A55: PTMA, GLUT1, PFKFB3, BNIP3L, KCTD11 and DDB2 genes are potentially prediction markers for CCRT response of Taiwanese CRC patients

Shiu-Ru Lin1,Long-Sen Chang2

1Division of Medical Research, Fooyin University Hospital, Pingtung, Taiwan,2Institute of Biomedical Science, National Sun Yat-sen University, Kaohsiung, Taiwan

Presenting date: Monday 2 November
Presenting time: 12.20-13.10


Colorectal cancer (CRC) is a common gastrointestinal malignancy tumor. It often use radiation combined with chemotherapy (Concurrent Chemoradiation Therapy; CCRT) before surgery as the treatment for tumor tissue of patients with low CRC. However, response to CCRT differs among individual tumors. Therefore, applying the individual cancerous tissue variability of radiation sensitivity to predict CCRT efficacy before treatment will become an important reference for those patients in designing their own treatment plans.


In our study, we designed oligonucleotides fragment for 28 candidate genes, and identified the best concentration of oligonucleotide for each gene on chip by serial dilution. The peripheral blood samples of 66 CRC patients treated with preoperative CCRT were collected to test chips using weighted enzymatic chip array (WEnCA) platform to analyze CCRT-related genes expression of CRC patients by chip assay. Then we analyzed the association between the results of CCRT related gene expression and clinical efficacy of CCRT using statistical software.


Our preliminary results demonstrated that among the 28 CCRT candidate gene, 6 gene, PTMA (P =0.045), GLUT1 (P =0.001), PFKFB3 (P =0.045), BNIP3L (P =0.047), KCTD11 (P =0.038) and DDB2 (P =0.045) genes are significantly differentially expressed between CCRT response group and non- response group. PTMA, GLUT1 and PFKFB3 genes are overexpressed in CCRT non-response group, and BNIP3L, KCTD11 and DDB2 genes are overexpressed in CCRT response group. We also demonstrated that overexpression of DDB2 is related to lymphoid infiltration of cancer patients.


Further, based on the results of our study, we will validate the best combination of candidate genes and the most appropriate weighted value for each gene to establish the clinically useful CCRT efficacy prediction chip. It is not only improve the accuracy of prediction of CCRT efficacy, but also increase the survival rate and reduce the cancer recurrence.