Staging the cancer ecosystem: Survival data from a registry study of patients with active cancer.

Abstract

e13505 Background: Predicting cancer evolutionary trajectories remains an unmet goal for current cancer staging systems. Understanding the influence of selection pressures operating in the host-cancer environment and capable of effecting neoplastic evolution may be a means of informing such predictions. Methods: An IRB-approved cancer ecology registry study was begun, recruiting subjects whose cancer required active treatment. A set of 22 clinical and laboratory parameters obtained at time of entry onto the registry were compiled into eight separate profiles ( tumor microenvironment, inflammation, energy balance, psychosocial stress, GI microbiome, endocrine, skeletal remodeling, mutagenic) to help define a subjects’ ecological landscape. Parameters were chosen based on previous evidence of selection influence and scored using a trichotimzation of data (0, 1, 2). Resulting quantitative profiles from each subject were then aggregated using a geometric figure, an octomer, (an ‘ecogram’), length of vertices representing individual profile scores and whose net area, bounded by the ecogram, it is hypothesized will reflect strength of net selection pressure occurring at the level of the whole-patient. Survival data from the enrolled registry subjects was then correlated with ecogram area. Results: Complete ecological assessments were obtained in 15 subjects participating in the registry. Resulting ecograms demonstrated considerable variation among participants both in derived ecogram area of over 12-fold (range 0-12.7 arbitrary units, mean 4.7±2.9) as well as in morphologic appearance suggesting sensitivity and specificity for strength and character of active selection pressures. Overall survival for registry participants ranged from 14-198 months (median 47 mos.). For 12 subjects with advanced stage disease, survival from time of initial cancer diagnosis demonstrated a moderate degree of inverse correlation with ecogram area (r = -.38, R2= 0.144). Conclusions: A method for making a quantitative ecological assessment of patients with active cancer demonstrated both sensitivity and specificity for differences among participants in a cancer ecology registry study. Overall survival among subjects with advanced disease demonstrated inverse correlation with ecogram area supporting further study to predict cancer evolutionary tendency.