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Introduction: There is a strong rationale for targeting HER3, as HER3 contributes to tumorigenesis and treatment resistance. However, the prognostic role of HER3 and their association with immunoregulatory protein expression has not been established., Methods: The main objective of this study was to investigate the prognostic role of HER3 expression and identify immunoregulatory marker expression according to HER3 status. HER3 expression and 10 immunoregulatory protein (PD-1/PD-L1/PD-L2/IDO/TIM-3/OX40/OX40L/B7-H2/B7-H3/B7-H4) expression was identified in 320 stage I-III breast cancer patients who received curative surgery at Seoul National University Hospital in 2008. The median follow-up duration was 88.8 months. Criteria for HER3 IHC was adopted from HER2 IHC score and only those with 3 + was considered positive., Results: Among 320 patients, 213 (67.2 %) had luminal A disease, 30 (9.5 %) had luminal B disease, 28 (8.8 %) had HER2-positive disease, and 46 (14.5 %) had triple negative disease. HER3 expression was shown in 153 patients (47.8 %). Tumors with HER3-expression had more immunogenic tumor microenvironment compared to HER3-negative tumor. In addition, patients with HER3 expression had favorable 5-year relapse free survival compared to HER3-negative patients (5-year RFS 92.5 % vs. 85.2 %, p = 0.038). However, in the multivariate analysis, HER3 expression was not a prognostic factor, but expression of immunoregulatory protein was a prognostic factor., Conclusions: This study identified immunoregulatory protein expression according to HER3 status in breast cancer patients. As tumor with HER3 expression have more immunogenic microenvironment, investigating combination treatment of HER3 targeting agent and immunotherapy in HER3 expressing breast cancer may be promising., Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests., (Copyright © 2024. Published by Elsevier Ltd.)

Background: The cutoff of <1% positive cells to define estrogen receptor (ER) negativity by immunohistochemistry (IHC) in breast cancer (BC) is debated. We explored the tumor immune microenvironment and gene-expression profile of patients with early-stage HER2-negative ER-low (ER 1%-9%) BC, comparing them to ER-negative (ER <1%) and ER-intermediate (ER 10%-50%) tumors., Methods: Among 921 patients with early-stage I-III, ER ≤50%, HER2-negative BCs, tumors were classified as ER-negative (n = 712), ER-low (n = 128), or ER-intermediate (n = 81). Tumor-infiltrating lymphocytes (TILs) were evaluated. CD8+, FOXP3+ cells, and PD-L1 status were assessed by IHC and quantified by digital pathology. We analyzed 776 BC-related genes in 116 samples. All tests were 2-sided at a <.05 significance level., Results: ER-low and ER-negative tumors exhibited similar median TILs, statistically significantly higher than ER-intermediate tumors. CD8/FOXP3 ratio and PD-L1 positivity rates were comparable between ER-low and ER-negative groups. These groups showed similar enrichment in basal-like intrinsic subtypes and comparable expression of immune-related genes. ER-low and ER-intermediate tumors showed significant transcriptomic differences. High TILs (≥30%) were associated with improved relapse-free survival (RFS) in ER-low (5-year RFS 78.6% vs 66.2%, log-rank P = .033, hazard ratio [HR] 0.37 [95% CI = 0.15 to 0.96]) and ER-negative patients (5-year RFS 85.2% vs 69.8%, log-rank P < .001, HR 0.41 [95% CI = 0.27 to 0.60])., Conclusions: ER-low and ER-negative tumors are similar biological and molecular entities, supporting their comparable clinical outcomes and treatment responses, including to immunotherapy. Our findings contribute to the growing evidence calling for a reevaluation of ER-positive BC classification and management, aligning ER-low and ER-negative tumors more closely., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Breast cancer prognosis remains a significant challenge due to the disease's molecular heterogeneity and complexity. Accurate predictive models are critical for improving patient outcomes and tailoring personalized therapies., Methods: We developed a Machine Learning-assisted Telomerase Signature (MLTS) by integrating multi-omics data from nine independent breast cancer datasets. Using multiple machine learning algorithms, we identified six telomerase-related genes significantly associated with patient survival. The predictive performance of MLTS was evaluated against 66 existing breast cancer prognostic models across diverse cohorts., Results: The MLTS demonstrated superior predictive accuracy, stability, and reliability compared to other models. Patients with high MLTS scores exhibited increased tumor mutational burden, chromosomal instability, and poor survival outcomes. Single-cell RNA sequencing analysis further revealed higher MLTS scores in aneuploid tumor cells, suggesting a role in cancer progression. Immune profiling indicated distinct tumor microenvironment characteristics associated with MLTS scores, potentially guiding therapeutic decisions., Conclusions: Our findings highlight the utility of MLTS as a robust prognostic biomarker for breast cancer. The ability of MLTS to predict patient outcomes and its association with key genomic and cellular features underscore its potential as a target for personalized therapy. Future research may focus on integrating MLTS with additional molecular signatures to enhance its clinical application in precision oncology., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Guo, Cao, Shi, Xing, Feng and Wang.)

Background: Presently incurable, metastatic breast cancer is estimated to occur in as many as 30% of those diagnosed with early-stage breast cancer. Timely and accurate identification of those at risk for developing metastasis using validated biomarkers has the potential to have profound impact on overall survival rates. Our primary goal was to conduct a systematic review and synthesize the existing body of scientific knowledge on the candidate genes and their respective single nucleotide polymorphisms associated with metastasis-related outcomes among patients diagnosed with breast cancer. This knowledge is critical to inform future hypothesis-driven and validation research aimed at enhancing clinical decision-making for breast cancer patients., Methods: Using PRISMA guidelines, literature searches were conducted on September 13th, 2023, using PubMed and Embase databases. The systematic review protocol was registered with INPLASY (DOI: https://doi.org/10.37766/inplasy2024.8.0014 ). Covidence software was used to facilitate the screening and article extraction processes. Peer-reviewed articles were selected if authors reported on single nucleotide polymorphisms directly associated with metastasis among adults diagnosed with breast cancer., Findings: We identified 451 articles after 44 duplicates were removed resulting in 407 articles to be screened for study inclusion. Three reviewers completed the article screening process which resulted in 86 articles meeting the study inclusion criteria. Sampling varied across studies with the majority utilizing a case-control design (n = 75, 87.2%), with sample sizes ranging from 23 to 1,017 participants having mean age 50.65 ± 4.50 (min-max: 20-75). The synthesis of this internationally generated evidence revealed that the scientific area on the underlying biological contributions to breast cancer metastasis remains predominantly exploratory in nature (n = 74, 86%). Of the 12 studies with reported power analyses, only 9 explicitly stated the power values which ranged from 47.88 to 99%., Discussion: Understanding the underlying biological mechanisms contributing to metastasis is a critical component for precision oncological therapeutics and treatment approaches. Current evidence investigating the contribution of SNPs to the development of metastasis is characterized by underpowered candidate gene studies. To inform individualized precision health practices and improve breast cancer survival outcomes, future hypothesis-driven research is needed to replicate these associations in larger, more diverse datasets., Competing Interests: Declarations. Ethics approval and consent to participate: This review study is exempt from ethical approval as this study is based exclusively on pre-existing published literature. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Background: CD147 belongs to the immunoglobulin superfamily, also known as Basigin (BSG), and is a highly glycosylated single transmembrane glycoprotein present in various tissues. Meta and bioinformatic analyses were used to explore the correlation between CD147 expression and the clinicopathological characteristics prognosis of breast cancer., Method: Literature related to breast cancer was retrieved through PubMed and CNKI databases, and a meta-analysis was conducted using Review Manager 5.2 software., Results: The meta-analysis revealed that all articles included data on 522 patients with breast cancer and 492 normal tissues. CD147 expression in breast cancer tissue was higher compared to that in normal tissue([8.92-139.52]; p < 0.00001 I 2  = 80%) and negatively correlated with LM, clinical stage, histological grade, and ER positive expression. Bioinformatic analysis revealed that the expression of CD147 in breast cancer tissue was higher than that in normal tissue, and its high expression was closely related to the clinicopathological characteristics of patients, such as LM, histological grading, and clinical staging. According to the TIMER database, CD147 expression was closely related to immune cell infiltration in breast cancer., Conclusion: These results indicated that high CD147 expression might be closely linked to the occurrence as well as the development of breast cancer, and can function as a good indicator of prognosis in the future, providing new methods and ideas for the prevention and treatment of breast cancer., Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Purpose: Tumor progression has been linked to stiffening of the extracellular matrix caused by fibrosis. Cancer cells can be mechanically conditioned by stiff extracellular matrix, exhibiting a 1,004-gene signature [mechanical conditioning (MeCo) score]. Nintedanib has demonstrated antifibrotic activity in idiopathic pulmonary fibrosis. This study explores nintedanib's antifibrotic effect on breast cancer outcomes., Experimental Design: We present long-term follow-up and analysis of a neoadjuvant randomized phase II trial in early HER2-negative breast cancer. Patients (N = 130) underwent a baseline biopsy and received 12 paclitaxel courses alone (control arm) or in combination with nintedanib (experimental arm). The tumor MeCo score was determined by RNA sequencing. The primary aim was to assess nintedanib's impact on event-free survival based on MeCo scores., Results: Follow-up data were retrieved from 111 patients; 75 baseline and 24 post-run-in phase samples were sequenced. After median follow-up of 9.67 years, median event-free survival was not statistically different between arms (P = 0.37). However, in the control arm, high- versus low-MeCo patients had a statistically higher relapse risk: HR = 0.21; P = 0.0075. This risk was corrected by nintedanib in the experimental arm: HR = 0.37; P = 0.16. Nintedanib demonstrated pharmacodynamic engagement, reducing the MeCo score by 25% during the run-in phase (P < 0.01). Patients with low MeCo after run-in had the best long-term prognosis (HR = 0.087; P = 0.03)., Conclusions: High MeCo is predictive of poor outcomes in HER2-negative early breast cancer, although this risk can be mitigated by nintedanib, which is able to specifically reduce MeCo., (©2024 American Association for Cancer Research.)

Indoleamine 2,3-dioxygenase 1 (IDO1) plays an important role in the initiation and progression of breast cancer. DNA promoter methylation status has the potential to be used as a biomarker for predicting the response to immunotherapy. This study aimed to investigate the biological and clinical significance of IDO1 promoter methylation in breast cancer. We analyzed IDO1 promoter methylation and its relationship with survival, patient prognosis, immune cell infiltration, immune-related pathways, and the expression of key immunomodulators via bioinformatics methods in The Cancer Genome Atlas (TCGA) breast cancer cohort (779 samples). Furthermore, the IDO1 promoter methylation status and expression of the IDO1 gene in the basal subtype of breast cancer were investigated in vitro via a methylation-specific PCR (MSP) assay and quantitative polymerase chain reaction (qPCR). The IDO1 promoter was significantly hypomethylated in the basal subtype of breast cancer tissues compared with normal adjacent tissues, and this effect was correlated with high expression of IDO1, resulting in abundant immune cell infiltration, activation of immune-related pathways, and upregulation of key immunomodulators. The influence of IDO1 promoter hypomethylation on the prognosis of patients with breast cancer was also investigated. The promoter hypomethylation of IDO1 in the basal subtype of breast cancer and its correlation with high expression of IDO1 were also investigated in vitro. Our results showed that IDO1 promoter methylation is vital for regulating its expression, which leads to the development of a tumor microenvironment in breast cancer. IDO1 promoter methylation and expression are associated with prognosis, immune cell infiltration, immune-related pathways, and immunomodulator expression in breast cancer. Our findings provide evidence for the validation of IDO1 promoter methylation as a promising biomarker to predict responses to immune checkpoint inhibitors in patients with breast cancer., Competing Interests: Competing interests The authors declare no competing interests. Ethics approval The use of the public data was approved by TCGA. Consent for publication Not applicable., (© 2024. The Author(s).)

Background: HER2-positivity is an essential marker for therapeutic decisions, while HER2 expression is heterogenous. In recent years, there has been increasing recognition of a subgroup of breast cancer patients who have low levels of HER2 expression, also known as HER2-low because trastuzumab deruxtecan offers clinical benefit for patients with HER2-low metastatic breast cancer. Despite the growing interest in HER2-low breast cancer, there is limited research on how multigene assays can help differentiate between HER2-low and HER2-negative breast cancer. Among HR + HER2- breast cancer, we compared genomic characteristics between HER2-low and HER2-zero using the 21-gene assay., Methods: A retrospective review of clinical records was performed in 2,295 patients who underwent Oncotype DX ® test in two hospitals between 2013 and 2020. Patients were classified into two groups as the HER2-zero and HER2-low based on HER2 immunohistochemistry. In cases with HER2 2+, no amplification of HER2 gene was confirmed by silver in situ hybridization. High genomic risk was defined as cases with 21-gene recurrence score (RS) > 25. Multivariable binary logistic-regression analysis was performed., Results: Of these, 944 (41.1%) patients were assigned to the HER2-zero group, while 1351 (58.9%) patients were assigned to the HER2-low group. The average Recurrence Score (RS) was found to be 17.802 in the HER2-zero breast cancer group and 18.503 in the HER2-low group, respectively (p-value < 0.005). When comparing the proportion of high RS between the two groups, the HER2-zero group had a high RS rate of 12.4% (117 out of 944), while the HER2-low group had a high RS rate of 17.0% (230 out of 1351) (p = 0.002). The HER2 score identified by qRT-PCR was 8.912 in the HER2-zero group and 9.337 in the HER2-low group (p < 0.005). In multivariable analysis, HER2-low status was found to be an independent factor for high RS, with an odds ratio of 1.517 (1.172-1.964), independent of ER, PR, and Ki67. Within the subgroup of patients with invasive ductal carcinoma, the high RS rates were 19% in the HER2-low group and 14% in the HER2-zero group. However, when considering all patients, there were no significant differences observed in recurrence-free survival and overall survival between the HER2-low and HER2-zero groups., Conclusion: Within HR + HER2- breast cancer, HER2-low tumors are associated with high RS, especially for histologically invasive ductal carcinoma. A prognostic influence of HER2-low expression among HR + HER2- breast cancer remains as an area that requires further study., (© 2024. The Author(s).)

Background: Inflammation influences tumour progression and cancer prognosis, but its role preceding breast cancer (BC) and its prognostic implications remain inconclusive., Methods: We studied pre-diagnostic plasma inflammatory biomarkers in 1538 women with BC from the EPIC study. Cox proportional hazards models assessed their relationship with all-cause and BC-specific mortality, adjusting for tumour characteristics and lifestyle factors., Results: Over a 7-year follow-up after diagnosis, 229 women died, 163 from BC. Elevated IL-6 levels were associated with increased all-cause mortality risk (HR 1-SD 1.25, 95% CI 1.07-1.47). Among postmenopausal, IL-6 was associated with higher all-cause (HR 1-SD 1.41, 95% CI 1.18-1.69) and BC-specific mortality (HR 1-SD 1.31, 95% CI 1.03-1.66), (P Heterogeneity (pre/postmenopausal)  < 0.05 for both), while IL-10 and TNFα were associated with all-cause mortality only (HR 1-SD 1.19, 95% CI 1.02-1.40 and HR 1-SD 1.28, 95% CI 1.06-1.56). Among ER+PR+, IL-10 was associated with all-cause and BC-specific mortality (HR 1-SD 1.35, 95% CI 1.10-1.65 and HR 1-SD 1.42 95% CI 1.08-1.86), while TNF-α was associated with all-cause mortality in HER2- (HR 1-SD 1.31, 95% CI 1.07-1.61). An inflammatory score predicted higher all-cause mortality, especially in postmenopausal women (HR 1-SD 1.30, 95% CI 1.07-1.58)., Conclusions: Higher pre-diagnosis IL-6 levels suggest poorer long-term survival among BC survivors. In postmenopausal survivors, elevated IL-6, IL-10, and TNFα and inflammatory scores seem to predict all-cause mortality., (© 2024. The Author(s).)

Purpose: Invasive micropapillary carcinoma (IMPC) of the breast is known for its high metastatic potential, but the definition of pure and mixed IMPC remains unclear. This retrospective cohort study aims to investigate the prognostic significance of the micropapillary component ratio and the expression of critical molecules of epithelial-mesenchymal transition (EMT), including E-cadherin (E-cad), N-cadherin (N-cad), CD44s, and β-catenin (β-cat), in distinguishing between pure and mixed IMPCs., Methods: We analyzed 100 cases of locally advanced IMPC between 2000 and 2018 and excluded patients who received neoadjuvant chemotherapy. Pure IMPC was defined as having a micropapillary component of over 90%. A comprehensive recording of prognostic parameters was conducted. The IMPC areas were analyzed using the immunohistochemical (IHC) staining method on the microarray set for pure and mixed IMPC patients. Pearson's chi-square, Fisher's exact tests, Kaplan-Meier analysis, and Cox proportional hazards analysis were employed., Results: The comparative survival analysis of the entire group, based on overall survival (OS) and disease-free survival (DFS), revealed no significant difference between the pure and mixed groups (P = 0.480, HR = 1.474 [0.502-4.325] and P = 0.390, HR = 1.587 [0.550-4.640], respectively). However, in the pure IMPC group, certain factors were found to be associated with a higher risk of short survival. These factors included skin involvement (P = 0.050), pT3&4 category (P = 0.006), a ratio of intraductal component (> 5%) (P = 0.032), and high-level expression of N-cad (P = 0.020). Notably, none of the risk factors identified for short OS in pure IMPC cases were observed as significant risks in mixed cases and vice versa. Furthermore, N-cad was identified as a poor prognostic marker for OS in pure IMPCs (P = 0.002)., Conclusion: The selection of a 90% ratio for classifying pure IMPCs revealed significant differences in certain molecular and prognostic parameters between pure and mixed groups. Notably, the involvement of N-cadherin in the epithelial-mesenchymal transition (EMT) process provided crucial insights for predicting OS and DFS while also distinguishing between the two groups. These findings strongly support the notion that the pure IMPC subgroup represents a distinct entity characterized by unique molecular characteristics and behavioral patterns., (© 2024. The Author(s).)

Purpose: To assess the association between tumor-infiltrating lymphocytes (TILs) in ductal carcinoma in situ (DCIS) samples and disease recurrence., Methods: This retrospective cohort study included women aged 18 years and older who underwent treatment between January 2007 and December 2020. Male patients, individuals diagnosed with invasive or microinvasive disease based on anatomopathological examination of surgical specimens, and those with a personal history of any other cancers were excluded. Additionally, the presence of "touching TILs" (lymphocytes in direct contact with tumor cells) and periductal desmoplasia were evaluated as complementary methods to represent the immunological microenvironment. The primary outcome was relapse-free survival based on TIL quantification adjusted for potential confounders. Pathologists assessed TILs in the sample with the highest tumor representation and quantified them as a percentage. Survival was evaluated using Kaplan‒Meier curves, log-rank tests, and Cox regression models., Results: A total of 191 patients met the eligibility criteria. The mean follow-up duration was 77.2 months, with a recurrence rate of 9.2%. Patients with TILs ≥ 17% had a greater risk of recurrence (HR 2.97, 95% CI 1.17-7.51; p = 0.02). Additionally, focal necrosis (HR 6.4, 95% CI 1.39-34.71; p = 0.018) or comedonecrosis (HR 4.53, 95% CI 1.34-15.28; p = 0.015) were associated with increased recurrence risk. According to the multivariate model, comedonecrosis and TILs ≥ 17% were significantly associated with recurrence (p = 0.034 and p = 0.035, respectively). Regarding the evaluations of "touching TILs" and periductal desmoplasia, no statistical significance was found when assessing their association with disease recurrence., Conclusion: In our cohort, a high percentage of TILs (≥ 17%) and the presence of comedonecrosis were independently associated with DCIS recurrence., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Breast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices., Methods: We integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression., Results: ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72-0.76. The enriched pathways were immune regulation and cell-cell signaling. EGFR serves as the hub gene for the protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3., Conclusion: Prognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms., (© 2024. The Author(s).)

Purpose: CD133, a cancer stem cells (CSC) marker, has been reported to be associated with treatment resistance and worse survival in triple-negative breast cancer (BC). However, the clinical relevance of CD133 expression in ER-positive/HER2-negative (ER + /HER2-) BC, the most abundant subtype, remains unknown., Methods: The BC cohorts from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1904) and The Cancer Genome Atlas (TCGA, n = 1065) were used to obtain biological variables and gene expression data., Results: Epithelial cells were the exclusive source of CD133 gene expression in a bulk BC. CD133-high ER + /HER2- BC was associated with CD24, NOTCH1, DLL1, and ALDH1A1 gene expressions, as well as with WNT/β-Catenin, Hedgehog, and Notch signaling pathways, all characteristic for CSC. Consistent with a CSC phenotype, CD133-low BC was enriched with gene sets related to cell proliferation, such as G2M Checkpoint, MYC Targets V1, E2F Targets, and Ki67 gene expression. CD133-low BC was also linked with enrichment of genes related to DNA repair, such as BRCA1, E2F1, E2F4, CDK1/2. On the other hand, CD133-high tumors had proinflammatory microenvironment, higher activity of immune cells, and higher expression of genes related to inflammation and immune response. Finally, CD133-high tumors had better pathological complete response after neoadjuvant chemotherapy in GSE25066 cohort and better disease-free survival and overall survival in both TCGA and METABRIC cohorts., Conclusion: CD133-high ER + /HER2- BC was associated with CSC phenotype such as less cell proliferation and DNA repair, but also with enhanced inflammation, better response to neoadjuvant chemotherapy and better prognosis., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Natural killer (NK) cells play crucial roles in mediating anti-cancer activity in breast cancer (BRCA). However, the potential of NK cell-related molecules in predicting BRCA outcomes and guiding personalized therapy remains largely unexplored. This study focused on developing a prognostic and therapeutic prediction model for BRCA by incorporating NK cell-related genes., Methods: The data analyzed primarily originated from the TCGA and GEO databases. The prognostic role of NK cells was evaluated, and marker genes of NK cells were identified via single-cell analysis. Module genes closely associated with immunotherapy resistance were identified by bulk transcriptome-based weighted correlation network analysis (WGCNA). Following taking intersection and LASSO regression, NK-related genes (NKRGs) relevant to BRCA prognosis were screened, and the NK-related prognostic signature was subsequently constructed. Analyses were further expanded to clinicopathological relevance, GSEA, tumor microenvironment (TME) analysis, immune function, immunotherapy responsiveness, and chemotherapeutics. Key NKRGs were screened by machine learning and validated by spatial transcriptomics (ST) and immunohistochemistry (IHC)., Results: Tumor-infiltrating NK cells are a favorable prognostic factor in BRCA. By combining scRNA-seq and bulk transcriptomic analyses, we identified 7 NK-related prognostic NKRGs (CCL5, EFHD2, KLRB1, C1S, SOCS3, IRF1, and CCND2) and developed an NK-related risk scoring (NKRS) system. The prognostic reliability of NKRS was verified through survival and clinical relevance analyses across multiple cohorts. NKRS also demonstrated robust predictive power in various aspects, including TME landscape, immune functions, immunotherapy responses, and chemotherapeutic sensitivity. Additionally, KLRB1 and CCND2 emerged as key prognostic NKRGs identified through machine learning and external validation, with their expression correlation with NK cells confirmed in BRCA specimens by ST and IHC., Conclusions: We developed a novel NK-related gene signature that has proven valuable for evaluating prognosis and treatment response in BRCA, expecting to advance precision medicine of BRCA., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hou, Li, Chong, Yin, Guo, Yang, Li and Yin.)

Aims: The immune checkpoint marker, Programmed cell death-ligand 1 (PD-L1), is expressed by both cancer epithelial cells and tumour-infiltrating immune cells (TICs) thus constituting a potential target for immunotherapy. This is of particular interest in triple negative breast cancer. In this study, we assessed the prognostic value of PD-L1 expression in tumour epithelial cells and TICs in a series of patients with breast cancer with long-term follow-up, and associations between PD-L1 expression and histopathological type and grade, proliferation and molecular subtype., Methods: Using immunohistochemistry for PD-L1 in tissue microarrays, we assessed PD-L1 expression in 821 tumours. Expression of PD-L1 was assessed separately in the epithelial and stromal compartments and classified as <1%, ≥1% to <10% or ≥10% positive staining cells. We correlated PD-L1 expression in tumour epithelial cells and TICs with tumour characteristics using Pearson's χ 2 test, and prognosis by cumulative incidence of death from breast cancer and Cox regression analyses., Results: We found membranous staining in ≥1% of tumour epithelial cells in 53/821 cases (6.5%). Of these, 21 (2.6%) were ≥10%. Among TICs, staining (≥1%) was seen in 144/821 cases (17.6%). Of these, 62 were ≥10% (7.6%). PD-L1 was associated with high histopathological grade and proliferation, and the medullary and metaplastic patterns. In TICs, PD-L1 ≥1% found in 22/34 (34.4%) human epidermal growth factor receptor 2 type and 29/58 (50%) basal phenotype. An independent association between PD-L1 expression and prognosis was not observed., Conclusions: PD-L1 is expressed more frequently in TICs than tumour epithelial cells. Expression in TICs is associated with aggressive tumour characteristics and non-luminal tumours but not with prognosis., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Breast cancer (BC) remains a significant health issue globally and most common cause of mortality in women. Enhancing our understanding on biomarkers may greatly improve both diagnostic and therapeutic approaches to this disease., Methods: We retrospectively assessed tumor samples from 228 BC cases and 51 normal samples, alongside relevant clinical data. Neuronal vesicle trafficking associated 2(NSG2) expression was evaluated through bioinformatics and multiplex immunohistochemistry. Associations between NSG2 expression, tumor-infiltrating immune cells (TIICs), immune checkpoints, and clinical outcomes were investigated., Results: NSG2 was present in both breast cancer cells and adjacent stromal cells. Increased NSG2 expression in cancer cells correlated with greater tumor size, distant metastasis, and more advanced clinical stages. Kaplan-Meier survival and multivariate analyses identified NSG2 expression in both cancer and stromal cells as an independent prognostic factor for breast cancer survival. Elevated NSG2 levels both in cancer and stroma cells were linked to increased CD4+ T, CD8+ T, and Lamp3+ dendritic cells infiltration in stromal regions ( P < 0.05). Conversely, the expression of NSG2 in the stroma was negatively correlated with CD20+ B cells ( P < 0.05). Additionally, NSG2 expression was found to be associated with CTLA-4 levels ( P < 0.05)., Conclusion: NSG2 seems to be a significant component of the BC immune microenvironment and may serve as an important prognostic marker., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Gu, Sun, Yang, Zhang, Lu and Ni.)

Background: Breast cancer (BC) is the most common cancer among women globally and poses the leading health threat to women worldwide, with persistently high incidence rates. Mitophagy is a selective autophagy process that specifically targets mitochondria within the cell, maintaining cellular energy balance and metabolic health by identifying and degrading damaged mitochondria. Although there is an understanding of the relationship between mitophagy and cancer, the specific mechanisms remain unclear due to the complexity and diversity of mitophagy, suggesting that it could be an effective and more targeted therapeutic approach for BC. Methods: In this study, we meticulously examined the BC expression and clinical pathology data from The Cancer Genome Atlas (TCGA) to assess the expression profiles, copy number variations (CNV), and to investigate the correlation, function, and prognostic impact of 34 mitophagy-related genes (MRGs). Differentially expressed genes (DEGs) were identified based on group classification. Lasso and Cox regression were used to determine prognostic genes for constructing a nomogram. Single-cell analysis mapped the distribution of these genes in BC cells. Additionally, the association between gene-derived risk scores and factors such as immune infiltration, tumor mutational burden (TMB), cancer stem cell (CSC) index, and drug responses was studied. In vitro experiments were conducted to confirm the analyses. Results: We included 34 MRGs and subsequently generated a risk score for 7 genes, including RPLP2, PCDHGA2, PRKAA2, CLIC6, FLT3, CHI3L1, and IYD. It was found that the low-risk group had better overall survival (OS) in BC, higher immune scores, but lower tumor mutational burden (TMB) and cancer stem cell (CSC) index, as well as lower IC50 values for commonly used drugs. To enhance clinical applicability, age and staging were incorporated into the risk score, and a more comprehensive nomogram was constructed to predict OS. This nomogram was validated and showed good predictive performance, with area under the curve (AUC) values for 1-year, 3-year, and 5-year OS of 0.895, 0.765, and 0.728, respectively. Conclusion: Our findings underscore the profound impact of prognostic genes on the immune response and prognostic outcomes in BC, indicating that they can provide new avenues for personalized BC treatment and potentially improve clinical outcomes., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Background: Bidirectional crosstalk between HER2 and estrogen receptor (ER) pathways may influence outcomes and the efficacy of endocrine therapy (ET). Low HER2 expression levels (HER2-low) have emerged as a predictive biomarker in patients with breast cancer (BC)., Methods: PALLAS is an open, international, phase 3 study evaluating the addition of palbociclib for 2 years to adjuvant ET in patients with stage II-III ER-positive/HER2-negative BC. To assess the impact of HER2 expression on patient outcomes in the phase III PALLAS trial, we analyzed (1) the association between rate of HER2-low with demographic and clinicopathological parameters, (2) the prognostic value of HER2-low status on invasive disease-free survival (iDFS), distant relapse-free survival (DRFS), and overall survival (OS) and (3) HER2 expression's value as a predictive biomarker of response to palbociclib. HER2-low was defined as HER2 immunohistochemistry (IHC) 1 + or IHC 2 + with negative in situ hybridization (ISH). All pathologic evaluation was performed locally. Prognostic and predictive power of HER2 were assessed with Cox models., Results: From the original PALLAS intention-to-treat population (N = 5753), 5304 patients (92.2%) were included in this analysis. Among these, 2254 patients (42.5%) were classified as having HER2 IHC 0 (HER2-0), and 3050 (57.5%) as having HER2-low disease (1838 with IHC 1 + and 1212 with IHC 2 +). Median follow-up was 59.8 months. HER2-low prevalence varied significantly across 21 participating countries (range 16.7% to 75.6%; p < 0.001) and was more frequent in patients enrolled in North America (63.1%) than in Europe (53.4%) or other regions (53.4%) (p < 0.001). HER2 status was not significantly associated with iDFS in a multivariable Cox model (hazard ratio 0.93, 95% confidence interval 0.81 - 1.06). No significant interaction was observed between treatment arm and HER2 status for iDFS (p = 0.43). Similar results were obtained for DRFS and OS., Conclusions: In this large, prospective, global patient cohort, no differences were observed in clinical parameters, prognosis, or differential benefit from palbociclib between HER2-0 and HER2-low tumors. Significant geographic variability was observed in the prevalence of HER2-low status, suggesting a high degree of variation in pathologic assessment of HER2 expression without impact on outcomes., (© 2024. The Author(s).)

Background: Breast cancer is a heterogeneous condition with variations in histopathological, genomic, and biological characteristics. Although clinicopathological prognostic factors and gene expression profiles are commonly used to guide treatment decisions in patients with breast cancer, there is still a need for new prognostic markers. One potential marker is survivin, a protein belonging to the apoptosis inhibitor family. However, studies examining the relationship between survivin and prognosis in breast cancer have yielded inconsistent results. This study aimed to evaluate the impact of survivin expression on the prognosis of breast cancer patients through a meta-analysis., Methods: Studies evaluating survivin expression were sourced from the PubMed, Embase, and Cochrane databases. We conducted a meta-analysis based on full-text articles that evaluated the relationship between survivin expression and survival by immunochemistry or polymerase chain reaction. The studies were initially divided into 2 groups based on the evaluation of overall survival (OS) and disease-free survival (DFS). Subsequently, each group was further categorized according to the method used to detect survivin expression. Statistical analyses for this study were conducted using Stata and JAMOVI., Results: After screening with keywords, we identified 24 retrospective studies evaluating OS and 15 retrospective studies evaluating DFS, which were included in the analysis. We found that the studies in the meta-analysis were not heterogeneous, and this remained consistent when categorizing the groups by survivin expression detection. Survivin expression was associated with OS (HR 1.23, 95% CI 0.81-1.65) and DFS (HR 0.89, CI 0.42-1.36), indicating poor prognosis. This significant relationship between survivin expression and survival persisted when the studies were categorized by the detection method, either immunohistochemistry or polymerase chain reaction., Conclusion: In this study, we evaluated the prognostic significance of survivin expression in patients with breast cancer through a meta-analysis. These results support the use of survivin expression as a prognostic marker in breast cancer, potentially guiding treatment decisions., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Histone H1 (H.H1) is involved in chromatin organisation and gene regulation and is overexpressed in many malignant tumours, including breast cancer (BC). This study proposed and evaluated the prognostic role of H.H1 expression in BC. H.H1 mRNA expression was evaluated in publicly available BC dataset bc-GenExMiner database (n=4421). H.H1 protein expression was assessed immunohistochemically in a well-characterised early-stage BC cohort (n=1311), and associations with clinicopathological data and survival outcomes were evaluated. At the mRNA level, there was a significant association between high H.H1 mRNA and basal-like BC subtype and with poor outcome. The association with shorter survival was observed in the whole cohort and in the basal-like class. H.H1 protein expression was detected in both tumour cells and surrounding stroma. Total expression was detected in 72% of the cases, including 28% in tumour cell nuclei and 44% in the stroma. There was strong association between high tumour H.H1 expression and triple-negative BC (TNBC) subtype (p=0.007) and with shorter survival (p=0.019), independent of other variables including tumour size, histologic tumour grade, and lymph node status. H.H1 expression is associated with poor prognosis in BC. Given poor prognostic role of H.H1 in TNBC, it may represent a potential therapeutic target for patients with this aggressive disease., (Crown Copyright © 2024. Published by Elsevier B.V. All rights reserved.)

Background: Breast cancer remains a leading cause of female mortality worldwide, exacerbated by limited awareness, inadequate screening resources, and treatment options. Accurate and early diagnosis is crucial for improving survival rates and effective treatment., Objectives: This study aims to develop an innovative artificial intelligence (AI) based model for predicting breast cancer and its various histopathological grades by integrating multiple biomarkers and subject age, thereby enhancing diagnostic accuracy and prognostication., Methods: A novel ensemble-based machine learning (ML) framework has been introduced that integrates three distinct biomarkers-beta-human chorionic gonadotropin (β-hCG), Programmed Cell Death Ligand 1 (PD-L1), and alpha-fetoprotein (AFP)-alongside subject age. Hyperparameter optimization was performed using the Particle Swarm Optimization (PSO) algorithm, and minority oversampling techniques were employed to mitigate overfitting. The model's performance was validated through rigorous five-fold cross-validation., Results: The proposed model demonstrated superior performance, achieving a 97.93% accuracy and a 98.06% F1-score on meticulously labeled test data across diverse age groups. Comparative analysis showed that the model outperforms state-of-the-art approaches, highlighting its robustness and generalizability., Conclusion: By providing a comprehensive analysis of multiple biomarkers and effectively predicting tumor grades, this study offers a significant advancement in breast cancer screening, particularly in regions with limited medical resources. The proposed framework has the potential to reduce breast cancer mortality rates and improve early intervention and personalized treatment strategies., Competing Interests: Declaration of competing interest The authors state that the study provided in the paper was not impacted by any known competing financial or interpersonal interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

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 establish the 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., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The treatment landscape for HR(+)HER2(-) metastatic breast cancer (MBC) is evolving for patients with ESR1 mutations (mut) and PI3K/AKT pathway genomic alterations (GA). We sought to inform clinical utility for comprehensive genomic profiling (CGP) using tissue (TBx) and liquid biopsies (LBx) in HR(+)HER2(-) MBC., Methods: Records from a de-identified breast cancer clinicogenomic database for patients who underwent TBx/LBx testing at Foundation Medicine during routine clinical care at ~ 280 US cancer clinics between 01/2011 and 09/2023 were assessed. GA prevalence [ESR1mut, PIK3CAmut, AKT1mut, PTENmut, and PTEN homozygous copy loss (PTENloss)] were calculated in TBx and LBx [stratified by ctDNA tumor fraction (TF)] during the first three lines of therapy. Real-world progression-free survival (rwPFS) and overall survival (rwOS) were compared between groups by Cox models adjusted for prognostic factors., Results:  ~ 60% of cases harbored 1 + GA in 1st-line TBx (1266/2154) or LBx TF ≥ 1% (80/126) and 26.5% (43/162) in LBx TF < 1%. ESR1mut was found in 8.1% TBx, 17.5% LBx TF ≥ 1%, and 4.9% LBx TF < 1% in 1st line, increasing to 59% in 3rd line (LBx TF ≥ 1%). PTENloss was detected at higher rates in TBx (4.3%) than LBx (1% in TF ≥ 1%). Patients receiving 1st-line aromatase inhibitor + CDK4/6 inhibitor (n = 573) with ESR1mut had less favorable rwPFS and rwOS versus ESR1 wild-type; no differences were observed for fulvestrant + CDK4/6 inhibitor (n = 348)., Conclusion: Our study suggests obtaining TBx for CGP at time of de novo/recurrent diagnosis, followed by LBx for detecting acquired GA in 2nd + lines. Reflex TBx should be considered when ctDNA TF < 1%., (© 2024. The Author(s).)

Invasive lobular carcinomas (ILC) are characterized by the loss of E-cadherin expression and CDH1 gene inactivation. Diagnostic reproducibility for this tumor type is currently suboptimal and could be improved by a better understanding of its histomolecular and clinical heterogeneity. We have analyzed the relationship between the presence, type, or position of CDH1 mutations, E-cadherin expression, and clinicopathological features (including outcome) in a retrospective series of 251 primary ILC with a long follow-up (median: 9.5 years). The mutational status of E-cadherin gene (CDH1) was determined by RNA sequencing from frozen tumor samples. E-cadherin immunohistochemistry (IHC) was performed with antibodies directed against the intracellular domain (clone 4A2C7) and the extracellular domain (clone NCH38). IHC expression of p120 and β-catenin was also assessed in E-cadherin diffusely positive cases. Three major patterns of E-cadherin membrane expression were identified by IHC, with good agreement between the 2 clones (overall concordance: 83.8%, Kappa 0.67): null/focal expression (≤10%) (72.8% of cases for 4A2C7 and 83.8% for NCH38), heterogeneous expression (11%-89%) (19.2% of cases for 4A2C7 and 6.9% for NCH38), and diffuse expression (≥90%) (8% of cases for 4A2C7 and 9.3% for NCH38). E-cadherin membranous expression, when present, was abnormal (incomplete labeling and/or reduced intensity). ILC with diffuse E-cadherin expression showed abnormal β-catenin or p120-catenin staining in 21% of cases. Interestingly, these cases with diffusely expressed E-cadherin had a CDH1 mutation rate as high as the E-cadherin null/focal cases (∼70%) but were enriched in nontruncating mutations. Regarding CDH1 mutation location, intracytoplasmic domain mutations correlated with a divergent E-cadherin IHC phenotype between the 2 antibodies (4A2C7 ≤ 10%/NCH38 ≥ 10%). Clinico-pathological correlation analyses found that stromal amount (inversely correlated with tumor cellularity) and tumor-infiltrating lymphocytes were less abundant in ILC with E-cadherin null/focal cases. In addition, CDH1 truncating mutations were associated with radiohistologic size discordance and were identified in multivariate survival analysis as an independent poor prognosis factor in terms of metastasis risk and breast cancer-related mortality. Overall, our study highlights the importance of the precise mutational status of CDH1 in the clinical, radiological, histologic, and phenotypic expression of lobular carcinomas. These findings should be taken into account in future attempts to improve diagnostic criteria or methods for ILC, as well as for clinicobiological studies dedicated to this tumor type., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Cytokeratin 15 (CK15) has been described as a stem cell marker in human organs and its expression is seen in breast tissue. CK15 expression is associated with aggressive features in endometrial and oesophageal cancers, but data on the breast are lacking. This study aims to investigate the clinicopathological associations and prognostic significance of CK15 in breast carcinomas. A multi-institute cohort of breast carcinomas were retrieved. Clinicopathological and outcome data were obtained and compared with immunohistochemical expression CK15 and a panel of biomarkers. In total, 1,476 cases were included, with an expression rate of 3.5%, preferentially expressed in luminal subtypes (p=0.024), with luminal B carcinomas being the highest (4.7%), as opposed to basal-like (1%) and HER2-overexpressed carcinomas (0%). Except for nodal stage (p=0.013) and nodal metastasis (p=0.048), oestrogen (p=0.035) and progesterone receptor (p=0.001) positivity, there were no associations with other clinicopathological parameters. A trend was observed with shorter breast cancer specific survival (BCSS) in CK15-positive luminal B carcinomas (p=0.062). On further subgroup multivariate analysis of luminal B HER2-negative carcinomas, CK15 expression exhibited robust correlation with shorter BCSS (HR=9.004, p=0.001) and disease-free survival (HR=7.085, p<0.001). Restricted to luminal breast carcinomas, specifically luminal B HER2-negative, CK15 is demonstrated to be a robust independent predictor of higher risk of recurrence and shorter survival, with potential as a clinical prognostic marker and an exclusive stem cell marker for this subgroup of carcinomas., (Copyright © 2024 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.)

Background: This study aims to analyze potential differences in clinicopathology, efficacy of neoadjuvant therapy (NAT), and clinical outcome among HER2-null, HER2-ultralow and HER2-low breast cancers., Methods: Consecutive cases of HER2-negative breast cancer that received NAT were included. They were classified as HER2-null (no staining), HER2-ultralow (incomplete faint staining in ≤ 10% of tumour cells) and HER2-low (HER2-1 + or HER2-2+, in situ hybridisation negative). Subgroup analysis was performed based on the HER2 expression level., Results: Out of 302 patients, 215 (71.19%) were HER2-low, 59 (19.54%) were HER2-ultralow, and 28 (9.27%) were HER2-null. In comparison to the HER2-ultralow group, the HER2-low group exhibited higher expression frequencies of ER (p < 0.001), PR (p < 0.001), and AR (p = 0.004), along with a greater prevalence of the luminal subtype (p < 0.001). The HER2-ultralow group also demonstrated a higher prevalence of lymph node metastasis compared to the HER2-null group (p = 0.026). Varied rates of pathologic complete response (pCR) were observed among the three subgroups: HER2-null, HER2-ultralow, and HER2-low, with rates of 35.71%, 22.03%, and 12.56%, respectively. Only the HER2-low subgroup exhibited a significant difference compared to HER2-null (p = 0.001). Despite variations in pCR rates, the three subgroups exhibited comparable disease-free survival (DFS) (p = 0.571). Importantly, we found HER2-low patients with better treatment response (RCB-0/I) exhibited significantly better DFS than those with significant residual disease (RCB-II/III) (P = 0.036). The overall rate of HER2 immunohistochemical score discordance was 45.24%, mostly driven by the conversion between HER2-0 and HER2-low phenotype. Notably, 32.19% of cases initially classified as HER2-0 phenotype on baseline biopsy were later reclassified as HER2-low after neoadjuvant therapy, and it is noteworthy that 22 out of these cases (78.57%) originally had an HER2-ultralow status in the pretreatment biopsy sample., Conclusions: Our results demonstrate the distinct clinicopathological features of HER2-low and HER2-ultralow breast tumors and confirm that RCB is an effective predictor of prognosis in HER2-low populations for the first time. Notably, our findings demonstrate high instability in both HER2-low and HER2-ultralow expression from the primary baseline biopsy to residual disease after NAT. Furthermore, this study is the first to investigate the clinicopathological feature and the effectiveness of NAT for HER2-ultralow breast cancer., (© 2024. The Author(s).)

Background: Breast cancer (BC) constitutes a significant peril to global women's health. Contemporary research progressively suggests that mitochondrial dysfunction plays a pivotal role in both the inception and advancement of BC. However, investigations delving into the correlation between mitochondrial-related genes (MRGs) and the prognosis and metastasis of BC are still infrequent., Methods: Utilizing data from the TCGA database, we employed the "limma" R package for differential expression analysis. Subsequently, both univariate and multivariate Cox regression analyses were executed, alongside LASSO Cox regression analysis, to pinpoint prognostic MRGs and to further develop the prognostic model. External validation (GSE88770 merged GSE425680) and internal validation were further conducted. Our investigation delved into a broad spectrum of analyses that included functional enrichment, metabolic and immune characteristics, immunotherapy response prediction, intratumor heterogeneity (ITH), mutation, tumor mutational burden (TMB), microsatellite instability (MSI), cellular stemness, single-cell, and drug sensitivity analysis. We validated the protein and mRNA expressions of prognostic MRGs in tissues and cell lines through immunohistochemistry and qRT-PCR. Moreover, leveraging the GSE102484 dataset, we conducted differential gene expression analysis to identify MRGs related to metastasis, subsequently developing metastasis models via 10 distinct machine-learning algorithms and then selecting the best-performing model. The division between training and validation cohorts was set at 70% and 30%, respectively., Results: A prognostic model was constructed by 9 prognostic MRGs, which were DCTPP1, FEZ1, KMO, NME3, CCR7, ISOC2, STAR, COMTD1, and ESR2. Patients within the high-risk group experienced more adverse outcomes than their counterparts in the low-risk group. The ROC curves and constructed nomogram showed that the model exhibited an excellent ability to predict overall survival (OS) for patients and the risk score was identified as an independent prognostic factor. The functional enrichment analysis showed a strong correlation between metabolic progression and MRGs. Additional research revealed that the discrepancies in outcomes between the two risk categories may be attributed to a variety of metabolic and immune characteristics, as well as differences in intratumor heterogeneity (ITH), tumor mutational burden (TMB), and cancer stemness indices. ITH, TIDE, and IPS analyses suggested that patients possessing a low-risk score may exhibit enhanced responsiveness to immunotherapy. Additionally, distant metastasis models were established by PDK4, NRF1, DCAF8, CHPT1, MARS2 and NAMPT. Among these, the XGBoost model showed the best predicting ability., Conclusion: In conclusion, MRGs significantly influence the prognosis and metastasis of BC. The development of dual clinical prediction models offers crucial insights for tailored and precise therapeutic strategies, and paves the way for exploring new avenues in understanding the pathogenesis of BC., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Fang, Zhang, Guo, Zheng, Liu, Zhang and Wu.)

Background: Breast cancer (BC) is the most common cancer in women, and its progression is closely related to the phenomenon of anoikis. Anoikis, the specific programmed death resulting from a lack of contact between cells and the extracellular matrix, has recently been recognized as playing a critical role in tumor initiation, maintenance, and treatment. The ability of cancer cells to resist anoikis leads to cancer progression and metastatic colonization. However, the impact of anoikis on the prognosis of BC patients remains unclear., Method: This study utilized data from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to collect transcriptome and clinical data of BC patients. Anoikis-related genes (ARGs) were classified into subtypes A and B through consensus clustering. Subsequently, survival prognosis analysis, immune cell infiltration analysis, and functional enrichment analysis were performed for both subtypes. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a set of 10 ARGs related to prognosis was identified. Immune cell infiltration and tumor microenvironment analyses were conducted on these 10 ARGs to develop a prognostic model. Furthermore, single-cell data analysis and real-time polymerase chain reaction (RT-PCR) analysis were employed to study the expression of the 10 identified prognostic ARGs in BC cells., Results: One hundred thirty-five ARGs were identified as differentially expressed genes in the TCGA and GEO databases, with 42 of them associated with the survival prognosis of BC patients. Analyses involving Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP) revealed distinct expression patterns of ARGs between types A and B. Patients in type A exhibited worse survival prognosis and lower immune cell infiltration compared to type B. Subsequent analyses identified 10 key ARGs (YAP1, PIK3R1, BAK1, PHLDA2, EDA2R, LAMB3, CD24, SLC2A1, CDC25C, and SLC39A6) relevant to BC prognosis. Kaplan-Meier analysis indicated that high-risk patients based on these ARGs had a poorer BC prognosis. Additionally, Cox regression analysis established gender, age, T (tumor), N (nodes), and risk score as predictive factors in a nomogram model for BC. The model demonstrated diagnostic value for BC patients at 1, 3, and 5 years. Decision curve analysis (DCA) verified the risk score as a reliable predictor of BC patient survival rates. Moreover, RT-PCR results confirmed differential expressions of YAP1, PIK3R1, BAK1, PHLDA2, CD24, SLC2A1, and CDC25C in BC cells, with SLC39A6, EDA2R, and LAMB3 showing low expression levels., Conclusion: ARGs markers can be used as BC biomarkers for risk stratification and survival prediction in BC patients. Besides, ARGs can be used as stratification factors for individualized and precise treatment of BC patients., (© 2024. The Author(s).)

Background: Despite evidence indicating the dominance of cell-of-origin signatures in molecular tumor patterns, translating these genome-wide patterns into actionable insights has been challenging. This study introduces breast cancer cell-of-origin signatures that offer significant prognostic value across all breast cancer subtypes and various clinical cohorts, compared to previously developed genomic signatures., Methods: We previously reported that triple hormone receptor (THR) co-expression patterns of androgen (AR), estrogen (ER), and vitamin D (VDR) receptors are maintained at the protein level in human breast cancers. Here, we developed corresponding mRNA signatures (THR-50 and THR-70) based on these patterns to categorize breast tumors by their THR expression levels. The THR mRNA signatures were evaluated across 56 breast cancer datasets (5040 patients) using Kaplan-Meier survival analysis, Cox proportional hazard regression, and unsupervised clustering., Results: The THR signatures effectively predict both overall and progression-free survival across all evaluated datasets, independent of subtype, grade, or treatment status, suggesting improvement over existing prognostic signatures. Furthermore, they delineate three distinct ER-positive breast cancer subtypes with significant survival in differences-expanding on the conventional two subtypes. Additionally, coupling THR-70 with an immune signature identifies a predominantly ER-negative breast cancer subgroup with a highly favorable prognosis, comparable to ER-positive cases, as well as an ER-negative subgroup with notably poor outcome, characterized by a 15-fold shorter survival., Conclusions: The THR cell-of-origin signature introduces a novel dimension to breast cancer biology, potentially serving as a robust foundation for integrating additional prognostic biomarkers. These signatures offer utility as a prognostic index for stratifying existing breast cancer subtypes and for de novo classification of breast cancer cases. Moreover, THR signatures may also hold promise in predicting hormone treatment responses targeting AR and/or VDR., (© 2024. The Author(s).)

Background: The novel anti-HER2 antibody drug conjugates (ADCs) can effectively improve the long-term survival of patients with HER2-low expression breast cancer. However, pathological responses to neoadjuvant therapy (NAT) within HER2-low expression breast cancer, the relationship between pathological response and prognosis and the transformation of HER2 status are all now poorly understood., Methods: The patients with HER2-0 and HER2-low expression breast cancer receiving NAT at Harbin Medical University Cancer Hospital between Jan. 2014 and Nov. 2018 were retrospectively explored. HER2 low expression refers to the IHC 1 + or 2 + and FISH negative. The Kappa test was utilized for analyzing the consistency rate of HER2 expression. To evaluate disease-free survival (DFS) and overall survival (OS), this research employed both the Kaplan-Meier analysis and the Cox regression., Results: In this study, 178 patients with HER2-0 and 344 patients with HER2-low expression breast cancer were included. In comparison with the HER2-0 group, it is shown that patients in the HER2-low group have more possibility to be younger compared to those 50 years old (P < 0.014), have more premenopausal patients (P < 0.001), a higher proportion of hormone receptor (HR) positive patients (P < 0.001), and less proportion of stage III V patients (P < 0.034). When NAT was finished, the pCR rate became 23.6% in the HER2-0 group while 22.1% in the HER2-low group, and there was also a higher pCR rate in HR- patients in comparison with that in HR + patients (P < 0.01). Considering HER2 expression inconsistency, the overall HER2 inconsistency rate was 30.4% (Kappa = 0.431, P < 0.01). Among patients initially diagnosed as HER2-0, 34% (N = 61) were re-diagnosed as HER2-low after NAT. After stratification by HR expression status, HR+/HER2-0 patients transformed to HER2-low after NAT in 37%, and 32% of HR- patients changed from HER2-0 to HER2-low. In this survival analysis, there were both better DFS rates (P = 0.009) and OS rates (P = 0.026) in the HR-/HER2-low patients in comparison with the HR-/HER2-0 patients, while the HER2-0 and HER2-low patients in the HR + group had no significant survival difference. Additionally, for non-pCR patients, there was better DFS (P = 0.029) and OS (P = 0.038) in the HER2-low group in comparison with that of the HER2-0 group, while no significant survival difference exists between pCR patients., Conclusion: After HR stratification, there are unique clinical characteristics and prognostic outcomes in HER2-low expression breast cancer, which indicates the potential to become a specific molecular subtype of breast cancer. The significant instability of HER2-low expression status between primary tumor and residual invasive disease suggests that multiple detections of HER2 status should be emphasized in NAT strategies., (© 2024. The Author(s).)

Background: Telomeres are a critical component of chromosome integrity and are essential to the development of cancer and cellular senescence. The regulation of breast cancer by telomere-associated lncRNAs is not fully known, though. The goals of this study were to describe predictive telomere-related LncRNAs (TRL) in breast cancer and look into any possible biological roles for these RNAs., Methods: We obtained RNA-seq data, pertinent clinical data, and a list of telomere-associated genes from the cancer genome atlas and telomere gene database, respectively. We subjected differentially expressed TRLs to co-expression analysis and univariate Cox analysis to identify a prognostic TRL. Using LASSO regression analysis, we built a prognostic model with 14 TRLs. The accuracy of the model's prognostic predictions was evaluated through the utilization of Kaplan-Meier (K-M) analysis as well as receiver operating characteristic (ROC) curve analysis. Additionally, immunological infiltration and immune drug prediction were done using this model. Patients with breast cancer were divided into two subgroups using cluster analysis, with the latter analyzed further for variations in response to immunotherapy, immune infiltration, and overall survival, and finally, the expression of 14-LncRNAs was validated by RT-PCR., Results: We developed a risk model for the 14-TRL, and we used ROC curves to demonstrate how accurate the model is. The model may be a standalone prognostic predictor for patients with breast cancer, according to COX regression analysis. The immune infiltration and immunotherapy results indicated that the high-risk group had a low level of PD-1 sensitivity and a high number of macrophages infiltrating. In addition, we've discovered a number of small-molecule medicines with considerable for use in treating high-risk groups. The cluster 2 subtype showed the highest immune infiltration, the highest immune checkpoint expression, and the worst prognosis among the two subtypes defined by cluster analysis, which requires more attention and treatment., Conclusion: As a possible biomarker, the proposed 14-TRL signature could be utilized to evaluate clinical outcomes and treatment efficacy in breast cancer patients., (© 2024. The Author(s).)

Background: Neoadjuvant chemotherapy (NAC) is an effective treatment for locally advanced breast cancer (BC). However, there are no effective biomarkers for evaluating its efficacy. CDR1-AS, well known for its important role in tumorigenesis, is a famous circular RNA involved in the chemosensitivity of cancers other than BC. However, the predictive role of CDR1-AS in the efficacy and prognosis of NAC for BC has not been fully elucidated. We herein aimed to clarify this role., Methods: The present study included patients treated with paclitaxel-cisplatin-based NAC. The expression of CDR1-AS was detected by real-time quantitative reverse transcription polymerase chain reaction testing. The predictive value of CDR1-AS expression was examined in pathological complete response (pCR) after NAC using logistic regression analysis. The relationship between CDR1-AS expression and survival was demonstrated using the Kaplan-Meier method, and tested by log-rank test and Cox proportional hazards regression model., Results: The present study enrolled 106 patients with BC. Multivariate logistic regression analysis revealed that CDR1-AS expression was an independent predictive factor for pCR (odds ratio [OR] = 0.244; 95% confidence interval [CI] 0.081-0.732; p = 0.012). Furthermore, pCR benefits with low CDR1-AS expression were observed across all subgroups. The Kaplan-Meier curves and log-rank test suggested that the CDR1-AS high-expression group showed significantly better disease-free survival (DFS; log-rank p = 0.022) and relapse-free survival (RFS; log-rank p = 0.012) than the CDR1-AS low-expression group. Multivariate analysis revealed that CDR1-AS expression was an independent prognostic factor for DFS (adjusted HR = 0.177; 95% CI 0.034-0.928, p = 0.041), RFS (adjusted HR = 0.061; 95% CI 0.006-0.643, p = 0.020), and distant disease-free survival (adjusted HR = 0.061; 95% CI 0.006-0.972, p = 0.047)., Conclusions: CDR1-AS may be a potential novel predictive biomarker of pCR and survival benefit in patients with locally advanced BC receiving NAC. This may help identify specific chemosensitive individuals and build personalized treatment strategies., (© 2024. The Author(s).)

Objective: 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., Methods: 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., Results: 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., Conclusions: 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., Competing Interests: Declaration of conflicting interestThe authors declare that there is no conflict of interest.

Introduction: Hotspots (HS) mutations in the PIK3CA gene may lead to poorer oncological outcomes and endocrine resistance in advanced breast cancer (BC), but their prognostic role in early-stage disease remains controversial. The overall agreement within plasma and tissue methods has not been well explored. Our aim was to correlate tissue and plasma approaches and to analyze the prognostic impact of PIK3CA mutations (PIK3CAm) in HR+/HER2- BC., Methods: A retrospective and unicentric analysis of PIK3CA mutational status in tissue and plasma samples by Cobas®PIK3CA Mutation Kit in patients with HR+/HER2- BC., Results: We analyzed 225 samples from 161 patients with luminal BC. PIK3CA mutations were identified in 62 patients (38.5%), of which 39.6% were found in tissue and 11.8% in plasma. In advanced disease, plasma and tissue correlation rate was performed in 64 cases, with an overall agreement of 70.3%. Eighty patients were treated with CDK4/6 inhibitors + endocrine therapy. We observed a moderately worse progression-free survival (PFS) in PIK3CAm versus wild-type (WT) (24 m vs. 30 m; HR = 1.39, p = 0.26). A subanalysis was carried out based on exons 9 and 20, which showed a statistically poorer PFS in PIK3CAm exon 9 versus 20 population (9.7 m vs. 30.3 m; HR = 2.84; p = 0.024). Furthermore, detection of PIK3CAm in plasma was linked to a worse PFS vs PIK3CAm detection just in tissue (12.4 vs. 29.3; HR = 2.4; p = 0.08)., Conclusions: Our findings suggest the PIK3CA evaluation in tissue as the diagnostic method of choice, however, additional investigations are required to improve the role of liquid biopsy in the PIK3CA assessment. PIK3CAm show worse outcomes in advanced luminal BC, especially in exon 9 mutation carriers, despite visceral involvement, prior exposure to endocrine therapy or detection of PIK3CAm in plasma, with an unclear prognosis in early-stage disease. Nonetheless, this should be validated in a prospective cohort study., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

Aims: In this study, we validate the use of Nottingham Prognostic x (NPx), consisting of tumour size, tumour grade, progesterone receptor (PR) and Ki67 in luminal BC., Materials and Methods: Two large cohorts of luminal early-stage BC (n = 2864) were included. PR and Ki67 expression were assessed using full-face resection samples using immunohistochemistry. NPx was calculated and correlated with clinical variables and outcome, together with Oncotype DX recurrence score (RS), that is frequently used as a risk stratifier in luminal BC., Results: In the whole cohort, 38% of patients were classified as high risk using NPx which showed significant association with parameters characteristics of aggressive tumour behaviour and shorter survival (P < 0.0001). NPx classified the moderate Nottingham Prognostic Index (NPI) risk group (n = 1812) into two distinct prognostic subgroups. Of the 82% low-risk group, only 3.8% developed events. Contrasting this, 14% of the high-risk patients developed events during follow-up. A strong association was observed between NPx and Oncotype Dx RS (P < 0.0001), where 66% of patients with intermediate risk RS who had subsequent distant metastases also had a high-risk NPx., Conclusion: NPx is a reliable prognostic index in patients with luminal early-stage BC, and in selected patients may be used to guide adjuvant chemotherapy recommendations., (© 2024 The Author(s). Histopathology published by John Wiley & Sons Ltd.)

Purpose: In metastatic breast cancer, differences in expression patterns of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) between the primary tumor (PT) and metastatic site (MET) have been reported. However, there is limited understanding of the relationship of tumor subtype discordance and overall survival (OS). We evaluated patterns of ER/PR/HER2 in PTs and corresponding METs and assessed the relationship between these patterns and OS., Methods: Patients diagnosed at our center with metastatic breast cancer (2011-2020) were included. ER/PR were stratified as < 1%/1-10%/ > 10% by immunohistochemistry and HER2 as positive/negative by immunohistochemistry/FISH. Tumor subtypes were classified as ER or PR + /HER2-, HER2+ , or triple-negative. Biomarker discordance data from PTs to METs were analyzed for expression patterns. OS was assessed., Results: Of 254 patients, 41 (16.1%) had synchronous and 213 (83.9%) had metachronous METs. Category change of ER/PR/HER2 expression was observed in 56 (22.0%), 117 (40.5%), and 30 (11.8%) patients, respectively. Tumor subtype changed in 56 (22.0%) patients. We identified a difference between PT and MET from ER > 10% to ER < 1% (n = 28,16.2% p < 0.01); PR > 10% to PR < 1% (n = 54,48.2%, p < 0.001); PR > 10% to PR 1-10% (n = 18,16.1%, p < 0.001), and ER or PR+/HER2- to triple-negative (n = 19,13.0%, p = 0.03). In log-rank analysis, change from an ER or PR+/HER2- (5-year OS 88.6%) PT to a HER2+(67.5%) or triple-negative (54.6%) MET was associated with decreased survival (p < 0.01); however, in multivariate analysis, discordant biomarker expression was not associated with decreased survival (p > 0.05)., Conclusion: Tumor expression of ER/PR/HER2 can differ between the PT and MET. Loss of ER/PR expression is common and may be related to worse survival. Routine assessment of MET tumor markers could inform prognosis and therapeutic decision-making., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Adhesion G protein-coupled receptors (aGPCRs), a distinctive subset of the G protein-coupled receptor (GPCR) superfamily, play crucial roles in various physiological and pathological processes, with implications in tumor development. Despite the global prevalence of breast cancer (BRCA), specific aGPCRs as potential drug targets or biomarkers remain underexplored., Methods: UALCAN, GEPIA, Kaplan-Meier Plotter, MethSurv, cBiopportal, String, GeneMANIA, DAVID, Timer, Metascape, and qPCR were applied in this work., Results: Our analysis revealed significantly increased transcriptional levels of ADGRB2, ADGRC1, ADGRC2, ADGRC3, ADGRE1, ADGRF2, ADGRF4, and ADGRL1 in BRCA primary tumors. Further analysis indicated a significant correlation between the expressions of certain aGPCRs and the pathological stage of BRCA. High expression of ADGRA1, ADGRF2, ADGRF4, ADGRG1, ADGRG2, ADGRG4, ADGRG6, and ADGRG7 was significantly correlated with poor overall survival (OS) in BRCA patients. Additionally, high expression of ADGRF2 and ADGRF4 indicated inferior recurrence-free survival (RFS) in BRCA patients. The RT-qPCR experiments also confirmed that the mRNA levels of ADGRF2 and ADGRF4 were higher in BRCA cells and tissues. Functional analysis highlighted the diverse roles of aGPCRs, encompassing GPCR signaling and metabolic energy reserves. Moreover, aGPCRs may exert influence or actively participate in the development of BRCA through their impact on immune status., Conclusion: aGPCRs, particularly ADGRF2 and ADGRF4, hold promise as immunotherapeutic targets and prognostic biomarkers in BRCA., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background and Objective: Aurora kinase A (AURKA) is reported to be overexpressed in breast cancer. In addition to its role in regulating cell cycle and mitosis, studies have reported AURKA involvements in oncogenic signaling in suppressing BRCA1 and BRCA2. We aimed to characterize AURKA protein and mRNA expression in a breast cancer cohort of the young, investigating its relation to clinico-pathologic features and survival, and exploring age-related AURKA-associated biological processes., Methods: Aurora kinase A immunohistochemical staining was performed on tissue microarrays of primary tumors from an in-house breast cancer cohort (n = 355) with information on clinico-pathologic data, molecular markers, and long and complete follow-up. A subset of the in-house cohort (n = 127) was studied by the NanoString Breast Cancer 360 expression panel for exploration of mRNA expression. METABRIC cohorts < 50 years at breast cancer diagnosis (n = 368) were investigated for differentially expressed genes and enriched gene sets in AURKA mRNA high tumors stratified by age. Differentially expressed genes and gene sets were investigated using network analyses and g:Profiler., Results: High Aurora kinase A protein expression associated with aggressive clinico-pathologic features, a basal-like subtype, and high risk of recurrence score. These patterns were confirmed using mRNA data. High AURKA gene expression demonstrated independent prognostic value when adjusted for traditional clinico-pathologic features and molecular subtypes. Notably, high AURKA expression significantly associated with reduced disease-specific survival within patients below 50 years, also within the luminal A subtype. Tumors of high AURKA expression showed gene expression patterns reflecting increased DNA damage activation and higher BRCAness score., Conclusions: Our findings indicate higher AURKA expression in young breast cancer, and associations between high Aurora-A/AURKA and aggressive tumor features, including higher tumor cell proliferation, and shorter survival, in the young. Our findings point to AURKA as a marker for increased DNA damage and DNA repair deficiency and suggest AURKA as a biomarker of clinical relevance in young breast cancer., (© 2024. The Author(s).)

In many countries, hormone receptor status assessment of ductal carcinoma in situ (DCIS) is routinely performed, as hormone receptor-positive DCIS patients are eligible for adjuvant anti-hormonal treatment, aiming to reduce the ipsilateral and contralateral breast cancer risk. Although HER2 gene amplification and its associated HER2 protein overexpression constitute a major prognostic and predictive marker in invasive breast carcinoma, its use in the diagnosis and treatment of DCIS is less straightforward. HER2 immunohistochemistry is not routinely performed yet, as the role of HER2-positivity in DCIS biology is unclear. Nonetheless, recent data challenge this practice. Here, we discuss the value of routine HER2 assessment for DCIS. HER2-positivity correlates strongly with DCIS grade: around four in five HER2-positive DCIS show high grade atypia. As morphological DCIS grading is prone to interobserver variability, HER2 immunohistochemistry could render grading more robust. Several studies showed an association between HER2-positive DCIS and ipsilateral recurrence risk, albeit currently unclear whether this is for overall, in situ or invasive recurrence. HER2-positive DCIS tends to be larger, with a higher risk of involved surgical margins. HER2-positive DCIS patients benefit more from adjuvant radiotherapy: it substantially decreases the local recurrence risk after lumpectomy, without impact on overall survival. HER2-positivity in pure biopsy-diagnosed DCIS is associated with increased upstaging to invasive carcinoma after surgery. HER2 immunohistochemistry on preoperative biopsies might therefore provide useful information to surgeons, favoring wider excisions. The time seems right to consider DCIS subtype-dependent treatment, comprising appropriate local treatment for HER2-positive DCIS patients and de-escalation for hormone receptor-positive, HER2-negative DCIS patients., (© 2024. The Author(s).)

Background: CLDN is a core component of tight junctions (TJs). Abnormal expressions of CLDNs are commonly detected in various types of tumors. CLDNs are of interest as a potential therapeutic target. CLDNs are closely associated with most cancers of epithelial origin, especially when CLDN7 promotes cancer cell metastasis, such as in gastric, cervical, and ovarian cancers.Its expression and prognosis in breast cancer (BC) remain unknown.The purpose of this study was to investigate the expression pattern of CLDN7 and related immune factors in BC and shed light on a better therapeutic avenue for BC patients., Method: The cBioPortal, GEPIA, and TCGA databases were used to comprehensively assess the expression of CLDN7 in BC. The Kaplan-Meier Plotter (KMP) database was applied to examine the relationship among the CLDN7 overexpression (OE), prognosis, and overall survival (OS) of BC patients. Immunohistochemical staining was performed on 92 BC tissue samples and 20 benign breast tumors to verify the expression level of CLDN-7 protein and its correlation with clinicopathological features and prognosis. TIMER2.0 was used to analyze the correlation between the CLDN7 OE and immune gene activation using BC-related transcriptomic data. Enrichment analyses of CLDN7-related immune pathways were conducted using online databases. The risk of expression of CLDN7-related immune genes was assessed and differentially expressed (DE) genes were included in the construction of the risk prognosis nomogram., Results: Both database analysis and clinical sample validation results showed that CLDN7 was significantly overexpressed (OE) in BC, and the OE was correlated with poor DFS in BC patients (p < 0.05). TIMER2.0 analysis indicated that CLDN7 OE was negatively associated with the activation of B-cells, CD4 + T-cells, and CD8 + T-cells but positively with the M 0 macrophages. Pathway enrichment analysis suggested that CLDN7-related immune factors were mostly involved in the NF-κB and T-cell receptor (TCR) signaling pathways. Univariate Cox regression was used to analyze the correlation between 52 CLDN7 related genes and OS, and 22 genes that are related to prognosis were identified. Prognostic genes were included in the prognostic nomogram of BC with a C-index of 0.76 to predict the 3-year and 5-year OS probabilities of BC individuals., Conclusions: These findings provide evidence for the role of CLDN7-linked tumor immunity, suggesting that CLDN7 might be a potential immunotherapeutic target for BC, and its association with immune markers could shed light on the better prognosis of BC., (© 2024. The Author(s).)

CLEC6A, (C-type lectin domain family 6, member A), plays a prominent role in regulating innate immunity and adaptive immunity. CLEC6A has shown great potential as a target for cancer immunotherapy. This study aims to explore the prognostic value of CLEC6A, and analyze the relationship associated with the common hematological parameters in breast cancer patients. We performed a retrospective analysis on 183 breast cancer patients data in hospital information system from January 2013 to December 2015. The expression of CLEC6A was recorded via semiquantitative immunohistochemistry in breast cancer. The association between expression of CLEC6A and relative parameters were performed by Chi-square test and Fisher's exact test. Kaplan-Meier assay and Log-rank test were performed to evaluate the survival time. The Cox proportional hazards regression analysis was applied to identify prognostic factors. Nomograms were conducted to predict 1-, 3-, and 5-year disease free survival (DFS) and overall survival (OS) for breast cancer, which could be a good reference in clinical practice. The nomogram model was estimated by calibration curve analysis for its function of discrimination. The accuracy and benefit of the nomogram model were appraised by comparing it to only CLEC6A via decision curve analysis (DCA). The prediction accuracy of CLEC6A was also determined by time-dependent receiver operating characteristics (TDROC) curves, and the area under the curve (AUC) for different survival time. There were 94 cases in the CLEC6A low-expression group and 89 cases in CLEC6A high-expression group. Compared to CLEC6A low-expression group, the CLEC6A high-expression group had better survival (DFS: 56.95 vs. 70.81 months, P = 0.0078 and OS: 67.98 vs. 79.05 months, P = 0.0089). The CLEC6A was a potential prognostic factor in multivariate analysis (DFS: P = 0.023, hazard ratio (HR): 0.454, 95 % confidence interval (CI): 0.229-0.898; OS: P = 0.020, HR: 0.504, 95 %CI: 0.284-0.897). The nomogram in accordance with these potential prognostic factors was constructed to predict survival and the calibration curve analysis had indicated that the predicted line was well-matched with reference line in 1-, 3-, and 5-year DFS and OS category. The 1-, 3-, and 5-year DCA curves have revealed that nomogram model yielded larger net benefits than CLEC6A alone. Finally, the TDROC curve indicated that CLEC6A could better predict 1-year DFS and OS than others. Furthermore, we combined these potential independent prognostic factors to analyze the relationship among these hematologic index and oxidative stress indicators, and indicated that higher CLEC6A level, higher CO2 level or low CHOL level or high HDL-CHO level would have survived longer and better prognosis. In breast cancer, high expression of CLEC6A can independently predict better survival. Our nomogram consisted of CLEC6A and other indicators has good predictive performance and can facilitate clinical decision-making., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Early evaluation of tumor heterogeneity related to metastasis and outcomes is a major challenge in the management of advanced breast cancer (BCa) in the clinic. In this study, we introduced the value of baseline circulating tumor cells (CTC) and ctDNA for early differentiation of clinical stages, tumor heterogeneity, and prognosis in clinic., Experimental Design: A total of 292 patients with BCa were enrolled in this study, including 254 Stage IV and 38 Stage III patients, and examined the baseline levels of CTCs, CTC-clusters, and plasma ctDNA before initiating therapies. Outcomes including progression-free survival (PFS) and overall survival were evaluated using proportional hazards regression analysis., Results: The baseline CTCs, including HER2+ CTCs, in Stage IV patients were approximately 9.5 times higher than those detected in Stage III patients. Baseline CTC counts with a cutoff of 5 were significantly associated with the prognosis. Within each stage, patients with <5 CTCs had significantly longer PFS. Stage III patients with no CTCs exhibited the longest survival compared with patients with ≥1 CTC. CTC-clusters were only found in Stage IV patients, among whom 15 Stage IV patients with ≥5 CTC-clusters had the worst PFS compared with the 239 Stage IV patients with <5 CTC-clusters. Similar outcomes were observed in 28 out of 254 Stage IV patients who had at least one CTC-cluster detected, as these patients had shorter PFS compared with CTC-cluster negative group. The major differences in ctDNA mutations between patients with Stage III and Stage IV BCa were in PIK3CA and ESR1, which were associated with specific organ metastasis and worse outcomes., Conclusions: Assessing the baseline levels of CTCs, CTC-clusters, and mutational ctDNA profile could reliably aid in differentiation of clinical stage and early prediction of metastasis and outcomes in advanced BCa., (©2024 American Association for Cancer Research.)

Purpose: Quantification of Ki67 in breast cancer is a well-established prognostic and predictive marker, but inter-laboratory variability has hampered its clinical usefulness. This study compares the prognostic value and reproducibility of Ki67 scoring using four automated, digital image analysis (DIA) methods and two manual methods., Methods: The study cohort consisted of 367 patients diagnosed between 1990 and 2004, with hormone receptor positive, HER2 negative, lymph node negative breast cancer. Manual scoring of Ki67 was performed using predefined criteria. DIA Ki67 scoring was performed using QuPath and Visiopharm® platforms. Reproducibility was assessed by the intraclass correlation coefficient (ICC). ROC curve survival analysis identified optimal cutoff values in addition to recommendations by the International Ki67 Working Group and Norwegian Guidelines. Kaplan-Meier curves, log-rank test and Cox regression analysis assessed the association between Ki67 scoring and distant metastasis (DM) free survival., Results: The manual hotspot and global scoring methods showed good agreement when compared to their counterpart DIA methods (ICC > 0.780), and good to excellent agreement between different DIA hotspot scoring platforms (ICC 0.781-0.906). Different Ki67 cutoffs demonstrate significant DM-free survival (p < 0.05). DIA scoring had greater prognostic value for DM-free survival using a 14% cutoff (HR 3.054-4.077) than manual scoring (HR 2.012-2.056). The use of a single cutoff for all scoring methods affected the distribution of prediction outcomes (e.g. false positives and negatives)., Conclusion: This study demonstrates that DIA scoring of Ki67 is superior to manual methods, but further study is required to standardize automated, DIA scoring and definition of a clinical cut-off., (© 2024. The Author(s).)

Background: The tumor microenvironment (TME) plays a crucial role in various aspects of breast cancer development and metastasis. Nevertheless, the expression, prognostic significance, and correlation with clinical features of SCARB2 in breast cancer, as well as the infiltrative characteristics of TME, remain largely unknown., Methods: We analyzed the differential presentation of SCARB2 mRNA in breast cancer tissues and nontumorous breast tissues and prognosis by The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Additionally, the Tumor Immunity Estimation Resource (TIMER) was taken to evaluate the correlation between SCARB2 mRNA presence and tumor-infiltrating immune cells and immune checkpoints in the TME in breast cancer. We performed multiple immunohistochemical staining to verify the SCARB2 protein expression in breast cancer tissues and its relationship to immune cells and checkpoints and clinicopathological features., Results: We identified elevated SCARB2 expression in breast cancer tissues, and high SCARB2 protein presentation was associated with advanced clinical stage and unfavorable prognosis. In addition, enhanced SCARB2 protein presence was closely correlated with up-regulation CD66b + neutrophils infiltration in tumor tissues (r = 0.210, P < 0.05) and CD68  +  CD163 + M2 macrophages in the interstitium (r = 0.233, P < 0.05), as well as the immune checkpoints, including PD-1 (r = 0.314, P < 0.01) protein expression., Conclusion: SCARB2 holds promise for predicting the clinical outcome of breast cancer patients and could serve as a potential therapeutic target., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To report the prospective long-term outcome data of patients whose chemotherapy decision was guided by the EndoPredict test., Methods: Patients with hormone receptor-positive HER2-negative early breast cancer with 0-3 positive lymph nodes were enrolled. The EndoPredict test was carried out on all tumor samples. Treatment compliance, local recurrence, distant metastases, and survival were evaluated. Associations of EPclin risk stratification with 5-year disease-free survival and distant metastasis-free survival were evaluated by time-to-event analysis., Results: 368 consecutive patients were included in the analysis. Median follow-up was 8.2 years. EndoPredict allocated 238 (65%) in the low-risk and 130 (35%) patients in the high-risk group. Risk for disease recurrence or death in EPclin high-risk patients was twofold higher than in EPclin low-risk patients (hazard ratio [HR] 2.08; 95% CI 1.26-3.44; p = 0.004). EPclin low-risk patients had a 5-year disease-free survival of 95.3% (95% CI 92.6-98.0%). EPclin high-risk patients were at higher risk of developing distant metastases or death (HR 2.21; 95% CI 1.27-3.88; p = 0.005). EPclin high-risk patients who underwent chemotherapy had a 5-year DFS of 89.1% (95% CI 82.7-96.1%) in contrast to high-risk patients without chemotherapy (68.9%; 95% CI 56.2-84.5%; HR 0.46; 95% CI 0.23-0.95; p = 0.036). EPclin high-risk patients were at higher risk of experiencing distant metastases or death than EPclin low-risk patients regardless of menopausal status (premenopausal: HR 3.55; 95% CI 1.17-12.32; p = 0.025; postmenopausal: HR 1.92; 95% CI 0.99-3.7; p = 0.054)., Conclusion: EndoPredict can guide decisions on adjuvant chemotherapy in early luminal breast cancer. EndoPredict risk stratification is also applicable in premenopausal women., (© 2024. The Author(s).)

Aims and Objectives: Although cyclin-dependent kinase 4/6 inhibitors (CDK 4/6i) are a vital part of the treatment of hormone receptor (HR)-positive/HER-2-negative metastatic breast cancer (BC), individuals have different sensitivities to CDK4/6i, indicating the need for biomarkers. The fasting triglyceride glucose (TyG) index is an easily accessible surrogate marker of insulin resistance (IR). Herein, we investigated the prognostic significance of the fasting triglyceride glucose (TyG) index in HR+/HER2- metastatic BC patients treated with CDK4/6i plus endocrine therapy (ET)., Methods: About 333 patients with HR+/HER2-metastatic BC treated with CDK4/6i plus ET were analyzed retrospectively. The TyG index was calculated within 3 months before the initiation of CDK4/6i plus ET. The median value of 8.43 was taken as the cutoff for the TyG index., Results: The median overall survival (OS) was 73.6 months (95% CI, 66.0-81.1) in the whole cohort. The progression-free survival (PFS) was significantly longer in the low-TyG subgroup than in the high-TyG subgroup (30.1 vs. 21.3 months, multivariate adjusted [HR] = 0.666, 95% CI, 0.450-0.987, P = .043). While the median OS was not reached in the low TyG subgroup, it was 69.0 months in the high TyG subgroup (multivariate-adjusted HR = 0.513, 95% CI, 0.281-0.936, P = .030). Although the ORR and DCR were numerically greater in the low-TyG subgroup, no significant differences were observed between the low-TyG subgroup and high-TyG subgroup (28.1% vs. 24.7%, P = .476; 83.2% vs. 80.1%, P = .463, respectively)., Conclusions: These data imply that the TyG index could be a predictive biomarker for the therapeutic efficacy of CDK4/6is. Extensive prospective studies are needed to confirm these findings., Competing Interests: Disclosure The authors declare that they have no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: HER2-positive breast cancer (BC) accounts for 20-30% of all BC subtypes and is linked to poor prognosis. Trastuzumab (Tz), a humanized anti-HER2 monoclonal antibody, is a first-line treatment for HER2-positive breast cancer which faces resistance challenges. This study aimed to identify the biomarkers driving trastuzumab resistance., Methods: Differential expression analysis of genes and proteins between trastuzumab-sensitive (TS) and trastuzumab-resistant (TR) cells was conducted using RNA-seq and iTRAQ. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to study their functions. The prognostic significance and protein levels of ARFIP2 and MSN were evaluated using online tools and immunohistochemistry. Sensitivity of MSN and ARFIP2 to other therapies was assessed using public pharmacogenomics databases and the R language., Results: Five genes were up-regulated, and nine genes were down-regulated in TR cells at both transcriptional and protein levels. Low ARFIP2 and high MSN expression linked to poor BC prognosis. MSN increased and ARFIP2 decreased in TR patients, correlating with shorter OS. MSN negatively impacted fulvestrant and immunotherapy sensitivity, while ARFIP2 had a positive impact., Conclusion: Our findings suggest that MSN and ARFIP2 could serve as promising biomarkers for predicting response to Tz, offering valuable insights for future research in the identification of diagnostic and therapeutic targets for BC patients with Tz resistance., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: Many patients with early breast cancer (eBC) undergoing neoadjuvant chemotherapy do not achieve pathological complete response (pCR), which is a prognostic factor. We examined the role of HER2-low expression in predicting pCR and prognosis in HER2-negative eBC., Methods: We evaluated patients with stage I-III HER2-negative BC, treated between 2013 and 2023 at The Royal Marsden NHS Foundation Trust, London. Tumors were classified based on estrogen receptor (ER) status and into HER2-low and HER2-zero subgroups. We analyzed pCR rates, relapse-free survival (RFS) and overall survival (OS)., Results: 754 patients were included in the analysis. pCR rate was 8.9% in the ER+ /HER2-low, 16.5% in the ER+ /HER2-zero, 38.9% in the ER- ER-/HER2-low and 35.9% in the ER-/HER2-zero eBC (p < 0.001). Multivariable analysis showed a significantly lower pCR rate in HER2-low compared to HER2-zero BC in the ER+ subgroup. At a median follow-up of 63.8 months (59.9-67.4), we observed longer OS in HER2-low compared to HER2-zero patients in the overall and in the ER+ population. There was no predictive or prognostic impact of HER2-low status in the ER- population., Conclusion: This study supports the interpretation of HER2 status as a possible prognostic and predictive biomarker for HER2-negative eBC, especially among patients with ER+ disease., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To establish a pathomic model using histopathological image features for predicting indoleamine 2,3-dioxygenase 1 (IDO1) status and its relationship with overall survival (OS) in breast cancer., Methods: A pathomic model was constructed using machine learning and histopathological images obtained from The Cancer Genome Atlas database to predict IDO1 expression. The model performance was evaluated based on the area under the curve, calibration curve, and decision curve analysis (DCA). Prediction scores (PSes) were generated from the model and applied to divide the patients into two groups. Survival outcomes, gene set enrichment, immune microenvironment, and tumor mutations were assessed between the two groups., Results: Survival analysis followed by multivariate correction revealed that high IDO1 is a protective factor for OS. Further, the model was calibrated, and it exhibited good discrimination. Additionally, the DCA showed that the proposed model provided a good clinical net benefit. The Kaplan-Meier analysis revealed a positive correlation between high PS and improved OS. Univariate and multivariate Cox regression analyses demonstrated that PS is an independent protective factor for OS. Moreover, differentially expressed genes were enriched in various essential biological processes, including extracellular matrix receptor interaction, angiogenesis, transforming growth factor β signaling, epithelial mesenchymal transition, cell junction, tryptophan metabolism, and heme metabolic processes. PS was positively correlated with M1 macrophages, CD8 + T cells, T follicular helper cells, and tumor mutational burden., Conclusion: These results indicate the potential ability of the proposed pathomic model to predict IDO1 status and the OS of breast cancer patients., (© 2024. The Author(s).)

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.