Germline Genetic Association between Stromal Interaction Molecule 1 (STIM1) and Clinical Outcomes in Breast Cancer Patients.
Chi-Cheng HuangMin-Rou LinYu-Chen YangYu-Wen HsuHenry Sung-Ching WongWei-Chiao ChangPublished in: Journal of personalized medicine (2020)
Among all cancers in women, breast cancer has the highest incidence. The mortality of breast cancer is highly associated with metastasis. Migration and malignant transformation of cancer cells have been reported to be modulated by store-operated calcium (SOC) channels, which control calcium signaling and cell proliferation pathways. Stromal interaction molecule 1 (STIM1) is a calcium sensor in the endoplasmic reticulum, triggering the activation of store-operated calcium signaling. However, the clinical relevance of STIM1 in breast cancer is still unclear. Here, we recruited 348 breast cancer patients and conducted a genetic association study to address this question. Four tagging germline single nucleotide variants (SNVs) in STIM1 were selected and RNA sequencing data of 525 breast cancer samples from The Cancer Genome Atlas (TCGA) database were evaluated. The results show that rs2304891 and rs3750996 were correlated with clinical stage of breast cancer. Expression quantitative trait loci (eQTL) analysis indicated that risk G allele of STIM1 contributed to the higher expression of STIM1. In addition, we found an increased risk of rs2304891 G allele and rs3750996 A allele in estrogen receptor (ER) positive and progesterone receptor (PR) positive patients. In conclusion, our results suggest that germline SNV, rs2304891 and rs3750996 as well as STIM1 expression are important biomarkers for the prediction of clinical outcomes in breast cancer patients.
Keyphrases
- estrogen receptor
- poor prognosis
- genome wide
- endoplasmic reticulum
- cell proliferation
- breast cancer risk
- bone marrow
- single cell
- dna repair
- end stage renal disease
- copy number
- newly diagnosed
- binding protein
- risk factors
- chronic kidney disease
- cardiovascular disease
- dna methylation
- emergency department
- electronic health record
- machine learning
- young adults
- ejection fraction
- high resolution
- long non coding rna
- childhood cancer
- dna damage
- pi k akt
- breast cancer cells
- data analysis
- adverse drug
- patient reported
- patient reported outcomes