29P Plasma tumor-derived small extracellular vesicles microRNAs plus CA-125 objectively detect residual disease risk after surgical debulking in advanced ovarian cancer

Abstract

BackgroundNo residual disease after debulking surgery is the most critical independent prognostic factor for advanced ovarian cancer (AOC). There is an unmet clinical need for selecting primary or interval debulking surgery in AOC patients using existing prediction models such as CA-125, CT, PET-CT, or laparoscopy.MethodsIn this multiphase cohort study, 348 pre-treatment plasma and postsurgical tissue consecutive samples, and 272 patients were collected from four clinical centers. Circulating sEVs miRNAs profile associated with residual disease was revealed by RNA sequencing in AOC patients. MiRNAs expression was measured via TaqMan quantitative real-time PCR. The prediction model was established via the least absolute shrinkage and selection operator (LASSO), and logistic regression analysis based on the discovery-validation set. Plasma and tissue sEVs were captured by the magnetic bead sorting system (MACS) using cell-type-specific proteins as markers (EpCAM, FAP, CD45, CD235a, CD31).ResultsAfter analyzing a comprehensive plasma sEVs miRNAs profile in AOC, we identified and optimized a risk prediction model consisting of plasma sEVs-derived 4-miRNA (miR-320a-3p, miR-378a-3p, miR-1307-3p, let-7d-3p) and CA-125 (AUC:0.903; sensitivity:0.897; specificity:0.910; PPV:0.926; NPV:0.871). The quantitative evaluation of Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) suggested that the additional predictive power of the combined model was significantly improved contrasted with CA-125 or 4-miRNA alone (model vs CA-125, NRI=0.471, P<0.001; IDI=0.538, P<0.001; model vs 4-miRNA panel, NRI=0.122, P=0.001; IDI=0.185, P=0.003). Tumor cells-derived sEVs captured on EpCAM+ magnetic beads were the major vehicles affecting circulating sEVs 4-miRNA expressions. Moreover, the model index scores were significant differences between AOC and other confusable diseases (e.g., advanced colorectal cancer).ConclusionsA reliable and stable model of circulating tumor-derived sEVs 4-miRNA plus CA-125 was established for preoperatively anticipating the high-risk AOC patients of residual disease to optimize clinical therapy.Legal entity responsible for the studyJ. Tang.FundingThis work was supported by Grants from the General Project of Natural Science Foundation of Hunan Province (No. 2020JJ4051); Promotion Project of Health Suitability Program in Health Department of Hunan Province (No. WZ2020-15); Science and Technology Innovation Program of Hunan Province (No. 2020SK51101); Hunan Cancer Hospital Climbing Fund (No. ZX2020004); Capacity Building Project of Central Subsidy Medical and Health Institutions (No. 20201127-1001); Key Specialty Construction Project in Hunan Province (No. 20210826-1004); General Project in Health Department of Hunan Province (No. 202205015388).DisclosureThe author has declared no conflicts of interest. BackgroundNo residual disease after debulking surgery is the most critical independent prognostic factor for advanced ovarian cancer (AOC). There is an unmet clinical need for selecting primary or interval debulking surgery in AOC patients using existing prediction models such as CA-125, CT, PET-CT, or laparoscopy. No residual disease after debulking surgery is the most critical independent prognostic factor for advanced ovarian cancer (AOC). There is an unmet clinical need for selecting primary or interval debulking surgery in AOC patients using existing prediction models such as CA-125, CT, PET-CT, or laparoscopy. MethodsIn this multiphase cohort study, 348 pre-treatment plasma and postsurgical tissue consecutive samples, and 272 patients were collected from four clinical centers. Circulating sEVs miRNAs profile associated with residual disease was revealed by RNA sequencing in AOC patients. MiRNAs expression was measured via TaqMan quantitative real-time PCR. The prediction model was established via the least absolute shrinkage and selection operator (LASSO), and logistic regression analysis based on the discovery-validation set. Plasma and tissue sEVs were captured by the magnetic bead sorting system (MACS) using cell-type-specific proteins as markers (EpCAM, FAP, CD45, CD235a, CD31). In this multiphase cohort study, 348 pre-treatment plasma and postsurgical tissue consecutive samples, and 272 patients were collected from four clinical centers. Circulating sEVs miRNAs profile associated with residual disease was revealed by RNA sequencing in AOC patients. MiRNAs expression was measured via TaqMan quantitative real-time PCR. The prediction model was established via the least absolute shrinkage and selection operator (LASSO), and logistic regression analysis based on the discovery-validation set. Plasma and tissue sEVs were captured by the magnetic bead sorting system (MACS) using cell-type-specific proteins as markers (EpCAM, FAP, CD45, CD235a, CD31). ResultsAfter analyzing a comprehensive plasma sEVs miRNAs profile in AOC, we identified and optimized a risk prediction model consisting of plasma sEVs-derived 4-miRNA (miR-320a-3p, miR-378a-3p, miR-1307-3p, let-7d-3p) and CA-125 (AUC:0.903; sensitivity:0.897; specificity:0.910; PPV:0.926; NPV:0.871). The quantitative evaluation of Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) suggested that the additional predictive power of the combined model was significantly improved contrasted with CA-125 or 4-miRNA alone (model vs CA-125, NRI=0.471, P<0.001; IDI=0.538, P<0.001; model vs 4-miRNA panel, NRI=0.122, P=0.001; IDI=0.185, P=0.003). Tumor cells-derived sEVs captured on EpCAM+ magnetic beads were the major vehicles affecting circulating sEVs 4-miRNA expressions. Moreover, the model index scores were significant differences between AOC and other confusable diseases (e.g., advanced colorectal cancer). After analyzing a comprehensive plasma sEVs miRNAs profile in AOC, we identified and optimized a risk prediction model consisting of plasma sEVs-derived 4-miRNA (miR-320a-3p, miR-378a-3p, miR-1307-3p, let-7d-3p) and CA-125 (AUC:0.903; sensitivity:0.897; specificity:0.910; PPV:0.926; NPV:0.871). The quantitative evaluation of Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) suggested that the additional predictive power of the combined model was significantly improved contrasted with CA-125 or 4-miRNA alone (model vs CA-125, NRI=0.471, P<0.001; IDI=0.538, P<0.001; model vs 4-miRNA panel, NRI=0.122, P=0.001; IDI=0.185, P=0.003). Tumor cells-derived sEVs captured on EpCAM+ magnetic beads were the major vehicles affecting circulating sEVs 4-miRNA expressions. Moreover, the model index scores were significant differences between AOC and other confusable diseases (e.g., advanced colorectal cancer). ConclusionsA reliable and stable model of circulating tumor-derived sEVs 4-miRNA plus CA-125 was established for preoperatively anticipating the high-risk AOC patients of residual disease to optimize clinical therapy. A reliable and stable model of circulating tumor-derived sEVs 4-miRNA plus CA-125 was established for preoperatively anticipating the high-risk AOC patients of residual disease to optimize clinical therapy.