Clinicopathological characteristics, local treatment, and prognostic factors in IE/IIE primary breast lymphoma: a retrospective study of 67 patients.

INTRODUCTION: Primary breast lymphoma (PBL) is a rare disease, treatment of which excerpts does not reach a consensus. This retrospective study was conducted to analyze clinical features and survival outcomes of different therapeutic methods. MATERIALS AND METHODS: Records of 67 patients with stage IE/IIE primary breast lymphoma were reviewed from the medical record system. Survival information was gathered by searching the outpatient system. Clinicopathological characteristics were compared by chi-squared or Fisher's exact tests. A comparison of survival curves was performed by log-rank tests. The Cox proportional hazard model was applied for multivariate analysis. RESULTS: At the median follow-up time of 65.23 months (range, 9-150 months), there were 27 (40.3%) relapses, 28 (41.8%) distant metastases, and 21 (31.3%) deaths. The 5-year progression-free survival (PFS) and overall survival (OS) were 52.1% and 72.4%. Pathological types (DLBCL vs. non-DLBCL, p = 0.001) and rituximab use (p < 0.001) were statistically associated with longer PFS in patients with PBL. Nodal sites involved and radiotherapy administration were significant predictors for 5-year OS. Multivariate analysis suggested that nodal sites involved (p = 0.005) and radiotherapy administration (p < 0.003) were independent prognostic factors for OS in patients with PBL (p < 0.05). Radical surgery was not an independent factor for patients with PBL. CONCLUSIONS: Radiotherapy improved the survival of patients with PBL. Radical mastectomy offered no additional benefit in the treatment of PBL.

Nomograms predict survival in elderly women with triple-negative breast cancer: A SEER population-based study.

BACKGROUND: The effective treatment of breast cancer in elderly patients remains a major challenge. OBJECTIVE: To construct a nomogram affecting the overall survival of triple-negative breast cancer (TNBC) and establish a survival risk prediction model. METHODS: A total of 5317 TPBC patients with negative expression of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) who were diagnosed and received systematic treatment from 2010 to 2015 were collected from the American Cancer Surveillance, Epidemiology and End Results (SEER) database. They were randomly divided into training set (n= 3721) and validation set (n= 1596). Univariate and multivariate Cox regression analysis were used to identify prognostic features, and a nomogram was established to predict the probability of 1-year, 3-year and 5-year OS and BCSS. We used consistency index (C-index), calibration curve, area under the curve (AUC) and decision curve analysis (DCA) to evaluate the predictive performance and clinical utility of the nomogram. RESULTS: The C-indices of the nomograms for OS and BCSS in the training cohort were 0.797 and 0.825, respectively, whereas those in the validation cohort were 0.795 and 0.818, respectively. The receiver operating characteristic (ROC) curves had higher sensitivity at all specificity values as compared with the Tumor Node Metastasis (TNM) system. The calibration plot revealed a satisfactory relationship between survival rates and predicted outcomes in both the training and validation cohorts. DCA demonstrated that the nomogram had clinical utility when compared with the TNM staging system. CONCLUSION: This study provides information on population-based clinical characteristics and prognostic factors for patients with triple-negative breast cancer, and constructs a reliable and accurate prognostic nomogram.

A Novel Oxidative Stress-Related lncRNA Signature That Predicts the Prognosis and Tumor Immune Microenvironment of Breast Cancer.

Background: The association between oxidative stress and lncRNAs within the cancer-related researching field has been a controversial subject. At present, the exact function of oxidative stress as well as lncRNAs exert in breast cancer (BC) are still unclear. Therefore, the present study examined the lncRNAs oxidative stress-related in BC. Methods: Transcriptome data of BC obtained from TCGA (The Cancer Genome Atlas) database were used to generate synthetic matrices. Patients with breast cancer were randomly assigned to training, testing, or combined groups. The prognostic signature of oxidative stress was created using the selection operator Cox regression method, and the difference in prognosis between groups was examined using Kaplan-Meier curves, the accuracy of which was calculated using a receiver-operating characteristic-area through the curve (ROC-AUC) analysis with internal validation. Also, the Gene Set Enrichment Analyses (GSEA) was applied for the analysis of the risk groups. To conclude, the half-maximal inhibitory concentration (IC50) of these groups were investigated by immunoassay assay. Results: A model based on 7 lncRNAs related to oxidative stress was proposed, and the calibration plots and projected prognosis matched well. For prognosis at 5, 3, and 1 year, the area under the ROC curve (AUC) values were 0.777, 0.777, and 0.759. The functions of target genes identified by GSEA appear to be mainly expressed in metabolism, signal transduction, tumorigenesis, and also the progression. The remarkable differences in IC50 and gene expression between risk groups in this study provide a deep insight for further systemic treatment. Higher macrophage scores were acquired in the high-risk group, of which patients showed more response to conventional chemotherapy drugs, such as AKT inhibitor VIII and Lapatinib, as well as immunotherapy strategies including anti-CD80, TNF SF4, CD276, and NRP1. Conclusion: The prognosis of breast cancer can be independently predicted by the markers, which sheds light on further research of the specific role of lncRNAs which are oxidative stress-related and clinical treatment of breast cancer.