Breast Invasive Ductal Carcinoma Patients Research Articles

Development and validation of survival nomograms in elder triple-negative invasive ductal breast carcinoma patients

ABSTRACT Background We aimed to develop a nomogram to predict the overall survival of elderly patients with Triple-negative invasive ductal breast carcinoma (TNIDC). Research design and methods 12165 elderly patients with nonmetastatic TNIDC were retrieved from the SEER database from 2010 to 2019 and were randomly assigned to training and validation cohorts. Stepwise Cox regression analysis was used to select variables for the nomogram based on the training cohort. Univariate and multivariate Cox analyses were used to calculate the correlation between variables and prognosis of the patients. Survival analysis was performed for high- and low-risk subgroups based on risk score. Results Eleven predictive factors were identified to construct our nomograms. Compared with the TNM stage, the discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.741 (95% CI 0.728–0.754) against 0.708 (95% CI 0.694–0.721) and 0.765 (95% CI 0.747–0.783) against 0.725 (95% CI 0.705–0.744) for the training and validation cohorts, respectively. Differences in OS were also observed between the high- and low-risk groups (p < 0.001). Conclusion The proposed nomogram provides a convenient and reliable tool for individual evaluations for elderly patients with M0_stage TNIDC. However, the model may only for Americans.

Secretory breast carcinoma: clinicopathological features and prognosis of 52 patients.

Secretory breast carcinoma is a rare histological subtype of invasive breast cancer and considered with an indolent clinical behavior. This study was conducted to analyze the clinicopathological features of patients with secretory breast carcinoma (SBC), explore the outcome, and compare the prognostic difference with invasive ductal breast carcinoma (IDC). METHODSAND MATERIALS: Patients with SBC diagnosed between 2006 and 2017 from Fudan University Shanghai Cancer Center were included in the study, excluding patients with previous malignant tumor history and incomplete clinical data or follow-up records. Peculiar clinicopathological and immunohistochemical features of the cases were fully described. Clinical data of 4979 cases of IDC were also evaluated during this period. After propensity score matching, prognostic analysis of SBCs and IDCs was calculated by Kaplan-Meier method and landmark analysis method. The data of 52 patients diagnosed with SBC were identified from the pathological files. Among them, 47 patients were women, and 5 were men. The median age of the 52 SBCs was 46years (mean, 48.1years; range, 10-80years). The tumor sizes ranged from 0.3 to 6.8cm, with a mean of 3.5cm. Eight patients (15.4%) had positive axillary lymph node involvement. The molecular classification was mostly triple-negative breast cancer (65.4%). Fluorescence in situ hybridization confirmed the presence of ETV6::NTRK3 rearrangement in 16 of 18 cases (88.9%). Furthermore, Kaplan-Meier survival analysis and landmark analysis demonstrated that there were no statistically significant differences in DFS and OS between SBC and IDC patients. Although SBCs are generally associated with a favorable prognosis, our work exhibited that the clinicopathological features of SBC were partly different from former understandings, indicating that therapeutic procedure should be prudent. Further studies are necessary to fully identify the clinical behavior and predictive markers to improvediagnosis and management in this unique subtype of breast cancer.

End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma.

Apart from invasive pathological examination, there is no effective method to differentiate breast diffuse large B-cell lymphoma (DLBCL) from breast invasive ductal carcinoma (IDC). In this study, we aimed to develop and validate an effective deep learning radiomics model to discriminate between DLBCL and IDC. A total of 324 breast nodules from 236 patients with baseline 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) were retrospectively analyzed. After grouping breast DLBCL and breast IDC patients, external and internal datasets were divided according to the data collected by different centers. Preprocessing was then used to process the original PET/CT images and an attention-based aggregate convolutional neural network (AACNN) model was designed. The AACNN model was trained using patches of CT or PET tumor images and optimized with an improved loss function. The final ensemble predictive model was built using distance weight voting. Finally, the model performance was evaluated and statistically verified. A total of 249 breast nodules from Fudan University Shanghai Cancer Center (FUSCC) and 75 breast nodules from Shanghai Proton and Heavy Ion Center (SPHIC) were selected as internal and external datasets, respectively. On the internal testing, our method yielded an area under the curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and harmonic mean of precision and sensitivity (F1) of 0.886, 83.0%, 80.9%, 85.0%, 84.8%, 81.2%, and 0.828, respectively. Meanwhile on the external testing, the results were 0.788, 71.6%, 61.4%, 84.7%, 84.0%, 62.6%, and 0.709, respectively. Our study outlines a deep learning radiomics method which can automatically, noninvasively, and accurately differentiate breast DLBCL from breast IDC, which will be more in line with the needs and strategies of precision medicine, individualized diagnosis, and treatment.

The prognostic value and immune microenvironment association of AR in HER2+ nonmetastatic breast cancer

This study aimed to investigate the prognostic value of AR in HER2+ nonmetastatic breast invasive ductal carcinoma (IDC) and its relationship with the immune microenvironment. HER2+ nonmetastatic breast IDC patients diagnosed by pathology who underwent surgery at Sun Yat-sen University Cancer Center from 2016 to 2017 were included. AR+ and AR− breast IDC samples were matched 1:1 in age, T stage, and N stage for immune infiltration analysis. A total of 554 patients with HER2+ nonmetastatic breast cancer were included in this retrospective study, regardless of HR status. The cut-off value for AR was set at 10%. ER+ (p < 0.001) and PR+ (p < 0.001) were associated with positive AR expression. Kaplan–Meier survival curve analysis suggested that AR was closely correlated with overall survival (OS) (p = 0.001) but not disease-free survival (DFS) (p = 0.051). After eliminating the potential impact caused by HR, AR also predicted longer OS (p = 0.014) and was an independent predictive factor for OS of HER2+HR− nonmetastatic breast IDC patients, as revealed by multivariate analysis (p = 0.036). For AR+ and AR− matched HER2+HR− patients, TILs (p = 0.043) and PD-L1 (p = 0.027) levels were significantly lower in AR+ patients. The strongest negative correlation was observed between AR and PD-L1 (Pearson’s r = −0.299, p = 0.001). AR+ status was markedly related to better OS in HER2+HR− nonmetastatic breast cancer patients, while a negative correlation was observed between AR and PD-L1/TILs. We provide new insights into the prognostic value of AR and its association with the immune microenvironment to optimize treatment strategies in HER2+ nonmetastatic breast IDCs.

A multi-omics signature to predict the prognosis of invasive ductal carcinoma of the breast

BackgroundPrecisely evaluating the prognosis of invasive ductal carcinoma (IDC) of the breast is challenging as most prognostic signatures use single-omics data based on gene or clinical information. MethodsWhole-slide images (WSIs), transcriptome, and clinical data of breast IDC were collected from the Cancer Genome Atlas Database. The cancer-associated fibroblast (CAF) gene sets were downloaded from the Molecular Signatures Database. The WSI feature was extracted by artificial feature engineering. The CAF prognostic genes were determined by the Gene Set Enrichment Analysis, the Wilcoxon test, and univariate Cox regression. The IDC patients were divided into the training and test sets. The prognostic signatures based on WSIs, IDC–CAFs, bi-omics, and tri-omics were constructed using multivariate Cox regression. The samples were divided into low- and high-risk groups according to the median risk score. The Kaplan–Meier survival and receiver operating characteristic curves were applied to validate the prediction performance of the four signatures. ResultsIn total, 508 IDC patients with complete data were included. The area under the curve (AUC) of single-omics signature based on WSI characteristics and CAFs was 0.765 and 0.775, whereas the AUC of bi-omics was 0.823. The tri-omics signature based on WSIs, CAFs, and lymph node status demonstrated the best predictive value with an AUC of 0.897. ConclusionThe multi-omics signature based on WSIs, CAFs, and clinical characteristics showed excellent prediction ability in breast IDC patients, whose risk factors can also provide a valuable diagnostic reference for the clinical course.

Comparison of the expression of GATA-3 protein from the transcription factor family and pathological prognostic parameters in invasive ductal carcinomas of the breast

Background GATA binding protein 3 (GATA-3) is one of the six transcription factor family members and is important for glandular development in the breast. Its expression becomes important in breast cancer. We aimed to compare GATA-3 immunoreactivity and pathological prognostic factors in patients with invasive ductal carcinoma.&#x0D; Material and Methods Our study was conducted retrospectively with 300 breast invasive ductal carcinoma patients who were operated on in our hospital between May 2013 and June 2014. Patient reports, slides and blocks in the pathology archive were scanned. GATA-3 immunohistochemical (IHC) staining was evaluated according to the nuclear staining, intensity and percentage. The relationship between clinicopathological prognostic parameters and GATA-3 IHC staining results was investigated. &#x0D; Results A positive staining was observed in 286 (95.3%) cases. According to the GATA-3 staining intensity and percentage, 210 (70%) cases stained strongly and 246 (82%) stained +4, respectively. There was a significant relationship between GATA-3 immunoreactivity with ER, PR, Cerb-B2, Ki-67, mitotic degree, mitotic count and histological grade.&#x0D; Conclusions There was a correlation between the high expression of GATA-3 and good prognostic markers. Hormone receptors can be evaluated with Cerb-B2 and Ki-67 and used as prognosis determinants in breast cancers. They can be used to identify both primary and secondary breast tumors.

A hierarchical approach to combine histological grade and immunohistochemical factors to identify high-risk luminal breast cancers.

BackgroundThe luminal subtype accounts for ~70% of newly diagnosed breast cancer patients. Although it has a better prognosis, approximately 30% of them develop a late relapse. Identifying those patients is of interest to improve treatment decisions.MethodsA retrospective observational, single-centre study based on data from medical records of 572 non-metastatic (I–III) invasive ductal breast carcinoma patients, 448 with luminal tumours and 124 with triple-negative tumours. Kaplan–Meier, Cox regression and time-dependent Cox regression were carried out to obtain the prognosis value of risk factors.ResultsDuring a median observation of 5.5 years, 105 distant metastasis events and 105 all-cause deaths were observed. In addition to known clinicopathological factors (i.e., age, tumour size and lymph node metastasis), the high semi-quantitative expression of both hormone receptors was associated with distant metastasis-free survival (DMFS) (adjusted hazard ratio (HaR): 0.524 (0.316–0.867), p = 0.012) and overall survival (OS) (adjusted HaR: 0.486 (0.286–0.827), p = 0.008). The stratified analysis made it possible to identify risk modification factors. Subsequent stratification by histological grade, Ki-67 and semi-quantitative PR expression or, mainly, the composite semi-quantitative expression of hormone receptors (cHR) enabled the identification of luminal breast cancer patients of adjuvant schema at higher risk for metastasis and death. However, initial analyses including patients of neoadjuvant therapy pointed to a path of subsequent stratification by cHR and histological grade, also enabling grouping of luminal breast cancer patients with similar prognosis for DMFS (cHR ≤ 4+ G2 or G3 versus triple-negative, adjusted HaR: 0.703 (0.415–1.189), p = 0.189) and OS (cHR ≤4+ G2 or G3 versus triple-negative, adjusted HaR: 0.662 (0.403–1.088), p = 0.104).ConclusionThe semi-quantitative expression of both cHR, Ki-67 proliferation index and histological grade can identify luminal breast cancer patients at greater risk of developing metastasis and death when combined in a hierarchical fashion, and could be useful for a better prognosis stratification in services from low- and middle-income countries.

Nomograms for Predicting Specific Distant Metastatic Sites and Overall Survival of Breast Invasive Ductal Carcinoma Patients After Surgery: A Large Population-Based Study.

BackgroundBreast cancer (BC) has become the most common malignancy worldwide, accounting for 11.7% of newly diagnosed cancer cases last year. Invasive ductal carcinoma (IDC) is the most common pathological type of BC. However, there were few studies to predict distant metastatic sites and overall survival (OS) of IDC patients.MethodsPost-operative IDC patients from 2010 to 2016 in the Surveillance, Epidemiology, and End Results (SEER) database were reviewed. Nomograms were developed to predict the specific distant metastatic sites and OS of IDC patients. The performance of nomograms was evaluated with the calibration curves, area under the curve (AUC), and decision curve analysis (DCA). Kaplan-Meier analysis and log-rank tests were used to estimate the survival times of IDC patients with distant metastases.ResultsA total of 171,967 post-operative IDC patients were enrolled in our study. Univariate and multivariate analyses were used to establish the nomograms of significant variables. The AUC of the nomograms for the prediction of liver, lung, bone, and brain metastases was 0.903, 0.877, 0.863, and 0.811, respectively. In addition, the AUC of the nomogram for the prediction of 1-, 3-, and 5-year OS was 0.809, 0.813, 0.787, respectively. Calibration curves and DCA showed good consistency and clinical benefits, respectively.ConclusionsWe constructed new predictive models for liver, lung, brain, bone metastases and 1-, 3-, and 5-year OS in IDC patients. These can help clinicians to individualize the treatment of IDC patients, so that patients can get the more appropriate treatment options.

Decreased Survival of Invasive Ductal Breast Cancer Patients With Two Macrometastatic Lymph Nodes Among Few Resected Ones: Should Current Sentinel-Lymph-Node Guidelines Be Revised?

PurposeSentinel-lymph-node (SLN) biopsy (SLB) is an efficient and safe axillary surgical approach with decreased morbidity than total axillary lymph node dissection (ALND) in initial patients (T1–T2). Current guidelines strongly suggest avoiding completion of ALND in patients with one or two positive SLNs that will be submitted to whole-breast radiation therapy, but must be done when three SLNs are affected.MethodsWe performed a SEER-based study with breast invasive ductal carcinoma patients treated between 2010 and 2015. Optimal cutoffs of positive LNs predictive of survival were obtained with ROC curves and survival as a continuous variable. Bias was reduced through propensity score matching. Cox regression was employed to estimate prognosis. Nomograms were constructed to analyze the predictive value of clinicopathological factors for axillary burden.ResultsOf 43,239 initial patients that had one to three analyzed LNs, only 425 had two positive LNs and matched analysis demonstrated no survival difference versus pN2 patients [HR: 0.960 (0.635–1.452), p = 0.846]. The positive-to-analyzed LN proportion demonstrated a strong prognostic factor for a low rate (1 positive to ≤1.5 analyzed) [HR = 1.567 (1.156–2.126), p = 0.004], and analysis derived from the results demonstrated that a “negative LN margin” improves survival. Nomograms shows that tumor size is the main factor of axillary burden.ConclusionMacrometastasis of two LNs is a poor prognostic factor, similar to pN2, in SLNB (-like) patients; more extensive studies including preconized therapies must be done in order to corroborate or refute the resistance of this prognostic difference in patients with two macrometastatic lymph nodes within few resected.

Mining immune-related genes with prognostic value in the tumor microenvironment of breast invasive ductal carcinoma.

The tumor microenvironment (TME) plays an important role in the development of breast cancer. Due to limitations in experimental conditions, the molecular mechanism of TME in breast cancer has not yet been elucidated. With the development of bioinformatics, the study of TME has become convenient and reliable.Gene expression and clinical feature data were downloaded from The Cancer Genome Atlas database and the Molecular Taxonomy of Breast Cancer International Consortium database. Immune scores and stromal scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data algorithm. The interaction of genes was examined with protein-protein interaction and co-expression analysis. The function of genes was analyzed by gene ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes analysis and gene set enrichment analysis. The clinical significance of genes was assessed with Kaplan-Meier analysis and univariate/multivariate Cox regression analysis.Our results showed that the immune scores and stromal scores of breast invasive ductal carcinoma (IDC) were significantly lower than those of invasive lobular carcinoma. The immune scores were significantly related to overall survival of breast IDC patients and both the immune and stromal scores were significantly related to clinical features of these patients. According to the level of immune/stromal scores, 179 common differentially expressed genes and 5 hub genes with prognostic value were identified. In addition, the clinical significance of the hub genes was validated with data from the molecular taxonomy of breast cancer international consortium database, and gene set enrichment analysis analysis showed that these hub genes were mainly enriched in signaling pathways of the immune system and breast cancer.We identified five immune-related hub genes with prognostic value in the TME of breast IDC, which may partly determine the prognosis of breast cancer and provide some direction for development of targeted treatments in the future.

Aberrant HDAC3 expression correlates with brain metastasis in breast cancer patients.

BackgroundBrain metastasis is an unsolved clinical problem in breast cancer patients due to its poor prognosis and high fatality rate. Although accumulating evidence has shown that some pan‐histone deacetylase (HDAC) inhibitors can relieve breast cancer brain metastasis, the specific HDAC protein involved in this process is unclear. Thus, identifying a specific HDAC protein closely correlated with breast cancer brain metastasis will not only improve our understanding of the functions of the HDAC family but will also help develop a novel target for precision cancer therapy.MethodsImmunohistochemical staining of HDAC1, HDAC2, and HDAC3 in 161 samples from breast invasive ductal carcinoma patients, including 63 patients with brain metastasis, was performed using the standard streptavidin‐peroxidase method. The relationships between HDAC1, HDAC2, and HDAC3 and overall survival/brain metastasis‐free survival/post‐brain metastatic survival were evaluated using Kaplan‐Meier curves and Cox regression analyses.ResultsHDAC1, HDAC2, and cytoplasmic HDAC3 all displayed typical oncogenic characteristics and were independent prognostic factors for the overall survival of breast cancer patients. Only cytoplasmic HDAC3 was an independent prognostic factor for brain metastasis‐free survival. Cytoplasmic expression of HDAC3 was further upregulated in the brain metastases compared with the matched primary tumors, while nuclear expression was downregulated. The HDAC1, HDAC2, and HDAC3 expression levels in the brain metastases were not correlated with survival post‐brain metastasis.ConclusionsOur studies first demonstrate a critical role for HDAC3 in the brain metastasis of breast cancer patients and it may serve as a promising therapeutic target for the vigorously developing field of precision medicine.Key pointsSignificant findings of the studyCytoplasmic HDAC3 is an independent prognostic factor for the overall survival and brain metastasis‐free survival of breast cancer patients.What this study addsCytoplasmic expression of HDAC3 was further upregulated in the brain metastases compared with the matched primary tumours, while nuclear expression was downregulated.

Gene expression profiling revealed MCM3 to be a better marker than Ki67 in prognosis of invasive ductal breast carcinoma patients

Invasive ductal carcinoma (IDC) is the most common breast cancer. Our study used gene microarray data to select differentially expressed genes between normal and IDC mammary tissues. From these, we selected genes related to the proliferation of tumor cells and compared their prognostic value with known biomarker Ki67 for IDC. Analysis of publicly available Gene Expression Omnibus (GEO) data revealed 24 differentially expressed genes (DEGs) in normal and 31 DEGS in IDC tissues that were used for further analyses. Gene chip analysis software was used to identify DEGs. DEG profiles were confirmed using quantitative PCR (qPCR). DEG functions where shown to be related to cell proliferation. We confirmed MCM3 expression using immunohistochemical staining in 45 IDC patients. The relationship between MCM3 expression and survival was investigated using Kaplan-Meier survival curves and Cox proportional hazard regression models. A total of 1307 differentially expressed genes were identified between IDC and normal tissues, which were enriched in 32 Gene Ontology (GO) terms and 9 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. qPCR demonstrated that both COL1A1 and MCM3 were significantly up-regulated in IDC tissues, of which only MCM3 was related to cell proliferation. Ki67 is closely associated with the tumor grade, ER status, PR status and HER2 status, while MCM3 was shown to relate to tumor size, lymph node, and PR status. There was significant association between survival and MCM3, but not for Ki67. High MCM3 expression demonstrated statistically significant associations with poor prognosis in IDC patients. Findings from the gene microarray data analysis confirmed that MCM3 is associated with the response to cell proliferation. MCM3 represents a better proliferation marker than Ki67 making it a valuable prognostic tool that is independent of ER and HER2 status.

Effect of the primary tumor location on the prognosis of breast invasive ductal carcinoma patients treated with radical mastectomy

Objective: To analyze the clinicopathological features and prognosis of breast invasive ductal carcinoma patients receiving radical mastectomy according to the primary tumor location. Methods: From January 2008 to December 2008, 993 patients with breast invasive ductal carcinoma received radical mastectomy in Tianjin Medical University Cancer Institute and Hospital. Patients were grouped according to the primary tumor location when breast cancer was diagnosed. The clinicopathological characteristics and follow-up information of them was collected and analyzed retrospectively. Results: Of the 993 patients, primary tumor located in the upper-outer quadrant (UOQ) in 556 patients (56.0%), the lower-outer quadrant (LOQ) in 97 (9.8%), the central portion in 99 (10.0%), the upper-inner quadrant (UIQ) in 186 (18.7%), and the lower-inner quadrant (LIQ) in 55 (5.5%). Patients in the central portion tended to have larger tumors, and more patients in the upper-inner quadrant received endocrine therapy. The estimated 5-year disease-free survival (DFS) rates of patients with primary lesion in the UOQ, LOQ, central portion, UIQ and LIQ were 90.3%, 88.7%, 79.8%, 86.0% and 72.7%, respectively, with significant differences (P<0.001). The 5-year overall survival (OS) rates were 97.5%, 96.9%, 90.9%, 94.1% and 87.3%, respectively, with significant differences (P<0.001). Multivariate analysis showed that 5-year recurrence and metastasis risks were significantly increased in patients with primary lesion in the central portion, UIQ and LIQ compared to other groups (P<0.001), and 5-year mortality risks were increased in these three groups (P=0.002). Conclusion: Primary lesion located in central portion and inner quadrant is an independent adverse prognostic factor for patients with breast invasive ductal carcinoma patients receiving radical mastectomy.

Luminal B is the Most Common Intrinsic Molecular Subtypes of Invasive Ductal Breast Carcinoma Patients in East Kalimantan, Indonesia.

Objective:Breast carcinoma has no longer been considered as a single and standalone disease. Its subtypes have been known to vary in terms of risk factors, natural histories, and responses to therapies. In particular, intrinsic molecular subtypes based on St. Gallen International Expert Consensus 2013 have classified breast carcinoma into luminal A, luminal B, HER2+, and triple-negative, depending on the expression of ER, PgR, HER2, and Ki-67. Research on intrinsic molecular subtypes of breast carcinoma in Indonesia, however, are rarely conducted, which then triggers the intention to conduct this study. Methods:In this work, a retrospective study was conducted on 92 formalin-fixed paraffin-embedded samples of invasive ductal breast carcinoma patients. These samples were from patients at Abdul Wahab Sjahranie County General Hospital Samarinda, East Kalimantan, Indonesia, in 2016. Next, immunohistochemical staining using anti-ER, PgR, HER2, and Ki-67 antibodies was applied to classify intrinsic molecular subtypes. Then, an association between clinical and immunohistochemical factors with intrinsic molecular subtypes of breast carcinoma were analyzed using Chi-square test. Results:Looking at results of the retrospective study, luminal B was discovered as the most common intrinsic molecular subtypes of breast carcinoma (42.39%) in East Kalimantan, Indonesia. The next ranks of breast carcinoma subtypes in the region included HER2+ (39.13%), triple-negative (10.87%), and luminal A (7.61%). In fact, there was a significant association between age (p = 0.019) with intrinsic molecular subtypes of breast carcinoma. Conclusion:The study found luminal B as the most common intrinsic molecular subtypes of Indonesian breast carcinoma in the region under investigation. In the future, the higher positivity rate of luminal B in breast carcinoma patients compared to prior studies would require further investigations.

Association of p53 expression with poor prognosis in patients with triple-negative breast invasive ductal carcinoma.

TP53 gene is mutated in approximately 80% of triple-negative breast cancer (TNBC). However, the prognostic significance of immunohistochemical (IHC)-detected p53 protein expression remains controversial in TNBC. In this study, we retrospectively analyzed the association between IHC-detected p53 expression and the prognosis in a cohort of 278 patients with stage I-III triple-negative breast invasive ductal carcinoma (IDC), who received surgery at the department of breast surgery in the Fourth Hospital of Hebei Medical University from 2010–01 to 2012–12. We found a positive expression ratio of IHC-detected p53 in triple-negative breast IDC of 58.6% (163/278). Furthermore, levels of expression were significantly associated with vessel tumor emboli and higher histologic grade (P = .038, P = .043, respectively), with the highest expression level observed in G3 breast cancer (64.7%). Additionally, Kaplan-Meier analysis showed that p53 expression indicated worse overall survival (OS) in the whole cohort (79.6% vs 89.6%, Log-rank test P = .025) as well as in stratified prognostic stage II patients (90.8% vs 100%, Log-rank test P = .027). The mortality risk of p53 expression patients was 2.22 times higher than that of p53 negative patients (HR: 2.222; 95%CI: 1.147–4.308). In addition, p53 expression was also associated with poor disease-free survival (DFS) (76.7% vs 86.8%, P = .020). Cox proportional hazard ratio model showed p53 expression was an independent risk factor for OS (P = .018) and DFS (P = .018) after controlling for tumor size, lymph node status, and vessel tumor emboli. Altogether, our data showed that IHC-detected p53 expression is a promising prognostic candidate for poor survival in triple-negative breast IDC patients. However, more studies are needed to determine if p53 may be applied to clinical practice as a biomarker and/or novel therapeutic target for TNBC.

Association of Protein Expression and Methylation of DAPK1 with Clinicopathological Features in Invasive Ductal Carcinoma Patients from Kashmir

Aims:Death-associated protein kinase-1 (DAPK1) is a pro-apoptotic Ser/Thr kinase that participates in cell apoptosis and tumor suppression. DAPK1 is frequently lost in many different tumor types including breast cancer. The aim of this study was to evaluate the promoter methylation status of DAPK1 and a possible correlation with the expression of DAPK1 and standard clinicopathological features in invasive ductal breast carcinoma patients (IDC).Methods:Methylation Specific PCR (MSP) was carried out to investigate the promoter methylation status of DAPK1 from 128 breast cancer patients. The effect of promoter methylation on protein expression was evaluated by immunohistochemistry (n=128) and western blotting (n=56).Results:We found significant difference in DAPK1 promoter methylation frequency among breast tumors when compared with the corresponding normal tissues. Hypermethylation of DAPK1 is significantly correlated with the loss of DAPK1 protein expression (P < .001, rs= -0.361). The loss of DAPK1 protein was significantly associated with estrogen receptor (ER) negativity (p= 0.003), triple negative breast cancer (TNB) (p= 0.024) and advanced tumor stages (P = 0.001). Moreover, age at diagnosis (p= 0.041), tumor stage (p= 0.034), ER negativity (p= 0.004) and TNB cancers (p=0.003) correlated significantly with the hypermethylation of the DAPK1 promoter.Coclusion:This study indicates that DAPK1 is methylated in IDC and promoter hypermethylation could be attributed to silencing of DAPK1 gene expression in breast cancer. Thus, we consider DAPK1 inactivation by promoter hypermethylation likely plays a role in the development and progression of breast cancer.

The prognostic value of the 8th edition of the American Joint Committee on Cancer (AJCC) staging system in triple-negative breast cancer.

The American Joint Committee on Cancer (AJCC) released its 8th edition of cancer staging implemented in early 2018. This study aims to compare anatomic staging (AS) with prognostic staging (PS) based on the updated AJCC 8th edition staging manual. A retrospective single-center analysis of 313 triple-negative breast invasive ductal carcinoma patients who received surgery at department of breast surgery in the Fourth Hospital of Hebei Medical University from 01/2010 -12/2012 was performed. All cases were restaged using the AJCC 8th edition AS and PS system. The 7-year disease-free survival (DFS) and the 7-year overall survival (OS) rates were 76.30% and 78.27%, respectively. Applying the PS system, 277 (88.5%) patients of the AS groups were upstaged to the PS groups, 31 cases with IIIC and 5 cases with IV unchanged (11.5%) and no cases downstaged. Both 7-year DFS and 7-year OS were significantly different in the different AS and PS groups (all, p<0.001). The PS system was found to provide better prognostic information in patients with AS group IIB. A total of 43 patients with AS group IIB were upstaged by PS system, in which 30 patients were +2 upstaged to PS IIIB, and 13 patients were +3 upstaged to PS IIIC. PS IIIB and IIIC from AS IIB had significant differences in 7-year DFS (χ2=5.628, p=0.014) and 7-year OS (χ2=6.037, p=0.018). Both AS and PS systems proposed in the 8th edition of the AJCC breast cancer staging manual had prognostic value in TNBC. Moreover, the PS system predicts clinical outcomes of TNBC patients more accurately than the traditional AS system.

Correlation of clinical factors between non-sentinel lymph nodes and 1, 2 positive patients with sentinel lymph node in breast cancer

Objective To analyze the relationship between non-sentinel lymph node(NSLN)metastases and clinicopathologic features in breast invasive ductal carcinoma patients with 1, 2 positive sentinel lymph node(SLN). Methods A total of one hundred and ninety-eight patients with breast invasive ductal carcinoma from January 2013 to December 2017 were enrolled in this prospective study.Modified radical mastectomy was performed after SLN1-2 positive cases were confirmed by biopsy.Postoperative NSLN was counted and the relationship between NSLN and clinical factors was analyzed. Results The positive rate of NSLN in 198 patients was 40.9% (81/198), of which 80 cases were positive at axillary level I and only 1 case was positive at axillary level I and II.There was no significant correlation between NSLN positive and age (χ2=1.258), lesion grade (χ2=1.327), molecular typing (χ2=1.020), neoadjuvant chemotherapy (χ2=0.923), estrogen receptor (χ2=0.189), progesterone receptor (χ2=0.109), Ki67 (χ2=1.755) (P>0.05). The positive rate of NSLN in HER-2 positive patients was 56.9% (29/51), which was significantly higher than 35.4% (52/147) in HER-2 negative patients (χ2=6.136, P=0.034). Logistic regression analysis showed that HER-2 positive was an independent risk factor for NSLN (OR=0.031, 95%CI 0.012-0.615, P=0.022). Conclusion The risk of NSLN positive in breast cancer patients such as SLN1-2 positive patients is still high, and the risk of NSLN positive in HER-2 positive patients is higher. Key words: Breast neoplasms; Sentinel lymph node biopsy; Mastectomy; Non-sentinel lymph node

High snail expression predicts a poor prognosis in breast invasive ductal carcinoma patients with HER2/EGFR-positive subtypes

BackgroundHigh Snail expression is known as a poor prognostic factor in breast cancer. However, its prognostic impact for breast cancer with different molecular subtypes is still controversial. MethodsSnail expression was examined by immunohistochemistry in tissue microarray slides of 85 corresponding tumor-adjacent normal (CTAN) and 247 breast invasive ductal carcinoma (IDC) tissues. Multivariable Cox regression analysis was used to assess the impact of Snail expression on survival rate by different molecular subtypes of breast IDC patients. ResultsThe level of Snail expression in IDC tumor tissues was significantly higher than that in CTAN tissues. Moreover, high Snail expression had direct impacts on poor disease specific survival (DSS) and disease-free survival (DFS) in breast IDC patients with human epidermal growth factor receptor 2 (HER2)-positive and human epidermal growth factor receptor (EGFR)-positive statuses as well as the HER2 intrinsic subtype. Additionally, breast IDC patients with a combination of three prognostic factors, including high Snail expression and HER2-positive and EGFR-positive statuses, had much poor DSS and DFS with a statistically significant linear trend. ConclusionHigh Snail expression could predict a poor prognosis for breast IDC patients with HER2/EGFR-positive subtypes.

Elevated expression of IRS-1 associates with phosphorylated Akt expression and predicts poor prognosis of breast invasive ductal carcinoma

Overexpression of insulin receptor substrate 1 (IRS-1) has been reported to promote cell growth, atypical hyperplasia, and carcinogenesis, and phosphorylated Akt (p-Akt) is certified to be involved in many types of cancers such as breast invasive ductal carcinoma (BIDC). However, the relationship between IRS-1 and Akt, as well as the role of expression of IRS-1 in BIDC, has never been reported. The purpose of this research is to investigate the association between expression of IRS-1 and p-Akt proteins and clinicopathological features of BIDC by immunohistochemistry, as well as the survival status. The results showed that the percentage of either elevated expression of IRS-1 or positive p-Akt expression in BIDC was significantly higher than that in control breast tissue from noncancer patients (P < .001 and P = .001, respectively). Overexpression of IRS-1 was evidently associated with positive expression of p-Akt (r = 0.337, P < .001). Also, positive percentage of p-Akt expression was statistically different among different molecular subtypes of BIDC (highest in luminal B BIDC, P = .009). Furthermore, significantly worse overall survival was found in BIDC patients with high expression of IRS-1 and p-Akt than in patients with low expression (P = .006 and P = .004, respectively). The multivariate Cox proportional hazard regression analysis showed that high expression of IRS-1 and positive expression of p-Akt protein were independent poor prognostic factors for patients with BIDC (P = .022 and P = .046, respectively). In conclusion, we report for the first time that overexpression of IRS-1 protein is associated with expression of p-Akt, and overexpression of IRS-1 and positive expression of p-Akt might be independent biomarkers for poor prognosis in BIDC.