Digital pathology has made it possible to measure microscopic objects, such as blood vessels in tumor tissue and then visualize them in density maps, showing hotspot regions. But for many applications in histopathology, there is no clear-cut definition of the hotspots, say researchers from Heidelberg University in Germany. Thus, most tumor models “implicitly assume” that blood vessels are equally abundant in different parts of a tumor. But the researchers’ new computational approach to mapping angiogenesis in colorectal cancer (CRC) could change that assumption.
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Their method analyzes blood vessels based on spatial statistics, identifying all hotspot areas that are unlikely to occur by chance. The researchers found that in nearly all cases, the blood vessels grouped in a distinctive beltlike pattern. In 33 of 34 untreated colorectal tumor samples, the blood vessels were aggregated at the interface of tumor tissue to the intestinal wall. The researchers found similar “hypervascularized” zones at the boundaries of liver tissue in 100% of the samples of CRC liver metastases. Ultimately, they describe a new model of tumor vascularization: a highly vascularized zone about 1.5-mm wide close to the intestinal lumen in CRC primary tumors and a highly vascularized zone approximately 1-mm wide close to the invasion front in CRC liver metastases.
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Their model has immediate and far-reaching implications, the researchers say. For instance, because vascular patterns determine how chemotherapeutic drugs are distributed in tumor tissue, it is likely that these drugs reach the luminal side of CRC tumors much easier than they reach the the basolateral side. Their new information also could be used in timing surgery, since the tumor parts of the deep invasion front may be less sensitive to chemotherapy. The researchers suggest that using their model could help optimize treatment in any number of ways: explaining early symptoms like gastrointestinal bleeding, the architecture of CRC, metastasis, and opening new pathways for investigation.
Source:
Kather JN, Zöllner FG, Schad LR. PLoS One. 2017;12(3):e0171378.
doi: 10.1371/journal.pone.0171378.
