Utility of Circulating Free DNA Fragmentomics in the Prediction of Pathological Response after Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

• Published in: Clinical chemistry (Baltimore, Md.) Vol. 69; no. 1; pp. 88 - 99
• Main Authors: Wang, Yaqi, Fan, Xiaojun, Bao, Hua, Xia, Fan, Wan, Juefeng, Shen, Lijun, Wang, Yan, Zhang, Hui, Wei, Yulin, Wu, Xue, Shao, Yang, Li, Xinxiang, Xu, Ye, Cai, Sanjun, Zhang, Zhen
• Format: Journal Article
• Language: English
• Published: England 04.01.2023
• Subjects: Cell-Free Nucleic Acids - genetics; Chemoradiotherapy; DNA; Humans; Neoadjuvant Therapy; Rectal Neoplasms - drug therapy; Rectal Neoplasms - therapy; Retrospective Studies; Treatment Outcome
• ISSN: 0009-9147; 1530-8561; 1530-8561
• DOI: 10.1093/clinchem/hvac173

A "Watch and Wait" (W&W) approach has become an alternative to surgery for locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (nCRT). Precise prediction of pathological complete response (pCR) will improve patient selection for W&W. We investigated the utility of cell-free DNA (cfDNA) fragmentomics in predicting pCR. We recruited 119 LARC patients and evaluated nCRT response by pCR status and pathological or MRI tumor regression grade (mrTRG). Plasma samples before, during, and after nCRT were applied to deep targeted-panel sequencing, with 103 patients having complete samples. cfDNA fragment and 5'-end motif profiles were used to construct elastic-net logistic regression models to predict non-pCR. Predictive performance was measured by area under the receiver operator characteristic curve (AUC), sensitivity, and specificity. In the training cohort, the model based on 5'-end motif profile plus mrTRG achieved the highest cross-validation AUC (0.92, 95% CI, 0.91-0.93). The AUC in a testing cohort was 0.96 (95% CI, 0.90-1.00). The models based on 5'-end motif profile alone or in combination with mrTRG both maintained good predictive ability for patients without detectable circulating tumor DNA (AUC 0.94, 95% CI, 0.93-0.95; AUC 0.95, 95% CI, 0.94-0.96). In an external validation cohort, the model trained with a local 5'-end motif profile obtained an AUC of 0.878 (95% CI, 0.801-0.956) in discriminating colorectal cancer from healthy subjects. The combination of a 5'-end motif profile with mrTRG has the potential to predict the response to nCRT, and therefore may improve the patient selection for a W&W approach.