Radiogenomic analysis of prediction HER2 status in breast cancer by linking ultrasound radiomic feature module with biological functions.

BACKGROUND: Human epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer and HER2 has been defined as a therapeutic target for breast cancer treatment. We aimed to explore the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive breast cancer using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in breast cancer. METHODS: This retrospective study included 489 patients who were diagnosed with breast cancer. URFs were extracted from a radiomics analysis set using PyRadiomics. The correlations between differential URFs and HER2-related genes were calculated using Pearson correlation analysis. Functional enrichment of the identified URFs-correlated HER2 positive-specific genes was performed. Lastly, the radiomics model was developed based on the URF-module mined from auxiliary differential URFs to assess the HER2 status of breast cancer. RESULTS: Eight differential URFs (p < 0.05) were identified among the 86 URFs extracted by Pyradiomics. 25 genes that were found to be the most closely associated with URFs. Then, the relevant biological functions of each differential URF were obtained through functional enrichment analysis. Among them, Zone Entropy is related to immune cell activity, which regulate the generation of calcification in breast cancer. The radiomics model based on the Logistic classifier and URF-module showed good discriminative ability (AUC = 0.80, 95% CI). CONCLUSION: We searched for the URFs of HER2-positive breast cancer, and explored the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-module relatively accurately predicted the HER2 status in breast cancer.

Comparison of breast-conserving surgery without radiotherapy and mastectomy in the treatment of elderly patients with early breast cancer: A PSM and SEER database study.

BACKGROUND: At present, there is no research on which surgical method can lead to a better prognosis in elderly patients with early breast cancer. The purpose of this study was to establish a nomogram to predict the survival outcome of elderly patients with early breast cancer and to compare the prognosis of the breast-conserving surgery (BCS) group who did not receive postoperative radiotherapy and the mastectomy group through risk stratification. METHODS: This study included patients with early breast cancer aged ≥70 years from the Surveillance, Epidemiology, and End Results database (n = 20,520). The group was randomly divided into a development cohort (n = 14,363) and a validation cohort (n = 6157) according to a ratio of 7:3. Risk factors affecting overall survival (OS) and breast-cancer-specific survival (BCSS) were analyzed using univariate and multivariate Cox regression. Present results were obtained by constructing nomograms and risk stratifications. Nomograms were evaluated by the concordance index and calibration curve. Kaplan-Meier curves were established based on BCSS and analyzed using the log-rank test. RESULTS: Multivariate Cox regression results showed that age, race, pathological grade, T and N stages, and progesterone receptor (PR) status were independent risk factors for OS and BCSS in the BCS group and mastectomy group. Subsequently, they were incorporated into nomograms to predict 3- and 5-year OS and BCSS in patients after BCS and mastectomy. The concordance index was between 0.704 and 0.832, and the nomograms also showed good calibration. The results of risk stratification showed that there was no survival difference between the BCS group and the mastectomy group in the low-risk and high-risk groups. In the middle-risk group, BCS improved the BCSS of patients to a certain extent. CONCLUSION: This study constructed a well-performing nomogram and risk stratification model to assess the survival benefit of BCS without postoperative radiotherapy in elderly patients with early breast cancer. The results of the study can help clinicians analyze the prognosis of patients and the benefits of surgical methods individually.