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Background Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients. Methods In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS). Results TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873–0.938]; 0.896, [0.860–0.931]; 0.882, [0.840–0.925] in the three cohorts). Conclusion These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

Neoadjuvant treatment is often considered in breast cancer patients with axillary lymph node involvement, but most of patients do not have a pathologic complete response to therapy. The detection of residual nodal disease has a significant impact on adjuvant therapy recommendations which may improve survival. Here we investigate whether multiphoton microscopy could identify the pathological changes of axillary lymphatic metastasis after neoadjuvant chemotherapy in breast cancer. And furthermore, we find that there are obvious differences in seven collagen morphological features between normal node and residual axillary disease by combining with a semi-automatic image processing method, and also find that there are significant differences in four collagen features between the effective and no-response treatment groups. These research results indicate that multiphoton microscopy may help estimate axillary treatment response in the neoadjuvant setting and thereby tailor more appropriate and personalized adjuvant treatments for breast cancer patients. This article is protected by copyright. All rights reserved.

Background: Except for BRCA1/2, there is no data on the relationship between genetic counseling for the range of mutations and early-onset breast cancer populations. We looked for a link between inherited genes and the molecular subtype of early-onset breast cancer. Methods: We genotyped 1214 individuals with early-onset sporadic breast cancer (age≤40 years) who were BRCA1/2-negative in 3 genes: TP53, PALB2, and RECQL. We focus on the immunohistochemistry characteristics that are unique to each patient. Results: The mutation rates of TP53, PALB2, and RECQL in 1214 BRCA-negative young individuals were 4/1214(0.33%), 8/1214(0.66%), 2/1214(0.16%), respectively. The fact that the TP53 mutation rate was 3.49% among estrogen receptor-and/or progesterone receptor-positive, human epidermal growth factor receptor 2 (HER-2) amplification patients under the age of 35 (PConclusion: According to the findings, TP53 genetic testing should focus on women under 35 with HR-positive and HER2-positve IDC patients.

Background Breast cancer is one of the most frequently occurring malignant cancers worldwide. Invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) are the two most common histological subtypes of breast cancer. The prognosis and survival of the two subtypes were significantly different even with specific molecular subgroup. In this study, we aimed to deeply explore molecular characteristics and the relationship between IDC and ILC subtypes in same molecular subgroup of breast cancer using comprehensive proteomics and phosphoproteomics analysis. Methods Cancer tissues and noncancerous adjacent tissues (NATs) with the luminal subtype (ER- and PR-positive, HER2-negative) were obtained from paired IDC and ILC patients respectively. Label-free quantitative proteomics and phosphoproteomics methods were used to detect differentially expressed proteins and the phosphorylation status between 10 paired breast cancer and NATs. Then, bioinformatics analysis was performed to explore the difference between IDC and ILC subtypes, including the difference in protein expression levels and the degree of phosphorylation. Meanwhile, Kinase-Substrate Enrichment Analysis (KSEA) revealed the activation difference of kinases and their substrates between IDC and ILC. Results A total of 5,044 high-confidence proteins and 3,808 phosphoproteins were identified from breast cancer tissues. The protein phosphorylation level in ILC tissues was higher than that in IDC tissues. From the quantitative analysis of 1259 proteins and 560 phosphoproteins with high patient coverage, Histone H1.10, Complement C4-B and Crk-like protein were found to be significantly differentially expressed in the two subtype tissues from the proteomics analysis. Moreover, the differences in protein expression of Septin-2, Septin-9, Heterogeneous nuclear ribonucleoprotein A1 and Kinectin and their phosphorylation clearly distinguished IDC from ILC. In addition, differentially expressed proteins and differentially expressed phosphoproteins in IDC were primarily related to energy metabolism and MAPK pathway, while ILC subtypes were more closely involved in the AMPK and p53/p21 pathways. Furthermore, the kinomes from IDC were primarily significantly activated in the CMGC (Cyclin-dependent kinases, Mitogen-activated protein kinases, Glycogen synthase kinases and CDK-like kinases) groups. Conclusions Our research provides insights into the molecular characterization of IDC and ILC and contributes to discovering novel targets for further drug development and targeted treatment.

The notion of personalized medicine demands proper prognostic biomarkers to guide the optimal therapy for an invasive breast cancer patient. However, various risk prediction models based on conventional clinicopathological factors and emergent molecular assays have been frequently limited by either a low strength of prognosis or restricted applicability to specific types of patients. Therefore, there is a critical need to develop a strong and general prognosticator. Methods: We observed five large-scale tumor-associated collagen signatures (TACS4-8) obtained by multiphoton microscopy at the invasion front of the breast primary tumor, which contrasted with the three tumor-associated collagen signatures (TACS1-3) discovered by Keely and coworkers at a smaller scale. Highly concordant TACS1-8 classifications were obtained by three independent observers. Using the ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8 and established a risk prediction model based on the TACS-score. In a blind fashion, consistent retrospective prognosis was obtained from 995 breast cancer patients in both a training cohort (n= 431) and an internal validation cohort (n = 300) collected from one clinical center, and in an external validation cohort (n = 264) collected from a different clinical center. Results: TACS1-8 model alone competed favorably with all reported models in predicting disease-free survival (AUC: 0.838, [0.800-0.872]; 0.827, [0.779-0.868]; 0.807, [0.754-0.853] in the three cohorts) and stratifying low- and high-risk patients (HR 7.032, [4.869-10.158]; 6.846, [4.370-10.726], 4.423, [2.917-6.708]). The combination of these factors with the TACS-score into a nomogram model further improved the prognosis (AUC: 0.865, [0.829-0.896]; 0.861, [0.816-0.898]; 0.854, [0.805-0.894]; HR 7.882, [5.487-11.323]; 9.176, [5.683-14.816], and 5.548, [3.705-8.307]). The nomogram identified 72 of 357 (~20%) patients with unsuccessful 5-year disease-free survival that might have been undertreated postoperatively. Conclusions: The risk prediction model based on TACS1-8 considerably outperforms the contextual clinical model and may thus convince pathologists to pursue a TACS-based breast cancer prognosis. Our methodology identifies a significant portion of patients susceptible to undertreatment (high-risk patients), in contrast to the multigene assays that often strive to mitigate overtreatment. The compatibility of our methodology with standard histology using traditional (non-tissue-microarray) formalin-fixed paraffin-embedded (FFPE) tissue sections could simplify subsequent clinical translation.

Aim: To screen clinical and genetic risk factors and examine their combined effect on docetaxel, epirubicin and cyclophosphamide (TEC) regimen-induced liver injury (TEC-ILI). Patients & methods: We enrolled 396 breast cancer patients, and TEC-ILI-associated factors were screened by logistic regression analyses. Results: SOD2 rs4880 and ABCG2 rs2231142 polymorphisms correlated with an increased risk of TEC-ILI. Multivariate analysis incorporating clinical and genetic factors revealed that ABCC1 rs246221 (CC) and SOD2 rs4880 (AG/GG) increased the risk of TEC-ILI. Patients with at least two risk factors among nonalcoholic fatty liver disease, high low-density lipoproteinemia levels and the rs246221 or rs4880 adverse genotypes exhibited a significantly increased risk of developing TEC-ILI. Conclusion: The combination of clinical and genetic risk factors had higher predictive value for TEC-ILI than the interclinical risk factors alone.

Purpose: Current trials support the application of sentinel lymph node biopsy (SLNB) in node-positive breast cancer treated with neoadjuvant chemotherapy (NAC) with a lower false negative rate (FNR) if dual-tracer (radioisotope and blue-dye) is used. However, radioisotopes are not available in many areas of the world. In this study, we evaluated the feasibility and accuracy of SLNB mapped with methylene-blue-dye alone. Methods: This study enrolled 132 patients with biopsy-proven node-positive breast cancer with a clip placed in the positive node who then received NAC. After chemotherapy and before operation, all patients underwent axillary ultrasound (AUS) assessment and were classified as either negative (AUS-) or positive (AUS+) according to the axillary status. All patients underwent both SLNB and axillary lymph node dissection (ALND). SLNB was mapped with methylene-blue-dye alone. FNRs were evaluated on factors potentially affecting false-negative SLN finding.Results: Using methylene-blue-dye alone, the FNR of SLNB was 9.9%. Post-NAC AUS assessment (p=0.009), number of SLNs retrieved (p=0.029), and the retrieved of the clipped node (p=0.086), showed association with FNRs in multivariate analysis. In AUS- group, FNR was as low as 2.5%. In AUS+ group, retrieving ≥4 SLNs including the clipped node improved FNR from 17.1% to 4.8%. A flowchart was designed with the combination of post-NAC AUS assessment, retrieved SLN number, and the retrieved of clipped node further improve overall FNR to 3.3%. Conclusion: In biopsy-proven node-positive breast cancer treated with NAC, using a flowchart to optimize patient selection reduces the FNR of single-tracer (methylene-blue-dye) guided SLNB.

CXCLs play critical roles in antitumor immunity by activating tumor-specific immune responses and stimulating tumor proliferation, thus affecting patient outcomes. However, the expression and prognostic values of CXCLs in breast cancer have not been well clarified. The aim of this study was to investigate the impact of CXCLs transcriptional expression on breast cancer patients. Oncomine database, GEPIA (Gene Expression Profiling Interactive Analysis), UALCAN, Kaplan–Meier Plotter, TIMER (Tumor Immune Estimation Resource), and DAVID were used in our study. The transcriptional levels of CXCL9/10/11/13 in breast cancer tissues were significantly elevated while the transcriptional levels of CXCL1/2/3/12 were decreased based on intersections of Oncomine database and GEPIA. Among them, breast cancer patients with high transcriptional levels of CXCL2/9/10/12/13 and low transcriptional level of CXCL3 were associated with a better prognosis. We also found that most of CXCLs expressions are significantly correlated with known prognostic factors, such as patient’s age, major subclasses, individual cancer stages, and nodal metastasis status. In addition, the expression of CXCL9/10/12/13 was also indicated to be correlated with the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells). The functions of differentially expressed CXCLs are primarily related to the immune response and cytokine-cytokine receptor interactions. Our results may provide novel evidence of new prognostic or predictive biomarkers for breast cancer patients.

Background Partner and localizer BRCA2 (PALB2) is a breast cancer predisposition gene, but the clinical relevance of PALB2 germline mutations in Chinese patients with breast cancer remains unknown. This study attempted to investigate the full prevalence and spectrum of PALB2 germline mutations in China and the associations between PALB2 germline mutations and breast cancer risk. Methods A total of 21,216 unselected patients with breast cancer were enrolled from 10 provinces in China, and 5890 Chinese women without cancer were enrolled as healthy controls. PALB2 screening was based on next‐generation sequencing. Results A total of 16,501 BRCA1/2‐negative patients with breast cancer were analyzed. Deleterious PALB2 mutation carriers accounted for 0.97% (n = 160) in the breast cancer cohort and for 0.19% (n = 11) in the healthy control cohort. Forty‐one novel PALB2 germline mutations were identified. A high frequency of PALB2 c.751C>T was detected, and it accounted for 10.63% of the PALB2 germline mutations detected (17 of 160). PALB2 mutations were significantly associated with increased breast cancer risk (odds ratio [OR], 5.23; 95% confidence interval [CI], 2.84‐9.65; P, This study reveals a comprehensive spectrum of PALB2 germline mutations and characteristics of PALB2‐related breast cancer, including the PALB2‐related breast cancer risk and distinctive clinical characteristics. Clinically, this study will provide solid evidence for the genetic counseling of patients with breast cancer and healthy women with PALB2 germline mutations, especially in the Chinese population and among those with Chinese ethnicities worldwide.

Background: PALB2 (Partner and Localizer of BRCA2) is a breast cancer predisposition gene, which plays a critical role in homologous recombination via interacting with BRCA1/2 and RAD51 when DNA break. However, the clinical relevance of PALB2 germline mutations in Chinese breast cancer patients remains unknown. We attempted to illustrate the full prevalence and spectrum of PALB2 germline mutations in Chinese breast cancer population, and to investigate the clinical outcomes of PALB2 germline mutations. Patients and methods: A total of 21216 unselected breast cancer patients were enrolled from multiple clinical centers in China. After evaluation of the DNA quality and clinical information, 16501 eligible BRCA1/2-negative breast cancer patients were analyzed. A group of 5890 Chinese women without cancer was enrolled as healthy controls. PALB2 screening was based on next-generation sequencing, by screening complete coding sequence and intron-exon boundaries of PALB2. Clinical information was synchronously collected. Results: The 79 PALB2 deleterious germline mutations included 25 nonsense mutations, 47 frameshift mutations, and 7 splicing mutations. The hotspot region for PALB2 mutations was exon4. A total of 41 novel mutations were identified in PALB2. Among the 16501 BRCA1/2-negative breast cancer patients and 5890 healthy women, PALB2 deleterious mutation carriers account for 0.97% (n=160) and 0.19% (n=11) separately. PALB2 mutations were significantly associated with increased breast cancer risk (OR: 5.23, 95% CI 2.89-9.49; P Citation Format: Jiaojiao Zhou, Honglian Wang, Fangmeng Fu, Zhanwen Li, Yun Liu, Qingjian Feng, Weizhu Wu, Hongxia Wang, Chuan Wang, Yiding Chen. Spectrum, prevalence and clinical outcomes of germline mutations in PALB2 genes in 16501 unselected BRCA1/2-negative breast cancer patients: A multi-center analysis [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-09-03.

Breakthrough progress has been made in Cyclin-Dependent kinase 4 and 6 (CDK4/6) inhibitors when combined with endocrine therapy (ET) for hormone receptor-positive (HR+), HER2-negative (HER2−) advanced breast cancer (ABC). Though significant improvements of progression-free survival (PFS) for CDK4/6 inhibitors were demonstrated, however, the results of overall survival (OS) profile were not consistent. This study is conducted to further evaluate the efficacy and safety of CDK4/6 inhibitors for HR+ /HER2− ABC, and explore the prefer population through subgroup analysis. We identified relevant randomized controlled trials that compared CDK4/6 inhibitors plus ET to ET alone in HR+ /HER2− ABC. We calculated the hazard ratios (HRs) for PFS and OS, and risk ratios (RRs) for objective response rate (ORR), clinical benefit rate (CBR), adverse events (AEs). Statistical analysis was performed with the random-effects model. Eight trials and 4580 patients were included in this meta-analysis. Compared to ET alone, CDK4/6 inhibitors plus ET not only produced a significantly longer PFS (HR = 0.55, 95% confidence interval [CI] 0.50–0.59, p

Background Nodal involvement and molecular subtypes were used as independent prognostic indicators in women with breast cancer. However, they did not adequately address the effect of node status by subtype in outcomes. Methods We performed a retrospective review of data from 2004 to 2011 from the Affiliated Union Hospital of Fujian Medical University with newly diagnosed stage I to III breast cancer to investigate the relationship between node status and 5-year disease-free survival (DFS) and breast cancer-specific survival (BCSS) by molecular subtype. The Cox proportional hazards model was used for multivariate analysis. Results Median follow-up time was 6.4 years. Luminal HER2 and luminal B were the subtypes with a higher percentage of nodal involvement and high-volume nodal involvement (≥4 positive lymph node) than luminal A. The effect of node status on the prognosis varied with molecular subtype. There was no difference in 5-year DFS and BCSS between stage N1 or N2 and N0 groups in patients with luminal A disease. Nodal involvement in women with the luminal B, luminal HER2, and triple-negative subtypes showed significant difference for 5-year DFS and BCSS compared to the node negative group. Conclusions Nodal involvement seems to be associated with worse survival in women with the luminal B, luminal HER2, and triple-negative subtypes, but not with the luminal A subtype.

Background: Despite the potential role of several chemokines in the migration of cytotoxic immune cells to prohibit breast cancer cell proliferation, a comprehensive view of chemokines and the risk and prognosis of breast cancer is scarce, and little is known about their causal associations.Methods: With a two-sample Mendelian randomization (MR) approach, genetic instruments associated with 30 plasma chemokines were created. Their genetic associations with breast cancer and its survival by molecular subtypes were extracted from the recent genome-wide association study of 133,384 breast cancer cases and 113,789 controls, with available survival information for 96,661 patients. We further tested the associations between the polygenic risk score (PRS) for chemokines and breast cancer in the UK Biobank cohort using logistic regression models, while the association with breast cancer survival was tested using Cox regression models. In addition, the association between chemokine expression in tumors and breast cancer survival was also analyzed in the TCGA cohort using Cox regression models.Results: Plasma CCL5 was causally associated with breast cancer in the MR analysis, which was significant in the luminal and HER-2 enriched subtypes and further confirmed using PRS analysis (OR = 0.94, 95% CI = 0.89–1.00). A potential causal association with breast cancer survival was only found for plasma CCL19, especially for ER-positive patients. Although not replicated in the UK Biobank, we still found an inverse association between CCL19 expression in tumors and breast cancer overall and relapse-free survival in the TCGA cohort (HR = 0.58, 95% CI = 0.35–0.95).Conclusion: We observed an inverse association between genetic predisposition to CCL5 and breast cancer, while CCL19 was associated with breast cancer survival. These associations suggested the potential of these chemokines as tools for breast cancer prevention and treatment.

Studies have shown that delayed initiation of surgery and adjuvant chemotherapy is associated with lower rates of breast cancer survival. However, it remains unclear whether delayed initiation of adjuvant hormone therapy (AHT) is associated with survival.To assess the association of time to adjuvant hormone therapy (TTH) with breast cancer survival and evaluate the factors associated with AHT.This cohort study examined data from the National Cancer Database from 2004 through 2014 to assess the association of TTH (stratified as ≤150 and150 days) with cancer survival. All patients included were diagnosed with stage I to stage III hormone receptor-positive, human epidermal growth factor receptor-2 (ERBB2; formerly HER2)-negative invasive breast cancer and underwent AHT without chemotherapy. Data were analyzed from April 2019 to May 2020.AHT was administered at different time points following surgical procedures for breast cancer treatment.An inverse probability of treatment weighting (IPTW) model was constructed to evaluate overall survival by adjusting for treatment facility, patient demographics, tumor characteristics, and treatment; multivariable logistic regression was conducted to assess factors associated with delayed treatment.A total of 144 103 patients (median [IQR] follow-up, 36.6 months [25.5-49.2 months]; mean [SD] age, 63.7 [11.6] years) were identified, which included 142 916 (99.2%) women, 11 574 (8.0%) Black patients, and 126 013 (87.4%) White patients. Of these, 134 873 patients (93.6%) had a TTH of 150 days or less and 9230 patients (6.4%) had a TTH longer than 150 days. The IPTW-based Cox model demonstrated that patients with delayed AHT (ie, a TTH past 150 days) were associated with decreased survival (hazard ratio [HR], 1.31; 95% CI, 1.26-1.35; P .001) compared with those receiving the timely treatment (TTH ≤150 days). Several sensitivity analyses (including IPTW with stabilized weight [HR, 1.31; 95% CI, 1.19-1.45; P .001], propensity score matching [HR, 1.41; 1.13-1.76; P = .002], and propensity score regression adjustment [HR, 1.29; 95% CI, 1.16-1.43; P .001]) and exploratory subgroup analyses yielded similar trends. Factors associated with delayed AHT included Black racial identity (OR, 1.66; 95% CI, 1.55-1.77), nonprivate insurance (eg, no insurance: OR, 1.46; 95% CI, 1.26-1.70), living in large metropolitan or metropolitan areas (reference vs urban, less urban, or rural: OR, 0.82; 95% CI, 0.76-0.87), treatment in a community hospital (reference vs academic or research: OR, 0.91; 95% CI, 0.84-0.98), Charlson-Deyo Comorbidity Index score 2 or higher (OR, 1.17; 95% CI, 1.04-1.32), poor grade differentiation (OR, 1.42; 95% CI, 1.32-1.53), II and III pathological stage (stage III: OR, 3.13; 95% CI, 2.76-3.54), estrogen receptor-positive (ER+)/progesterone receptor-negative (PR-) or ER-/PR+ (OR, 1.22; 95% CI, 1.13-1.31), receiving breast conservation surgery (reference vs mastectomy: OR, 0.87; 95% CI, 0.79-0.94), and radiotherapy (reference vs no radiotherapy: OR, 0.56; 95% CI, 0.52-0.61).The delay of the initiation of AHT past 150 days was associated with diminished survival in hormone receptor-positive, ERBB2-negative patients with breast cancer who did not receive chemotherapy. Efforts should be made to address factors associated with delayed treatment to improve survival.

Background: Compelling evidence has indicated a significant association between leukocyte mitochondrial DNA copy number (mtDNAcn) and prognosis of several malignancies in a cancer-specific manner. However, whether leukocyte mtDNAcn can predict the clinical outcome of breast cancer (BC) patients has not been well investigated.Methods: The mtDNA copy number of peripheral blood leukocytes from 661 BC patients was measured using a Multiplex AccuCopy™Kit based on a multiplex fluorescence competitive PCR principle. Kaplan–Meier curves and Cox proportional hazards regression model were applied to investigate the association of mtDNAcn with invasive disease-free survival (iDFS), distant disease-free survival (DDFS), breast cancer special survival (BCSS), and overall survival (OS) of patients. The possible mtDNAcn-environment interactions were also evaluated by the Cox proportional hazard regression models.Results: Breast cancer (BC) patients with higher leukocyte mtDNA-CN exhibited a significantly worse iDFS than those with lower leukocyte mtDNAcn (5-year iDFS: fully-adjusted model: HR=1.433[95%CI 1.038-1.978], P=0.028). Interaction analyses showed that mtDNAcn was significantly associated with hormone receptor status (adjusted p for interaction: 5-year BCSS: 0.028, 5-year OS: 0.022), so that further analysis was mainly in the HR subgroup. Multivariate Cox regression analysis demonstrated that mtDNAcn was an independent prognostic factor for both BCSS and OS in HR-positive patients (HR+: 5-year BCSS: adjusted HR (aHR) = 2.340[95% CI 1.163-4.708], P=0.017 and 5-year OS: aHR = 2.446 [95% CI 1.218-4.913], P=0.011).Conclusions: For the first time, our study demonstrated that leukocyte mtDNA copy number might influence the outcome of early-stage breast cancer patients depending on intrinsic tumor subtypes in Chinese women.

BACKGROUND: The YTH domain family protein 3 (YTHDF3) is an important N6-methyladenosine (m(6)A) reader which is involved in multiple cancers. However, the biological role and mechanisms of action for YTHDF3 in triple-negative breast cancer (TNBC) remains to be elucidated. METHODS: The expression of YTHDF3 in TNBC tissues was evaluated using The Cancer Genome Atlas (TCGA) database, BC-GenExMiner, and immunohistochemistry (IHC) staining. Cell migration, invasion, and epithelial-mesenchymal transition (EMT) were validated by wound healing assays, transwell assays, and Western blot (WB) analyses. The association between YTHDF3 and zinc finger E-box-binding homeobox 1 (ZEB1) was confirmed by Pearson correlation analysis. RNA-binding protein immunoprecipitation (RIP) assays and mRNA actinomycin stability analyses were applied to confirm whether YTHDF3 could interact with ZEB1in an m(6)A-dependent manner. RESULTS: The expression of YTHDF3 was correlated with poorer disease-free survival (DFS) and overall survival (OS) in TNBC patients. Functional experiments indicated that YTHDF3 positively regulated cell migration, invasion, and EMT in TNBC cells. Moreover, ZEB1 was identified as a key downstream target for YTHDF3 and YTHDF3 could enhance ZEB1 mRNA stability in an m(6)A-dependent manner. Inhibition of YTHDF3 reduced migration, invasion, and EMT, all of which were reversed by rescue experiments overexpressing ZEB1. CONCLUSIONS: The findings herein confirmed that the YTHDF3/ZEB1 axis plays an important role in the progression and metastasis of TNBC. YTHDF3 is a promising prognosis biomarker and potential therapeutic target for patients with TNBC.

A significant portion of breast cancer patients are nonresponsive to well-established drugs and destined for a poor outcome regardless of molecular subtype. Although several (multiparameter) molecular markers have predicted their resistance to some of these drugs, profound uniparameter markers predictive of a convergent nonresponse to all these drugs remain elusive. We employ co-registered standard-multiphoton histology to representatively sample a few peripheral niches of the primary tumor, so that hundreds of patients can be stratified with either a wound-like or non-wound tumor periphery. With no fitting variable, this simple uniparameter morphological marker is: (a) highly sensitive and specific to predict a multidrug-nonresponsive phenotype that accounts for the majority of recurrence or death, independent of the molecular subtype or related adjuvant drug selection, clinical endpoint (disease-free versus overall survival), and hosting medical center; (b) robust against intratumor heterogeneity and valid at the earliest clinicopathological stage; and (c) dominant in predicting prognosis in the context of routine clinicopathological markers. Considering the mechanistic link between a wound-like extracellular matrix and a microenvironment supporting migratory or mesenchymal tumor cells, we attribute these unusual capabilities to an epithelial-mesenchymal transition nature of the morphological marker long sought after by pathologists.

Peripherally inserted central catheters have been extensively applied in clinical practices. However, they are associated with an increased risk of thrombosis. To improve patient care, it is critical to timely identify patients at risk of developing peripherally inserted central catheter-related thrombosis. Artificial neural networks have been successfully used in many areas of clinical events prediction and affected clinical decisions and practice.To develop and validate a novel clinical model based on artificial neural network for predicting peripherally inserted central catheter-related thrombosis in breast cancer patients who underwent chemotherapy and determine whether it may improve the prediction performance compared with the logistic regression model.A prospective cohort study.A large general hospital in Fujian Province, China.One thousand eight hundred and forty-four breast cancer patients with peripherally inserted central catheters placement for chemotherapy were eligible for the study.The dataset was divided into a training set (N = 1497) and an independent validation set (N = 347). The synthetic minority oversampling technique (SMOTE) was used to handle the effect of imbalance class. Both the artificial neural network and logistic regression models were then developed on the training set with and without SMOTE, respectively. The performance of each model was evaluated on the validation set using accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).Of the 1844 enrolled patients, 256 (13.9%) were diagnosed with peripherally inserted central catheter-related thrombosis. Predictive models were constructed in the training set and assessed in the validation set. Eight factors were selected as input variables to develop the artificial neural network model. Without SMOTE, the artificial neural network model (AUC = 0.725) outperformed the logistic regression model (AUC = 0.670, p = 0.039). SMOTE improved the performance of both two models based on AUC. With the SMOTE sampling, the artificial neural network model performed the best across all evaluated models, the AUC value remained statistically better than that of the logistic regression model (0.742 vs. 0.675, p = 0.004).Artificial neural network model can effectively predict peripherally inserted central catheter-related thrombosis in breast cancer patients receiving chemotherapy. Identifying high-risk groups with peripherally inserted central catheter-related thrombosis can provide close monitoring and an opportune time for intervention.

Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer with an aggressive phenotype and a poor prognosis. The mechanism of tumorigenesis of IMPC in breast remains unknown. Integrative analysis of the proteome and phosphoproteome may shed light on the mechanism of IMPC carcinogenesis. In our study, primary IMPC and paired normal breast tissue were collected from six patients and subjected to label free LC-MS/MS for quantitative proteomic and phosphoproteomic analysis. Kinase-substrate enrichment analysis (KSEA) was conducted to identify hyperactivated/inhibited kinases. Proteomic and phosphoproteomic data was combined to investigate cancer specific activated pathways. A total of 1331 differentially expressed proteins were identified. The proteomic analysis revealed a dysregulation of protein homeostasis in IMPC. Phosphoproteomic profiling identified 856 differentially phosphorylated phosphosites in 655 proteins. KSEA found that cyclin dependent kinases (CDKs) and the p90 ribosomal S6 kinases (RSKs) were highly activated, while protein kinase A (PKA) and protein kinase C (PKC) families were significantly inhibited in IMPC. Finally, cancer-specific activation of mTORC1/S6K2 signaling was also discerned in our integrative analysis. Overall, this study provides a comprehensive landscape of the proteome and phosphoproteome of IMPC, which will contribute to a further understanding of IMPC tumorigenesis and treatment. SIGNIFICANCE: This is the first study to provide the integrative proteomic and phosphoproteomic landscape of IMPC. Our study demonstrated that protein homeostasis dysregulation is one of the most prominent characteristics in IMPC. We also identifying several kinases which might have the potential to be novel targets in clinical practice. Cancer-specific activation of mTORC1/S6K2 signaling was discerned by integrative proteomic and phosphoproteomic analysis. The present study might contribute to a further understanding of IMPC tumorigenesis and treatment.

Biomarkers are indispensable for precision medicine. However, focused single-biomarker development using human tissue has been complicated by sample spatial heterogeneity. To address this challenge, we tested a representation of primary tumor that synergistically integrated multiple in situ biomarkers of extracellular matrix from multiple sampling regions into an intratumor graph neural network. Surprisingly, the differential prognostic value of this computational model over its conventional non-graph counterpart approximated that of combined routine prognostic biomarkers (tumor size, nodal status, histologic grade, molecular subtype, etc.) for 995 breast cancer patients under a retrospective study. This large prognostic value, originated from implicit but interpretable regional interactions among the graphically integrated in situ biomarkers, would otherwise be lost if they were separately developed into single conventional (spatially homogenized) biomarkers. Our study demonstrates an alternative route to cancer prognosis by taping the regional interactions among existing biomarkers rather than developing novel biomarkers.

This study was to assess the prognosis stratification of the clinical-pathologic staging system incorporating estrogen receptor (ER)-negative disease, the nuclear grade 3 tumor pathology (CPS + EG), Neo-Bioscore, and a modified Neo-Bioscore system in breast cancer patients after preoperative systemic therapy (PST). A retrospective multicenter cohort study was conducted from 12 participating hospitals’ databases from 2006 to 2015. Five-year disease free survival (DFS), disease specific survival (DSS), and overall survival (OS) were calculated using Kaplan–Meier Method. Area under the curve (AUC) of the three staging systems was compared. Wald test and maximum likelihood estimates in Cox proportional hazards model were used for multivariate analysis. A total of 1,077 patients were enrolled. The CPS + EG, Neo-Bioscore, and modified Neo-Bioscore could all stratify the DFS, DSS, and OS (all P < 0.001). While in the same stratum of Neo-Bioscore scores 2 and 3, the HER2-positive patients without trastuzumab therapy had much poorer DSS (P = 0.013 and P values < 0.01, respectively) as compared to HER2-positive patients with trastuzumab therapy and HER2-negative patients. Only the modified Neo-Bioscore had a significantly higher stratification of 5-year DSS than PS (AUC 0.79 vs. 0.65, P = 0.03). So, the modified Neo-Bioscore could circumvent the limitation of CPS + EG or Neo-Bioscore.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT03437837.

Background The eighth edition of new staging systems for breast cancer incorporated four biological factors and the anatomic staging system. Validating analysis on Chinese patients has been limited. Our study performed analysis comparing the prognostic value of the staging system based on Chinese data. Methods and materials All patients were classified according to the eighth edition and compared between anatomic and prognostic staging systems. The Kaplan-Meier test was used to calculate the overall survival (OS) and disease-free survival (DFS). We performed Harrell concordance index (C-index) analyses to quantify a models’ predictive performance. Akaike information criterion (AIC) via Cox regression analysis was used to conduct bootstrap-based goodness-of-fit comparisons of the competing staging systems. Results A total of 1556 patients were enrolled in the cohort. The median follow-up time was 76 mo (range, 4-146 mo), the median age was 48 y old (range, 21-87 y). The ratio of movement between anatomic stage (AS) and prognostic stage (PS) was 50.9%. Of these, 691 (44.5%) AS patients were down staged and 100 (6.4%) patients were upstaged when reclassified based on PS. Significant differences between two stages were achieved for stage IIIC in 5-y OS rates and for IIIB in 5-y DFS rates (63.5% versus 50.0% and 58.0% versus44.0%). The value of the C-index for PS and AS were 0.711 and 0.687 (P = 0.04). The AIC reaches a value of 3452.9 for the PS and a value of 3476.4 for the AS. Conclusions The PS might provide better accuracy than the AS in predicting the prognosis of Chinese female breast cancer patients. It also provides a strong basis for the utility of clinical biomarkers to evaluate the prognosis of patients.

Wenxin Chen,1 Chuan Wang,2 Fangmeng Fu,2 Binglin Yang,1 Changming Chen,3 Yingming Sun4 1Department of Breast Surgery, Affiliated Sanming First Hospital of Fujian Medical University, Sanming, Fujian Province 365001, People’s Republic of China; 2Breast Surgery Ward, Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian Province 350001, People’s Republic of China; 3Department of Pathology, Affiliated Sanming First Hospital of Fujian Medical University, Sanming, Fujian Province 365001, People’s Republic of China; 4Department of Radiation and Medical Oncology, Affiliated Sanming First Hospital of Fujian Medical University, Sanming, Fujian Province 365001, People’s Republic of ChinaCorrespondence: Yingming SunDepartment of Radiation and Medical Oncology, Affiliated Sanming First Hospital of Fujian Medical University, Sanming, Fujian Province 365001, People’s Republic of ChinaTel +86-598-8803619Email sunwise26@whu.edu.cnChuan WangBreast Surgery Ward, Department of General Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian Province 350001, People’s Republic of ChinaEmail Chuanwang1968@outlook.comBackground: Sentinel lymph node biopsy (SLNB) and axillary lymph node dissection (ALND) may cause lymphatic and nervous system side effects in patients with breast cancer. It is imperative to develop a model to evaluate the risk of sentinel lymph node metastasis to avoid unnecessary operation.Patients and Methods: A total of 2705 cases of female breast cancer patients enrolled in this retrospective study. We divided into the training group (SLNB group) and the validation group (ALND group) to analyze the relathionship between lymph node metastasis and clinical-pathological factors. Logistic regression analysis was performed to verify the variables which involved in ALN metastasis and established a prediction model. ROC curves were employed to evaluate the predictive ability of the model.Results: In the SLNB group, 9 variables, including pathological type, histological grade, tumor size, hormone receptor, HER-2, Ki-67, multifocality, and molecular subtypes, were related to breast cancer ALN metastasis. Clinically negative lymph nodes, favorable histologic type, tumor size < 2 cm, and Ki-67 < 15% were at very low risk for lymph node metastasis. The AUC of the validation group was 0.786.Conclusion: We successfully establish a mathematics model to predict lymph node metastasis of breast cancer. Axillary surgery should be individual with preoperative clinical characteristics, especially for patients with a longer life expectancy.Keywords: breast cancer, predict model, axillary lymph node metastasis, surgery