Bioinformatics analysis of prognostic value of PITX1 gene in breast cancer.

Abstract

BACKGROUND:

Paired-like homeodomain transcription factor 1 (PITX1) participates in miscellaneous biological processes including cell growth, development, progression and invasion in various malignant tumors. However, the analysis of the association between PITX1 expression and the survival in breast cancer remains unclear.

METHODS:

Clinical prognostic parameters and survival data related to PITX1 in breast cancer patients were performed using the bioinformatic analysis including Oncomine, Bc-GenExMiner v4.3, PrognoScan and UCSC Xena.

RESULTS:

We found that PITX1 gene expression was significantly higher in different histological classification of breast cancer. The Scarff-Bloom-Richardson (SBR) grade, Nottingham prognostic index (NPI), estrogen receptor (ER) negative, epidermal growth factor receptor-2 (HER2) positive, lymph node positive, triple-negative status and basal-like status were positively correlated with PITX1 level, except for patients' age and the progesterone receptor (PR) status. We have found that the increased PITX1 expression correlated with worse relapse-free survival, disease specific survival and overall survival. PITX1 was positively correlated with metastatic relapse-free survival and distant metastasis-free survival. We also confirmed positive correlation between PITX1 and the nucleotide-binding oligomerization domain 2 (NOD2).

CONCLUSION:

The lower expression of PITX1 was associated with better clinical prognostic parameters and clinical survival in breast cancer according to the bioinformatic analysis.

• Authors: Qiaoyun Wang, Shuai Zhao, Lei Gan, Zhixiang Zhuang
• Journal: Bioscience reports (Biosci Rep) Vol. 40 Issue 9 (09 30 2020) ISSN: 1573-4935 [Electronic] England
• PMID: 32830857 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © 2020 The Author(s).

Chemical References

• Paired Box Transcription Factors
• homeobox protein PITX1

Topics

• Breast Neoplasms (genetics, mortality, pathology)
• Computational Biology (methods)
• Databases, Factual
• Female
• Gene Expression Regulation, Neoplastic
• Humans
• Paired Box Transcription Factors (genetics)
• Prognosis