Comparison of three lymph node staging methods for predicting outcome in breast cancer patients with mastectomy.

BACKGROUND: Axillary lymph node (ALN) staging is essential in predicting the clinical outcome of breast cancer (BC) patients. Traditionally, it follows the tumor-node-metastasis (TNM) staging, but its accuracy needs further improvement. METHODS: A total of 9,616 BC patients from the Surveillance, Epidemiology, and End Results (SEER) database and 675 patients from the First Affiliated Hospital of China Medical University underwent mastectomy together with ALN dissection were reviewed. Univariate and multivariate logistic analyses were conducted to find the most meaningful factors relevant to prognosis. RESULTS: After univariate and multivariate analyses, age, race, primary site, radiation, chemotherapy, grade, T-stage, estrogen receptor (ER), progesterone receptor (PR), total number of positive lymph nodes (pN), positive lymph node ratio (LNR) and log odds of positive LNs (LODDS) were found to be significantly associated with overall survival (OS). Using these non-LN risk factors, we further compared the efficacy of three different ALN staging methods in prognosis via nomograms. Harrell's concordance index (C-index) and Akaike Information Criterion (AIC) were used to measure nomogram performance of the ALN staging methods: pN: C-index=0.687 (95% CI: 0.678-0.696), AIC =61,398.24; LNR: C-index =0.691 (95% CI: 0.683-0.701), AIC =61,313.56; and LODDS: C-index =0.691 (95% CI: 0.682-0.700), AIC =61,315.60. We found that the nomogram incorporating LODDS had better predictive ability compared with other two methods. Furthermore, an external validation revealed a C-index of 0.753 (95% CI: 0.690-0.816) for the Asian population, which indicates the nomogram based on LODDS may have universality for both Western and Asian populations. CONCLUSIONS: Compared with pN and LNR, LODDS showed higher homeostasis in LN evaluation, and showed marked efficacy in evaluating survival differences among patients with negative LN staging. We constructed a BC prognosis model by incorporating highly relevant clinical pathological factors and a new method of LN staging, which may greatly aid in guiding postoperative treatment.

Nomogram for predicting axillary lymph node status after neoadjuvant chemotherapy in breast cancer.

BACKGROUND: Many breast cancer patients benefit from neoadjuvant chemotherapy (NAC). However, sentinel lymph node biopsy (SLNB) after NAC remains controversial, especially for patients with axillary lymph node metastasis (ALNM) at diagnosis. We developed a nomogram for predicting axillary lymph node (ALN) status after NAC to screen for patients for whom SLNB may be beneficial. METHODS: A total of 320 cT1-4N0-1M0 breast cancer patients receiving ALN dissection (ALND) after NAC were included. Univariate and multivariate logistic regression analyses determined significant factors for predicting ALN status. Efficacy of the resulting nomogram was assessed using receiver operating characteristic (ROC) and calibration curves, while decision curve analysis (DCA) was used to evaluated net clinical benefit. Our nomogram was validated using female patients grouped according to a diagnosis of node-positive (cN1) or node-negative (cN0) by ultrasound-guided needle biopsy of suspected lymph nodes before NAC. RESULTS: Logistic regression analyses indicated that estrogen receptor (ER), Ki67, degree of tumor regression, clinical tumor T stage after NAC, and ALN Breast Imagining-Reporting and Data System (BI-RADS) category after NAC, were associated with ALN status. The resulting nomogram had an area under the curve (AUC) of 0.802 [95% confidence interval (CI), 0.7485-0.8554], and the calibration plot showed strong uniformity between predicted and actual ALN status. DCA indicated a positive net benefit of nomogram predictions in our cohort. After internal validation, the cN1 and cN0 groups had an AUC of 0.7926 (95% CI, 0.7187-0.8665) and 0.8165 (95% CI, 0.7381-0.8949), respectively. The calibration plot indicated better performance in the cN0 group. CONCLUSIONS: After NAC, some patients may benefit from SLNB. Our nomogram predicts ALN status after NAC and has great potential to assist in clinical decision-making.

The Undervalued Effects of Polychlorinated Biphenyl Exposure on Breast Cancer.

The incidence of breast cancer across the world has been on the rise in recent decades. Because identified risk factors can only explain a relatively small portion of the cases, environmental exposure to organic pollutants is suspected to play a role in breast cancer etiology. Polychlorinated biphenyls (PCBs) are among the most abundant pollutants, and the impact of their exposure on breast cancer risk has been extensively studied in recent decades. However, the results of most epidemiologic studies do not support an association between PCB exposure and breast cancer risk. We hypothesized that the effects of PCBs on breast cancer might have been undervalued for reasons such as insufficient recognition of the confounding effects of several factors and lack of attention on the innate heterogeneity of PCB mixtures or breast cancer. After reviewing the evidence in the existing literature, we concluded that early life exposure, known risk factors of breast cancer, and impact of exposure to other pollutants are the main sources of confounding effects and have potentially masked the associations between PCBs and breast cancer. Because PCBs are mixtures of congeners with varied properties, and because breast cancers of different subtypes are etiologically distinct diseases, the absence of stratified subgroup analysis on individual PCBs and patients with specific biological subtypes and insufficient attention paid to the results of these subgroup analyses may result in an underestimation of the correlations between PCBs and breast cancer. In future studies, these factors must be taken into consideration when exploring the effect of PCB exposure on breast cancer risk.

Long non-coding RNA-CTD-2108O9.1 represses breast cancer metastasis by influencing leukemia inhibitory factor receptor.

Breast cancer (BC) is an aggressive malignant disease in women worldwide with a high tendency to metastasize. However, important biomarkers for BC metastasis remain largely undefined. In the present study, we identified that long non-coding RNA-CTD-2108O9.1 is downregulated in BC tissues and cells and acts as a metastatic inhibitor of BC. Mechanistic investigation determined that lncRNA-CTD-2108O9.1 represses metastasis by targeting leukemia inhibitory factor receptor (LIFR), which is designated as a metastasis suppressor in BC. Our study characterizes a significant tumor suppressor active in BC metastasis repression through the known metastasis inhibitor LIFR.