Abstract
Background
Early screening is the most effective way to control breast cancer. Due to the lack
of accurate biomarkers, early diagnosis of breast cancer is still very difficult.
Therefore, it is necessary to discover new candidate genes of breast cancer and improve
the early diagnosis and prognosis.
Methods
A DO-UniBIC gene screening method was proposed. First, Disease Ontology (DO) analysis
was used to screen out breast cancer related genes from differentially expressed genes,
and then the UniBIC algorithm was used to find all gene clusters with the same changing
trend based on the longest common subsequence. In addition, an eight-gene prognostic
model was constructed to assess the prognostic risk of breast cancer patients.
Results
The prognostic analysis of the candidate genomes based on multivariate Cox proportional
regression model revealed eight genes that were significantly related to prognosis.
The eight genes were ACSL1, CD24, EMP1, JPH3, CAMK4, JUN, S100B and TP53AIP1. Among them, ACSL1 was a new potential breast cancer related gene screened by the DO-UniBIC method.
Conclusions
More comprehensive cancer-related genes can be screened based on the DO-UniBIC method,
which can be used as the candidate gene set for prognostic analysis.
Key Indexing Terms
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Article info
Publication history
Published online: April 22, 2022
Accepted:
April 8,
2022
Received:
January 29,
2021
Identification
Copyright
© 2022 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.
