Image analysis-derived metrics of histomorphological complexity predicts prognosis and treatment response in stage II-III colon cancer.

Mezheyeuski A, Hrynchyk I, Karlberg M, Portyanko A, Egevad L, Ragnhammar P, Edler D, Glimelius B, Östman A

Sci Rep 6 (-) 36149 [2016-11-02; online 2016-11-02]

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 "αmax" -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.

Tissue Profiling [Service]

QC bibliography QC xrefs

PubMed 27805003

DOI 10.1038/srep36149

Crossref 10.1038/srep36149

srep36149

pmc PMC5095346

Laboratories for Chemical Biology at Karolinska Institutet (LCBKI)