Prognosis Of Breast Cancer Patients Research Articles

GATA factor TRPS1, a new DNA repair protein, cooperates with reversible PARylation to promote chemoresistance in patients with breast cancer

Resistance to DNA-damaging agents is a major unsolved challenge for breast cancer patients undergoing chemotherapy. Here, we show that elevated expression of transcriptional repressor GATA binding 1 (TRPS1) is associated with lower drug sensitivity, reduced response rate, and poor prognosis in chemotherapy-treated breast cancer patients. Mechanistically, elevated TRPS1 expression promotes hyperactivity of DNA damage repair (DDR) in breast cancer cells. We provide evidence that TRPS1 dynamically localizes to DNA breaks in a Ku70- and Ku80-dependent manner, and that TRPS1 is a new member of the DDR protein family. We also discover that the dynamics of TRPS1 assembly at DNA breaks is regulated by its reversible PARylation in the DDR, and that mutations of the PARylation sites on TRPS1 lead to increased sensitivity to chemotherapeutic drugs. Taken together, our findings provide new mechanistic insights into the DDR and chemoresistance in breast cancer patients and identify TRPS1 as a critical DDR protein. TRPS1 may also be considered as a target to improve chemo-sensitization strategies and, consequently, clinical outcomes for breast cancer patients.

NUAKs promote mTOR/c-Myc-induced glucose and glutamine reprogramming for cell growth and metastasis in breast cancer cells

Breast cancer progression and metastasis are closely connected to changes in glucose and glutamine metabolism. While Novel (nua) kinase family 1 (NUAK1) and Novel (nua) kinase family 2 (NUAK2), which are two members of the AMPK-related kinases, have been associated with breast tumorigenesis, their role in the metabolic reprogramming that occurs during breast cancer progression remains unclear. Our research uncovers that NUAKs expression is significantly higher in breast cancer tissues and cell lines, and it is positively related to glycolysis, the pentose phosphate pathway (PPP), glutamine metabolism, and a poor prognosis for breast cancer patients. We show that NUAKs significantly increase metabolic reprogramming, including aerobic glycolysis, PPP, and glutamine metabolism in triple negative breast cancer subtypes but only induce aerobic glycolysis and PPP in luminal breast cancer subtypes to meet the anabolic demands of rapidly dividing breast cancer cells. In contrast, the depletion of NUAKs has the opposite effect. Mechanistic insights reveal that NUAKs activate mammalian target of rapamycin (mTOR) signaling, which in turn upregulates the c-Myc transcription factor, a crucial regulator of glucose and glutamine metabolic gene expression. Moreover, we demonstrate that NUAKs enhance mTOR/c-Myc signaling pathways, leading to increased glucose and glutamine reprogramming, which supports rapid cell proliferation and metastatic potential in breast cancer cells. Importantly, pretreating breast cancer cells with mTOR inhibitors blocked the metabolic reprogramming and tumor-promoting effect of NUAK1/2. Therefore, targeting NUAKs may represent a novel therapeutic strategy for the treatment of breast cancer.

Identification of lysine lactylation (kla)-related lncRNA signatures using XGBoost to predict prognosis and immune microenvironment in breast cancer patients

Breast cancer (BC) stands as a predominant global malignancy, significantly contributing to female mortality. Recently uncovered, histone lysine lactylation (kla) has assumed a crucial role in cancer progression. However, the correlation with lncRNAs remains ambiguous. Scrutinizing lncRNAs associated with Kla not only improves clinical breast cancer management but also establishes a groundwork for antitumor drug development. We procured breast tissue samples, encompassing both normal and cancerous specimens, from The Cancer Genome Atlas (TCGA) database. Utilizing Cox regression and XGBoost methods, we developed a prognostic model using identified kla-related lncRNAs. The model's predictive efficacy underwent validation across training, testing, and the overall cohort. Functional analysis concerning kla-related lncRNAs ensued. We identified and screened 8 kla-related lncRNAs to formulate the risk model. Pathway analysis disclosed the connection between immune-related pathways and the risk model of kla-related lncRNAs. Significantly, the risk scores exhibited a correlation with both immune cell infiltration and immune function, indicating a clear association. Noteworthy is the observation that patients with elevated risk scores demonstrated an increased tumor mutation burden (TMB) and decreased tumor immune dysfunction and exclusion (TIDE) scores, suggesting heightened responses to immune checkpoint blockade. Our study uncovers a potential link between Kla-related lncRNAs and BC, providing innovative therapeutic guidelines for BC management.

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

To develop and validate machine learning models for human epidermal growth factor receptor 2 (HER2)-zero and HER2-low using MRI features pre-neoadjuvant therapy (NAT). Five hundred and sixteen 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 (tumour diameter, enhancement type, background parenchymal enhancement, enhancement pattern, percentage of enhancement, signal enhancement ratio, breast oedema, and apparent diffusion coefficient) were reviewed. Logistic regression (LR), support vector machine (SVM), k-nearest neighbour (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, which was 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 receiver operating characteristic 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 (hazard ratio: 2.748, 95% CI, 1.016-7.432, P = .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. 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.

High NTRK2 protein expression levels may be associated with poorer prognosis of breast cancer patients.

Previous research has shown that the role of neurotrophic receptor tyrosine kinase 2 (NTRK2) in breast cancer (BRCA) remains ambiguous. To help elucidate this, we conducted a retrospective study to investigate the relationship between NTRK2 protein expression and BRCA. The prognostic significance of NTRK2 protein expression patterns was assessed by performing immunohistochemistry assays on 131 BRCA tissues and 56 adjacent normal tissues in a retrospective study. Furthermore, the sensitivity to chemotherapeutic drugs was quantified by "pRRophetic" and the sensitivity to immunotherapy was estimated using The Cancer Immunome Atlas website. NTRK2 protein was expressed at significantly higher levels in BRCA samples compared with normal tissues. The data indicated that NTRK2 expression is an independent risk factor for BRCA patient prognosis. Additionally, the high NTRK2 group exhibited increased sensitivity to certain chemotherapy drugs and achieved higher scores for immune checkpoint blockade therapy compared with the low NTRK2 group. Our study demonstrated that higher NTRK2 protein expression is related to a less favorable prognosis in BRCA patients, as well as to enhanced sensitivity to specific chemotherapy and immunotherapy drugs.

Exploring chromosomal instability and clonal heterogeneity in breast cancer.

Chromosomal instability (CIN), characterized by fluctuations in chromosome number or structure within cells, stands out as a hallmark of cancer, enabling tumors to thrive in hostile conditions. CIN serves as a driver of genetic diversity, giving rise to clonal heterogeneity (CH). Emerging evidence points to a potential correlation between CIN, CH, and the prognosis of breast cancer (BC) patients, especially in tumors exhibiting overexpression of the human epidermal growth factor receptor 2 (HER2+). However, our understanding of the role of CIN in other subtypes of BC is limited. Furthermore, it remains unclear whether CIN levels above a certain threshold in BC tumors could adversely affect tumor growth, or if lower to moderate levels of CIN might be associated with a more favorable prognosis for BC patients compared to elevated levels. Elucidating these relationships could significantly influence risk assessment and the formulation of future therapeutic approaches targeting CIN in BC. This study aimed to assess CIN and CH in tumor tissue samples obtained from Colombian patients diagnosed with luminal A, luminal B, HER2+, or triple-negative BC, and compare them with established clinicopathological parameters. The findings of this study indicate that BC patients, exhibit intermediate CIN, high CH, and stable aneuploidy. All these characteristics were found to be related with clinicopathological features. Our results suggest that the identification of CIN, CH and aneuploidy could improve cancer risk stratification, which could help to clarify the prediction of clinical outcomes and guiding personalized therapeutic strategies for patients with different BC subtypes.

Identification of TAT as a Biomarker Involved in Cell Cycle and DNA Repair in Breast Cancer.

Breast cancer (BC) is the most frequently diagnosed cancer and the primary cause of cancer-related mortality in women. Treatment of triple-negative breast cancer (TNBC) remains particularly challenging due to its resistance to chemotherapy and poor prognosis. Extensive research efforts in BC screening and therapy have improved clinical outcomes for BC patients. Therefore, identifying reliable biomarkers for TNBC is of great clinical importance. Here, we found that tyrosine aminotransferase (TAT) expression was significantly reduced in BC and strongly correlated with the poor prognosis of BC patients, which distinguished BC patients from normal individuals, indicating that TAT is a valuable biomarker for early BC diagnosis. Mechanistically, we uncovered that methylation of the TAT promoter was significantly increased by DNA methyltransferase 3 (DNMT3A/3B). In addition, reduced TAT contributes to DNA replication and cell cycle activation by regulating homologous recombination repair and mismatch repair to ensure genomic stability, which may be one of the reasons for TNBC resistance to chemotherapy. Furthermore, we demonstrated that Diazinon increases TAT expression as an inhibitor of DNMT3A/3B and inhibits the growth of BC by blocking downstream pathways. Taken together, we revealed that TAT is silenced by DNMT3A/3B in BC, especially in TNBC, which promotes the proliferation of tumor cells by supporting DNA replication, activating cell cycle, and enhancing DNA damage repair. These results provide fresh insights and a theoretical foundation for the clinical diagnosis and treatment of BC.

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.

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.

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.

HNRNPA2B1 induces cell proliferation and acts as biomarker in breast cancer.

Numerous studies have shown that m6A plays an important regulatory role in the development of tumors. HNRNPA2B1, one of the m6A RNA methylation reading proteins, has been proven to be elevated in human cancers. In this study, we aimed to identify the role of HNRNPA2B1 in breast cancer. HNRNPA2B1 expression was investigated via RT-qPCR and TCGA database in breast cancer. Then, the function of HNRNPA2B1 on cancer cell was measured by CCK8 assays, colony formation and scratch assays. In addition, HNRNPA2B1 expression in BRCA was explored via the Wilcoxon signed-rank test, KruskalWallis test and logistic regression. The association with HNRNPA2B1 expression and survival were considered by KaplanMeier and Cox regression analyses. The biological function of HNRNPA2B1 was analyzed via gene set enrichment analysis (GSEA) and the cluster Profiler R software package. We found that HNRNPA2B1 was highly expressed and induced cell proliferation and migration in breast cancer. Moreover, we observed HNRNPA2B1 induced tumor growth in vivo. In addition, we also found HNRNPA2B1 expression was associated with characteristics and prognosis in breast cancer patients. Our findings suggested that HNRNPA2B1 promoted tumor growth and could function as a new potential molecular marker in breast cancer.

Prognostic and clinicopathological significance of fibrinogen-to-albumin ratio (FAR) in patients with breast cancer: a meta-analysis

BackgroundThe fibrinogen-to-albumin ratio (FAR) has been extensively studied for its role in predicting the prognosis of breast cancer (BC) patients; however, existing findings are conflicting. Therefore, this meta-analysis was conducted to identify the significance of FAR in predicting BC prognosis.MethodsWe searched PubMed, Embase, Web of Science, Cochrane Library, and China National Knowledge Infrastructure databases until May 25, 2024. The value of FAR for predicting overall survival (OS) and disease-free survival (DFS) in BC was examined by calculating the combined hazard ratios (HRs) and 95% confidence intervals (CIs). Correlations between FAR and clinicopathological factors were analyzed using combined odds ratios (ORs) and 95% CIs.ResultsEight studies involving 4094 patients were included in this work. As shown by our combined data, increased FAR significantly predicted poor OS (HR = 2.84, 95% CI = 1.83–4.39, p < 0.001) and poor DFS (HR = 2.43, 95% CI = 1.66–3.58, p < 0.001) of BC. Moreover, the combined data showed that increased FAR was significantly correlated with age ≥ 50 years (OR = 2.04, 95% CI = 1.37–3.04, p < 0.001), stage III cancer (OR = 1.53, 95% CI = 1.04–2.27, p = 0.033), and the presence of lymph node metastases (OR = 1.33, 95% CI = 1.11–1.61, p = 0.002). Nonetheless, FAR was not significantly associated with tumor size, ER/PR/HER-2 status, or lymphovascular invasion in patients with BC.ConclusionIn this meta-analysis, higher FAR was significantly associated with unfavorable OS and DFS in patients with BC and significantly correlated with several features predictive of cancer development in BC.

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.

Overexpression of cytoplasmic poly(A)-binding protein 1 as a biomarker for the prognosis and selection of postoperative regimen in breast cancer.

The dysregulation of the cytoplasmic poly(A)-binding protein 1 (PABPC1) is involved in a variety of tumors but little is known about its role in human breast cancer. Therefore, the effect of PABPC1 in the prognosis and regimen selection in breast cancer patients was evaluated. A total of 791 cases of invasive breast cancer were included in this study, although only 416 were involved in subsequent analyses after the propensity score matching (PSM) test. PABPC1 expression was detected by immunohistochemistry. The relationship between PABPC1 expression and clinicopathological factors, postoperative regimens, and outcomes was determined. In the total 791 cases, 583 cases were positive for PABPC1, but only 212 (26.8%) showed high PABPC1 expression (PABPC1-HE). The overall survival (OS) and disease-free survival (DFS) of PABPC1-HE patients after PSM were significantly worse than those in patients with PABPC1 low expression (PABPC1-LE), regardless of age, molecular type, tumor size, nodal status, or pStage. Postoperative chemotherapy (CT) increased the OS of PABPC1-HE patients but not that of PABPC1-LE patients. Among patients receiving endocrine therapy, those in the PABPC-LE group had an extended OS, while CT or chemoradiotherapy (CT/CRT) only significantly extended the OS time of PABPC-HE patients. CT/CRT did not significantly extend the survival of PABPC1-LE HER2-positive patients but extended the OS of PABPC1-HE HER2-positive patients. However, the OS of patients treated with CT/CRT + trastuzumab therapy was significantly longer than that of other patients under other therapies in the PABPC1-HE group, suggesting that PABPC1-HE might be sensitive to trastuzumab-based therapy. The multivariate analysis revealed that PABPC1-HE was an independent prognostic factor for both poor OS and DFS in breast cancer except luminal A type. Our results revealed that PABPC1 might be considered as a biomarker to help in subtyping, as well as in the prognosis and regimen selection of breast cancer patients.

Detecting cell types and densities in the tumor microenvironment improves prognostic risk assessment for breast cancer.

A comprehensive evaluation of the relationship between the densities of various cell types in the breast cancer tumor microenvironment and patient prognosis is currently lacking. Additionally, the absence of a large patch-level whole slide imaging (WSI) dataset of breast cancer with annotated cell types hinders the ability of artificial intelligence to evaluate cell density in breast cancer WSI. We first employed Lasso-Cox regression to build a breast cancer prognosis assessment model based on cell density in a population study. Pathology experts manually annotated a dataset containing over 70,000 patches and used transfer learning based on ResNet152 to develop an artificial intelligence model for identifying different cell types in these patches. The results showed that significant prognostic differences were observed among breast cancer patients stratified by cell density score (P = 0.0018), with the cell density score identified as an independent prognostic factor for breast cancer patients (P < 0.05). In the validation cohort, the predictive performance for overall survival (OS) was satisfactory, with area under the curve (AUC) values of 0.893 (OS) at 1-year, 0.823 (OS) at 3-year, and 0.861 (OS) at 5-year intervals. We trained a robust model based on ResNet152, achieving over 99% classification accuracy for different cell types in patches. These achievements offer new public resources and tools for personalized treatment and prognosis assessment.

Prognostic risk model under the immune-associated long chain non-coding ribonucleic acid and its application in survival prognosis assessment of patients with breast cancer

This study aimed to develop a prognostic risk model based on immune-related long non-coding RNAs (lncRNAs). By analyzing the expression profiles of specific long non-coding RNAs, the objective was to construct a predictive model to accurately assess the survival prognosis of breast cancer (BC) patients. This effort seeks to provide personalized treatment strategies for patients and improve clinical outcomes. Based on the median risk value, 300 samples of triple-negative BC (TNBC) patients were rolled into a high-risk group (HR group, n = 140) and a low-risk group (LR group, n = 160). Multivariate Cox (MVC) analysis was performed by combining the patient risk score and clinical information to evaluate the prognostic value of the prognostic risk (PR) model. A total of 371 immune-related lncRNAs associated with the prognosis of TNBC were obtained from 300 TNBC samples. Nine associated with prognosis were obtained by univariate Cox (UVC) analysis, and 3 (AC090181.2, LINC01235, and LINC01943) were selected by MVC analysis for the construction of TNBC PR model. Survival analysis showed a great difference in TNBC patients in different groups (P < 0.001). The receiver operator characteristic (ROC) curve showed the model possessed a good area under ROC curve (AUC), which was 0.928. The patient RS jointing with clinical information as well as the MVC analysis revealed that RS was an independent risk factor (IRF) for prognosis of TNBC (P < 0.05, HR = 1.033286). Therefore, the lncRNAs associated with TNBC immunity can be screened by bioinformatics analysis, and the established PR model of TNBC could better predict the prognosis of patients with TNBC, exhibiting a high application value in clinic.

Increasing survivors of anthracycline-related cardiomyopathy with breast cancer in trastuzumab era: thirty-one-year trends in a Japanese Community

BackgroundTrastuzumab has improved breast cancer (BC) prognosis and reduced anthracycline use. However, the characteristic changes of anthracycline-related cardiomyopathy (ARCM) in patients with BC remain unclear. We aimed to update our understanding of ARCM in the trastuzumab era.METHODSThis retrospective observational cohort study included 2959 patients with BC treated with anthracyclines at three regional cancer centers in Niigata City between 1990 and 2020. Seventy-five patients (2.5%) developed ARCM and were categorized into two groups: pre- 2007 (early phase) and post-2007 (late phase), corresponding to before and during the trastuzumab era in Japan.ResultsARCM incidence peaked at 6% in the 1990s, then decreased and stabilized at 2% until the 2010s. Survivors of anthracycline-treated BC increased more rapidly in the late phase, with four times as many patients with ARCM compared to the end of the early phase (26 and six, respectively). Although the rate of change in accumulation from the early phase to the late phase was slight in the anthracycline-treated BC group, it was more pronounced in the ARCM group (P < 0.001). Mean anthracycline use in the late phase was significantly lower than in the early phase (307 vs. 525 mg/m2, P < 0.001). Five-year survival rates in the late phase tended to be higher than early phase (45% and 28%, respectively. P = 0.058). Human epidermal growth factor receptor type 2 (HER2) positivity with trastuzumab therapy in the late phase was an independent predictor for mortality within 10 years (hazard ratio = 0.24, 95% confidence interval: 0.10–0.56; P = 0.001).ConclusionsHER2-positive patients with ARCM receiving trastuzumab therapy had a better prognosis than HER2-positive and HER2-negative patients with ARCM not receiving trastuzumab therapy, and this trend has been increasing in the trastuzumab era. These findings highlight the importance of HER2-targeted treatments in improving prognosis for BC patients with ARCM.

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.

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.