A Liquid Biopsy Assay for Noninvasive Identification of Lymph Node Metastases in T1 Colorectal Cancer.

ABSTRACT Background & Aims We recently reported use of tissue-based transcriptomic biomarkers (miRNA or mRNA) for identification of lymph node metastasis (LNM) in patients with invasive submucosal colorectal cancers (T1 CRC). In this study, we translated our tissue-based biomarkers into a blood-based liquid biopsy assay for noninvasive detection of LNM in patients with high-risk T1 CRC. Methods We analyzed 330 specimens from patients with high-risk T1 CRC, which included 188 serum samples from two clinical cohorts (training cohort: n=46, validation cohort: n=142) and matched FFPE samples (n=142). We performed RT-qPCR followed by logistic regression analysis to develop an integrated transcriptomic panel and establish a risk-stratification model, combined with clinical risk factors. Results We used comprehensive expression profiling of a training cohort of LNM-positive and -negative serum specimens to identify an optimized transcriptomic panel of four miRNAs (miR-181b, miR-193b, miR-195, miR-411) and five mRNAs (AMT, FOXA1, PIGR, MMP1, MMP9), which robustly identified patients with LNM (area under the curve [AUC]=0.86, 95% CI=0.72–0.94). We validated panel performance in an independent validation cohort (AUC=0.82, 95% CI=0.74–0.88). Our risk-stratification model was more accurate than the panel and an independent predictor for identification of LNM (AUC=0.90, Univariate: odds ratio [OR]=37.17, 95% CI=4.48–308.35, P Conclusions A novel risk-stratification model for noninvasive identification of T1 CRC has the potential to avoid unnecessary surgeries for patients classified as high-risk by conventional risk-classification criteria.