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Measuring intratumoral vessel density using automated image analysis

Digital scanning of slides labelled via IHC / ISH and subsequent automated algorithm driven image analysis are crucial tools in generating standardised and robust quantitative data from pre-clinical studies and clinical trials. In this study, Mezheyeuski et al. utilised digital image analysis to analyse the intratumoral vessel density within specified regions of resected colon and TMA sections of colon tumour.

Following mesocolic excision, recurrence in stage II and III colorectal cancer is currently a regular event, with up to a quarter of patients in stage II and almost every other patient in stage III patients suffering further oncological progression.

There is need for the identification of better criteria in deciding which patients will benefit from post-surgery adjuvant therapy (5FU fluorouracil). The impact of tumour vessel characteristics on drug delivery and sensitivity to chemotherapy has been suggested by previous trials.

Tissue sourced from 2 unique groups. 1) ‘Discovery’ cohort - resected colorectal tumours from clinical trial evaluating efficacy of 5FU - randomised to either surgery alone or surgery followed by adjuvant 5FU Chemotherapy. 2) ‘Validation’ cohort – TMA FFPE blocks from stage II/III colorectal cancer – all treated with adjuvant therapy according to ESMO guidelines.

Dual IHC Labelling performed on all samples. Vessels labelled with CD34 and tumour stroma labelled with PDGFR‑β. All slides were scanned and saved as digital image files using Aperio Scanscope software.

3 separate tissue regions were identified microscopically and digitally highlighted. These were tumour centre, invasive margin and peritumoral stroma. Digital images from each of these regions were then analysed using automated image analysis algorithms to define the total tissue area, stromal area and vessel quantity for each selected region. Areas of necrotic tissue and empty space were manually removed from the analysis.

For each of the 3 regions, 2 vessel density values were calculated: number of vessels per analysed total tissue area (Vessel density tissue - VDT) and number of vessels per tumour stroma area (Vessel density stroma - VDS). This allowed 6 VD metrics per case to be generated (VDT TC, VDT IM, VDT PERI, VDS TC, VDS IM and VDS PERI) to allow focus on specific regions within the tumour.

Vessel density data was correlated to TTR (time to recurrence – surgery to first record of disease progression and OS (Overall survival – surgery to death).

Within the ‘Discovery’ cohort, a significant benefit of adjuvant 5FU therapy was seen in the VDS IM group using TTR as the endpoint. The result was very similar using OS as the endpoint.

Within the ‘Validation’ cohort, the VDS IM data was very similar to that in the ‘Discovery’ cohort but marginally missed out on a statistically significant result. Analyses from both cohorts however, indicated that the stroma normalised vessel density metric (VDS) performs better as a biomarker in this instance than total vessel density (VDT) These analyses identified high sample VDS as a potential biomarker for a stage II/III colon cancer subset most likely to benefit from post-surgery adjuvant 5FU therapy with the strongest data from the region VDS IM.

Vascular profiling is becoming increasingly involved in developing a predictive vascular biomarker of clinical relevance. This study highlights the biological importance of intratumoral vessel density and the importance that automated image analysis has in this research.


Mezheyeuski et al. 2019 Stroma-normalised vessel density predicts benefit from adjuvant fluorouracil-based chemotherapy in patients with stage II/III colon cancer. British Journal of Cancer DOI: 10.1038/s41416-019-0519-1

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