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Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome.

ABSTRACT: BACKGROUND:Tumor budding, meaning a detachment of tumor cells at the invasion front of colorectal carcinoma (CRC) into single cells or clusters (<=5 tumor cells), has been shown to correlate to an inferior clinical outcome by several independent studies. Therefore, it has been discussed as a complementary prognostic factor to the TNM staging system, and it is already included in national guidelines as an additional prognostic parameter. However, its application by manual evaluation in routine pathology is hampered due to the use of several slightly different assessment systems, a time-consuming manual counting process and a high inter-observer variability. Hence, we established and validated an automatic image processing approach to reliably quantify tumor budding in immunohistochemically (IHC) stained sections of CRC samples. METHODS:This approach combines classical segmentation methods (like morphological operations) and machine learning techniques (k-means and hierarchical clustering, convolutional neural networks) to reliably detect tumor buds in colorectal carcinoma samples immunohistochemically stained for pan-cytokeratin. As a possible application, we tested it on whole-slide images as well as on tissue microarrays (TMA) from a clinically well-annotated CRC cohort. RESULTS:Our automatic tumor budding evaluation tool detected the absolute number of tumor buds per image with a very good correlation to the manually segmented ground truth (R2 value of 0.86). Furthermore the automatic evaluation of whole-slide images from 20 CRC-patients, we found that neither the detected number of tumor buds at the invasion front nor the number in hotspots was associated with the nodal status. However, the number of spatial clusters of tumor buds (budding hotspots) significantly correlated to the nodal status (p-value?=?0.003 for N0 vs. N1/N2). TMAs were not feasible for tumor budding evaluation, as the spatial relationship of tumor buds (especially hotspots) was not preserved. CONCLUSIONS:Automatic image processing is a feasible and valid assessment tool for tumor budding in CRC on whole-slide images. Interestingly, only the spatial clustering of the tumor buds in hotspots (and especially the number of hotspots) and not the absolute number of tumor buds showed a clinically relevant correlation with patient outcome in our data.

SUBMITTER: Weis CA

PROVIDER: S-EPMC6114534 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome.

Weis Cleo-Aron CA Kather Jakob Nikolas JN Melchers Susanne S Al-Ahmdi Hanaa H Pollheimer Marion J MJ Langner Cord C Gaiser Timo T

Diagnostic pathology 20180828 1

<h4>Background</h4>Tumor budding, meaning a detachment of tumor cells at the invasion front of colorectal carcinoma (CRC) into single cells or clusters (<=5 tumor cells), has been shown to correlate to an inferior clinical outcome by several independent studies. Therefore, it has been discussed as a complementary prognostic factor to the TNM staging system, and it is already included in national guidelines as an additional prognostic parameter. However, its application by manual evaluation in ro ...[more]

PMID: 30153844

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Project description:Budding at the tumor invasive front has been correlated with the malignant properties of many cancers. Malic enzyme 1 (ME1) promotes the Warburg effect in cancer cells and induces epithelial-mesenchymal transition (EMT) in oral squamous cell carcinoma (OSCC). Therefore, we investigated the role of ME1 in tumor budding in OSCC. Tumor budding was measured in 96 human OSCCs by immunostaining for an epithelial marker (AE1/AE3), and its expression was compared with that of ME1. A significant correlation was observed between tumor budding and ME1 expression. The correlation increased with the progression of cancer. In human OSCC cells, lactate secretion decreased when lactate fermentation was suppressed by knockdown of ME1 and lactate dehydrogenase A or inhibition of pyruvate dehydrogenase (PDH) kinase. Furthermore, the extracellular pH increased, and the EMT phenotype was suppressed. In contrast, when oxidative phosphorylation was suppressed by PDH knockdown, lactate secretion increased, extracellular pH decreased, and the EMT phenotype was promoted. Induction of chemical hypoxia in OSCC cells by CoCl2 treatment resulted in increased ME1 expression along with HIF1? expression and promotion of the EMT phenotype. Hypoxic conditions also increased matrix metalloproteinases expression and decreased mitochondrial membrane potential, mitochondrial oxidative stress, and extracellular pH. Furthermore, the hypoxic treatment resulted in the activation of Yes-associated protein (YAP), which was abolished by ME1 knockdown. These findings suggest that cancer cells at the tumor front in hypoxic environments increase their lactate secretion by switching their energy metabolism from oxidative phosphorylation to glycolysis owing to ME1 overexpression, decrease in extracellular pH, and YAP activation. These alterations enhance EMT and the subsequent tumor budding. Tumor budding and ME1 expression are thus considered useful markers of OSCC malignancy, and ME1 is expected to be a relevant target for molecular therapy.

Dataset Information

Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome.

Publications

Automatic evaluation of tumor budding in immunohistochemically stained colorectal carcinomas and correlation to clinical outcome.

Similar Datasets

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