Literature DB >> 32281132

Computerised scoring protocol for identification and quantification of different immune cell populations in breast tumour regions by the use of QuPath software.

Lieze Berben1, Hans Wildiers1,2, Lukas Marcelis3, Asier Antoranz3, Francesca Bosisio3,4, Sigrid Hatse1, Giuseppe Floris3,4.   

Abstract

AIMS: As important prognostic and predictive information can be obtained from the composition, functionality and spatial arrangement of different immune cell subtypes, this study aims at characterizing the immune infiltrate in breast tumours. METHODS AND
RESULTS: Tumour-infiltrating lymphocytes (TILs) in 62 patients with luminal B-like breast cancer were characterised by immunohistochemical staining with standard markers, and were subsequently classified and quantified by the use of QuPath software. In different delineated tumour regions, the proportion and density of CD3+ , CD4+ , CD5+ , CD8+ , CD20+ and FOXP3+ cells were assessed. The results of the software analysis were compared with those of manual counting for CD8 and CD20 staining. The QuPath scoring protocol slightly overestimated positive, negative and total lymphocyte counts and density, while minimally underestimating the proportion of positively stained lymphocytes. However, for density and proportion, no real differences from manual counting were observed. For all markers, the density of positively stained immune cells was higher in the invasive front than in the tumour centre, pointing to an accumulation of immune cells near the tumour boundaries. When we looked at the proportion of immunohistochemically positive immune cells, we observed enrichment of CD5 (P = 0.025) and CD20 (P < 0.001) at the periphery, and FOXP3 enrichment in the centre (P < 0.001).
CONCLUSION: The QuPath scoring protocol can adequately identify positively stained immune cells in breast tumours, and allows the evaluation of differences in immune cell proportion and density within different tumour regions. The entire tumour section can be quantitatively assessed quite rapidly, which is a major advantage over manual counting.
© 2020 John Wiley & Sons Ltd.

Entities:  

Keywords:  QuPath; breast cancer; scoring protocol; tumour immune infiltration

Mesh:

Year:  2020        PMID: 32281132     DOI: 10.1111/his.14108

Source DB:  PubMed          Journal:  Histopathology        ISSN: 0309-0167            Impact factor:   5.087


  14 in total

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Authors:  Sofian Al Shboul; Olimpia E Curran; Javier A Alfaro; Fiona Lickiss; Erisa Nita; Jacek Kowalski; Faris Naji; Rudolf Nenutil; Kathryn L Ball; Radovan Krejcir; Borivoj Vojtesek; Ted R Hupp; Paul M Brennan
Journal:  Life Sci Alliance       Date:  2021-10-13

2.  Simultaneous and Spatially-Resolved Analysis of T-Lymphocytes, Macrophages and PD-L1 Immune Checkpoint in Rare Cancers.

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Journal:  Cancers (Basel)       Date:  2022-06-06       Impact factor: 6.575

3.  Age-related remodelling of the blood immunological portrait and the local tumor immune response in patients with luminal breast cancer.

Authors:  Lieze Berben; Giuseppe Floris; Cindy Kenis; Bruna Dalmasso; Ann Smeets; Hanne Vos; Patrick Neven; Asier Antoranz Martinez; Annouschka Laenen; Hans Wildiers; Sigrid Hatse
Journal:  Clin Transl Immunology       Date:  2020-10-03

4.  Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer.

Authors:  Hanwen Wang; Huilin Ma; Richard J Sové; Leisha A Emens; Aleksander S Popel
Journal:  J Immunother Cancer       Date:  2021-02       Impact factor: 13.751

5.  Assessing Tumor-Infiltrating Lymphocytes in Breast Cancer: A Proposal for Combining Immunohistochemistry and Gene Expression Analysis to Refine Scoring.

Authors:  Hanne Locy; Stefaan Verhulst; Wilfried Cools; Wim Waelput; Stefanie Brock; Louise Cras; Ann Schiettecatte; Jan Jonckheere; Leo A van Grunsven; Marian Vanhoeij; Kris Thielemans; Karine Breckpot
Journal:  Front Immunol       Date:  2022-02-11       Impact factor: 7.561

6.  Integrin αvβ6 as a Target for Tumor-Specific Imaging of Vulvar Squamous Cell Carcinoma and Adjacent Premalignant Lesions.

Authors:  Bertine W Huisman; Merve Cankat; Tjalling Bosse; Alexander L Vahrmeijer; Robert Rissmann; Jacobus Burggraaf; Cornelis F M Sier; Mariette I E van Poelgeest
Journal:  Cancers (Basel)       Date:  2021-11-29       Impact factor: 6.639

7.  Whole-Slide Image Analysis of Human Pancreas Samples to Elucidate the Immunopathogenesis of Type 1 Diabetes Using the QuPath Software.

Authors:  Paola S Apaolaza; Peristera-Ioanna Petropoulou; Teresa Rodriguez-Calvo
Journal:  Front Mol Biosci       Date:  2021-06-11

8.  Digital Pathology Analysis Quantifies Spatial Heterogeneity of CD3, CD4, CD8, CD20, and FoxP3 Immune Markers in Triple-Negative Breast Cancer.

Authors:  Haoyang Mi; Chang Gong; Jeremias Sulam; Elana J Fertig; Alexander S Szalay; Elizabeth M Jaffee; Vered Stearns; Leisha A Emens; Ashley M Cimino-Mathews; Aleksander S Popel
Journal:  Front Physiol       Date:  2020-10-19       Impact factor: 4.566

9.  Blood Immunosenescence Signatures Reflecting Age, Frailty and Tumor Immune Infiltrate in Patients with Early Luminal Breast Cancer.

Authors:  Lieze Berben; Asier Antoranz; Cindy Kenis; Ann Smeets; Hanne Vos; Patrick Neven; Giuseppe Floris; Hans Wildiers; Sigrid Hatse
Journal:  Cancers (Basel)       Date:  2021-05-02       Impact factor: 6.639

10.  Transcriptomic and Immunophenotypic Characterization of Tumor Immune Microenvironment in Squamous Cell Carcinoma of the Oral Tongue.

Authors:  Kyriakos Chatzopoulos; Sotiris Sotiriou; Andrea R Collins; Panagiotis Kartsidis; Alessandra C Schmitt; Xianfeng Chen; Khashayarsha Khazaie; Michael L Hinni; Colleen A Ramsower; Matthew A Zarka; Samir H Patel; Joaquin J Garcia
Journal:  Head Neck Pathol       Date:  2020-10-03
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