Prognosis Of Breast Cancer Patients Research Articles

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.

Upregulated Nuclear Expression of Soluble Epoxide Hydrolase Predicts Poor Outcome in Breast Cancer Patients: Importance of the Digital Pathology Approach

Breast cancer (BC) is the most common cancer in women, with incidence rates increasing globally in recent years. Therefore, it is important to find new molecules with prognostic and therapeutic value to improve therapeutic response and quality of life. The polyunsaturated fatty acids (PUFAs) metabolic pathway participates in various physiological processes, as well as in the development of malignancies. Although aberrancies in the PUFAs metabolic pathway have been implicated in carcinogenesis, the functional and clinical relevance of this pathway has not been well explored in BC. To evaluate the clinical significance of soluble epoxide hydrolase (EPHX2) expression in Mexican patients with BC using tissue microarrays (TMAs) and digital pathology (DP). Immunohistochemical analyses were performed on 11 TMAs with 267 BC samples to quantify this enzyme. Using DP, EPHX2 protein expression was evaluated solely in tumor areas. The association of EPHX2 with overall survival (OS) was detected through bioinformatic analysis in public databases and confirmed in our cohort via Cox regression analysis. Clear nuclear expression of EPHX2 was identified. Receiver operating characteristics (ROC) curves revealed the optimal cutoff point at 2.847062 × 10−3 pixels, with sensitivity of 69.2% and specificity of 67%. Stratification based on this cutoff value showed elevated EPHX2 expression in multiple clinicopathological features, including older age and nuclear grade, human epidermal growth factor receptor 2 (HER2) and triple negative breast cancer (TNBC) subtypes, and recurrence. Kaplan–Meier curves demonstrated how higher nuclear expression of EPHX2 predicts shorter OS. Consistently, multivariate analysis confirmed EPHX2 as an independent predictor of OS, with a hazard ratio (HR) of 3.483 and a 95% confidence interval of 1.804–6.724 (p < 0.001). Our study demonstrates for the first time that nuclear overexpression of EPHX2 is a predictor of poor prognosis in BC patients. The DP approach was instrumental in identifying this significant association. Our study provides valuable insights into the potential clinical utility of EPHX2 as a prognostic biomarker and therapeutic target in BC.

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.

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.

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

Stanniocalcin-2: A Potential Predictor of Residual Breast Cancer After Neoadjuvant Chemotherapy

Compared to patients of pathological complete response (pCR), patients of residual lesion afterwards neoadjuvant chemotherapy (NAC) have worse prognosis and higher distant metastasis. Irrespective, there exists limited data on effective indicators and treatment methods for these patients. In our study, we evaluated the relationship between stanniocalcin-2 (STC2) marker and the prognosis of breast cancer patients of residual lesion after receiving NAC. The relationship between STC2 and patients’ prognosis was evaluated by transcriptome analysis. The impact of the level of STC2 on cell migration, invasion, and proliferation was evaluated at the cellular level. Immunohistochemistry was performed on 293 patients with residual disease after NAC to assess STC2 protein levels. The relationship between STC2 and survival rate was estimated using Cox regression model and Kaplan Meier analysis. The results demonstrated that high level of STC2 significantly inhibited migration, invasion, and proliferation of breast cancer cells. Compared to patients with low STC2, high STC2 were directly proportional to overall survival (OS) and disease-free survival (DFS) (OS: 86.96 vs. 84.62 months, P = 0.017 DFS: 77.33 vs. 66.95 months, P-value &lt; 0.001). In conclusion, our research suggested that the of level STC2 may be a promising prognostic marker or therapeutic targe for breast cancer patients with residual lesion after NAC.

Construction and validation of a nomogram for predicting the prognosis of breast cancer patients who received adjuvant therapy: an analysis based on the SEER database.

Breast cancer is the most common malignant tumor in women globally. Despite advances in primary treatment, the role of adjuvant therapy in reducing recurrence and improving survival is critical; however, there is a notable lack of tailored prognostic models for patients receiving adjuvant therapy. This study used the Surveillance, Epidemiology, and End Results (SEER) database to develop a prognostic nomogram for breast cancer patients receiving adjuvant therapy. The data of breast cancer patients who received adjuvant therapy after surgery in 2014-2015 were extracted from the SEER database. Univariate Cox regression identified significant prognostic variables that were further refined by least absolute shrinkage and selection operator (LASSO) regression and cross-validation analyses. These variables were incorporated into a multivariate Cox regression analysis to establish the predictive model. This model was visualized and validated using various statistical measures. A total of 54,960 patients were included in the study, with 38,472 in the training set and 16,488 in the validation set. Age, sex, race, marital status, grade, tumor (T) stage, lymph node (N) stage, subtype, and radiotherapy were found to be significant independent risk factors of 1-, 3-, and 5-year overall survival (OS). The receiver operating characteristic curve area for 1-, 3-, and 5-year OS was >0.76 in both sets. The consistency index values were 0.768 and 0.763 for the training and validation sets, respectively. The calibration curves showed good fit, and the nomogram exhibited substantial clinical utility. Incorporating various significant factors, the constructed nomogram was able to effectively predict the prognosis of breast cancer patients who received adjuvant therapy. This nomogram extends understandings of complex prognosis scenarios. In addition, it could enhance personalized treatment plans and assist in patient counseling.

PiRNAs and PIWI-like proteins in cancer and their future as biomarkers and therapy targets in breast cancer

Globally, breast cancer (BC) is the most common type of cancer, with 2.296.840 new cases in 2020 with almost 700.000 related deaths. Due to the high burden this represents, it is imperative to expand horizons to be able to find novel biomarkers and therapeutic targets that can be used to improve prognosis, treatment, and survival of breast cancer patients. In recent years, numerous studies have been conducted looking for the association between piRNAs (PIWI – interacting RNAs) and the development, pathogenesis, metastasis, and progression of different types of cancer, including BC. PiRNAs are small molecules (24-31 nucleotides) that interact with the PIWI-protein complex (PIWI-like proteins - HIWI/HILI in humans) performing regulatory functions by inducing transcriptional, post-transcriptional, translational, and post-translational epigenetic changes, which has been observed to contribute to cancer development through modifications in cell proliferation, transposon silencing, genome rearrangement, epigenetic regulation, protein regulation, and stem cell maintenance. In breast cancer, a strong association has been found between the expression of some piRNAs, PIWI-like proteins and tumor development. If a specific piRNA could be associated with a distinct type of cancer, it could then be used as an early biomarker which would allow for a better prognosis. Findings surrounding these molecular mechanisms could also spark interest in studies focusing on the modification of the expression of piRNAs in cancer cells. In this article, we intend to review in a straightforward manner the current information about piRNAs/PIWI-like proteins focusing on their expression in BC.

Lumacaftor as a potential repurposed drug in targeting breast cancer stem cells: insights from in silico study.

Breast cancer stem cells (BCSCs) are a small subset of cells within breast tumors with characteristics similar to normal stem cells. Despite advancements in chemotherapy and targeted therapy for breast cancer, the prognosis for breast cancer patients has remained poor due to drug resistance, reoccurrence, and metastasis. Growing evidence suggests that deregulation of the self-renewal pathways, like the Wnt signaling pathway mediated by β-catenin, plays a crucial role in the survival of breast cancer stem cells. Targeting the Wnt signaling pathway in breast cancer stem cells offers a promising avenue for developing effective therapeutic strategies targeting these cells, potentially leading to improved patient outcomes and reduced tumor recurrence. For this purpose, we have screened a 1615 FDA-approved drug library against our target protein, β-catenin, which is involved in the Wnt signaling pathway using molecular docking analysis, molecular dynamics (MD) simulations, and molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations. Molecular docking studies showed that the Lumacaftor- β-catenin complex had the lowest docking score of - 8.7kcal/mol towards β-catenin protein than the reference inhibitor. Molecular dynamic simulations and MM/PBSA calculations were also performed for the Lumacaftor-β-catenin complex to establish the stability of the interactions involved. Considering its promising attributes and encouraging results, Lumacaftor holds significant potential as a novel therapeutic option to target BCSCs. This study opens avenues for further investigation and may pave the way for developing therapeutic potential in breast cancer treatment. Further confirmation is warranted through in vitro and clinical studies to validate the findings of this study.

SPDYC serves as a prognostic biomarker related to lipid metabolism and the immune microenvironment in breast cancer.

Breast cancer remains the most common malignant carcinoma among women globally and is resistant to several therapeutic agents. There is a need for novel targets to improve the prognosis of patients with breast cancer. Bioinformatics analyses were conducted to explore potentially relevant prognostic genes in breast cancer using The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) databases. Gene subtypes were categorized by machine learning algorithms. The machine learning-related breast cancer (MLBC) score was evaluated through principal component analysis (PCA) of clinical patients' pathological statuses and subtypes. Immune cell infiltration was analyzed using the xCell and CIBERSORT algorithms. Kyoto Encyclopedia of Genes and Genomes enrichment analysis elucidated regulatory pathways related to speedy/RINGO cell cycle regulator family member C (SPDYC) in breast cancer. The biological functions and lipid metabolic status of breast cancer cell lines were validated via quantitative real-time polymerase chain reaction (RT‒qPCR) assays, western blotting, CCK-8 assays, PI‒Annexin V fluorescence staining, transwell assays, wound healing assays, and Oil Red O staining. Key differentially expressed genes (DEGs) in breast cancer from the TCGA and GEO databases were screened and utilized to establishthe MLBC score. Moreover, the MLBC score we established was negatively correlated with poor prognosis in breast cancer patients. Furthermore, the impacts of SPDYC on the tumor immune microenvironment and lipid metabolism in breast cancer were revealed and validated. SPDYC is closely related to activated dendritic cells and macrophages and is simultaneously correlated with the immune checkpoints CD47, cytotoxic T lymphocyte antigen-4 (CTLA-4), and poliovirus receptor (PVR). SPDYC strongly correlated with C-C motif chemokine ligand 7 (CCL7), a chemokine that influences breast cancer patient prognosis. A significant relationship was discovered between key genes involved in lipid metabolism and SPDYC, such as ELOVL fatty acid elongase 2 (ELOVL2), malic enzyme 1 (ME1), and squalene epoxidase (SQLE). Potent inhibitors targeting SPDYC in breast cancer were also discovered, including JNK inhibitor VIII, AICAR, and JW-7-52-1. Downregulation of SPDYC expression in vitro decreased proliferation, increased the apoptotic rate, decreased migration, and reduced lipid droplets. SPDYC possibly influences the tumor immune microenvironment and regulates lipid metabolism in breast cancer. Hence, this study identified SPDYC as a pivotal biomarker for developing therapeutic strategies for breast cancer.

Prognosis of locoregional recurrence after early breast cancer with immediate breast reconstruction.

e12595 Background: Several studies have shown no difference in the prognosis of breast cancer patients who underwent total mastectomy (MT) with or without immediate breast reconstruction (IBR), which is now a standard surgical technique in the treatment of breast cancer. While some studies have reported a poor prognosis for locoregional recurrence (LRR) following breast cancer surgery, the prognosis of LRR without simultaneous distant metastasis after IBR is not known. We conducted a multi-facility retrospective observational study to investigate the prognosis of breast cancer patients with LRR after IBR. Methods: Of the 4,726 primary breast cancer patients for whom IBR was performed at 12 Japanese medical facilities between January 1, 2008, and December 31, 2016, MT or skin-sparing mastectomy (SSM) was performed in 3,295 patients. LRR was observed in 87 of these patients, 17 of whom had distant metastasis (n=13) or metastasis to the supraclavicular or internal mammary lymph nodes (n=4) before LRR was excluded. The measured outcomes were IBR-LRR-related prognostic factors, five-year distant metastasis-free survival (DMFS), and five-year overall survival (OS). The statistical analyses employed Kaplan–Meier curves and a Cox proportional hazards model. Results: The median observation period was 39.3 months and the median age at which IBR was performed was 44 years. There were 61 cases (87.1%) of invasive cancer. Sixty-one cases (87.1%) were ER-positive, 54 (77.1%) were PR-positive, and 13 (19.7%) were HER2-positive. Fifteen cases (21.4%) had pathological lymph node metastasis (pN), 60 cases (85.7%) underwent implant reconstruction, 33 cases (47.1%) had a disease-free interval ≤ 36 months, 9 cases (12.9%) had regional lymph node recurrence (RR), and 65 cases (92.9%) underwent surgical resection to treat LRR. The five-year DMFS after LRR was 92.4%, and the five-year OS was 91.2%. The relationship between DMFS and clinical pathology factors was analyzed using a Cox proportional hazards model. Univariate analysis revealed significant differences for pN (HR 10.634, 95% CI 1.102–102.616, P=0.041) and RR (HR 9.960, 95% CI 1.400–70.862, P=0.022), and multivariate analysis indicated that RR was the only independent prognostic factor for DMFS (HR 7.834, 95% CI 1.085–56.587, P=0.041) (Table 1). Univariate analysis revealed significant differences for post-mastectomy radiation therapy (PMRT) (HR 130.676, 95% CI 1.552–412.278, P=0.023) and RR (HR 8.181, 95% CI 1.106–60.503, P=0.043), and multivariate analysis indicated that both PMRT (HR 61.281, 95% CI 2.540–1478.426, P=0.010) and RR (HR 15.687, 95% CI 1.354–181.772, P=0.028) were independent prognostic factors for OS. Conclusions: This is the first study to report the prognosis of breast cancer patients with LRR after IBR. Although these patients have a favorable prognosis overall, our results indicate that RR may be a significant factor for poor prognosis.