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

Abstract

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 "α_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.

Figure 1. Representative images from cases with low and high MF metrics scores.

Two tumors are shown after pan-cytokeratin staining and after completion of “contour-formation”. Cases are selected to illustrate low and high MF metrics scores. α_max and f(α)_max scores are shown as for ‘outline’-based and ‘internal structure’-bases image analyses.

Figure 2. Survival-associations for MF metrics and histomorphological scores in stage II-III colon cancer treated with surgery alone.

(A) Association between MF metrics (α_max and f(α)_max), histomorphological features and TTR. Cox regression analyses were used for determination of HRs. (B) Kaplan-Meier plots illustrating TTR of stage II-III colon cancer treated with surgery alone after median-based dichotomization of cases based on the f(α)_max metric. All MF metric-related analyses were performed with median-based dichotomization of cases into “metric-high” and “metric-low” groups.

Figure 3. Treatment-efficacy in MF-metric-defined subgroups of stage II-III colon cancer.

(Left and middle part) Kaplan-Meier plots illustrating TTR of stage II-III colon cancer patients receiving surgery alone (red lines) or surgery together with adjuvant chemotherapy after dichotomization of the study cohort based on α_max (upper part), or f(α)_max (lower part). Log-rank test was used for statistical analyses. (Right part) Interaction between MF metrics and treatment were analyzed using “formal interaction test”. All MF metric-related analyses were based on median-based dichotomization of cases into “metric-high” and “metric-low” groups.