Integrative Systemic and Local Metabolomics with Impact on Survival in High-Grade Serous Ovarian Cancer

Clin Cancer Res. 2017 Apr 15;23(8):2081-2092. doi: 10.1158/1078-0432.CCR-16-1647. Epub 2016 Oct 19.

Abstract

Purpose: Cancer metabolism is characterized by alterations including aerobic glycolysis, oxidative phosphorylation, and need of fuels and building blocks.Experimental Design: Targeted metabolomics of preoperative and follow-up sera, ascites, and tumor tissues, RNA sequencing of isolated tumor cells, local and systemic chemokine, and local immune cell infiltration data from up to 65 high-grade serous ovarian cancer patients and 62 healthy controls were correlated to overall survival and integrated in a Systems Medicine manner.Results: Forty-three mainly (poly)unsaturated glycerophospholipids and four essential amino acids (citrulline) were significantly reduced in patients with short compared with long survival and healthy controls. The glycerophospholipid fingerprint is identical to the fingerprint from isolated (very) low-density lipoproteins (vLDL), indicating that the source of glycerophospholipids consumed by tumors is (v)LDL. A glycerophospholipid-score (HR, 0.46; P = 0.007) and a 100-gene signature (HR, 0.65; P = 0.004) confirmed the independent impact on survival in training (n = 65) and validation (n = 165) cohorts. High concentrations of LDLs and glycerophospholipids were independently predictors for favorable survival. Patients with low glycerophospholipids presented with more systemic inflammation (C-reactive protein and fibrinogen negatively and albumin positively correlated) but less adaptive immune cell tumor infiltration (lower tumor and immune cell PD-L1 expression), less oxygenic respiration and increased triglyceride biosynthesis in tumor cells, and lower histone expressions, correlating with higher numbers of expressed genes and more transcriptional noise, a putative neo-pluripotent tumor cell phenotype.Conclusions: Low serum phospholipids and essential amino acids are correlated with worse outcome in ovarian cancer, accompanied by a specific tumor cell phenotype. Clin Cancer Res; 23(8); 2081-92. ©2016 AACR.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biomarkers, Tumor / analysis*
  • Cystadenocarcinoma, Serous / diagnosis
  • Cystadenocarcinoma, Serous / metabolism*
  • Cystadenocarcinoma, Serous / mortality
  • Female
  • Humans
  • Kaplan-Meier Estimate
  • Metabolomics / methods*
  • Middle Aged
  • Neoplasm Grading
  • Ovarian Neoplasms / diagnosis
  • Ovarian Neoplasms / metabolism*
  • Ovarian Neoplasms / mortality
  • Prognosis
  • Proportional Hazards Models
  • Transcriptome

Substances

  • Biomarkers, Tumor