely on 1-3 chromogenic stains and computer interpretation of the tissue using only hematoxylin counterstain to identify T-lymphocytes. In a proof-of-concept study, we utilized our Tissue Image Analysis (tIA) tools to determine the morphometric parameters which could identify T-lymphocytes, independent of staining for the T-lymphocyte marker CD3. A cohort of non-small cell lung cancer (NSCLC) tissues was stained by CD3 IHC, and both CD3- and isotype-stained tissues were analyzed with Flagship’s CellMap™ software to capture the morphometric and staining features of cells in the tissues. The morphometric features which characterized CD3-positive T-lymphocytes were used to approximate the T-lymphocyte population frequency in the isotype-stained tissues.
This T-lymphocyte classification scheme was defined based on hematoxylin staining alone, and accuracy of T-lymphocyte classification was verified by CD3 staining. Based on this study, the method described herein could be utilized to estimate the frequency of T-lymphocytes without the need for an additional T-lymphocyte marker such as CD3. The approach could, therefore, provide an added dimension of analysis for tissues stained by IHC for additional leukocyte subsets without adding complexity to the wet assay by necessitating a general marker for T-lymphocytes, or could be used to evaluate patient tissues stained previously for which there is no longer tissue material ilable to evaluate the inflammatory landscape.