DCBLD1 as a novel prognostic biomarker and therapeutic target in breast cancer: clinical validation and mechanistic insights

Objective: To investigate the expression of DCBLD1 (discoidin, CUB, and LCCL domain-containing protein 1) in breast cancer tissues and its correlation with patient prognosis, and evaluate its potential as a novel prognostic marker and therapeutic target. Methods: Differential expression of DCBLD1 between breast cancer and normal tissues was analyzed using GEO and METABRIC databases, combined with survival analysis and Cox multivariate regression analysis to evaluate its prognostic value. Effective interference sequences were screened using quantitative polymerase chain reaction, and knockdown efficiency was validated by quantitative reverse transcription polymerase chain reaction and Western blot. The effects of DCBLD1 on breast cancer cell proliferation, apoptosis, migration, and invasion were investigated using CCK-8, flow cytometry, Transwell migration and invasion assays, and wound healing assays. Results: = 0.009). Knockdown of DCBLD1 significantly inhibited breast cancer cell proliferation, colony formation, migration, and invasion capacities while promoting apoptosis. Conclusion: DCBLD1 exhibits oncogene functions in breast cancer and can serve as an independent prognostic marker and potential therapeutic target, with its expression level closely correlated to tumor malignancy and metastasis risk.

Authors

Institutions

Publication Details

Journal
Annals of Medicine and Surgery
Published
2026-04-07
DOI
https://doi.org/10.1097/ms9.0000000000004870
Primary Topic
Cell Adhesion Molecules Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DCBLD1 as a novel prognostic biomarker and therapeutic target in breast cancer: clinical validation and mechanistic insights

Hong Hu, Zhi-Yong Liu
Annals of Medicine and Surgery
Cell Adhesion Molecules Research
article

DCBLD1 as a novel prognostic biomarker and therapeutic target in breast cancer: clinical validation and mechanistic insights

Hong Hu, Zhi-Yong Liu
article en

Abstract

Objective: To investigate the expression of DCBLD1 (discoidin, CUB, and LCCL domain-containing protein 1) in breast cancer tissues and its correlation with patient prognosis, and evaluate its potential as a novel prognostic marker and therapeutic target. Methods: Differential expression of DCBLD1 between breast cancer and normal tissues was analyzed using GEO and METABRIC databases, combined with survival analysis and Cox multivariate regression analysis to evaluate its prognostic value. Effective interference sequences were screened using quantitative polymerase chain reaction, and knockdown efficiency was validated by quantitative reverse transcription polymerase chain reaction and Western blot. The effects of DCBLD1 on breast cancer cell proliferation, apoptosis, migration, and invasion were investigated using CCK-8, flow cytometry, Transwell migration and invasion assays, and wound healing assays. Results: = 0.009). Knockdown of DCBLD1 significantly inhibited breast cancer cell proliferation, colony formation, migration, and invasion capacities while promoting apoptosis. Conclusion: DCBLD1 exhibits oncogene functions in breast cancer and can serve as an independent prognostic marker and potential therapeutic target, with its expression level closely correlated to tumor malignancy and metastasis risk.

Annals of Medicine and SurgeryVol. 88(5)
First Affiliated Hospital of Gannan Medical University (CN)
Good health and well-being
Openalex Percentile: Top 27%
Cell Adhesion Molecules Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.