A Panel of Tumor Biomarkers to Predict Complete Pathological Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer

Abstract

Pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer patients is related to a favorable prognosis. The identification of early biomarkers predictive of pathological complete response would help to optimize the multimodality management of the patients. A panel of 11 tumor-related proteins was investigated by immunohistochemistry in the pre-treatment biopsy of a group of locally advanced rectal cancer patients, to identify early biomarkers of pathological complete response to neoadjuvant chemoradiotherapy. A mono-institutional retrospective cohort of 95 stage II/III locally advanced rectal cancer patients treated with neoadjuvant chemoradiotherapy and surgery was selected based on clinical-pathological characteristics and the availability of a pre-treatment tumor biopsy. Eleven selected protein markers expression (MLH1, GLUT1, Ki67, CA-IX, CXCR4, COX2, CXCL12, HIF1, VEGF, CD44, and RAD51) was investigated. The optimal cut-off values were calculated by receiver operating characteristic curve analysis. Classification and regression tree analysis was performed to investigate the biomarkers interaction. Patients presenting either Ki67, HIF1 or RAD51 below the cut-off value, or CXCR4 or COX2 above the cut-off value, were more likely to get a pathological complete response. Classification and regression tree analysis identified three groups of patients resulting from the combination of Ki67 and CXCR4 expression. Patients with high expression of Ki67 had the lowest chance to get a pathological complete response (18%), as compared to patients with low expression of both Ki67 and CXCR4 (29%), and patients with low Ki67 and high CXCR4 expression (70%). Pre-treatment Ki67, CXCR4, COX2, HIF1, RAD51 in tumor biopsies are associated with pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer. A combined evaluation of Ki67 and CXCR4 would increase their predictive potential. If validated, their optimal cut-off could be used to select patients for a tailored multi-modality treatment.

Predicting response to neoadjuvant chemoradiotherapy in rectal cancer: from biomarkers to tumor models

“…Other studies used a combination of different protein markers to improve the response prediction. For instance, Dalle Fratte et al 91 determined protein levels of a panel of 11 cancer-related proteins by immunohistochemistry and found that the combination of low Ki67 and high CXCR4 levels had the highest predictive potential. To obtain a more global view of altered protein levels, proteomic methods were applied to identify predictive protein signatures in pretreatment tumor tissue.…”

Biomarkers for Predicting the Response to Radiation-Based Neoadjuvant Therapy in Rectal Cancer

“…Herein, we focus mainly on newly identified proteins from biopsies and blood which were mainly listed in Table 4 (Ref. [73][74][75][76][77][78][79][80][81][82][83][84]).…”

“…These proteins are thought to contribute to radio-resistance in an IL-4-mediated signalling pathway by downregulating γ-H2AX expression and modifying the progression of cell apoptosis and proliferation [82]. Fratte et al [83] investigated the expression of 11 tumour-related proteins (RAD51, CD44, HIF1, CXCR4, COX2, Ki67, GLUT1, CA-IX, VEGF, CXCL12, and MLH1) in pre-nCRT tissue biopsies of RC patients. These authors report that pre-treatment expression levels of RAD51, HIF1, CXCR4, COX2 and Ki67 were predictors of the response to nCRT.…”