Utility of ctDNA in predicting response to neoadjuvant chemoradiotherapy and prognosis assessment in locally advanced rectal cancer: A prospective cohort study

Author summary Why was this study done? For patients with locally advanced rectal cancer (LARC) who achieve clinical complete response (cCR) after neoadjuvant chemoradiotherapy (nCRT), a "Watch and Wait" (W&W) strategy can be used to improve the quality of life of these patients. cCR does not necessarily mean pathological complete response (pCR) or the absence of minimal residual disease (MRD). Patients with MRD who receive W&W approach may have a high risk for local recurrence and distance metastasis. There are no reliable biomarkers for the prediction of pCR/non-pCR currently. Circulating tumor DNA (ctDNA) is a cell-free DNA derived from tumor cells and has been proven to be a sensitive biomarker for tumor burden. ctDNA testing alone or combining with magnetic resonance imaging (MRI) may improve the prediction of pCR/non-pCR, thereby guiding patient selection for "W&W" approach. ctDNA may also be used for the postoperative risk stratification in LARC patients receiving nCRT and surgery. What did the researchers do and find? We conducted a prospective cohort study including 119 LARC patients undergoing nCRT followed by total mesorectal excision (TME). We collected 531 serial plasma samples at baseline, during nCRT, and after surgery and performed next-generation sequencing using a panel containing 422 cancer-related genes. We found that baseline ctDNA features, as well as the clearance of ctDNA during nCRT, were significantly correlated with pCR status. By establishing predictive models based on ctDNA alone, MRI alone, and combination of ctDNA and MRI, we found that the performance of the combining model in predicting pCR/non-pCR was significantly better than ctDNA alone or MRI alone. We also demonstrated that ctDNA testing combining with high-risk pathological features could achieve better risk stratification for postoperative recurrence. What do these findings mean? Combining ctDNA testing with MRI can improve the prediction of pCR/non-pCR after nCRT, identify patients with MRD, and help patient selection for W&W strategy. ctDNA can be used in recurrence risk assessment and stratification in patients receiving nCRT and surgery. The findings from this study should be validated in larger studies. Moreover, whether utility of ctDNA in patient selection for W&W strategy can reduce local regrowth (LR) or distant metastasis (DM) in the patients also needs clinical trial to confirm. Background For locally advanced rectal cancer (LARC) patients who receive neoadjuvant chemoradiotherapy (nCRT), there are no reliable indicators to accurately predict pathological complete response (pCR) before surgery. For patients with clinical complete response (cCR), a "Watch and Wait" (W&W) approach can be adopted to improve quality of life. However, W&W approach may increase the recurrence risk in patients who are judged to be cCR but have minimal residual disease (MRD). Magnetic resonance imaging (MRI) is a major tool to evaluate response to nCRT; however, its ability to predict pCR needs to be improved. In this prospective cohort study, we explored the value of circulating tumor DNA (ctDNA) in combination with MRI in the prediction of pCR before surgery and investigated the utility of ctDNA in risk stratification and prognostic prediction for patients undergoing nCRT and total mesorectal excision (TME). Methods and findings We recruited 119 Chinese LARC patients (cT3-4/N0-2/M0; median age of 57; 85 males) who were treated with nCRT plus TME at Fudan University Shanghai Cancer Center (China) from February 7, 2016 to October 31, 2017. Plasma samples at baseline, during nCRT, and after surgery were collected. A total of 531 plasma samples were collected and subjected to deep targeted panel sequencing of 422 cancer-related genes. The association among ctDNA status, treatment response, and prognosis was analyzed. The performance of ctDNA alone, MRI alone, and combining ctDNA with MRI was evaluated for their ability to predict pCR/non-pCR. Ranging from complete tumor regression (pathological tumor regression grade 0; pTRG0) to poor regression (pTRG3), the ctDNA clearance rate during nCRT showed a significant decreasing trend (95.7%, 77.8%, 71.1%, and 66.7% in pTRG 0, 1, 2, and 3 groups, respectively, P = 0.008), while the detection rate of acquired mutations in ctDNA showed an increasing trend (3.8%, 8.3%, 19.2%, and 23.1% in pTRG 0, 1, 2, and 3 groups, respectively, P = 0.02). Univariable logistic regression showed that ctDNA clearance was associated with a low probability of non-pCR (odds ratio = 0.11, 95% confidence interval [95% CI] = 0.01 to 0.6, P = 0.04). A risk score predictive model, which incorporated both ctDNA (i.e., features of baseline ctDNA, ctDNA clearance, and acquired mutation status) and MRI tumor regression grade (mrTRG), was developed and demonstrated improved performance in predicting pCR/non-pCR (area under the curve [AUC] = 0.886, 95% CI = 0.810 to 0.962) compared with models derived from only ctDNA (AUC = 0.818, 95% CI = 0.725 to 0.912) or only mrTRG (AUC = 0.729, 95% CI = 0.641 to 0.816). The detection of potential colorectal cancer (CRC) driver genes in ctDNA after nCRT indicated a significantly worse recurrence-free survival (RFS) (hazard ratio [HR] = 9.29, 95% CI = 3.74 to 23.10, P < 0.001). Patients with detectable driver mutations and positive high-risk feature (HR_feature) after surgery had the highest recurrence risk (HR = 90.29, 95% CI = 17.01 to 479.26, P < 0.001). Limitations include relatively small sample size, lack of independent external validation, no serial ctDNA testing after surgery, and a relatively short follow-up period. Conclusions The model combining ctDNA and MRI improved the predictive performance compared with the models derived from individual information, and combining ctDNA with HR_feature can stratify patients with a high risk of recurrence. Therefore, ctDNA can supplement MRI to better predict nCRT response, and it could potentially help patient selection for nonoperative management and guide the treatment strategy for those with different recurrence risks.