Details

Autor(en) / Beteiligte

• Dum, David
• Henke, Tjark L C
• Mandelkow, Tim
• Yang, Cheng
• Bady, Elena
• Raedler, Jonas B
• Simon, Ronald
• Sauter, Guido
• Lennartz, Maximilian
• Büscheck, Franziska
• Luebke, Andreas M
• Menz, Anne
• Hinsch, Andrea
• Höflmayer, Doris
• Weidemann, Sören
• Fraune, Christoph
• Möller, Katharina
• Lebok, Patrick
• Uhlig, Ria
• Bernreuther, Christian
• Jacobsen, Frank
• Clauditz, Till S
• Wilczak, Waldemar
• Minner, Sarah
• Burandt, Eike
• Steurer, Stefan
• Blessin, Niclas C

Titel

Semi-automated validation and quantification of CTLA-4 in 90 different tumor entities using multiple antibodies and artificial intelligence

Ist Teil von

• Laboratory investigation, 2022-06, Vol.102 (6), p.650-657

Ort / Verlag

United States: Nature Publishing Group

Erscheinungsjahr

2022

Quelle

MEDLINE

Beschreibungen/Notizen

• CTLA-4 is an inhibitory immune checkpoint receptor and a negative regulator of anti-tumor T-cell function. This study is aimed for a comparative analysis of CTLA-4 cells between different tumor entities. To quantify CTLA-4 cells, 4582 tumor samples from 90 different tumor entities as well as 608 samples of 76 different normal tissue types were analyzed by immunohistochemistry in a tissue microarray format. Two different antibody clones (MSVA-152R and CAL49) were validated and quantified using a deep learning framework for automated exclusion of unspecific immunostaining. Comparing both CTLA-4 antibodies revealed a clone dependent unspecific staining pattern in adrenal cortical adenoma (63%) for MSVA-152R and in pheochromocytoma (67%) as well as hepatocellular carcinoma (36%) for CAL49. After automated exclusion of non-specific staining reaction (3.6%), a strong correlation was observed for the densities of CTLA-4 lymphocytes obtained by both antibodies (r = 0.87; p < 0.0001). A high CTLA-4 cell density was linked to low pT category (p < 0.0001), absent lymph node metastases (p = 0.0354), and PD-L1 expression in tumor cells or inflammatory cells (p < 0.0001 each). A high CTLA-4/CD3-ratio was linked to absent lymph node metastases (p = 0.0295) and to PD-L1 positivity on immune cells (p = 0.0026). Marked differences exist in the number of CTLA-4 lymphocytes between tumors. Analyzing two independent antibodies by a deep learning framework can facilitate automated quantification of immunohistochemically analyzed target proteins such as CTLA-4.