4.7 Article

Targeted proteomics-derived biomarker profile develops a multi-protein classifier in liquid biopsies for early detection of esophageal squamous cell carcinoma from a population-based case-control study

Journal

BIOMARKER RESEARCH
Volume 9, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s40364-021-00266-z

Keywords

Esophageal squamous cell carcinoma; Early detection; Diagnostic biomarkers; Affinity proteomics; Proximity extension assay; Screening

Funding

  1. National Natural Science Foundation of China [81973116, 82073637, 91846302, 81573229]
  2. National Key Research and Development program of China [2017YFC0907002, 2017YFC0907003]
  3. International S&T Cooperation Program of China [2015DFE32790]
  4. European Research Council [682663]
  5. Shandong Provincial Natural Science Foundation [ZR2020QH302]
  6. European Research Council (ERC) [682663] Funding Source: European Research Council (ERC)

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This study demonstrated that a combination of specific serum proteins could serve as a potential tool for screening and early diagnosis of esophageal squamous cell carcinoma, especially with the establishment of a three-level hierarchical screening strategy for disease control.
Background: Early diagnosis of esophageal squamous cell carcinoma (ESCC) remains a challenge due to the lack of specific blood biomarkers. We aimed to develop a serum multi-protein signature for the early detection of ESCC. Methods: We selected 70 healthy controls, 30 precancerous patients, 60 stage I patients, 70 stage II patients and 70 stage III/IV ESCC patients from a completed ESCC case-control study in a high-risk area of China. Olink Multiplex Oncology II targeted proteomics panel was used to simultaneously detect the levels of 92 cancer-related proteins in serum using proximity extension assay. Results: We found that 10 upregulated and 13 downregulated protein biomarkers in serum could distinguish the early-stage ESCC from healthy controls, which were validated by the significant dose-response relationships with ESCC pathological progression. Applying least absolute shrinkage and selection operator (LASSO) regression and backward elimination algorithm, ANXA1 (annexin A1), hK8 (kallikrein-8), hK14 (kallikrein-14), VIM (vimentin), and RSPO3 (R-spondin-3) were kept in the final model to discriminate early ESCC cases from healthy controls with an area under curve (AUC) of 0.936 (95% confidence interval: 0.899 similar to 0.973). The average accuracy rates of the five-protein classifier were 0.861 and 0.825 in training and test data by five-fold cross-validation. Conclusions: Our study suggested that a combination of ANXA1, hK8, hK14, VIM and RSPO3 serum proteins could be considered as a potential tool for screening and early diagnosis of ESCC, especially with the establishment of a three-level hierarchical screening strategy for ESCC control.

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