Published online Feb 7, 2018. doi: 10.3748/wjg.v24.i5.631
Peer-review started: November 13, 2017
First decision: December 3, 2017
Revised: December 13, 2017
Accepted: December 19, 2017
Article in press: December 19, 2017
Published online: February 7, 2018
5-fluorouracil (5-FU) remains one of the most effective and commonly used chemotherapeutic agents in both adjuvant and palliative settings for advanced colorectal cancer (CRC). However, many CRC patients treated with 5-FU-based adjuvant chemotherapy not only fail to show an objective response to chemotherapy treatment but also suffer from side effects. Therefore, predictive markers are in urgent demand to identify whether patients can benefit from adjuvant chemotherapy.
Multiple studies have indicated that PIK3CA and TP53 mutation status was correlated with drug resistance of tumor cells. By analyzing the associations between mutation status of these two genes and overall survival (OS), we may be able to identify subgroups of patients who have a poor prognosis, which can help clinicians make suitable treatment of patients.
The objectives of this study were to detect gene mutations of PIK3CA and TP53 by using targeted next-generation sequencing (NGS) in a large cohort of CRC patients, and to investigate the predictive value of the mutational status of PIK3CA and TP53, alone or in combination.
A total of 315 patients with histologically proven CRC between 2007 and 2011 were retrospectively analyzed. Formalin-fixed paraffin-embedded lesion samples of the patients with curatively resected CRC were collected from the pathology department. Ten-μm-thick sections from FFPE tumor samples were used for DNA extraction with a QIAamp DNA FFPE Tissue kit (Qiagen). Targeted NGS was performed using the Ion Torrent platform to characterize the mutational spectrum of PIK3CA and TP53 genes. The distribution of gene mutation according to clinicopathologic variables was analyzed using Chi-square tests. The associations between mutation status of PIK3CA and TP53 and OS were evaluated using Cox proportional hazards models adjusted for clinicopathologic variables. The Kaplan-Meier method was performed to generate a survival curve, with significance evaluated using a log-rank test.
Among the 315 patients, the incidence of PIK3CA and TP53 mutations was 38.4% (n = 121) and 65.1% (n = 205), respectively. A significant difference was observed in the distribution of PIK3CA mutations according to tumor location (P = 0.036). The frequency of PIK3CA mutations in the proximal, distal, and rectum location was 50% (39/78), 38.7% (29/75), and 32.7% (53/162), respectively. The PIK3CA and/or TP53 mutation was detected in 177 out of 241 patients with stage II/III CRC receiving 5-FU-based adjuvant chemotherapy, of whom 54 had PIK3CA and TP53 double mutations. In both univariate and multivariate analyses, neither PIK3CA nor TP53 mutation was significantly correlated with OS. In Kaplan-Meier survival curve, patients with TP53 mutation had a worse clinical outcome than patients with wild-type TP53 (Log-rank P = 0.046). Compared with patients without PIK3CA and TP53 mutations, those with double PIK3CA-TP53 mutations had a significantly poorer OS (univariate HR = 2.21; 95%CI: 1.15-4.24; multivariate HR = 2.02; 95%CI: 1.04-3.91). In contrast, the presence of a single gene mutation, either PIK3CA or TP53, was not significantly associated with OS. The Kaplan-Meier curve showed that shorter OS was detected in patients harboring double PIK3CA and TP53 mutations (Log-rank P = 0.034). In Kaplan-Meier survival curve, patients harboring the PIK3CA mutation located in the kinase domain experienced a significantly shorter OS when compared with wild-type status (Log-rank P = 0.041).
This study is by far the first to report the predictive role of the combined mutation status of PIK3CA and TP53 in CRC patients receiving 5-FU-based adjuvant chemotherapy. Our data revealed that the double mutation of PIK3CA and TP53 is correlated with a shorter OS of stage II/III CRC patients receiving 5-FU-based therapy and hence serves as a novel biomarker to identify subgroups of patients who have poor clinical outcome, with potential clinical utility.