Plasma anti-DLAT autoantibody as a novel diagnostic biomarker in breast cancer.
1/5 보강
PICO 자동 추출 (휴리스틱, conf 2/4)
유사 논문P · Population 대상 환자/모집단
환자: benign breast nodules (BN), and healthy controls (NC)
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases were used to analyze the expression levels of DLAT in tumor and normal breast tissues from BC patients.
[BACKGROUND] Tumor-associated autoantibodies (TAAbs) represent promising biomarkers for tumor diagnosis.
- p-value P < 0.0001
APA
Zhao Q, Zhang L, et al. (2026). Plasma anti-DLAT autoantibody as a novel diagnostic biomarker in breast cancer.. Clinical immunology (Orlando, Fla.), 284, 110678. https://doi.org/10.1016/j.clim.2026.110678
MLA
Zhao Q, et al.. "Plasma anti-DLAT autoantibody as a novel diagnostic biomarker in breast cancer.." Clinical immunology (Orlando, Fla.), vol. 284, 2026, pp. 110678.
PMID
41643757 ↗
Abstract 한글 요약
[BACKGROUND] Tumor-associated autoantibodies (TAAbs) represent promising biomarkers for tumor diagnosis. This study aimed to evaluate the prognostic value of anti- Dihydrolipoamide S-acetyltransferase (DLAT) AAb in breast cancer (BC).
[METHODS] Levels of plasma anti-DLAT AAb were measured by ELISA in a total of 1013 samples from BC patients, patients with benign breast nodules (BN), and healthy controls (NC). Western blot was performed to confirm the ELISA results. The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases were used to analyze the expression levels of DLAT in tumor and normal breast tissues from BC patients.
[RESULTS] Plasma anti-DLAT AAb levels were decreased in BC compared to NC and BN, achieving AUCs of 0.803 (P < 0.0001) and 0.591 (P < 0.0001), respectively. Among individuals under 45 years old, anti-DLAT AAb showed high power in distinguishing BC and BC at early-stage from NC, yielding an AUC of 0.873 (P < 0.0001) and 0.845 (P < 0.0001). Besides, anti-DLAT AAb distinguished BC from BN with an AUC of 0.617 (P = 0.0016) in individuals under 45 while there was no difference between them above 45. Combining anti-DLAT AAb with CEA improved the AUCs to 0.824 (P < 0.0001) and 0.623 (P < 0.0001) for distinguishing BC from NC and BN. This combination also achieved higher AUCs of 0.891 (P < 0.0001) and 0.635 (P = 0.0003) for distinguishing BC from NC and BN among individuals under 45 years old.
[CONCLUSIONS] These findings suggest that anti-DLAT AAb shows potential for BC diagnosis, especially among individuals under 45 years old. Besides, multicenter validation should be carried out to confirm this finding in the future.
[METHODS] Levels of plasma anti-DLAT AAb were measured by ELISA in a total of 1013 samples from BC patients, patients with benign breast nodules (BN), and healthy controls (NC). Western blot was performed to confirm the ELISA results. The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases were used to analyze the expression levels of DLAT in tumor and normal breast tissues from BC patients.
[RESULTS] Plasma anti-DLAT AAb levels were decreased in BC compared to NC and BN, achieving AUCs of 0.803 (P < 0.0001) and 0.591 (P < 0.0001), respectively. Among individuals under 45 years old, anti-DLAT AAb showed high power in distinguishing BC and BC at early-stage from NC, yielding an AUC of 0.873 (P < 0.0001) and 0.845 (P < 0.0001). Besides, anti-DLAT AAb distinguished BC from BN with an AUC of 0.617 (P = 0.0016) in individuals under 45 while there was no difference between them above 45. Combining anti-DLAT AAb with CEA improved the AUCs to 0.824 (P < 0.0001) and 0.623 (P < 0.0001) for distinguishing BC from NC and BN. This combination also achieved higher AUCs of 0.891 (P < 0.0001) and 0.635 (P = 0.0003) for distinguishing BC from NC and BN among individuals under 45 years old.
[CONCLUSIONS] These findings suggest that anti-DLAT AAb shows potential for BC diagnosis, especially among individuals under 45 years old. Besides, multicenter validation should be carried out to confirm this finding in the future.
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