Integrative analysis identifies cancer cell-intrinsic RARRES1 as a predictor of prognosis and immune response in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis and limited treatment options. Although immune checkpoint inhibitors (ICIs) have been proven to improve outcomes in TNBC patients, the potential mechanisms and markers that determine the therapeutic response to ICIs remains uncertain. Revealing the relationship and interaction between cancer cells and tumor microenvironment (TME) could be helpful in predicting treatment efficacy and developing novel therapeutic agents. By analyzing single-cell RNA sequencing dataset, we comprehensively profiled cell types and subpopulations as well as identified their signatures in the TME of TNBC. We also proposed a method for quantitatively assessment of the TME immune profile and provided a framework for identifying cancer cell-intrinsic features associated with TME through integrated analysis. Using integrative analyses, RARRES1 was identified as a TME-associated gene, whose expression was positively correlated with prognosis and response to ICIs in TNBC. In conclusion, this study characterized the heterogeneity of cellular components in TME of TNBC patients, and brought new insights into the relationship between cancer cells and TME. In addition, RARRES1 was identified as a potential predictor of prognosis and response to ICIs in TNBC.

A multicenter study of the clinicopathological characteristics and a risk prediction model of early-stage breast cancer with hormone receptor-positive/human epidermal growth factor receptor 2-low expression.

BACKGROUND: In light of the significant clinical benefits of antibody-drug conjugates in clinical trials, the human epidermal growth factor receptor 2 (HER2)-low category in breast cancers has gained increasing attention. Therefore, we studied the clinicopathological characteristics of Chinese patients with hormone receptor (HR)-positive/HER2-low early-stage breast cancer and developed a recurrence risk prediction model. METHODS: Female patients with HR-positive/HER2-low early-stage breast cancer treated in 29 hospitals of the Chinese Society of Breast Surgery (CSBrS) from Jan 2015 to Dec 2016 were enrolled. Their clinicopathological data and prognostic information were collected, and machine learning methods were used to analyze the prognostic factors. RESULTS: In total, 25,096 patients were diagnosed with breast cancer in 29 hospitals of CSBrS from Jan 2015 to Dec 2016, and clinicopathological data for 6486 patients with HER2-low early-stage breast cancer were collected. Among them, 5629 patients (86.79%) were HR-positive. The median follow-up time was 57 months (4, 76 months); the 5-year disease-free survival (DFS) rate was 92.7%, and the 5-year overall survival (OS) rate was 97.7%. In total, 412 cases (7.31%) of metastasis were observed, and 124 (2.20%) patients died. Multivariate Cox regression analysis revealed that T stage, N stage, lymphovascular thrombosis, Ki-67 index, and prognostic stage were associated with recurrence and metastasis ( P <0.05). A recurrence risk prediction model was established using the random forest method and exhibited a sensitivity of 81.1%, specificity of 71.7%, positive predictive value of 74.1%, and negative predictive value of 79.2%. CONCLUSION: Most of patients with HER2-low early-stage breast cancer were HR-positive, and patients had favorable outcome; tumor N stage, lymphovascular thrombosis, Ki-67 index, and tumor prognostic stage were prognostic factors. The HR-positive/HER2-low early-stage breast cancer recurrence prediction model established based on the random forest method has a good reference value for predicting 5-year recurrence events. REGISTRITATION: ChiCTR.org.cn, ChiCTR2100046766.

Comparison of adverse effects of anti-tumor therapy for breast cancer shortly after COVID-19 diagnosis vs. the control period.

Background: COVID-19 is an acute infectious disease caused by SARS-CoV-2. The best time to restart antitumor therapy in breast cancer patients after SARS-CoV-2 infection is unknown. This study aimed to evaluate treatment-related adverse events in breast cancer patients who received antitumor therapies within a short time after SARS-CoV-2 infection (observation) as well as before (control) and to provide safety data. Methods: We conducted a self-controlled cohort study using the data from the Breast Disease Center of Peking University First Hospital. We identified patients who received antitumor therapy within 28 days after COVID-19 infection between December 20, 2022, and January 20, 2023. The primary outcome was treatment-related adverse events. McNemar's test was used to compare the incidence rate of adverse reactions between periods. Results: We identified 183 patients with breast cancer, of whom 109 were infected with SARS-CoV-2 within 28 days before antitumor treatment and were included. In total, 28 patients (25.7%) received neoadjuvant therapy, 60 (55.0%) received adjuvant therapy, and 21 (19.3%) received advanced rescue therapy. None of patients required hospitalization for severe or critical COVID-19, but 15 patients (13.8%) still had sequelae of COVID-19 while receiving antitumor treatment. The most common adverse events were peripheral neuropathy (n = 32 [29.4%]), pain (n = 29 [26.6%]), fatigue (n = 28 [25.7%]), nausea (n = 23 [21.1%]), and neutropenia (n = 19 [17.4%]). There was no increased risk of overall treatment-related adverse events (n = 87 [79.8%] vs. n = 91 [83.5%]; p = 0.42) or serious adverse events (n = 13 [11.9%] vs. n = 12 [11.0%]; p = 1.00) from receiving antitumor therapy shortly after the diagnosis of COVID-19. We also found no increased risk in subgroup analyses, and no patients discontinued antitumor therapy due to adverse events. Conclusion: Restarting antitumor therapy 2-4 weeks after having mild or moderate COVID-19 is a relatively safe strategy for breast cancer patients that does not increase the risk of treatment-related adverse events.

Development and external validation of a prediction model for brain metastases in patients with metastatic breast cancer.

BACKGROUND: Breast cancer patients with brain metastasis (BM) have a poor prognosis. This study aims to identify the risk factors of BM in patients with metastatic breast cancer (MBC) and establish a competing risk model for predicting the risk of brain metastases at different time points along the course of disease. METHODS: Patients with MBC admitted to the breast disease center of Peking University First Hospital from 2008 to 2019 were selected and retrospectively analyzed to establish a risk prediction model for brain metastases. Patients with MBC admitted to eight breast disease centers from 2015 to 2017 were selected for external validation of the competing risk model. The competing risk approach was used to estimate cumulative incidence. Univariate Fine-Gray competing risk regression, optimal subset regression, and LASSO Cox regression were used to screen potential predictors of brain metastases. Based on the results, a competing risk model for predicting brain metastases was established. The discrimination of the model was evaluated using AUC, Brier score, and C-index. The calibration was evaluated by the calibration curves. The model was assessed for clinical utility by decision curve analysis (DCA), as well as by comparing the cumulative incidence of brain metastases between groups with different predicted risks. RESULTS: From 2008 to 2019, a total of 327 patients with MBC in the breast disease center of Peking University First Hospital were admitted into the training set for this study. Among them, 74 (22.6%) patients developed brain metastases. From 2015 to 2017, a total of 160 patients with MBC in eight breast disease centers were admitted into the validation set for this study. Among them, 26 (16.3%) patients developed brain metastases. BMI, age, histological type, breast cancer subtype, and extracranial metastasis pattern were included in the final competing risk model for BM. The C-index of the prediction model in the validation set was 0.695, and the AUCs for predicting the risk of brain metastases within 1, 3, and 5 years were 0.674, 0.670, and 0.729, respectively. Time-dependent DCA curves demonstrated a net benefit of the prediction model with thresholds of 9-26% and 13-40% when predicting the risk of brain metastases at 1 and 3 years, respectively. Significant differences were observed in the cumulative incidence of brain metastases between groups with different predicted risks (P < 0.05 by Gray's test). CONCLUSIONS: In this study, a competing risk model for BM was innovatively established, with the multicenter data being used as an independent external validation set to confirm the predictive efficiency and universality of the model. The C-index, calibration curves, and DCA of the prediction model indicated good discrimination, calibration, and clinical utility, respectively. Considering the high risk of death in patients with metastatic breast cancer, the competing risk model of this study is more accurate in predicting the risk of brain metastases compared with the traditional Logistic and Cox regression models.

Diagnostic Value of Ultrasound Elastography in the Differentiation of Breast Invasive Ductal Carcinoma and Ductal Carcinoma In situ.

BACKGROUND: Ultrasound elastography (US-E) has been shown superior to the conventional US in diagnosing benign and malignant breast lesions. In contrast, the role of US-E in the differentiation of breast invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS) has been poorly described. OBJECTIVE: This study was designed to examine the diagnostic value of US-E in the differentiation of IDC and DCIS. METHODS: Medical records of all patients who underwent preoperative US-E evaluation and were diagnosed with IDC or DCIS at our hospital from April-December 2019 were retrieved and analyzed. Those who had prior surgical treatment, chemotherapy or radiotherapy were excluded. RESULTS: Twenty women with DCIS and 111 women with IDC were included in this study. There were no significant differences in age, maximum lesion diameter and tumor volume between the two groups. While shear wave velocity (SWV) inside the lesion and in the surrounding tissue, strain ratio and tumor area ratio were not substantially different between the two groups, SWV at the edge of the lesion was significantly higher in IDC cases, which had an AUC value of 0.66 with a sensitivity of 65.8% and a specificity of 60.0% for the differential diagnosis of IDC and DCIS. CONCLUSION: Edge SWV is significantly higher in IDC than that in DCIS, which had a moderate diagnostic value for the differentiation of IDC and DCIS, similar to the performance of diffusion-weighted magnetic resonance imaging as reported in the literature. In terms of cost-effectiveness, US-E could be very useful while waiting for further evaluations to determine whether US-E combined with other diagnostic modalities improves the diagnostic performance.

To diagnose primary and secondary squamous cell carcinoma of the thyroid with ultrasound malignancy risk stratification.

Objectives: This study aimed to investigate the clinico-ultrasound features of primary squamous cell carcinoma of the thyroid (PSCCT) and secondary SCCT (SSCCT) and evaluate the accuracy of fine needle aspiration (FNA) recommendation for SCCT with American College of Radiology-Thyroid Imaging and Reporting Data System (ACR-TIRADS) and Chinese-TIRADS (C-TIRADS). Materials and methods: We retrieved 26 SCCT patients (11 PSCCT, 15 SSCCT) from our hospital's pathology database (5,718 patients with thyroid malignancy) over 23 years. Medical records and ultrasound data of the 26 patients with 27 SCCTs were analyzed retrospectively, and each SCCT focus was categorized based on the two TIRADSs. Results: For 26 patients (21 males, 5 females) with an age range of 42-81 years, rapidly enlarging thyroid/neck nodules (18/26, 69.2%), dysphagia (7/26, 26.9%), hoarseness (6/26, 23.1%), dyspnea (5/26, 19.6%), cough (4/26, 15.4%), neck pain (2/26, 7.7%), B symptoms (2/26, 7.7%), and blood in sputum (1/26, 3.8%) were presented at diagnosis. Five asymptomatic patients (5/26, 19.2%) were detected by ultrasound. Hoarseness was more common in PSCCT (5/11, 45.5%) than in SSCCT (1/15, 6.7%) (P=0.032). For 27 SCCTs with a mean size of 3.7 ± 1.3 cm, the ultrasound features consisted of solid (25/27, 92.6%) or almost completely solid composition (2/27, 7.4%), hypoechoic (17/27, 63%) and very hypoechoic echogenicity (10/27, 37%), irregular/lobulated margin with extra-thyroidal extension (27/27, 100%), taller-than-wide shape (13/27, 48.1%), punctate echogenic foci (6/27, 22.2%), hypervascularity (23/27, 85.2%) and involved neck lymph (13/26, 50.0%). A total of 27 SCCTs were evaluated as high malignancy risk stratification (≥TR4 and 4B) by the two TIRADSs and recommended FNA in 96.3-100% (26/27, 27/27). Pathologically, more than half of PSCCTs (7/12, 58.3%) and a quarter of SSCCTs (4/15, 26.7%) were poorly differentiated, while moderately and well-differentiated grades were observed in 5 PSCCTs and 11 SSCCTs (P=0.007). Thirteen patients (50.0%) underwent surgery with radical operation in 5 cases (5/13, 38.5%). Conclusion: SCCT is an extremely rare and aggressive malignancy with a male predominance. PSCCT and SSCCT had similar clinical and ultrasound features except for tumor differentiation and the symptom of hoarseness. SCCT showed a high malignancy risk stratification in ACR-TIRADS and C-TIRADS, with a high rate of FNA recommendation.

A multicenter study on efficacy of dual-target neoadjuvant therapy for HER2-positive breast cancer and a consistent analysis of efficacy evaluation of neoadjuvant therapy by Miller-Payne and RCB pathological evaluation systems (CSBrS-026).

Objective: The aim of this study was to investigate the factors influencing pathological complete response (pCR) rate in early breast cancer patients receiving neoadjuvant dual-target [trastuzumab (H) + pertuzumab (P)] therapy combined with chemotherapy. Additionally, the consistency of the Miller-Payne and residual cancer burden (RCB) systems in evaluating the efficacy of neoadjuvant therapy for early human epidermal growth factor receptor-2 (HER2)+ breast cancer was analyzed. Methods: The clinicopathological data of female patients with early-stage HER2+ breast cancer who received dual-target neoadjuvant therapy at 26 hospitals of the Chinese Society of Breast Surgery (CSBrS) from March 2019 to December 2021 were collected. Patients were allocated to four groups: the HER2 immunohistochemistry (IHC) 3+/hormone receptor (HR)-, IHC3+/HR+, IHC2+ in situ hybridization (ISH)+/HR- and IHC2+ ISH+/HR+ groups. The overall pCR rate for patients, the pCR rate in each group and the factors affecting the pCR rate were analyzed. The consistency between the Miller-Payne and RCB systems in assessing the efficacy of neoadjuvant therapy was analyzed. Results: From March 1, 2019, to December 31, 2021, 77,376 female patients with early-stage breast cancer were treated at 26 hospitals; 18,853 (24.4%) of these patients were HER2+. After exclusion of unqualified patients, 2,395 patients who received neoadjuvant dual-target (H+P) therapy combined with chemotherapy were included in this study. The overall pCR rate was 53.0%, and the patients' HR statuses and different HER2+ statuses were significantly correlated with the pCR rate (P<0.05). The consistency of the pathological efficacy assessed by the Miller-Payne and RCB systems was 88.0% (κ=0.717, P<0.001). Conclusions: Different HER2 expression statuses and HR expression statuses are correlated with the pCR rate after dual-target neoadjuvant therapy in HER2+ breast cancer patients. There is a relatively good consistency between Miller-Payne and RCB systems in evaluating the pathologic efficacy of neoadjuvant therapy for HER2+ breast cancer.

Correlation between Androgen Receptor Expression in Luminal B (HER-2 Negative) Breast Cancer and Disease Outcomes.

(1) Background: Hormone receptor positive breast cancer is a subtype of breast cancer with relatively good prognosis, but luminal B (HER−2 negative) breast cancer has a higher risk of recurrence and metastasis. Patients with endocrine therapy resistance and chemotherapy insensitivity have poor prognosis. Androgen receptor (AR) is widely expressed in breast cancer, but there is no clear conclusion about its function and correlation with prognosis in luminal B breast cancer. Further research is needed to reveal the role of AR in luminal B (HER−2 negative) breast cancer. (2) Methods: Retrospectively analyzed patients with early−stage luminal B breast cancer. The correlation between AR and its associated indexes with long−term survival was determined. (3) Results: A total of 985 patients were included with 143 treated by neoadjuvant therapy. Of these, 83.5% of the patients had AR expression ≥65%. High AR expression was associated with good disease−free survival (DFS) and overall survival (OS). In the neoadjuvant population, AR/estrogen receptor (ER) > 1.06 and residual tumor Ki67 > 23% had significantly worse DFS. (4) Conclusion: Low AR (<65%) expression is associated with poor prognosis in luminal B (HER−2 negative) breast cancer patients. High AR/ER and residual tumor Ki67 were associated with poor DFS in neoadjuvant group with a cutoff value of AR/ER > 1.06 and residual tumor Ki67 > 23%.

Regulation of piglet T-cell immune responses by thioredoxin peroxidase from Cysticercus cellulosae excretory-secretory antigens.

Taenia solium (T. solium) cysticercosis is a serious threat to human health and animal husbandry. During parasitization, Cysticercus cellulosae (C. cellulosae) can excrete and secrete antigens that modulate the host's T-cell immune responses. However, the composition of C. cellulosae excretory-secretory antigens (ESAs) is complex. This study sought to identify the key molecules in C. cellulosae ESAs involved in regulating T-cell immune responses. Thus, we screened for thioredoxin peroxidase (TPx), with the highest differential expression, as the key target by label-free quantification proteomics of C. cellulosae and its ESAs. In addition, we verified whether TPx protein mainly exists in C. cellulosae ESAs. The TPx recombinant protein was prepared by eukaryotic expression, and ESAs were used as the experimental group to further investigate the effect of TPx protein on the immune response of piglet T cells in vitro. TPx protein induced an increase in CD4+ T cells in piglet peripheral blood mononuclear cells (PBMCs), while CD8+ T cells did not change significantly. This resulted in an imbalance in the CD4+/CD8+ T-cell ratio and an increase in CD4+CD25+Foxp3+ Treg cells in the PBMCs. In addition, TPx protein initiated T helper 2 (Th2)-type immune responses by secreting IL-4 and IL-10 and suppressed Th1/Th17-type immune responses. The results showed that ESAs were involved in regulating piglet T-cell immune responses cells. This suggests that TPx protein found in ESAs plays an essential role to help the parasite evade host immune attack. Moreover, this lays a foundation for the subsequent exploration of the mechanism through which TPx protein regulates signaling molecules to influence T-cell differentiation.

The value of ultrasound elastography combined with multi-parameters in the diagnosis of BI-RADS 4 breast lesions.

BACKGROUND: Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%) in the global cancer statistics 2020. OBJECTIVE: To evaluate the diagnostic value of ultrasound elastography combined with multi-parameters in differentiating category 4 benign and malignant lesions in the breast imaging reporting and data system (BI-RADS). METHODS: This study retrospectively analyzed 206 patients (213 breast lesions) who visited the Department of Breast Surgery and underwent a breast core needle biopsy in the Department of Ultrasound in Peking University First hospital from April to December 2019. The shear wave velocity (SWV) values were collected at the following locations by virtual touch tissue imaging quantification (VTIQ): breast lesion interior, breast lesion margin, surrounding glands, and surrounding fat. Simultaneously, the strain ratio (SR) of breast lesions to glands and the area ratio (AR) of breast lesions were collected under strain elastography and a two-dimensional ultrasound mode. RESULTS: Univariate analysis found that the SWV value, measured by ultrasound elastography parameters, and the AR between the elasticity and the two-dimensional ultrasound breast lesions showed statistical differences when differentiating benign and malignant lesions (p< 0.05). Binary logistic regression analysis found that the SWV values of the lesion interior and the surrounding glands were statistically significant. The joint predictors were calculated and analyzed by Receiver Operating Characteristic (ROC), and it was found that the joint predictors and the SWV values of the lesion interior have great diagnostic value. The cut-off value, sensitivity and specificity of the joint predictor and the SWV value of the lesion interior were > 3.65, 88.35% and 76.36% and > 5.55 m/s, 79.61% and 82.73%, respectively. CONCLUSIONS: Ultrasound elastography combined with multi-parameters has good diagnostic value in differentiating BI-RADS 4 breast lesions.

Multicenter study of the clinicopathological features and recurrence risk prediction model of early-stage breast cancer with low-positive human epidermal growth factor receptor 2 expression in China (Chinese Society of Breast Surgery 021).

BACKGROUND: : Breast cancer with low-positive human epidermal growth factor receptor 2 (HER2) expression has triggered further refinement of evaluation criteria for HER2 expression. We studied the clinicopathological features of early-stage breast cancer with low-positive HER2 expression in China and analyzed prognostic factors. METHODS: : Clinical and pathological data and prognostic information of patients with early-stage breast cancer with low-positive HER2 expression treated by the member units of the Chinese Society of Breast Surgery and Chinese Society of Surgery of Chinese Medical Association, from January 2015 to December 2016 were collected. The prognostic factors of these patients were analyzed. RESULTS: : Twenty-nine hospitals provided valid cases. From 2015 to 2016, a total of 25,096 cases of early-stage breast cancer were treated, 7642 (30.5%) of which had low-positive HER2 expression and were included in the study. After ineligible cases were excluded, 6486 patients were included in the study. The median follow-up time was 57 months (4-76 months). The disease-free survival rate was 92.1% at 5 years, and the overall survival rate was 97.4% at 5 years. At the follow-up, 506 (7.8%) cases of metastasis and 167 (2.6%) deaths were noted. Multivariate Cox regression analysis showed that tumor stage, lymphvascular invasion, and the Ki67 index were related to recurrence and metastasis (P < 0.05). The recurrence risk prediction model was established using a machine learning model and showed that the area under the receiving operator characteristic curve was 0.815 (95% confidence interval: 0.750-0.880). CONCLUSIONS: : Early-stage breast cancer patients with low-positive HER2 expression account for 30.5% of all patients. Tumor stage, lymphvascular invasion, and the Ki67 index are factors affecting prognosis. The recurrence prediction model for breast cancer with low-positive HER2 expression based on a machine learning model had a good clinical reference value for predicting the recurrence risk at 5 years. TRIAL REGISTRATION: : ChiCTR.org.cn, ChiCTR2100046766.

Androgen Receptor: A New Marker to Predict Pathological Complete Response in HER2-Positive Breast Cancer Patients Treated with Trastuzumab Plus Pertuzumab Neoadjuvant Therapy.

(1) Background: Neoadjuvant therapy is the main therapeutic strategy for human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients, and the combination of trastuzumab and pertuzumab (HP) has become a routine treatment. How to predict and screen patients who are less likely to respond to neoadjuvant therapy is the focus of research. The androgen receptor (AR) is a biomarker that is widely expressed in all breast cancer subtypes and is probably related to treatment response and prognosis. In this study, we investigated the relationship between AR expression and treatment response in HER2-positive breast cancer patients treated with HP neoadjuvant therapy. (2) Methods: We evaluated early breast cancer patients treated with HP neoadjuvant therapy from Jan. 2019 to Oct. 2020 at Peking University First Hospital Breast Cancer Center. The inclusion criteria were as follows: early HER2-positive breast cancer patients diagnosed by core needle biopsy who underwent both HP neoadjuvant therapy and surgery. We compared the clinical and pathological features between pathological complete response (pCR) and non-pCR patients. (3) Results: We included 44 patients. A total of 90.9% of patients received neoadjuvant therapy of taxanes, carboplatin, trastuzumab and pertuzumab (TCHP), and the total pCR rate was 50%. pCR was negatively related to estrogen receptor (ER) positivity (OR 0.075 [95% confidence interval (CI) 0.008-0.678], p = 0.021) and positively related to high expression levels of AR (OR 33.145 [95% CI 2.803-391.900], p = 0.005). We drew a receiver operating characteristic (ROC) curve to assess the predictive value of AR expression for pCR, and the area under the curve was 0.737 (95% CI 0.585-0.889, p = 0.007). The optimal cutoff of AR for predicting pCR was 85%. (4) Conclusion: AR is a potential marker for the prediction of pCR in HER2-positive breast cancer patients treated with HP neoadjuvant therapy.

Radiomics features based on automatic segmented MRI images: Prognostic biomarkers for triple-negative breast cancer treated with neoadjuvant chemotherapy.

PURPOSE: To establish radiomics prediction models based on automatic segmented magnetic resonance imaging (MRI) for predicting the systemic recurrence of triple-negative breast cancer (TNBC) in patients after neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: A total of 147 patients with TNBC who underwent NAC between January 2009 and December 2018 were enrolled in this study. Clinicopathologic data were collected, and the differences between the recurrent and nonrecurrent patients were analyzed by univariate and multivariate analyses. Patients were randomly divided into training and testing sets. The training set consisted of 104 patients (recurrence: 22, nonrecurrence: 82), and the testing set consisted of 43 patients (recurrence: 9, nonrecurrence: 34). To establish the radiomics prediction model, we used a deep learning segmentation model to automatically segment tumor areas on dynamiccontrast-enhanced-MRI images of pre- and post-NAC magnetic resonance examinations. Radiomics features were then extracted from the tumor areas. Three MRI radiomics models were developed in the training set: a radiomics model based on pre-NAC MRI features (model 1), a radiomics model based on post-NAC MRI features (model 2), and a radiomics model based on both pre- and post-NAC MRI features (model 3). A clinical model for predicting systemic recurrence was built in the training set using independent clinical prediction factors. Receiver operating characteristic curve analysis was used to evaluate the performance of the radiomics and clinical models. RESULTS: The clinical model yielded areas under the curve (AUCs) of 0.747 in the training set and 0.737 in the testing set in terms of predicting systemic recurrence. Models 1, 2, and 3 yielded AUCs of 0.879, 0.91, and 0.963 in the training set and 0.814, 0.802, and 0.933 in the testing set, respectively, in terms of predicting systemic recurrence. All of the radiomics models had achieved higher AUCs than the clinical model in the testing set. DeLong test was used to compare the AUCs between the models and indicated that the predictive performance of model 3 was better than the clinical model, and the difference was statistically significant (p < 0.05). CONCLUSION: The radiomics models built based on the combination of pre- and post-NAC MRI features showed good performance in predicting whether patients with TNBC will have systemic recurrence within 3 years post-NAC. This can help us non-invasively identify which patients are at high risk of recurrence post-NAC, so that we can strengthen follow-up and treatment of these patients. Then the prognosis of these patients might be improved.

A nomogram for predicting brain metastasis in patients with de novo stage IV breast cancer.

BACKGROUND: Brain metastasis (BM) is a very serious event in patients with breast cancer. The aim of this study was to establish a nomogram to predict the risk of BM in patients with de novo stage IV breast cancer. METHODS: We gathered female patients diagnosed with de novo stage IV breast cancer between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. After randomly allocating the patients to the training set and verification set, we used univariate and multivariate logistic regression to analyze the relationship between BM and clinicopathological features. Finally, we developed a nomogram which was validated by the analysis of calibration curve and receiver operating characteristic curve. RESULTS: Of 7,154 patients with de novo stage IV breast cancer, 422 developed BM. Age, tumor size, subtype, and the degree of lung involvement were significantly correlated with BM. The nomogram had discriminatory ability with an area under curve (AUC) of 0.640 [95% confidence interval (CI): 0.607 to 0.673] in the training set, and 0.644 (95% CI: 0.595 to 0.693) in the validation set. CONCLUSIONS: Our study developed a nomogram to predict BM for de novo stage IV breast cancer, thus helping clinicians to identify patients at high-risk of BM and implement early preventive interventions to improve their prognoses.

Retrospective analysis of sentinel lymph node biopsy using methylene blue dye for early breast cancer.

BACKGROUND: Methylene blue is the most commonly used tracer for sentinel lymph node (SLN) biopsy (SLNB) in China. This study aimed to investigate the feasibility of clinical application of SLNB using methylene blue dye (MBD) for early breast cancer and the prognosis of patients with different SLN and non-SLN statuses. METHODS: We retrospectively analyzed the clinicopathological data of patients with early breast cancer treated at the Peking University First Hospital between 2013 and 2018. We calculated the SLN identification rate (IR) in SLNB with MBD and the false-negative rate (FNR), and analyzed the prognosis of patients with different SLN and non-SLN statuses using Kaplan-Meier curves. RESULTS: Between January 2013 and December 2018, 1603 patients with early breast cancer underwent SLNB with MBD. The SLN IR was 95.8% (1536/1603). Two SLNs (median) were detected per patient. There were significant differences in FNR between patients with SLN micrometastasis and macrometastasis (19.0% vs. 4.5%, χ2 = 12.771, P < 0.001). Chi-square test showed that there were significant differences in SLN successful detection rates among patients with different vascular tumor embolism status (96.3% vs. 90.8%, χ2 = 9.013, P = 0.003) and tumor (T) stages (96.6% vs. 94.1%, χ2 = 5.189, P = 0.023). Multivariate analysis showed that vascular tumor embolism was the only independent factor for SLN successful detection (odds ratio: 0.440, 95% confidence interval: 0.224-0.862, P = 0.017). Survival analysis showed a significant difference in disease-free survival (DFS) between patients with non-SLN metastasis and patients without non-SLN metastasis (P = 0.006). CONCLUSION: Our single-center data show that, as a commonly used tracer in SLNB in China, MBD has an acceptable SLN IR and a low FNR in frozen sections. This finding is consistent with reports of dual tracer-guided SLNB. Positive SLNs with non-SLN metastasis are associated with DFS.

Prognostic value of residual cancer burden and Miller-Payne system after neoadjuvant chemotherapy for breast cancer.

BACKGROUND: To verify the feasibility of using the residual cancer burden (RCB) index to stratify prognosis of patients after neoadjuvant chemotherapy (NAC) and to compare RCB with the Miller-Payne system. METHODS: We retrospectively analyzed clinicopathological data of patients receiving treatment between January 1, 2010 and December 31, 2018. Kaplan-Meier curves were used to compare the survival outcomes and estimate disease-free survival (DFS) and disease-specific survival (DSS). Harrell's concordance index (C-index) was used to evaluate the predictive accuracy of RCB and Miller-Payne system. RESULTS: A total of 423 female patients with complete data were included in the analysis, with a median follow-up time of 58.5 months (range, 7-126 months); 84 patients experienced recurrence, and 48 experienced breast cancer related death. RCB index and the Miller-Payne system were associated with prognosis in the whole cohort. Patients who achieved RCB-I had similar survival outcomes as those with pathological complete response (pCR, RCB-0). In whole cohort, for the RCB index and the Miller-Payne system, respectively, C-indexes for DFS were 0.73 and 0.64, for DSS were 0.74 and 0.64. The average RCB score was different among three subtypes (F=9.335, P<0.001). CONCLUSIONS: The RCB index and the Miller-Payne system can stratify survival outcome of patients after NAC, and RCB had a superior prediction accuracy, especially for triple-negative breast cancer (TNBC). New cut-off value should be sought in order to improve prediction accuracy.

A Clinical-Radiomics Model for Predicting Axillary Pathologic Complete Response in Breast Cancer With Axillary Lymph Node Metastases.

PURPOSE: To develop a clinical-radiomics model based on radiomics features extracted from MRI and clinicopathologic factors for predicting the axillary pathologic complete response (apCR) in breast cancer (BC) patients with axillary lymph node (ALN) metastases. MATERIALS AND METHODS: The MR images and clinicopathologic data of 248 eligible invasive BC patients at the Peking University First Hospital from January 2013 to December 2020 were included in this study. All patients received neoadjuvant chemotherapy (NAC), and the presence of ALN metastases was confirmed through cytology pre-NAC. The data from January 2013 to December 2018 were randomly divided into the training and validation sets in a ratio of 7:3, and the data from January 2019 to December 2020 served as the independent testing set. The following three types of prediction models were investigated in this study. 1) A clinical model: the model was built by independently predicting clinicopathologic factors through logistic regression. 2) Radiomics models: we used an automatic segmentation model based on deep learning to segment the axillary areas, visible ALNs, and breast tumors on post-NAC dynamic contrast-enhanced MRI. Radiomics features were then extracted from the region of interest (ROI). Radiomics models were built based on different ROIs or their combination. 3) A clinical-radiomics model: it was built by integrating radiomics signature and independent predictive clinical factors by logistic regression. All models were assessed using a receiver operating characteristic curve analysis and by calculating the area under the curve (AUC). RESULTS: The clinical model yielded AUC values of 0.759, 0.787, and 0.771 in the training, validation, and testing sets, respectively. The radiomics model based on the combination of MRI features of breast tumors and visible ALNs yielded the best AUC values of 0.894, 0.811, and 0.806 in the training, validation, and testing sets, respectively. The clinical-radiomics model yielded AUC values of 0.924, 0.851, and 0.878 in the training, validation, and testing sets, respectively, for predicting apCR. CONCLUSION: We developed a clinical-radiomics model by integrating radiomics signature and clinical factors to predict apCR in BC patients with ALN metastases post-NAC. It may help the clinicians to screen out apCR patients to avoid lymph node dissection.

The detection rate of methylene blue combined with another tracer in sentinel lymph node biopsy of early-stage breast cancer: a systematic review and network meta-analysis.

BACKGROUND: Methylene blue (MB) alone or combined with 99mtechnetium-labeled sulphur colloid (Tc99m) or indocyanine green (ICG) is widely used for sentinel lymph node biopsy (SLNB) of early-stage breast cancer in developing countries and regions. However, studies investigating the effectiveness of MB combined with another tracer have produced heterogeneous results. The purpose of this network meta-analysis (NMA) was to evaluate the detection rate of MB alone, MB + Tc99m, and MB + ICG, and to examine the differences between the 3 methods. METHODS: We conducted a comprehensive electronic literature search on the PubMed, Embase, Web of Science, CNKI, and Wanfang Data databases from inception to October 2021. The meta-analysis included 7,498 patients in 49 studies. The risk of bias for each study was independently assessed as low, moderate, or high using criteria adapted from the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Fixed- and random-effects models were used to calculate pooled estimates. Mixed-comparison analysis using random-effects models. We assessed statistical heterogeneity by I2 statistics and evaluated publication bias using Begg's test. RESULTS: The identification rate (IR), false-negative rate (FNR), sensitivity (SEN), and accuracy rate (AR) using MB + Tc99m were 96%, 7%, 93%, and 96%, respectively; the IR, FNR, SEN, and AR using MB + ICG were 97%, 7%, 93%, and 97%, respectively. The NMA found that IR and AR between MB + ICG and MB + Tc99m was OR =1.37 (95% CI: 0.41-4.20) and OR =1.33 (95% CI: 0.56-3.32), respectively. DISCUSSION: Our results are similar to those of most previous studies, and meta-analysis showed that the MB + Tc99m or MB + ICG mapping methods can be used to obtain higher IR and lower FNR than MB alone. Our NMA showed no statistical significance between MB + Tc99m and MB + ICG with IR and AR. Both MB + Tc99m and MB + ICG can be used as effective mapping methods in SLNB of early-stage breast cancer to improve the detection rate.

Clinicopathological analysis of early-stage breast cancer patients that meet indications for BRCA1/2 genetic testing.

OBJECTIVE: To investigate the clinicopathological characteristics and prognostic factors of early-stage breast cancer patients with indications for breast cancer susceptibility genes 1/2 (BRCA1/2) genetic testing in China. METHODS: Based on the indication criteria for BRCA genetic testing specified in the National Comprehensive Cancer Network (NCCN) clinical practice guidelines in oncology, genetic/familial high-risk assessment: Breast and ovarian (Version 2. 2019), a retrospective analysis was performed on patients with early-stage invasive breast cancer treated at Breast Disease Center, Peking University First Hospital between January 2008 and December 2016. Clinicopathological characteristics of all patients were analyzed, and prognoses were calculated using the Kaplan-Meier method and a Cox proportionate hazards model. RESULTS: A total of 906 early-stage breast cancer patients who had indications for BRCA genetic testing and had complete clinicopathological data and follow-up information were included in the study group, accounting for 34.7% of all breast cancer patients treated in Breast Disease Center, Peking University First Hospital during the study period. Compared with breast cancer patients without indications for BRCA genetic testing, the overall survival (OS) and disease-free survival (DFS) of patients with indications were not significantly different. In the study group, patients with premenopausal status, high T stage, lymph node positive, estrogen receptor (ER) negative, Ki-67>20% and presence of a vascular tumor thrombus had worse prognosis. There were more family histories of gastrointestinal cancer in patients with related indications than in patients without such indications. CONCLUSIONS: Single-center data showed that more than 30% of patients with early-stage breast cancer had indications for BRCA genetic testing. There was no prognostic difference in patients with or without indications for BRCA genetic testing. Premenopausal status, high T stage, lymph node positive, ER negative, Ki-67>20%, and presence of a vascular tumor thrombus were associated with poor prognosis.