Rebecca C Arend 1 , Carly B Scalise 1 , Emily R Gordon 2 , Allison M Davis 1 , McKenzie E Foxall 1 , Bobbi E Johnston 2 , David K Crossman 3 , Sara J Cooper 2 Show Affiliations »
Abstract
PURPOSE: Our study used transcriptomic and metabolomic strategies to determine the molecular profiles of HGSOC patient samples derived from primary tumor and ascites cells. These data identified clinically relevant heterogeneity among and within patients and highlighted global and patient-specific cellular responses to neoadjuvant chemotherapy (NACT). EXPERIMENTAL DESIGN: Tissue from 61 treatment-naïve patients with HGSOC were collected. In addition, 11 benign, 32 ascites, and 18 post-NACT samples (matched to the individual patient's pre-NACT sample) were collected. RNA sequencing (RNA-seq) was performed on all samples collected. Two-dimensional spatial proteomic data was collected for two pairs of pre- and post-NACT. Untargeted metabolomics data using GCxGC-MS was generated for 30 treatment-naive tissues. Consensus clustering, analysis of differential expression, pathway enrichment, and survival analyses were performed. RESULTS: Treatment-naïve HGSOC tissues had distinct transcriptomic and metabolomic profiles. The mesenchymal subtype harbored a metabolomic profile distinct from the other subtypes. Compared with primary tumor tissue, ascites showed significant changes in immune response and signaling pathways. NACT caused significant alterations in gene expression and WNT activity, and this corresponded to altered immune response. Overall, WNT signaling levels were inversely correlated with immune cell infiltration in HGSOC tissues and WNT signaling post-NACT was inversely correlated with progression-free survival. CONCLUSIONS: Our study concluded that HGSOC is a heterogenous disease at baseline and growing molecular differences can be observed between primary tumor and ascites cells or within tumors in response to treatment. Our data reveal potential exploratory biomarkers relevant for treatment selection and predicting patient outcomes that warrant further research. ©2022 American Association for Cancer Research.
PURPOSE: Our study used transcriptomic and metabolomic strategies to determine the molecular profiles of HGSOC patient samples derived from primary tumor and ascites cells. These data identified clinically relevant heterogeneity among and within patients and highlighted global and patient-specific cellular responses to neoadjuvant chemotherapy (NACT). EXPERIMENTAL DESIGN: Tissue from 61 treatment-naïve patients with HGSOC were collected. In addition, 11 benign, 32 ascites, and 18 post-NACT samples (matched to the individual patient's pre-NACT sample) were collected. RNA sequencing (RNA-seq) was performed on all samples collected. Two-dimensional spatial proteomic data was collected for two pairs of pre- and post-NACT. Untargeted metabolomics data using GCxGC-MS was generated for 30 treatment-naive tissues. Consensus clustering, analysis of differential expression, pathway enrichment, and survival analyses were performed. RESULTS: Treatment-naïve HGSOC tissues had distinct transcriptomic and metabolomic profiles. The mesenchymal subtype harbored a metabolomic profile distinct from the other subtypes. Compared with primary tumor tissue, ascites showed significant changes in immune response and signaling pathways. NACT caused significant alterations in gene expression and WNT activity, and this corresponded to altered immune response. Overall, WNT signaling levels were inversely correlated with immune cell infiltration in HGSOC tissues and WNT signaling post-NACT was inversely correlated with progression-free survival. CONCLUSIONS: Our study concluded that HGSOC is a heterogenous disease at baseline and growing molecular differences can be observed between primary tumor and ascites cells or within tumors in response to treatment. Our data reveal potential exploratory biomarkers relevant for treatment selection and predicting patient outcomes that warrant further research. ©2022 American Association for Cancer Research.
Entities: Chemical
Mesh： See more »
Year: 2022
PMID： 35031546 PMCID： PMC9066364 DOI： 10.1158/1078-0432.CCR-21-2984
Source DB: PubMed Journal: Clin Cancer Res ISSN： 1078-0432 Impact factor: 13.801