High-mobility group box 2 (HMGB2) is implicated in tumorigenesis in various cancers. However, the clinical significance of HMGB2 signaling in human breast cancer progression remains unknown. We investigated HMGB2 expression in 185 cases of primary breast cancer and matched normal breast tissue specimens, and explored the underlying mechanisms of altered HMGB2 expression as well as the impact of this altered expression on breast cancer growth and on aerobic glycolysis using in vitro and animal models of breast cancer. HMGB2 was more highly expressed in tumor-cell nuclei of breast cancer cells than in the adjacent normal breast tissues (P < 0.05). Higher HMGB2 expression correlated with larger tumor size (P = 0.003) and advanced tumor stage (P = 0.033). A Cox proportional hazards model revealed that HMGB2 expression was an independent prognostic factor for breast cancer after radical resection (P < 0.05). Experimentally, knockdown of HMGB2 expression by stable transfected shRNA significantly decreased the growth and glycolysis of breast cancer cells both in vitro and in mouse models. Mechanically, promotion of breast cancer progression by HMGB2 directly and significantly correlated with activation of LDHB expression and inactivation of FBP1 expression. These results disclose a novel role for HMGB2 in reprogramming the metabolic process in breast cancer cells by targeting LDHB and FBP1 and provide potential prognostic predictors for breast cancer patients.

Background: Young breast cancer (YBC) patients are more prone to lymph node metastasis than other age groups. Our study aimed to investigate the predictive value of lymph node ratio (LNR) in YBC patients and create a nomogram to predict overall survival (OS), thus helping clinical diagnosis and treatment.Methods: Patients diagnosed with YBC between January 2010 and December 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into a training set and an internal validation set with a ratio of 7:3. An independent cohort from our hospital was used for external validation. Univariate and least absolute shrinkage and selection operator (LASSO) regression were used to identify the significant factors associated with prognosis, which were used to create a nomogram for predicting 3- and 5-year OS.Results: We selected seven survival predictors (tumor grade, T-stage, N-stage, LNR, ER status, PR status, HER2 status) for nomogram construction. The C-indexes in the training set, the internal validation set, and the external validation set were 0.775, 0.778 and 0.817, respectively. The nomogram model was well calibrated, and the time-dependent ROC curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improve the discrimination of YBC prognosis.Conclusions: LNR is a strong predictor of OS in YBC patients. The novel nomogram based on LNR is a reliable tool to predict survival, which may assist clinicians in identifying high-risk patients and devising individual treatments.

Aberrant DNA methylation that leads to the inactivation of tumor suppressor genes is known to play an important role in the development and progression of breast cancer. Methylation status of cancer-related genes is considered to be a promising biomarker for the early diagnosis and prognosis of tumors. This study investigated the methylation status of the Sox17 gene in breast cancer tissue and its corresponding plasma DNA to evaluate the association of methylation levels with clinicopathological parameters and prognosis.The methylation status of the Sox17 gene promoter was evaluated with methylation-specific polymerase chain reaction (MSP) in 155 paired breast cancer tissue and plasma samples and in 60 paired normal breast tissue and plasma samples. Association of Sox17 methylation status with clinicopathological parameters was analyzed by χ tests. Overall and disease-free survival (DFS) curves were calculated using Kaplan-Meier analysis, and the differences between curves were analyzed by log-rank tests.The frequency of Sox17 gene methylation was 72.9% (113/155) in breast cancer tissues and 58.1% (90/155) in plasma DNA. Sox17 gene methylation was not found in normal breast tissues or in their paired plasma DNA. There was a significant correlation of Sox17 methylation between corresponding tumor tissues and paired plasma DNA (r = 0.688, P < 0.001). Aberrant Sox17 methylation in cancer tissues and in plasma DNA was significantly associated with the tumor node metastasis stage (P = 0.035 and P = 0.001, respectively) and with lymph node metastasis (P < 0.001 and P = 0.001, respectively). Kaplan-Meier survival curves showed that aberrant Sox17 promoter methylation in cancer tissues and plasma DNA was associated with poor DFS (P < 0.005) and overall survival (OS) (P < 0.005). Multivariate analysis showed that Sox17 methylation in plasma DNA was an independent prognostic factor in breast cancer for both DFS (P = 0.020; hazard ratio [HR] = 2.142; 95% confidence interval [CI]: 1.128-4.067) and for OS (P = 0.001; HR = 4.737; 95% CI: 2.088-10.747).Sox17 gene promoter methylation may play an important role in breast cancer progression and could be used as a prognostic biomarker to identify patients at risk of developing metastasis or recurrence after mastectomy.

The aim of this study was to explore the characteristics and prognostic information of estrogen receptor-positive/progesterone receptor-negative (ER+/PR−) male breast cancer. Using the US National Cancer Institute’s Surveillance, Epidemiology, and End Results database, we compared the demographics, clinical characteristics, and outcome of estrogen receptor-positive/progesterone receptor-positive (ER+/PR+) patients with ER+/PR− male breast cancer patients from 1990 to 2010. Two thousand three hundred twenty-two patients with ER+/PR+ tumors and 355 patients with ER+/PR− tumors were included in our study. ER+/PR− patients were younger (P = 0.008) and more likely to be African American (P < 0.001) while presented with higher histological grade (P < 0.001), larger tumor size (P = 0.010), and more invasion to the lymph nodes (P = 0.034) and distant sites (P < 0.001), thus later stage (P = 0.001). Despite higher chance of receiving chemotherapy (51.0% vs 36.5%, P < 0.001), ER+/PR− patients experienced significantly worse breast cancer-specific survival (BSCC) (P < 0.001) and shorter overall survival (OS) (P = 0.003). Multivariate Cox model confirmed that tumor size, lymph node invasion, metastasis, and surgery were independent prognostic factors of both BSCC and OS for ER+/PR− male breast cancer. Age at diagnosis and chemotherapy were significantly associated with OS but not with BSCC. ER+/PR− male breast cancer was more aggressive and experienced shorter survival than ER+/PR+ patients. The prognosis was mainly associated with tumor size, lymph node invasion, metastasis, and surgery.

Background: Cancer-associated fibroblasts (CAFs) play a pivotal role in cancer progression and are known to mediate endocrine and chemotherapy resistance through paracrine signaling. Additionally, they directly influence the expression and growth dependence of ER in Luminal breast cancer (LBC). This study aims to investigate stromal CAF-related factors and develop a CAF-related classifier to predict the prognosis and therapeutic outcomes in LBC.Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to obtain mRNA expression and clinical information from 694 and 101 LBC samples, respectively. CAF infiltrations were determined by estimating the proportion of immune and cancer cells (EPIC) method, while stromal scores were calculated using the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Weighted gene co-expression network analysis (WGCNA) was used to identify stromal CAF-related genes. A CAF risk signature was developed through univariate and least absolute shrinkage and selection operator method (LASSO) Cox regression model. The Spearman test was used to evaluate the correlation between CAF risk score, CAF markers, and CAF infiltrations estimated through EPIC, xCell, microenvironment cell populations-counter (MCP-counter), and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms. The TIDE algorithm was further utilized to assess the response to immunotherapy. Additionally, Gene set enrichment analysis (GSEA) was applied to elucidate the molecular mechanisms underlying the findings.Results: We constructed a 5-gene prognostic model consisting of RIN2, THBS1, IL1R1, RAB31, and COL11A1 for CAF. Using the median CAF risk score as the cutoff, we classified LBC patients into high- and low-CAF-risk groups and found that those in the high-risk group had a significantly worse prognosis. Spearman correlation analyses demonstrated a strong positive correlation between the CAF risk score and stromal and CAF infiltrations, with the five model genes showing positive correlations with CAF markers. In addition, the TIDE analysis revealed that high-CAF-risk patients were less likely to respond to immunotherapy. Gene set enrichment analysis (GSEA) identified significant enrichment of ECM receptor interaction, regulation of actin cytoskeleton, epithelial-mesenchymal transition (EMT), and TGF-β signaling pathway gene sets in the high-CAF-risk group patients.Conclusion: The five-gene prognostic CAF signature presented in this study was not only reliable for predicting prognosis in LBC patients, but it was also effective in estimating clinical immunotherapy response. These findings have significant clinical implications, as the signature may guide tailored anti-CAF therapy in combination with immunotherapy for LBC patients.