ArticleFrontiers in oncology2021
Identification of Novel Autoantibodies Based on the Human Proteomic Chips and Evaluation of Their Performance in the Detection of Gastric Cancer.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 32 citations in OpenAlex.
- Autoantibody-Based Models for the Diagnosis and Activity Assessment of Takayasu Arteritis.Journal of cardiovascular translational research · 2026Article
- Tumor antigen-associated autoantibodies: generation mechanisms, roles in tumorigenesis and progression, and clinical application prospects.Frontiers in immunology · 2026Review
- Dephosphorylation-related signature predicts the prognosis of papillary renal cell carcinoma.Translational cancer research · 2024Article
- Humoral immune response to tumor-associated antigen Ubiquilin 1 (UBQLN1) and its tumor-promoting potential in lung cancer.BMC cancer · 2024Article
- ASPSCR-1 and Sirt-5 alleviate Clonorchis liver fluke rCsNOSIP-induced oxidative stress, proliferation, and migration in cholangiocarcinoma cells.PLoS neglected tropical diseases · 2023Article
- Identification and evaluation of novel serum autoantibody biomarkers for early diagnosis of gastric cancer and precancerous lesion.Journal of cancer research and clinical oncology · 2023Article
- Successful targeting in situ of an oncogenic nuclear antigen by hapten induced tumor associated autoantibodies (iTAA).Scientific reports · 2023Article
- Temporal reproducibility of IgG and IgM autoantibodies in serum from healthy women.Scientific reports · 2022Article
- A novel immunodiagnosis panel for hepatocellular carcinoma based on bioinformatics and the autoantibody-antigen system.Cancer science · 2022Article
- Evaluating a Panel of Autoantibodies Against Tumor-Associated Antigens in Human Osteosarcoma.Frontiers in genetics · 2022Article
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12 authors at 1 institution in 1 country.
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Abstract
Autoantibodies against tumor-associated antigens (TAAbs) can be used as potential biomarkers in the detection of cancer. Our study aims to identify novel TAAbs for gastric cancer (GC) based on human proteomic chips and construct a diagnostic model to distinguish GC from healthy controls (HCs) based on serum TAAbs. The human proteomic chips were used to screen the candidate TAAbs. Enzyme-linked immunosorbent assay (ELISA) was used to verify and validate the titer of the candidate TAAbs in the verification cohort (80 GC cases and 80 HCs) and validation cohort (192 GC cases, 128 benign gastric disease cases, and 192 HCs), respectively. Then, the diagnostic model was established by Logistic regression analysis based on OD values of candidate autoantibodies with diagnostic value. Eleven candidate TAAbs were identified, including autoantibodies against INPP5A, F8, NRAS, MFGE8, PTP4A1, RRAS2, RGS4, RHOG, SRARP, RAC1, and TMEM243 by proteomic chips. The titer of autoantibodies against INPP5A, F8, NRAS, MFGE8, PTP4A1, and RRAS2 were significantly higher in GC cases while the titer of autoantibodies against RGS4, RHOG, SRARP, RAC1, and TMEM243 showed no difference in the verification group. Next, six potential TAAbs were validated in the validation cohort. The titer of autoantibodies against F8, NRAS, MFGE8, RRAS2, and PTP4A1 was significantly higher in GC cases. Finally, an optimal prediction model with four TAAbs (anti-NRAS, anti-MFGE8, anti-PTP4A1, and anti-RRAS2) showed an optimal diagnostic performance of GC with AUC of 0.87 in the training group and 0.83 in the testing group. The proteomic chip approach is a feasible method to identify TAAbs for the detection of cancer. Moreover, the panel consisting of anti-NRAS, anti-MFGE8, anti-PTP4A1, and anti-RRAS2 may be useful to distinguish GC cases from HCs.
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