Differential plasma lipids profiling and lipid signatures as biomarkers in the early diagnosis of ovarian carcinoma using UPLC-MS

Hou, Yan; Li, Junnan; Xie, Hongyu; Sun, Fengyu; Yang, Kai; Wang, Jingtao; Ke, Chaofu; Lou, Ge; Li, Kang

doi:10.1007/s11306-015-0891-7

Cited by 20 publications

(30 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our previous metabolomic studies have demonstrated that lysophosphatidylcholine (LysoPC) might be a potential asset in the discrimination between EOC and controls [ 16 ]. In addition, we have previously reported a lipidomics study based on global plasma lipid profiling and found that a series of glycerophospholipids (GPs) were decreased, while a series of sphingolipids (SPs) were increased in EOC patients [ 17 ]. Besides, several studies have identified the predictive lipid biomarkers for disease recurrence [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry

Xie

et al. 2016

Oncotarget

Self Cite

View full text Add to dashboard Cite

Epithelial ovarian cancer (EOC) is the most deadly gynecologic malignancy worldwide due to its high recurrence rate after surgery and chemotherapy. There is a critical need for discovery of novel biomarkers for EOC recurrence providing higher prediction power than that of the present ones. Lipids have been reported to associate with development and progression of cancer. In the current study, we aim to identify and validate the lipids which were relevant to the ovarian cancer recurrence based on plasma lipidomics performed by ultra-performance liquid chromatography coupled with mass spectrometry. In order to fulfill this objective, plasma from 70 EOC patients with follow up information was obtained. The results revealed that patients with and without recurrence could be clearly distinguished based on their lipid profiles. Thirty-one lipid metabolites were identified as potential biomarkers for EOC recurrence. The AUC value of these metabolite combinations for predicting EOC recurrence was 0.897. In terms of clinical applicability, LysoPG(20:5) arose as a potential EOC recurrence predictive biomarker to increase the predictive power of clinical predictors from AUC value 0.739 to 0.875. Additionally, we still found that individuals with early relapses (< 6 months) had a distinctive metabolomic pattern compared with late EOC and non-EOC recurrence subjects. Interestingly, decreased levels of triglycerides (TGs) were found to be a specific metabolic feature foreshadowing an early relapse. In conclusion, plasma lipidomics study could be used for predicting EOC recurrences, as well as early and late recurrent cases. The lipid biomarker research improves the predictive power of clinical predictors and the identified biomarkers are of great prognostic and therapeutic potential.

show abstract

Section: Introductionmentioning

confidence: 99%

Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry

Xie

et al. 2016

Oncotarget

Self Cite

View full text Add to dashboard Cite

show abstract

“…22,31 In previous EOC-related metabolomics studies, various sorts of metabolite-biomarkers, including amino acids, fatty acids, bile acids and diverse lipids, have been discovered and proven to be able to efficiently differentiate EOC patients from benign tumor and healthy control subjects. 19,25,30,32 Of note, in a former study launched by our group, 18 the combination of 53 differential metabolites revealed much better performances than CA125 in differentiating both overall EOCs and EOCs in early stages from BOTs (AUC, 0.91vs. 0.85 for overall EOC, 0.84 vs. 0.69 for early stages).…”

Section: Discussionmentioning

confidence: 90%

“…As plasma golden standard for EOC diagnosis, CA125, despite its satisfactory sensitivity, still cannot be regarded as an ideal biomarker in the clinic discrimination of BOT and EOC by the conventional threshold of > 35 U/mL because of its poor specificity especially when benign ovarian tumors are included . In previous EOC‐related metabolomics studies, various sorts of metabolite‐biomarkers, including amino acids, fatty acids, bile acids and diverse lipids, have been discovered and proven to be able to efficiently differentiate EOC patients from benign tumor and healthy control subjects . Of note, in a former study launched by our group, the combination of 53 differential metabolites revealed much better performances than CA125 in differentiating both overall EOCs and EOCs in early stages from BOTs (AUC, 0.91vs.…”

Section: Discussionmentioning

confidence: 99%

Selection of small plasma peptides for the auxiliary diagnosis and prognosis of epithelial ovarian cancer by using UPLC/MS‐based nontargeted and targeted analyses

Xia

Bai

et al. 2019

Intl Journal of Cancer

Self Cite

View full text Add to dashboard Cite

Epithelial ovarian cancer (EOC) is the leading cause of gynecologic cancer-related death due to its non-specific characteristics compared to benign cases and poor prognosis after conventional therapies. Small peptides (SPs) demonstrated to have potential for diagnosis and prognosis were focused on in this study for the discovery of biomarkers that address these issues. Metabolic profiles of fifteen SPs, including nine dipeptides and six tripeptides were acquired from plasma samples of 140 EOC and 158 benign ovarian tumor (BOT) patients. Partial least square discriminant analysis showed separations between EOC and BOT subjects of different age brackets. Hyp-Leu, Glu-Trp and Phe-Phe were selected as promising predictive SP-biomarkers for better EOC diagnosis compared to conventional biomarkers. Combined Hyp-Leu, Glu-Trp and CA125 presented an area under the curve (AUC) of 0.904, with a sensitivity and specificity of 0.804 and 0.944, respectively. This finding suggested that the combination of these biomarkers performed much better than CA125 alone. Hyp-Leu and Gly-Phe-Trp showed significantly improved performances in the log-rank tests and Kaplan-Meier curves demonstrating their prognostic potential. All SP-biomarkers proved to have excellent stabilities at room temperature. Correlation network analysis implied latent conversions among amino acids, dipeptides and tripeptides during EOC. In conclusion, the selected SPs in combination with CA125 show profound promise for discriminating EOCs from BOTs and for predicting the progression after surgery, which provides invaluable information for clinicians in the precision diagnosis and treatment of EOC. This article is protected by copyright. All rights reserved.

show abstract

“…Parameters are described in our previous studies. 4,11 We used the R package CAMERA for annotating isotope peaks, adducts, and fragments in the peak lists and excluded the isotopic peaks before conducting statistical analysis.…”

Section: Lipidomics and Treatmentmentioning

confidence: 99%

<p>Mediation Analysis Reveals Potential Biological Mechanism of Ascites Influencing Recurrence in Patients with Epithelial Ovarian Cancer</p>

Yang¹,

Rong²,

Xu³

et al. 2020

CMAR

Self Cite

View full text Add to dashboard Cite

Objective: Ascites, an accumulation of peritoneal fluid, is associated with poor prognosis of certain cancers. The potential mechanism that ascites worsens prognosis has not been well understood. Lipids have been reported to correlate with the prognosis of patients with epithelial ovarian cancer (EOC). Therefore, we aimed here to investigate whether lipids mediate the effect of ascites on the recurrence of EOC. Methods: We collected the demographic and pathological data of 437 previously untreated patients with EOC to investigate the influence of ascites on recurrence. To identify the mechanism that mediates the potential influence of ascites on recurrence, we used ultraperformance liquid chromatography coupled with mass spectrometry (UPLC-MS) to determine the plasma lipid profiles of 53 patients with EOC. We used mediation analysis to evaluate if lipids mediated the effects of ascites on the recurrence of EOC. Results: Patients with ascites had a poorer prognosis, which was associated with higher levels of carbohydrate antigen-CA125 (CA125) and FIGO stage. We identified six different lipid metabolites that were associated with ascites and recurrence. Mediation analysis revealed that the lipids LysoPC(P-15:0), PC(P-34:4), and PC(38:6) may mediate the effects of ascites on recurrence. Conclusion: Our findings suggest that LysoPC(P-15:0), PC(P-34:4), and PC(38:6) mediate the effect of ascites on the prognosis of patients with EOC. We believe therefore that it is reasonable to consider metabolic interventions targeting the metabolism of LysoPC(P-15:0), PC(P-34:4), and PC(38:6) as a palliative treatment for patients with EOC with ascites. Further studies of more patients will be required to validate our findings.

show abstract

Differential plasma lipids profiling and lipid signatures as biomarkers in the early diagnosis of ovarian carcinoma using UPLC-MS

Cited by 20 publications

References 42 publications

Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry

Distinct plasma lipids profiles of recurrent ovarian cancer by liquid chromatography-mass spectrometry

Selection of small plasma peptides for the auxiliary diagnosis and prognosis of epithelial ovarian cancer by using UPLC/MS‐based nontargeted and targeted analyses

<p>Mediation Analysis Reveals Potential Biological Mechanism of Ascites Influencing Recurrence in Patients with Epithelial Ovarian Cancer</p>

Contact Info

Product

Resources

About