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Image analysis-derived metrics of histomorphological complexity predicts prognosis and treatment response in stage II-III colon cancer
Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden.;Belarusian State Med Univ, Dept Pathol, Minsk, Byelarus..
City Clin Pathologoanat Bur, Minsk, Byelarus..
Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden..
Belarusian State Med Univ, Dept Pathol, Minsk, Byelarus..
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2016 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, 36149Article in journal (Refereed) Published
Abstract [en]

The complexity of tumor histomorphology reflects underlying tumor biology impacting on natural course and response to treatment. This study presents a method of computer-aided analysis of tissue sections, relying on multifractal (MF) analyses, of cytokeratin-stained tumor sections which quantitatively evaluates of the morphological complexity of the tumor-stroma interface. This approach was applied to colon cancer collection, from an adjuvant treatment randomized study. Metrics obtained with the method acted as independent markers for natural course of the disease, and for benefit of adjuvant treatment. Comparative analyses demonstrated that MF metrics out-performed standard histomorphological features such as tumor grade, budding and configuration of invasive front. Notably, the MF analyses-derived "alpha(max)" -metric constitutes the first response-predictive biomarker in stage II-III colon cancer showing significant interactions with treatment in analyses using a randomized trial-derived study population. Based on these results the method appears as an attractive and easy-to-implement tool for biomarker identification.

Place, publisher, year, edition, pages
2016. Vol. 6, 36149
National Category
Cancer and Oncology
URN: urn:nbn:se:uu:diva-308895DOI: 10.1038/srep36149ISI: 000386725900001PubMedID: 27805003OAI: diva2:1051300
Swedish Cancer Society
Available from: 2016-12-01 Created: 2016-12-01 Last updated: 2016-12-01Bibliographically approved

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