The possibility of evaluation mRNA expression profiling to predict progression of local stage colorectal cancer

Abstract

Progression assessment enables implementation of the colorectal cancer (CRC) tertiary prevention measures aimed at early detection and timely treatment of metastatic cancer. The study was aimed to develop a model of CRC progression using pathomorphological and molecular genetic characteristics of tumors. Relative expression of mRNAs of 63 genes from various functional groups was determined in the tumor specimens of 223 patients with stage T1–4N0–2M0 CRC. The median follow-up period was 42 months. Binary logistic regression models were constructed, in which likelihood of progression within 36 months after the CRC diagnosis was a target variable. Explanatory variables were as follows: tumor grade, angiolymphatic invasion, ratio of the number of metastatic lymph nodes to the total number of lymph nodes in the surgical specimen, patient’s age and tumor localization, as well as expression levels of genes CCNB1, Ki67, GRB7, IGF1, Il2, Il6, Il8, GATA3. Prediction accuracy of the model using clinical and morphological characteristics was 56.6%. Inclusion of CCNB1, Ki67, GRB7, IGF1, Il2, Il6, Il8, GATA3 expression profiles in the model increased accuracy to 80.6%. Thus, prediction of CRC progression for treatment personalization requires additional parameters beyond information acquired within the framework of conventional morphological TNM classification. The use of molecular markers as predictors significantly increases the CRC progression prediction accuracy. Further research is needed for validation and quality improvement of prognostic models.