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Histopathology research quickly evolves thanks to advances in whole slide imaging (WSI) and artificial intelligence (AI). However, existing WSI viewers are tailored either for clinical or research environments, but none suits both. This hinders the adoption of new methods and communication between the researchers and clinicians. The paper presents xOpat, an open‐source, browser‐based WSI viewer that addresses these problems. xOpat supports various data sources, such as tissue images, pathologists' annotations, or additional data produced by AI models. Furthermore, it provides efficient rendering of multiple data layers, their visual representations, and tools for annotating and presenting findings. Thanks to its modular, protocol‐agnostic, and extensible architecture, xOpat can be easily integrated into different environments and thus helps to bridge the gap between research and clinical practice. To demonstrate the utility of xOpat, we present three case studies, one conducted with a developer of AI algorithms for image segmentation and two with a research pathologist. [ABSTRACT FROM AUTHOR]

Background: Various markers are used to identify the unique sub-population of breast cancer cells with stem cell properties. Whether these markers are expressed in all breast cancers, identify the same population of cells, or equate to therapeutic response is controversial.Methods: We investigated the expression of multiple cancer stem cell markers in human breast cancer samples and cell lines in vitro and in vivo, comparing across and within samples and relating expression with growth and therapeutic response to doxorubicin, docetaxol and radiotherapy.Results: CD24, CD44, ALDH and SOX2 expression, the ability to form mammospheres and side-population cells are variably present in human cancers and cell lines. Each marker identifies a unique rather than common population of cancer cells. In vivo, cells expressing these markers are not specifically localized to the presumptive stem cell niche at the tumour/stroma interface. Repeated therapy does not consistently enrich cells expressing these markers, although ER-negative cells accumulate.Conclusions: Commonly employed methods identify different cancer cell sub-populations with no consistent therapeutic implications, rather than a single population of cells. The relationships of breast cancer stem cells to clinical parameters will require identification of specific markers or panels for the individual cancer. [ABSTRACT FROM AUTHOR]

Objectives: Development and metastases of colorectal cancer (CRC) are characterized by multiple genetic alterations. MicroRNAs (miRNAs) are endogenously expressed regulatory noncoding RNAs. Previous, mainly preclinical studies showed altered expression levels of several miRNAs in CRC. Methods: In our study, the expression levels of miR-21, miR-31, miR-143 and miR-145 in 29 primary colorectal carcinomas and 6 non-tumor adjacent tissue specimens were examined by real-time polymerase chain reaction. miRNA expression levels were also correlated with commonly used clinicopath-ologic features of CRC. Results: Expression levels of analyzed miRNAs significantly differed among tumors and adjacent non-tumor tissues: miR-21 (p = 0.0001) and miR-31 (p = 0.0006) were upregulated, and miR-143 (p = 0.011) and miR-145 (p = 0.003) were downregulated in tumors. For the first time, a high expression of miR-21 was associated with lymph node positivity (p = 0.025) and the development of distant metastases (p = 0.009) in CRC patients. Thus, expression of miR-21 correlated with CRC clinical stage (p = 0.032). Furthermore, tumors >50 mm in maximal tumor diameter were characterized by lower expression of miR-143 (p = 0.006) and miR-145 (p = 0.003). We found no correlation between analyzed miRNAs and serum levels of carcinoembryonic antigen. Conclusion: Our results suggest possible roles of miR-21, miR-31, miR-143 and miR-145 in CRC. Copyright © 2008 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]