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Surgical and blood-based minimal residual disease in patients with ovarian cancer after frontline therapy: Clinical outcomes and translational opportunities [Spatial Transcriptomics]


ABSTRACT: Minimal residual disease (MRD) after frontline treatment of advanced stage ovarian cancer remains a longstanding barrier to cure. We investigated the prognostic and translational value of MRD detection by second look laparoscopy (SLL) and circulating tumor DNA (ctDNA) at the completion of frontline therapy. Patients with high-grade epithelial ovarian cancer with complete clinical response to frontline therapy who underwent SLL and plasma collection for ctDNA were included. Progression-free survival (PFS) and overall survival (OS) were estimated based on MRD and clinicopathologic status. Spatial transcriptomics (GeoMx and Visium) and proteomics (CODEX) profiling were performed on serial samples from select patients. Forty of 95 (42.1%) patients had surgically detected MRD, and this was associated with worse PFS (median PFS 7.4 vs 23.8 months; p<0.001) and OS (median OS 33.9 vs not reached; p<0.001). SLL positivity was found to be an independent negative prognostic factor for OS (HR 4.40, 95% CI 1.37-14.21, p=0.013) in multivariable analysis. Among 44 patients who underwent SLL and had ctDNA testing, 34% (15/44) were ctDNA-positive, which was associated with worse PFS (6.4 vs 28.1 months; p<0.001) and OS (32.4 months vs not reached; p=0.008). We demonstrated the feasibility of spatial multi-omics in studying MRD, and their ability to provide hypothesis-generating observations, implicating the upregulation of the hypoxia signaling pathway, expression of multiple druggable targets (CDK6, GLS, MSLN, and ERBB2), and immune exclusion, in the development of MRD lesions. In summary, approximately half of patients in clinical remission after frontline therapy have assessable MRD which can inform prognosis, therapeutic target discovery, and clinical trials.

ORGANISM(S): Homo sapiens

PROVIDER: GSE284100 | GEO | 2025/06/20

REPOSITORIES: GEO

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