Background: With the rapid development and wide application of high-throughput sequencing technology, biomedical research has entered the era of large-scale omics data. We aim to identify genes associated with breast cancer prognosis by integrating multi-omics data.Method: Gene-gene interactions were taken into account, and we applied two differential network methods JDINAC and LGCDG to identify differential genes. The patients were divided into case and control groups according to their survival time. The TCGA and METABRIC database were used as the training and validation set respectively.Result: In the TCGA dataset, C11orf1, OLA1, RPL31, SPDL1 and IL33 were identified to be associated with prognosis of breast cancer. In the METABRIC database, ZNF273, ZBTB37, TRIM52, TSGA10, ZNF727, TRAF2, TSPAN17, USP28 and ZNF519 were identified as hub genes. In addition, RPL31, TMEM163 and ZNF273 were screened out in both datasets. GO enrichment analysis shows that most of these hub genes were involved in zinc ion binding.Conclusion: In this study, a total of 15 hub genes associated with long-term survival of breast cancer were identified, which can promote understanding of the molecular mechanism of breast cancer and provide new insight into clinical research and treatment.

Objective: The aim of this study was to evaluate the relationship between lifestyle habits and health-related quality of life (HRQoL) among different ages who were initially diagnosed with breast cancer (within the first 2 weeks) and to determine the contribution of lifestyle habits factors on HRQoL.Methods: Patients with breast cancer were recruited from 22 hospitals in 11 provinces or municipalities in northern and eastern China. The Functional Assessment of Cancer Therapy-Breast Cancer (FACT-B) was used to measure HRQoL. Chi-square test, ANOVA, and multivariable generalized linear models were conducted to identify the differences in HRQoL between two age groups (age <50 years and ≥50 years) and to evaluate the contribution of lifestyle habits factors on HRQoL of patients with breast cancer.Results: About 1,199 eligible patients with breast cancer were used for analysis. Younger women (aged <50 years) appeared to show lower scores than older women (aged ≥50 years) in HRQoL subscales, including emotional well-being (p = 0.003), functional well-being (p = 0.006), breast cancer subscale (p = 0.038), and FACT-B Total scores (p = 0.028). Tea and alcohol consumption and being very satisfied with sleep and current life were the strongest predictors of higher HRQoL in younger group. Meanwhile, no coffee consumption, frequent participation in physical activities, high sleep satisfaction, and current life satisfaction were the key predictors of higher HRQoL in older women with breast cancer.Conclusion: The relationship of the nine lifestyle habit items with HRQoL differed among younger and older women. The associated variable of low HRQoL can help clinicians take intervention early in order to improve the prognosis of patients with breast cancer.