Abstract

Simple SummaryExosomal miRNAs are associated with colorectal cancer liver metastasis (CRLM)-related biological behavior and prognosis. However, an exosomal miRNA signature predicting postoperative survival and the value of adjuvant chemotherapy for CRLM remains elusive. Using miRNA sequencing and the LASSO model, we constructed an miRNA signature comprising four exosomes. The signature showed a good predictive performance for patient outcome and the advantage of adjuvant chemotherapy after hepatectomy in two institutions’ training and validation cohorts. In addition, we found that the four miRNAs could target signaling molecules playing crucial roles in colorectal cancer metastasis, vesicle-related processing, and T cell activation. Furthermore, the exosomal miRNA score also increased with the decreasing Immunoscore. We believe that our signature can predict the prognosis and guide adjuvant chemotherapy decisions after liver metastasectomy in CRLM patients, further improving the predictive performance of the current CRLM predictive model system.Background: The clinical risk score (CRS) for prediction and treatment decision in colorectal liver metastasis (CRLM) is important, but imprecise. Exosomal miRNAs play critical roles in CRLM-related biological behavior. However, an exosomal miRNA score system for predicting posthepatectomy survival and the adjuvant chemotherapy benefit of CRLM remains elusive. Methods: miRNA sequencing was used to identify differentially expressed miRNAs, and the LASSO model was used to select miRNAs to construct the intent model. The predictive performance of the model was evaluated by the area under the ROC curve (AUC) in the training, internal validation, and external validation cohorts. Results: Sixteen differentially expressed exosomal miRNAs were identified, and four miRNAs were selected for model construction. Our model performed well in predicting prognosis with five-year AUCs of 0.70 (95% CI: 0.59–0.81), 0.70 (0.61–0.81), and 0.72 (057–0.86) in the training, internal, and external validation cohorts, respectively. miRNA classifier high-risk patients had better survival benefit from adjuvant chemotherapy regardless of CRS. All four miRNAs target signaling molecules play crucial roles in colorectal cancer metastasis, vesicle-related processing, and T cell activation. It also negatively correlated with the liver metastasis Immunoscore. Conclusion: We developed a circulating exosomal miRNA signature that can predict the prognosis and guide adjuvant chemotherapy decisions after hepatectomy in CRLM.

Highlights

  • Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death [1]

  • We brought forward an exosomal miRNA signature based on the levels of circulating exosomal miR-6087, miR132-5p, miR-93-3p, and miR-320d, which showed good performance in predicting colorectal liver metastasis (CRLM)

  • Our results suggest that this exosomal miRNA signature can potentially predict the prognosis and guide adjuvant chemotherapy decision for CRLM patients following hepatectomy

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Summary

Introduction

Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related death [1]. Despite the advances in hepatectomy and adjuvant therapies, the five-year survival rate of colorectal cancer liver metastases (CRLM) remains only 25–50% [4]. The clinical risk score (CRS) for prediction and treatment decision in colorectal liver metastasis (CRLM) is important, but imprecise. An exosomal miRNA score system for predicting posthepatectomy survival and the adjuvant chemotherapy benefit of CRLM remains elusive. Our model performed well in predicting prognosis with five-year AUCs of 0.70 (95% CI: 0.59–0.81), 0.70 (0.61–0.81), and 0.72 (057–0.86) in the training, internal, and external validation cohorts, respectively. All four miRNAs target signaling molecules play crucial roles in colorectal cancer metastasis, vesicle-related processing, and T cell activation. It negatively correlated with the liver metastasis

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Conclusion

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