Preoperative Breast Immune Prognostic Index as Prognostic Factor Predicts the Clinical Outcomes of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.

This study aims at investigating the potential prognostic significance of the breast immune prognostic index (BIPI) in breast cancer patients who received neoadjuvant chemotherapy (NACT). The optimal cutoff value was calculated through the receiver operating characteristic curve (ROC). The correlations between BIPI and clinicopathologic characteristics were determined by the chi-square test or Fisher's exact test. The Kaplan-Meier method was used to estimate the survival probability, and the log-rank test was used to analyze the differences in the survival probability among patients. The univariate and multivariate Cox proportional hazard regression model was used to screen the independent prognostic factors. A prognostic nomogram for disease-free survival (DFS) and overall survival (OS) was built on the basis of the multivariate analyses. Furthermore, the calibration curve and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram. All enrolled patients were split into three subgroups based on the BIPI score. The mean DFS and OS of the BIPI score 0 group and BIPI score 1 group were significantly longer than those of the BIPI score 2 group (42.02 vs. 38.61 vs. 26.01 months, 77.61 vs. 71.83 vs. 53.15 months; p < 0.05). Univariate and multivariate analyses indicated that BIPI was an independent prognostic factor for patients' DFS and OS (DFS, hazard ratio (HR): 6.720, 95% confidence interval (CI): 1.629-27.717; OS, HR: 8.006, 95% CI: 1.638-39.119). A nomogram with a C-index of 0.873 (95% CI: 0.779-0.966) and 0.801 (95% CI: 0.702-0.901) had a favorable performance for predicting DFS and OS survival rates for clinical use by combining immune scores with other clinical features. The calibration curves at 1-, 3-, and 5-year survival suggested a good consistency between the predicted and actual DFS and OS probability. The DCA demonstrated that the constructed nomogram had better clinical predictive usefulness than only BIPI in predictive clinical applications of 5-year DFS and OS prognostic assessments. The patients with low BIPI score have better prognoses and longer DFS and OS. Furthermore, the BIPI-based nomogram may serve as a convenient prognostic tool for breast cancer and help in clinical decision-making.

Chen L ，Kong X ，Huang S ，Su Z ，Zhu M ，Fang Y ，Zhang L ，Li X ，Wang J ... -  《Frontiers in Immunology》

PD-L1 Protein Expression Is Associated With Good Clinical Outcomes and Nomogram for Prediction of Disease Free Survival and Overall Survival in Breast Cancer Patients Received Neoadjuvant Chemotherapy.

This study aims to investigate the potential prognostic significance of programmed death ligand-1 (PD-L1) protein expression in tumor cells of breast cancer patients received neoadjuvant chemotherapy (NACT). Using semiquantitative immunohistochemistry, the PD-L1 protein expression in breast cancer tissues was analyzed. The correlations between PD-L1 protein expression and clinicopathologic characteristics were analyzed using Chi-square test or Fisher's exact test. The survival curve was stemmed from Kaplan-Meier assay, and the log-rank test was used to compare survival distributions against individual index levels. Univariate and multivariate Cox proportional hazards regression models were accessed to analyze the associations between PD-L1 protein expression and survival outcomes. A predictive nomogram model was constructed in accordance with the results of multivariate Cox model. Calibration analyses and decision curve analyses (DCA) were performed for the calibration of the nomogram model, and subsequently adopted to assess the accuracy and benefits of the nomogram model. A total of 104 breast cancer patients received NACT were enrolled into this study. According to semiquantitative scoring for IHC, patients were divided into: low PD-L1 group (61 cases) and high PD-L1 group (43 cases). Patients with high PD-L1 protein expression were associated with longer disease free survival (DFS) (mean: 48.21 months vs. 31.16 months; P=0.011) and overall survival (OS) (mean: 83.18 months vs. 63.31 months; P=0.019) than those with low PD-L1 protein expression. Univariate and multivariate analyses indicated that PD-L1, duration of neoadjuvant therapy, E-Cadherin, targeted therapy were the independent prognostic factors for patients' DFS and OS. Nomogram based on these independent prognostic factors was used to evaluate the DFS and OS time. The calibration plots shown PD-L1 based nomogram predictions were basically consistent with actual observations for assessments of 1-, 3-, and 5-year DFS and OS time. The DCA curves indicated the PD-L1 based nomogram had better predictive clinical applications regarding prognostic assessments of 3- and 5-year DFS and OS, respectively. High PD-L1 protein expression was associated with significantly better prognoses and longer DFS and OS in breast cancer patients. Furthermore, PD-L1 protein expression was found to be a significant prognostic factor for patients who received NACT.

Chen L ，Huang S ，Liu Q ，Kong X ，Su Z ，Zhu M ，Fang Y ，Zhang L ，Li X ，Wang J ... -  《Frontiers in Immunology》

A prognostic model based on CLEC6A predicts clinical outcome of breast cancer patients.

CLEC6A, (C-type lectin domain family 6, member A), plays a prominent role in regulating innate immunity and adaptive immunity. CLEC6A has shown great potential as a target for cancer immunotherapy. This study aims to explore the prognostic value of CLEC6A, and analyze the relationship associated with the common hematological parameters in breast cancer patients. We performed a retrospective analysis on 183 breast cancer patients data in hospital information system from January 2013 to December 2015. The expression of CLEC6A was recorded via semiquantitative immunohistochemistry in breast cancer. The association between expression of CLEC6A and relative parameters were performed by Chi-square test and Fisher's exact test. Kaplan-Meier assay and Log-rank test were performed to evaluate the survival time. The Cox proportional hazards regression analysis was applied to identify prognostic factors. Nomograms were conducted to predict 1-, 3-, and 5-year disease free survival (DFS) and overall survival (OS) for breast cancer, which could be a good reference in clinical practice. The nomogram model was estimated by calibration curve analysis for its function of discrimination. The accuracy and benefit of the nomogram model were appraised by comparing it to only CLEC6A via decision curve analysis (DCA). The prediction accuracy of CLEC6A was also determined by time-dependent receiver operating characteristics (TDROC) curves, and the area under the curve (AUC) for different survival time. There were 94 cases in the CLEC6A low-expression group and 89 cases in CLEC6A high-expression group. Compared to CLEC6A low-expression group, the CLEC6A high-expression group had better survival (DFS: 56.95 vs. 70.81 months, P = 0.0078 and OS: 67.98 vs. 79.05 months, P = 0.0089). The CLEC6A was a potential prognostic factor in multivariate analysis (DFS: P = 0.023, hazard ratio (HR): 0.454, 95 % confidence interval (CI): 0.229-0.898; OS: P = 0.020, HR: 0.504, 95 %CI: 0.284-0.897). The nomogram in accordance with these potential prognostic factors was constructed to predict survival and the calibration curve analysis had indicated that the predicted line was well-matched with reference line in 1-, 3-, and 5-year DFS and OS category. The 1-, 3-, and 5-year DCA curves have revealed that nomogram model yielded larger net benefits than CLEC6A alone. Finally, the TDROC curve indicated that CLEC6A could better predict 1-year DFS and OS than others. Furthermore, we combined these potential independent prognostic factors to analyze the relationship among these hematologic index and oxidative stress indicators, and indicated that higher CLEC6A level, higher CO2 level or low CHOL level or high HDL-CHO level would have survived longer and better prognosis. In breast cancer, high expression of CLEC6A can independently predict better survival. Our nomogram consisted of CLEC6A and other indicators has good predictive performance and can facilitate clinical decision-making.

Chen L ，Dhoomun DK ，Liu Q ，Kong X ，Li X ，Peng S ，Lan P ，Wang J ... -  《-》

Pre-treatment systemic immune-inflammation index is a useful prognostic indicator in patients with breast cancer undergoing neoadjuvant chemotherapy.

The systemic immune-inflammation index (SII = N × P/L) based on neutrophil (N), platelet (P) and lymphocyte (L) counts is used to predict the survival of patients with malignant tumours and can fully reflect the balance between host inflammatory and immune status. This study is conducted to explore the potential prognostic significance of SII in patients with breast cancer undergoing neoadjuvant chemotherapy (NACT). A total of 262 patients with breast cancer received NACT were enrolled in this study. According to the receiver operating characteristic curve, the optimal cut-off value of SII was divided into two groups: low SII group (<602 × 109 /L) and high SII group (≥602 × 109 /L). The associations between breast cancer and clinicopathological variables by SII were determined by chi-squared test or Fisher's exact test. The Kaplan-Meier plots and log-rank test were used to determine clinical outcomes of disease-free survival (DFS) and overall survival (OS). The prognostic value of SII was analysed by univariate and multivariate Cox proportional hazards regression models. The toxicity of NACT was accessed by National Cancer Institute Common Toxicity Criteria (NCICTC). According to univariate and multivariate Cox regression survival analyses, the results showed that the value of SII had prognostic significance for DFS and OS. The patients with low SII value had longer DFS and OS than those with high SII value (31.11 vs 40.76 months, HR: 1.075, 95% CI: 0.718-1.610, P = .006; 44.47 vs 53.68 months, HR: 1.051, 95% CI: 0.707-1.564, P = .005, respectively). The incidence of DFS and OS in breast cancer patients with low SII value was higher than that in those patients with high SII value in 3-, 5- and 10-year rates. The common toxicities after NACT were haematological and gastrointestinal reaction, and there were no differences by SII for the assessment of side effects of neoadjuvant chemotherapy. Meanwhile, the results also proved that breast cancer patients with low SII value and high Miller and Payne grade (MPG) survived longer than those breast cancer with high SII value and low MPG grade. In patients without lymph vessel invasion, these breast cancer patients with low SII value had better prognosis and lower recurrence rates than those with high SII value. Pre-treatment SII with the advantage of reproducible, convenient and non-invasive was a useful prognostic indicator for breast cancer patients undergoing neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.

Chen L ，Kong X ，Wang Z ，Wang X ，Fang Y ，Wang J ... -  《-》

Prognostic Nutritional Index (PNI) in Patients With Breast Cancer Treated With Neoadjuvant Chemotherapy as a Useful Prognostic Indicator.

Prognostic nutritional index (PNI), calculated as serum albumin (ALB) (g/L) + 5 × total lymphocyte count (109/L), is initially used to evaluate nutritional status in patients undergoing surgery and may evaluate the therapeutic effects and predict the survival of various solid tumors. The present study aimed to evaluate the potential prognostic significance of PNI in breast cancer patients receiving neoadjuvant chemotherapy (NACT). A total of 785 breast cancer patients treated with neoadjuvant chemotherapy were enrolled in this retrospective study. The optimal cutoff value of PNI by receiver operating characteristic curve stratified patients into a low-PNI group (<51) and a high PNI group (≥51). The associations between breast cancer and clinicopathological variables by PNI were determined by chi-square test or Fisher's exact test. Kaplan-Meier plots and log-rank test were used to evaluate the clinical outcomes of disease-free survival (DFS) and overall survival (OS). The prognostic value of PNI was analyzed by univariate and multivariate Cox proportional hazards regression models. The toxicity of NACT was accessed by the National Cancer Institute Common Toxicity Criteria (NCI-CTC). The results indicated that PNI had prognostic significance by an optimal cutoff value of 51 on DFS and OS in univariate and multivariate Cox regression survival analyses. Breast cancer patients with a high PNI value had longer DFS and OS than those with a low PNI value [47.64 vs. 36.60 months, P < 0.0001, hazard ratio (HR) = 0.264, 95%CI = 0.160-0.435; 73.61 vs. 64.97 months, P < 0.0001, HR = 0.319, 95%CI = 0.207-0.491, respectively]. Furthermore, the results indicated that patients with high PNI had longer DFS and OS than those with low PNI in early stage and advanced breast cancer, especially in advanced breast cancer. The mean DFS and OS times for breast cancer patients with high PNI by the log-rank test were longer than in those with low PNI in different molecular subtypes. Moreover, the mean DFS and OS times in patients with high PNI by the log-rank test were longer than in those patients with low PNI without or with lymph vessel invasion. The common toxicities after neoadjuvant chemotherapy were hematologic and gastrointestinal reaction, and the PNI had no significance on the toxicities of all enrolled patients, except in anemia, leukopenia, and myelosuppression. Pretreatment PNI with the advantages of being convenient, noninvasive, and reproducible was a useful prognostic indicator for breast cancer patients receiving neoadjuvant chemotherapy and is a promising biomarker for breast cancer on treatment strategy decisions.

Chen L ，Bai P ，Kong X ，Huang S ，Wang Z ，Wang X ，Fang Y ，Wang J ... -  《Frontiers in Cell and Developmental Biology》