Literature DB >> 32278036

Metabolomics identified new biomarkers for the precise diagnosis of pancreatic cancer and associated tissue metastasis.

Xialin Luo1, Jingjing Liu1, Huaizhi Wang2, Haitao Lu3.   

Abstract

Pancreatic cancer (PC) is one of the most aggressive malignancies with high mortality due to a complex and latent pathogenesis leading to the severe lack of early diagnosis methods. To improve clinical diagnosis and enhance therapeutic outcome, we employed the newly developed precision-targeted metabolomics method to identify and validate metabolite biomarkers from the plasma samples of patients with pancreatic cancer that can sensitively and efficiently diagnose the onsite progression of the disease. Many differential metabolites have the capacity to markedly distinguish patients with pancreatic cancer (n = 60) from healthy controls (n = 60). To further enhance the specificity and selectivity of metabolite biomarkers, a dozen tumor tissues from PC patients and paired normal tissues were used to clinically validate the biomarker performance. We eventually verified five new metabolite biomarkers in plasma (creatine, inosine, beta-sitosterol, sphinganine and glycocholic acid), which can be used to readily diagnose pancreatic cancer in a clinical setting. Excitingly, we proposed a panel biomarker by integrating these five individual metabolites into one pattern, demonstrating much higher accuracy and specificity to precisely diagnose pancreatic cancer than conventional biomarkers (CA125, CA19-9, CA242 and CEA); moreover, this plasma panel biomarker used for PC diagnosis is also quite convenient to implement in clinical practice. Using the same metabolomics method, we characterized succinic acid and gluconic acid as having a great capability to monitor the progression and metastasis of pancreatic cancer at different stages. Taken together, this metabolomics method was used to identify and validate metabolite biomarkers that can precisely and sensitively diagnose the onsite progression and metastasis of pancreatic cancer in a clinical setting. Furthermore, such effort should leave clinicians with the correct time frame to facilitate early and efficient therapeutic interventions, which could largely improve the five-year survival rate of PC patients by significantly lowering clinical mortality.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Clinical applications; Molecular diagnosis; New metabolite biomarkers; Pancreatic cancer; T metabolomics; Tissue metastasis

Mesh:

Substances:

Year:  2020        PMID: 32278036     DOI: 10.1016/j.phrs.2020.104805

Source DB:  PubMed          Journal:  Pharmacol Res        ISSN: 1043-6618            Impact factor:   7.658


  8 in total

1.  1H-NMR Based Metabolomics Technology Identifies Potential Serum Biomarkers of Colorectal Cancer Lung Metastasis in a Mouse Model.

Authors:  Junfei Zhang; Yuanxin Du; Yongcai Zhang; Yanan Xu; Yanying Fan; Yan Li
Journal:  Cancer Manag Res       Date:  2022-04-14       Impact factor: 3.602

2.  Gene Differential Expression and Interaction Networks Illustrate the Biomarkers and Molecular Biological Mechanisms of Unsaponifiable Matter in Kanglaite Injection for Pancreatic Ductal Adenocarcinoma.

Authors:  Bowen Xu; Wenchao Dan; Xiaoxiao Zhang; Heping Wang; Luchang Cao; Shixin Li; Jie Li
Journal:  Biomed Res Int       Date:  2022-06-06       Impact factor: 3.246

3.  High-performance Collective Biomarker from Liquid Biopsy for Diagnosis of Pancreatic Cancer Based on Mass Spectrometry and Machine Learning.

Authors:  Tomohiko Iwano; Kentaro Yoshimura; Genki Watanabe; Ryo Saito; Sho Kiritani; Hiromichi Kawaida; Takeshi Moriguchi; Tasuku Murata; Koretsugu Ogata; Daisuke Ichikawa; Junichi Arita; Kiyoshi Hasegawa; Sen Takeda
Journal:  J Cancer       Date:  2021-11-04       Impact factor: 4.207

Review 4.  Recent Metabolomics Analysis in Tumor Metabolism Reprogramming.

Authors:  Jingjing Han; Qian Li; Yu Chen; Yonglin Yang
Journal:  Front Mol Biosci       Date:  2021-11-25

5.  Meta-Analysis Reveals Both the Promises and the Challenges of Clinical Metabolomics.

Authors:  Heidi E Roth; Robert Powers
Journal:  Cancers (Basel)       Date:  2022-08-18       Impact factor: 6.575

6.  Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer.

Authors:  Chang Liu; Henan Qin; Huiying Liu; Tianfu Wei; Zeming Wu; Mengxue Shang; Haihua Liu; Aman Wang; Jiwei Liu; Dong Shang; Peiyuan Yin
Journal:  Front Oncol       Date:  2022-09-02       Impact factor: 5.738

7.  Metabolic Biomarkers Affecting Cell Proliferation and Prognosis in Polycythemia Vera.

Authors:  Ziqing Wang; Yan Lv; Erpeng Yang; Yujin Li; Dehao Wang; Guang Hu; Yumeng Li; Mingjing Wang; Weiyi Liu; Mingqian Sun; Xiaomei Hu
Journal:  Cancers (Basel)       Date:  2022-10-07       Impact factor: 6.575

Review 8.  New insights into molecules and pathways of cancer metabolism and therapeutic implications.

Authors:  Zhenye Tang; Zhenhua Xu; Xiao Zhu; Jinfang Zhang
Journal:  Cancer Commun (Lond)       Date:  2020-11-10
  8 in total

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