Prognosis Of Breast Cancer Patients Research Articles

LncRNA HAGLROS promotes breast cancer evolution through miR-135b-3p/COL10A1 axis and exosome-mediated macrophage M2 polarization.

Long non-coding RNAs (lncRNAs) play an important role in breast cancer progression, but the function of lncRNAs in regulating tumor-associated macrophages (TAMs) remains unclear. As carriers of lncRNAs, exosomes play an important role as mediators in the communication between cancer cells and the tumor microenvironment. In this study, we found that lncRNA HAGLROS was highly expressed in breast cancer tissues and plasma exosomes, and its high expression was related to the poor prognosis of breast cancer patients. Functionally, breast cancer cell-derived exosomal lncRNA HAGLROS promotes breast cancer cell proliferation, migration, epithelial-mesenchymal transition (EMT) process and angiogenesis by inducing TAM/M2 polarization. Mechanistically, lncRNA HAGLROS competitively binds to miR-135-3p to prevent the degradation of its target gene COL10A1. Collectively, these results indicated that the lncRNA HAGLROS/miR-135b-3p/COL10A1 axis promoted breast cancer progression, and revealed the interactive communication mechanism between breast cancer cells and TAMs, suggesting that lncRNA HAGLROS may be a potential biomarker and therapeutic target for breast cancer.

Tumor size measurements predicted by digital mammography, ultrasonography, and magnetic resonance imaging in primary invasive breast cancer disease

Background and objective: The size of the tumor significantly influences the prognosis and treatment approach for breast cancer patients. The aim of this study was to find the most accurate imaging method for estimating pre-treatment tumor size in women with newly diagnosed primary invasive breast cancer by comparing the predicted tumor size obtained from mammography, ultrasonography, and magnetic resonance imaging with the pathologic size obtained from the surgical specimens. Methods: This cross-sectional study included 181 primary invasive breast cancer patients from September 2021 to March 2023. The difference in tumor size was evaluated based on imaging and pathological reports. Variables such as age, breast density, and tumor characteristics like histologic type, grade, location, and side were recorded and analyzed. The American College of Radiology Breast Imaging Reporting and Data System was used for reporting. Data analysis, performed using SPSS Statistics software, included descriptive statistics, Spearman's correlation coefficient, and Lin's index. The statistical significance level was set at P <0.05. Results: The mean tumor size was 29.68, 29.07, 28.37, and 27.7mm by mammography, ultrasonography, magnetic resonance imaging, and pathology, respectively. All diagnostic procedures revealed a statistically significant correlation with pathologic tumor size with the Spearman correlation test, P = 0.000. MRI had the highest Lin’s concordance correlation coefficient (0.93). Conclusion: The study determined that all imaging modalities were accurate in estimating tumor size when compared to the gold standard of pathological specimens and that magnetic resonance imaging outperformed digital mammography and ultrasonography.

Low cytoplasmic NUB1 protein exerts hypoxic cell death with poorer prognosis in oestrogen receptor negative breast cancer patients

Current prognostic biomarkers fall short in stratifying Oestrogen receptor (ER)-negative breast cancer patients regarding tumour progression risk at diagnosis. The role of AIPL1 in activating its tumour suppressor client protein, NEDD8 Ultimate Buster-1 (NUB1) remains unknown in cancer. Our study demonstrated how downregulated AIPL1 results in the deactivated NUB1 protein under hypoxic conditions. We examined the AIPL1-NUB1 pathwayin vitro using cell lines i.e. MCF-7, MDA-MB-231, RCC4 etc. NUB1 expression was assessed using Oncomine, and cBioPortal was performed to assess NUB1′s prognostic significance in human cancers. In the John Radcliffe Hospital cohort (n = 122), immunohistochemistry analysis revealed downregulated AIPL1 (Log2 fold change=-0.28; p < 0.001) and upregulated NUB1 transcripts (Log2 fold change=0.59; p < 0.001) compared to adjacent normal tissues. In severe chronic hypoxia, multimerised AIPL1 localisedin the cytoplasm while NUB1 protein migrated to the nucleus, where the absence of NUB1 nuclear localisation led to cell cycle arrest. Biopsies showed that patients with lower cytoplasmic NUB1 expression (n = 57) had poorer overall survival compared to those with higher cytoplasmic expression (n = 57), HR=1.78; 95 % CI=1.01–3.35, p = 0.048. Low NUB1 protein levels in both normoxic and hypoxic conditions were associated with cell cycle arrest and upregulation ofp21 and p27 in breast cancer cell lines, correlating significantly withpoorer survival outcomes in all breast cancer and ER-negative breast cancer patients.

Immune-related gene signature improves prognosis prediction in patients with breast cancer and associates it with tumor immunity and inflammatory response

BackgroundThe prognostic potential of immune-related genes, particularly immune checkpoint inhibitors (ICIs) and long non-coding RNAs (lncRNAs), is gaining attention for evaluating the prognosis of breast cancer patients.MethodsWe analyzed 23 datasets to identify 15 ICI-related mRNAs and 5 immune-related lncRNAs, creating a robust immune score (IS). This score was used to classify patients into high and low IS groups and assess their survival outcomes.ResultsPatients with high IS showed significantly poorer overall survival (OS) and progression-free survival (PFS) compared to those with low IS. Multivariate Cox regression analysis confirmed IS as an independent prognostic factor. Additionally, high IS was associated with higher mutation loads and neoantigen profiles, while low IS correlated with enhanced immune cell infiltration.ConclusionsThe immune score developed from ICI-related mRNAs and lncRNAs effectively predicts the prognosis of breast cancer patients and highlights the differential immune and inflammatory responses between patients with varying levels of immune score. This underscores the relevance of IS in guiding therapeutic decisions and tailoring patient management strategies in clinical settings.

Analysis of the relationship between primary tumor site and clinicopathological characteristics and survival prognosis of breast cancer patients based on SEER database

PurposeThis study aimed to analyze the association between the primary tumor site and clinicopathological characteristics and survival prognosis of breast cancer (BC) patients using a large population database. MethodsBC patients screened in the Surveillance, Epidemiology, and End Results (SEER) database were categorized into 6 groups based on primary sites. Descriptive statistics, Kaplan-Meier curves, Cox regression models, forest plots were used to assess the effect of primary sites on overall survival (OS) and breast cancer-specific survival (BCSS). Multivariate Cox proportional analyses were conducted to calculate hazard ratios (HRs) and adjusted subgroups’ hazard ratios (AHRs). Nomograms were utilized to predict OS and BCSS. ResultsAmong 193,043 BC patients, the highest incidence was found in the upper outer quadrant (52.60%). Central portion patients are associated with more clinical features indicating a poor prognosis, and had worse OS and BCSS than other sites. Univariate and multifactorial Cox analyses showed associations between OS/BCSS and various factors. Subgroup analyses revealed differences in OS and BCSS between central portion and upper outer quadrant varied among age, T and N stage. The nomogram was established to predict the survival of central portion BC patients. ConclusionsPrimary tumor site is associated with clinicopathological features and prognosis of BC, may be influenced by age at diagnosis and T and N stage. Central portion BC patients have worse prognosis due to older age at diagnosis, higher T stage and higher likelihood of lymph node metastasis. Early diagnosis and treatment may help to improve survival of central portion BC. Micro AbstractThis paper explores the relationship between primary tumor sites and clinicopathological features and prognosis of breast cancer patients. Through a multi-model joint analysis, it was found that the primary site, as an important clinical feature, has the worst prognosis for the central portion, which provides a basis for clinical attention and strengthening the diagnosis and treatment of breast cancer in this site.

Preoperative plasma fibrinogen level is a risk factor for the long-term survival of postmenopausal women after surgery for breast cancer

BackgroundStudies have indicated an association between fibrinogen levels and the prognosis of breast cancer patients. However, fibrinogen levels are notably susceptible to fluctuations due to the menstrual cycle. This study explored the relationship between preoperative plasma fibrinogen levels and the prognosis of postmenopausal breast cancer women after surgery. Method855 patients with postmenopausal breast cancer were monitored for 10 years. Cox proportional hazards regression models were used to perform univariate and multivariate analyses to identify factors that are of substantial prognostic value. ResultsThe median follow-up was 77 months (51–105 months), and the maximum 142 months. Over the follow-up period, 65 deaths (7.6 %) were recorded. Multivariate Cox regression results show that preoperative plasma fibrinogen level (hazard ratio [HR] =1.615, 95 % confidence interval [CI]: 1.233–2.115) and age (HR = 1.626, 95%CI: 1.250–2.116) were independent risk factors for 10-year overall survival after surgery in postmenopausal breast cancer patients, while endocrine therapy (HR = 0.414, 95%CI: 0.202–0.846) was an independent protective factor. Multivariate Cox regression results also show preoperative plasma fibrinogen level was an independent risk factor for 10-year disease-free survival (HR = 1.398, 95 % CI: 1.137–1.719) and 10-year distant metastasis-free survival (HR = 1.436, 95%CI: 1.153–1.787). ConclusionElevated pretreatment plasma fibrinogen levels are associated with a poorer long-term prognosis in postmenopausal breast cancer patients following surgical treatment.

Trim21-mediated CCT2 ubiquitination suppresses malignant progression and promotes CD4+T cell activation in breast cancer

Breast cancer remains a significant global health challenge, and its mechanisms of progression and metastasis are still not fully understood. In this study, analysis of TCGA and GEO datasets revealed a significant increase in CCT2 expression in breast cancer tissues, which was associated with poor prognosis in breast cancer patients. Functional analysis revealed that CCT2 promoted breast cancer growth and metastasis through activation of the JAK2/STAT3 signaling pathway. Additionally, the E3 ubiquitin ligase Trim21 facilitated CCT2 ubiquitination and degradation, significantly reversing the protumor effects of CCT2. Most interestingly, we discovered that exosomal CCT2 derived from breast cancer cells suppressed the activation and proinflammatory cytokine secretion of CD4+ T cell. Mechanistically, exosomal CCT2 constrained Ca2+-NFAT1 signaling, thereby reducing CD40L expression on CD4+ T cell. These findings highlight CCT2 upregulation as a potential driver of breast cancer progression and immune evasion. Our study provides new insights into the molecular mechanisms underlying breast cancer progression, suggesting that CCT2 is a promising therapeutic target and prognostic predictor for breast cancer.

Nerve growth factor inducible (VGF) is a secreted mediator for metastatic breast cancer tropism to the brain.

Brain metastases are one of the most serious clinical problems in breast cancer (BC) progression, associated with lower survival rates and a lack of effective therapies. Thus, to dissect the early stages of the brain metastatic process, we studied the impact of brain organotropic BC cells' secretomes on the establishment of the brain pre-metastatic niche (PMN). We found that BC cells with specific tropism to the brain caused significant blood-brain barrier (BBB) disruption, as well as microglial activation, in both in vitro and in vivo models. Further, we searched for a brain-organotropic metastatic signature, as a promising source for the discovery of new biomarkers involved in brain metastatic progression. Of relevance, we identified VGF (nerve growth factor inducible) as a key mediator in this process, also impacting the BBB and microglial functions both in vitro and in vivo. In a series of human breast tumors, VGF was found to be expressed in both cancer cells and the adjacent stroma. Importantly, VGF-positive tumors showed a significantly worse prognosis and were associated with HER2 (human epidermal growth factor receptor 2) overexpression and triple-negative molecular signatures. Further clinical validation in primary tumors from metastatic BC cases showed a significant association between VGF and the brain metastatic location, clearly and significantly impacting on the prognosis of BC patients with brain metastasis. In conclusion, our study reveals a unique secretome signature for BC with a tropism for the brain, highlighting VGF as a crucial mediator in this process. Furthermore, its specific impact as a poor prognostic predictor for BC patients with brain metastasis opens new avenues to target VGF to control the progression of brain metastatic disease. © 2024 The Pathological Society of Great Britain and Ireland.

A novel high-risk model identified by epithelial-mesenchymal transition predicts prognosis and radioresistance in rectal cancer.

Many studies have shown that tumor cells that survive radiotherapy are more likely to metastasize, but the underlying mechanism remains unclear. Here we aimed to identify epithelial-mesenchymal transition (EMT)-related key genes, which associated with prognosis and radiosensitivity in rectal cancer. First, we obtained differentially expressed genes by analyzing the RNA expression profiles of rectal cancer retrieved from The Cancer Genome Atlas database, EMT-related genes, and radiotherapy-related databases, respectively. Then, Lasso and Cox regression analyses were used to establish an EMT-related prognosis model (EMTPM) based on the identified independent protective factor Fibulin5 (FBLN5) and independent risk gene EHMT2. The high-EMTPM group exhibited significantly poorer prognosis. Then, we evaluated the signature in an external clinical validation cohort. Through in vivo experiments, we further demonstrated that EMTPM effectively distinguishes radioresistant from radiosensitive patients with rectal cancer. Moreover, individuals in the high-EMTPM group showed increased expression of immune checkpoints compared to their counterparts. Finally, pan-cancer analysis of the EMTPM model also indicated its potential for predicting the prognosis of lung squamous cell carcinoma and breast cancer patients undergoing radiotherapy. In summary, we established a novel predictive model for rectal cancer prognosis and radioresistance based on FBLN5 and EHMT2 expressions, and suggested that immune microenvironment may be involved in the process of radioresistance. This predictive model could be used to select management strategies for rectal cancer.

Preclinical research progress in HER2-targeted small-molecule probes for breast cancer.

Breast cancer is amalignant tumor that has the highest morbidity and mortality in women worldwide. Human epidermal growth factor receptor2 (HER2) is akey driver of breast cancer development. Therefore, accurate assessment of HER2 expression in cancer patients and timely initiation or termination of anti-HER2 treatment are crucial for the prognosis of breast cancer patients. The emergence of radiolabeled molecular probes targeting HER2 makes this assessment possible. This article describes different types of small-molecule probes that target HER2 and are used in current preclinical applications and summarizes their advantages and disadvantages.

Effect of PR status on the prognosis of advanced ER-high HER2-negative breast cancer patients receiving CDK4/6 inhibitor combined with endocrine as first-line therapy

BackgroundThis study was designed to evaluate the effect of progesterone receptor (PR) status on the prognosis of advanced estrogen receptor (ER)-high human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients receiving CDK4/6 inhibitor combined with endocrine as first-line therapy.MethodsAdvanced ER-high HER2-negative breast cancer patients who were admitted to Harbin Medical University Cancer Hospital and received cyclin-dependent kinase (CDK)4/6 inhibitor combined with endocrine as first-line therapy were included for analysis. Patients were divided into PR-high group (11-100%), PR-low group (1-10%), and PR-negative group (< 1%) according to the expression of PR. Chi-square test was used to analyze the correlation of variables between groups. COX regression analysis were used to analyze the risk factors of survival. Kaplan-Meier survival curve was used to analyze the differences of progression-free survival (PFS) and overall survival (OS) between groups.ResultsAmong the 152 patients, 72 were PR-high, 32 were PR-low, and 48 were PR-negative. Compared with PR-negative group, the proportions of disease-free survival (DFS) ≥ 5 years and Ki-67 index ≤ 30% in PR-low group and PR-high group were significant higher. PR-negative patients were more likely to occur first-line progression of disease within 24 months (POD24) than PR-high(P = 0.026). Univariate and multivariate analysis showed that PR-negative and first-line POD24 occurrence were risk factors for survival. Survival curve analysis showed that compared with PR-high group, the PFS and OS were significantly lower in PR-negative group (P = 0.001, P = 0.036, respectively). Patients with first-line POD24 had shorter OS in the overall population as well as in subgroups stratified by PR status.ConclusionsPR-negative and first-line POD24 occurrence were risk factors of advanced ER-high HER2-negative breast cancer patients receiving CDK4/6 inhibitor combined with endocrine as first-line therapy. PR-negative patients had shortest PFS and OS. Regardless of PR status, first-line POD24 occurrence predicted shorter OS.

Establishing nomograms for predicting disease-free survival and overall survival in patients with breast cancer

Background Prognostic factors-based nomograms have been utilised to detect the likelihood of the specific cancer events. We have focused on the roles of aldehyde dehydrogenase 1 (ALDH1) and p-AKT in predicting the prognosis of BC patients. This study was designed to establish nomograms based on the integration of aldehyde dehydrogenase 1 (ALDH1) and p-AKT in predicting the disease-free survival (DFS) and overall survival (OS) of breast cancer (BC) patients. Methods Demographic and clinical data were obtained from BC patients admitted to our hospital between September 2015 and August 2016. Univariate and multivariate Cox regression analyses were utilised to analyse the risk factors of recurrence and mortality. The nomograms for predicting the DFS and OS were established using the screened risk factors. Stratified analysis was performed with the cut-off value of exp (pi) of 4.0-fold in DFS and OS, respectively. Results Multivariate Cox regression analysis indicated that ALDH, p-AKT and pathological stage III were independent risk factors for the recurrence among BC patients. ALDH1, p-AKT, pathological stage III and ER-/PR-/HER2- were independent risk factors for the mortality among BC patients. The established nomograms based on these factors were effective for predicting the DFS and OS with good agreement to the calibration curve and acceptable area under the receiver operating characteristic (ROC) curve. Finally, stratified analyses showed patients with a low pi showed significant decrease in the DFS and OS compared with those of high risk. Conclusion We established nomograms for predicting the DFS and OS of BC patients based on ALDH1, p-AKT and pathological stages. The ER-/PR-/HER2- may be utilised to predict the OS rather than DFS in the BC patients.

Development and validation of machine learning models for predicting HER2-zero and HER2-low breast cancers.

To develop and validate machine learning models for HER2-zero and -low using MRI features pre-neoadjuvant therapy (pre-NAT). 516 breast cancer patients post-NAT surgery were randomly divided into training (n = 362) and internal validation sets (n = 154) for model building and evaluation. MRI features (tumor diameter, enhancement type, background parenchymal enhancement, enhancement pattern, percentage of enhancement, signal enhancement ratio, breast edema, and ADC) were reviewed. Logistic regression (LR), support vector machine (SVM), k-nearest neighbor (KNN), and extreme gradient boosting (XGBoost) models utilized MRI characteristics for HER2 status assessment in training and validation datasets. The best-performing model generated a HER2 score, subsequently correlated with pathological complete response (pCR) and disease-free survival (DFS). The XGBoost model outperformed LR, SVM, and KNN, achieving an area under the ROC curve (AUC) of 0.783(95% CI: 0.733-0.833) and 0.787(95% CI: 0.709-0.865) in the validation dataset. Its HER2 score for predicting pCR had an AUC of 0.708 in the training datasets and 0.695 in the validation dataset. Additionally, the low HER2 score was significantly associated with shorter DFS in the validation dataset (HR: 2.748,95% CI: 1.016-7.432, P = 0.037). The XGBoost model could help distinguish HER2-zero and HER2-low breast cancers, and has the potential to predict pCR and prognosis in breast cancer patients undergoing NAT. Human epidermal growth factor receptor 2 (HER2)-low-expressing breast cancer can benefit from the HER2 targeted therapy. Prediction of HER2-low expression is crucial for appropriate management. MRI features offer a solution to this clinical issue.

CDCA5 accelerates progression of breast cancer by promoting the binding of E2F1 and FOXM1

BackgroundBreast cancer is one of the most common malignant tumors in women. Cell division cycle associated 5 (CDCA5), a master regulator of sister chromatid cohesion, was reported to be upregulated in several types of cancer. Here, the function and regulation mechanism of CDCA5 in breast cancer were explored.MethodsCDCA5 expression was identified through immunohistochemistry staining in breast cancer specimens. The correlation between CDCA5 expression with clinicopathological features and prognosis of breast cancer patients was analyzed using a tissue microarray. CDCA5 function in breast cancer was explored in CDCA5-overexpressed/knockdown cells and mice models. Co-IP, ChIP and dual-luciferase reporter assay assays were performed to clarify underlying molecular mechanisms.ResultsWe found that CDCA5 was expressed at a higher level in breast cancer tissues and cell lines, and overexpression of CDCA5 was significantly associated with poor prognosis of patients with breast cancer. Moreover, CDCA5 knockdown significantly suppressed the proliferation and migration, while promoted apoptosis in vitro. Mechanistically, we revealed that CDCA5 played an important role in promoting the binding of E2F transcription factor 1 (E2F1) to the forkhead box M1 (FOXM1) promoter. Furthermore, the data of in vitro and in vivo revealed that depletion of FOXM1 alleviated the effect of CDCA5 overexpression on breast cancer. Additionally, we revealed that the Wnt/β-catenin signaling pathway was required for CDCA5 induced progression of breast cancer.ConclusionsWe suggested that CDCA5 promoted progression of breast cancer via CDCA5/FOXM1/Wnt axis, CDCA5 might serve as a novel therapeutic target for breast cancer treatment.

Development and validation of a nomogram model of depression and sleep disorders and the risk of disease progression in patients with breast cancer

BackgroundIn this study, we investigated the relationship between the risk of postoperative progressive disease (PD) in breast cancer and depression and sleep disorders in order to develop and validate a suitable risk prevention model.MethodsA total of 750 postoperative patients with breast cancer were selected from the First People’s Hospital of LianYunGang, and the indices of two groups (an event group and a non-event group) were compared to develop and validate a risk prediction model. The relationship between depression, sleep disorders, and PD events was investigated using the follow-up data of the 750 patients.ResultsSAS, SDS, and AIS scores differed in the group of patients who experienced postoperative disease progression versus those who did not; the differences were statistically significant and the ability to differentiate prognosis was high. The area under the receiver operating characteristic (ROC) curves (AUC) were: 0.8049 (0.7685–0.8613), 0.768 (0.727–0.809), and 0.7661 (0.724-–0.808), with cut-off values of 43.5, 48.5, and 4.5, respectively. Significant variables were screened by single-factor analysis and multi-factor analysis to create model 1, by lasso regression and cross-lasso regression analysis to create model 2, by random forest calculation method to create model 3, by stepwise regression method (backward method) to create model 4, and by including all variables for Cox regression to include significant variables to create model 5. The AUC of model 2 was 0.883 (0.848–0.918) and 0.937 (0.893–0.981) in the training set and validation set, respectively. The clinical efficacy of the model was evaluated using decision curve analysis and clinical impact curve, and then the model 2 variables were transformed into scores, which were validated in two datasets, the training and validation sets, with AUCs of 0.884 (0.848–0.919) and 0.885 (0.818–0.951), respectively.ConclusionWe established and verified a model including SAS, SDS and AIS to predict the prognosis of breast cancer patients, and simplified it by scoring, making it convenient for clinical use, providing a theoretical basis for precise intervention in these patients. However, further research is needed to verify the generalization ability of our model.

Glycosylphosphatidylinositol anchor biosynthesis pathway-based biomarker identification with machine learning for prognosis and T cell exhaustion status prediction in breast cancer.

As the primary component of anti-tumor immunity, T cells are prone to exhaustion and dysfunction in the tumor microenvironment (TME). A thorough understanding of T cell exhaustion (TEX) in the TME is crucial for effectively addressing TEX in clinical settings and promoting the efficacy of immune checkpoint blockade therapies. In eukaryotes, numerous cell surface proteins are tethered to the plasma membrane via Glycosylphosphatidylinositol (GPI) anchors, which play a crucial role in facilitating the proper translocation of membrane proteins. However, the available evidence is insufficient to support any additional functional involvement of GPI anchors. Here, we investigate the signature of GPI-anchor biosynthesis in the TME of breast cancer (BC)patients, particularly its correlation with TEX. GPI-anchor biosynthesis should be considered as a prognostic risk factor for BC. Patients with high GPI-anchor biosynthesis showed more severe TEX. And the levels of GPI-anchor biosynthesis in exhausted CD8 T cells was higher than normal CD8 T cells, which was not observed between malignant epithelial cells and normal mammary epithelial cells. In addition, we also found that GPI -anchor biosynthesis related genes can be used to diagnose TEX status and predict prognosis in BC patients, both the TEX diagnostic model and the prognostic model showed good AUC values. Finally, we confirmed our findings in cells and clinical samples. Knockdown of PIGU gene expression significantly reduced the proliferation rate of MDA-MB-231 and MCF-7 cell lines. Immunofluorescence results from clinical samples showed reduced aggregation of CD8 T cells in tissues with high expression of GPAA1 and PIGU.

Immunohistochemical Expression of CD47 and CD68 in Breast Carcinoma and Their Prognostic Value.

Cluster of differentiation 47 (CD47) has been identified as a new immune checkpoint. The exact role of CD47 in prognosis of breast cancer remains unclear. This study aims to evaluate immunohistochemical (IHC) expression of CD47 in breast cancer, and to measure the density of tumor associated macrophages (TAMs) infiltration by CD68 IHC staining. Furthermore, assessing the relations of CD47 and CD68 expression to different clinicopathological variables and evaluating the prognostic role of CD47 and CD68 in breast cancer cases. This retrospective cohort study included 200 diagnosed primary breast cancer cases who underwent surgical resection at the Oncology Center of Mansoura University (OCMU), Faculty of Medicine, Egypt. Clinicopathological and survival data were collected. IHC for CD47 and CD68 was performed. Among 200 breast cancer cases, high CD47 expression was detected in 89 cases (44.5%). CD47 high expression was significantly associated with presence of distant metastasis (P=0.04), advanced TNM stage (P=0.02), ER & PR negativity (P=0.04 & 0.004 respectively), and molecular subtype (P=0.03). Their was a statistically significant association between CD47 and CD68 expression (P=0.002). CD47 high expression was found to predict poor overall survival, but it is not considered alone as independent poor prognostic factor by multivariate analysis. Multivariate analysis spotted combined high expression of CD47 and CD68 as an independent prognostic predictor for shorter OS in breast cancer patients (P=0.002). CD47 high expression is related to poor prognosis in breast cancer patients especially when associated with high CD68+TAMs infiltration. Therefore, CD47 is a promising prognostic and therapeutic target in breast carcinoma that may direct selection of patients for immunotherapy.

Association of Glycogen Synthase Kinase 3A (GSK3A) Gene and Prognosis in Breast Cancer Patients: Exploring GSK3α Ligands Using Molecular Docking

Association of Glycogen Synthase Kinase 3A (GSK3A) Gene and Prognosis in Breast Cancer Patients: Exploring GSK3α Ligands Using Molecular Docking

KMT2D-mediated H3K4me1 recruits YBX1 to facilitate triple-negative breast cancer progression through epigenetic activation of c-Myc.

Lysine methyltransferase 2D (KMT2D) mediates mono-methylation of histone H3 lysine 4 (H3K4me1) in mammals. H3K4me1 mark is involved in establishing an active chromatin structure to promote gene transcription. However, the precise molecular mechanism underlying the KMT2D-mediated H3K4me1 mark modulates gene expression in triple-negative breast cancer (TNBC) progression is unresolved. We recognized Y-box-binding protein 1 (YBX1) as a "reader" of the H3K4me1 mark, and a point mutation of YBX1 (E121A) disrupted this interaction. We found that KMT2D and YBX1 cooperatively promoted cell growth and metastasis of TNBC cells in vitro and in vivo. The expression levels of KMT2D and YBX1 were both upregulated in tumour tissues and correlated with poor prognosis for breast cancer patients. Combined analyses of ChIP-seq and RNA-seq data indicated that YBX1 was co-localized with KMT2D-mediated H3K4me1 in the promoter regions of c-Myc and SENP1, thereby activating their expressions in TNBC cells. Moreover, we demonstrated that YBX1 activated the expressions of c-Myc and SENP1 in a KMT2D-dependent manner. Our results suggest that KMT2D-mediated H3K4me1 recruits YBX1 to facilitate TNBC progression through epigenetic activation of c-Myc and SENP1. These results together unveil a crucial interplay between histone mark and gene regulation in TNBC progression, thus providing novel insights into targeting the KMT2D-H3K4me1-YBX1 axis for TNBC treatment. YBX1 is a KMT2D-mediated H3K4me1-binding effector protein and mutation of YBX1 (E121A) disrupts its binding to H3K4me1. KMT2D and YBX1 cooperatively promote TNBC proliferation and metastasis by activating c-Myc and SENP1 expression in vitro and in vivo. YBX1 is colocalized with H3K4me1 in the c-Myc and SENP1 promoter regions in TNBC cells and increased YBX1 expression predicts a poor prognosis in breast cancer patients.

Correlations of high miRNA expressions with traditional proteins and prognosis of breast cancer

Abstract Background In this study, we aimed to analyze the correlations of high expressions of micro ribonucleic acids (miRNAs) with traditional proteins and prognosis of breast cancer. Methods The clinical data of 60 breast cancer patients treated from August 2018 to July 2019 were retrospectively analyzed. All the patients received radical mastectomy combined with postoperative adjuvant chemoradiotherapy and were followed up for 3 years after treatment. The 3-year survival was recorded. The surviving patients were included in a good prognosis group, and the deceased ones were assigned to a poor prognosis group. The levels of miRNAs (miR-182, miR-155, and miR-217) and traditional breast cancer proteins [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (CerbB-2/HER-2), and cell proliferation factor-67 (Ki-67)] were measured. Receiver operating characteristic (ROC) curve was plotted to investigate the predictive value of miRNA levels for poor prognosis. Results The relative expressions of miR-182, miR-155 and miR-217 were negatively correlated with ER and PR (r&lt;0, P&lt;0.05), but positively correlated with positive Ki-67 expression (r&gt;0, P&lt;0.05). High relative expressions of miR-182, miR-155 and miR-217 and positive Ki-67 expression were risk factors for poor prognosis, and the positive expressions of ER and PR were protective factors (OR&lt;1, P&lt;0.05). The areas under the curves of the relative expressions of miR-182, miR-155 and miR-217 and combined detection for predicting poor prognosis all exceeded 0.70. The combined detection had the highest predictive value. Conclusions The high expressions of miR-182, miR-155 and miR-217 are correlated with the expressions of traditional breast cancer proteins ER, PR, and Ki-67, and may predict the prognosis of breast cancer patients.