Metabolic alterations and WNT signaling impact immune response in HGSOC
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.
乐备实是国内专注于提供高质量蛋白检测以及组学分析服务的实验服务专家,自2018年成立以来,乐备实不断寻求突破,公司的服务技术平台已扩展到单细胞测序、空间多组学、流式检测、超敏电化学发光、Luminex多因子检测、抗体芯片、PCR Array、ELISA、Elispot、PLA蛋白互作、多色免疫组化、DSP空间多组学等30多个,建立起了一套涵盖基因、蛋白、细胞以及组织水平实验的完整检测体系。
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数据分析:流式数据分析、组化数据分析、多因子数据分析
基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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