Metabolomics identifies serum and exosomes metabolite markers of pancreatic cancer

Luan, Tao; Zhou, Juntuo; Yuan, Chunhui; Zhang, Lingfu; Li, Deyu; Si, Daoyuan; Xiu, Dianrong; Zhong, Liang

doi:10.1007/s11306-019-1550-1

Cited by 114 publications

(113 citation statements)

References 27 publications

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“…This will include comprehensive genomic analysis focusing on small RNA species as initiated previously in a study for monitoring the immunomodulatory potential of neonatal umbilical cord stromal cell-derived EVs [18]. Our quantitative EV purification approach will also allow for combining lipidomics, glycomics and metabolomics for a more broad view on PLX-EV biology using upcoming technology [35]- [37]. EV characterization can not be limited to key pathways of angiogenesis and immunity.…”

Section: Discussionmentioning

confidence: 99%

A functional corona around extracellular vesicles enhances angiogenesis during skin regeneration and signals in immune cells

Wolf

Poupardin

Ebner-Peking

et al. 2019

Preprint

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words)Allogeneic regenerative cell therapy has shown surprising results despite lack of engraftment of the transplanted cells. Their efficacy was so far considered to be mostly due to secreted trophic factors. We hypothesized that extracellular vesicles (EVs) can also contribute to their mode of action. Here we provide evidence that EVs derived from therapeutic placental-expanded (PLX) stromal cells are potent inducers of angiogenesis and modulate immune cell proliferation in a dose-dependent manner.Crude EVs were enriched >100-fold from large volume PLX conditioned media via tangential flow filtration (TFF) as determined by tunable resistive pulse sensing (TRPS).Additional TFF purification was devised to separate EVs from cell-secreted soluble factors. EV identity was confirmed by western blot, calcein-based flow cytometry and electron microscopy. Surface marker profiling of tetraspanin-positive EVs identified expression of cell-and matrix-interacting adhesion molecules. Differential tandem mass tag proteomics comparing PLX-EVs to PLX-derived soluble factors revealed significant differential enrichment of 258 proteins in purified PLX-EVs involved in angiogenesis, cell movement and immune system signaling. At the functional level, PLX-EVs and cells inhibited T cell mitogenesis. PLX-EVs and soluble factors displayed dose-dependent proangiogenic potential by enhancing tube-like structure formation in vitro.Our findings indicate that the mode of PLX action involves an EV-mediated proangiogenic function and immune response modulation that may help explaining clinical efficacy beyond presence of the transplanted allogeneic cells.

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Section: Discussionmentioning

confidence: 99%

A functional corona around extracellular vesicles enhances angiogenesis during skin regeneration and signals in immune cells

Wolf

Poupardin

Ebner-Peking

et al. 2019

Preprint

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“…acids, phosphatidylglycerol and choline between tissues (47) and were closely related to the occurrence and development of PC (47)(48)(49)(50). Our results showed that the relative amount of LPC-11 in the GEM-S subgroup decreased markedly upon treatment with either GEM monotherapy or combination therapy compared with no treatment; LPC-11 could be a metabolic predictor of the efficacy of GEM-based chemotherapy.…”

Section: Discussionmentioning

confidence: 75%

Pharmacometabolomics Identifies 3-Hydroxyadipic Acid, d-Galactose, Lysophosphatidylcholine (P-16:0), and Tetradecenoyl-l-Carnitine as Potential Predictive Indicators of Gemcitabine Efficacy in Pancreatic Cancer Patients

Zhang

et al. 2020

Front. Oncol.

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Gemcitabine (GEM)-based chemotherapy is the standard regimen for the treatment of pancreatic cancer (PC). However, chemoresistance is a major challenge in PC treatment. Reliable biomarkers are urgently needed to predict the response to GEM-based therapies. GEM-sensitive (GEM-S) and GEM-resistant (GEM-R) pancreatic carcinoma xenograft models were established, and GEM monotherapy and GEM plus nanoparticle albumin-bound paclitaxel (nab-PTX) doublet therapy were administered to GEM-S/R tumor-bearing mice. Metabolomic mass spectrometry (MS) analysis of serum, liver, and tumor samples was performed using an ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometer. The results showed that both GEM monotherapy and combination therapy significantly inhibited the tumor growth in GEMS subgroup. However, in the GEM-R subgroup, tumor growth was not significantly inhibited by GEM monotherapy, but was significantly suppressed by GEM combination therapy. Metabolic profiling analysis by hierarchical cluster analysis and partial least squares discriminant analysis showed that the differences in metabolites were most significant in serum of three types of samples in the GEM-S/R subgroups, regardless of the administration of GEM monotherapy or combination therapy. The differential metabolite analysis of serum samples revealed 38 and 26 differential metabolites between the GEM-R and GEMS subgroups treated with GEM monotherapy or combination therapy, and four common discriminating metabolites were investigated: 3-hydroxyadipic acid, D-galactose, lysophosphatidylcholine (LysoPC) (P-16:0), and tetradecenoyl-L-carnitine. The relative amounts of the four metabolites changed significantly and consistently after GEM monotherapy or combination therapy. The levels of these four metabolites Wu et al.

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“…Lysophosphatidylethanolamine (LPE) is a group of lipids that has been recently shown to be related to breast cancer [42]. In addition, PE (16:0/18:1) is associated with the stage and prognosis of pancreatic cancer and may be a potential diagnostic marker [43]. Yang et al found 25 different lipid metabolites, including PE, between malignant pleural effusion (MPE) and benign pleural effusion (NPE), indicating that lipid metabolites may be used to partition MBE and BPE [44].…”

Section: Discussionmentioning

confidence: 99%

Circulating Tumor Cell and Metabolites as Novel Biomarkers for Early-stage Lung Cancer Diagnosis

Wan

He²,

Liu

et al. 2020

Preprint

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Background: Lung cancer is a malignant tumor that has the highest morbidity and mortality rate among all cancers. Early diagnosis of lung cancer is a key factor in reducing mortality and improving prognosis. Methods: In this study, we performed CTC next-generation sequencing (NGS) in early-stage lung cancer patients to identify lung cancer-related gene mutations. Meanwhile, a serum liquid chromatography-tandem mass spectrometry (LC-MS) untargeted metabolomics analysis was performed in the CTC-positive patients, and the early diagnostic value of these assays in lung cancer was analyzed. Results: 62.5% (30/48) of lung cancer patients had ≥ 1 CTC. By CTC NGS, we found that > 50% of patients had 4 commonly mutated genes, namely, NOTCH1, IGF2, EGFR, and PTCH1. 47.37% (9/19) patients had ARIDH1 mutations. Additionally, 30 CTC-positive patients and 30 healthy volunteers were subjected to LC-MS untargeted metabolomics analysis. We found 100 different metabolites, and 10 different metabolites were identified through analysis, which may have potential clinical application value in the diagnosis of CTC-positive early-stage lung cancer (AUC > 0.9). Conclusions: Our results indicate that NGS of CTC and metabolomics may provide new tumor markers for the early diagnosis of lung cancer. This possibility requires more in-depth large-sample research for verification.

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Metabolomics identifies serum and exosomes metabolite markers of pancreatic cancer

Cited by 114 publications

References 27 publications

A functional corona around extracellular vesicles enhances angiogenesis during skin regeneration and signals in immune cells

A functional corona around extracellular vesicles enhances angiogenesis during skin regeneration and signals in immune cells

Pharmacometabolomics Identifies 3-Hydroxyadipic Acid, d-Galactose, Lysophosphatidylcholine (P-16:0), and Tetradecenoyl-l-Carnitine as Potential Predictive Indicators of Gemcitabine Efficacy in Pancreatic Cancer Patients

Circulating Tumor Cell and Metabolites as Novel Biomarkers for Early-stage Lung Cancer Diagnosis

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