Development of a reliable and accurate algorithm to quantify the tumor immune stroma (QTiS) across tumor types
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Rainer Christoph Miksch1,*, Jingcheng Hao1,*, Markus Bo Schoenberg1,*, Katharina Dötzer1, Friederike Schlüter1, Maximilian Weniger1, Shuai Yin1, Steffen Ormanns2, Jan Goesta D’Haese1, Markus Otto Guba1, Jens Werner1,3, Barbara Mayer1 and Alexandr V. Bazhin1,3
1Department of General, Visceral and Transplantation Surgery, Ludwig-Maximilians University, Munich, Germany
2Department of Pathology, Ludwig-Maximilians University, Munich, Germany
3German Cancer Consortium (DKTK), Partner Site Munich, Germany
*These authors contributed equally to this work
Markus Bo Schoenberg, email: [email protected]
Keywords: tumor-infiltrating lymphocytes; colorectal cancer; ovarian cancer; hepatocellular carcinoma; pancreatic cancer
Received: August 08, 2017 Accepted: November 05, 2017 Published: December 04, 2017
The tumor microenvironment plays an important role in the tumor biology. Overall survival of tumor patients after resection is influenced by tumor-infiltrating lymphocytes (TILs) as a component of the tumor stroma. However, it is not clear how to assess TILs in the tumor stroma due to heterogeneous methods in different cancer types. Therefore, we present a novel Quantification of the Tumor immune Stroma (QTiS) Algorithm to reliably and accurately quantify cells in the tumor stroma. Immunohistochemical staining of CD3 and CD8 cells in sections of metastatic colorectal cancer (mCRC), ovarian cancer (OvCa), hepatocellular carcinoma (HCC), and pancreatic ductal adenocarcinoma (PDAC), alltogether N = 80, was performed. Hot spots of infiltrating immune cells are reported in the literature. Reliability of the hot spot identification of TILs was examined by two blinded observers. Accuracy was tested in 1 and 3 hot spots using computed counting methods (ZEN 2 software counting (ZC), ImageJ software with subjective threshold (ISC) and ImageJ with color deconvolution (IAC)) and compared to manual counting. All tumor types investigated showed an accumulation of TILs in the tumor stroma (peri- and intratumoral). Reliability between observers indicated a high level consistency. Accuracy for CD8+/CD3+ ratio and absolute cell count required 1 and 3 hot spots, respectively. ISC was found to be the best for paraffin sections, whereas IAC was ideal for frozen sections. ImageJ software is cost-effective and yielded the best results. In conclusion, an algorithm for quantification of tumoral stroma could be established. With this QTiS Algorithm counting of tumor stromal cells is reliable, accurate, and cost-effective.
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