Prognostic Marker In Breast Cancer Research Articles

Suppressing mitochondrial inner membrane protein (IMMT) inhibits the proliferation of breast cancer cells through mitochondrial remodeling and metabolic regulation

Metabolic reprogramming is widely recognized as a hallmark of malignant tumors, and the targeting of metabolism has emerged as an appealing approach for cancer treatment. Mitochondria, as pivotal organelles, play a crucial role in the metabolic regulation of tumor cells, and their morphological and functional alterations are intricately linked to the biological characteristics of tumors. As a key regulatory subunit of mitochondria, mitochondrial inner membrane protein (IMMT), plays a vital role in degenerative diseases, but its role in tumor is almost unknown. The objective of this research was to investigate the roles that IMMT play in the development and progression of breast cancer (BC), as well as to elucidate the underlying biological mechanisms that drive these effects. In this study, it was confirmed that the expression of IMMT in BC tissues was significantly higher than that in normal tissues. The analysis of The Cancer Genome Atlas (TCGA) database revealed that IMMT can serve as an independent prognostic factor for BC patients. Additionally, verification in clinical specimens of BC demonstrated a positive association between high IMMT expression and larger tumor size (> 2 cm), Ki-67 expression (> 15%), and HER-2 status. Furthermore, in vitro experiments have substantiated that the suppression of IMMT expression resulted in a reduction in cell proliferation and alterations in mitochondrial cristae, concomitant with the liberation of cytochrome c, but it did not elicit mitochondrial apoptosis. Through Gene Set Enrichment Analysis (GSEA) analysis, we have predicted the associated metabolic genes and discovered that IMMT potentially modulates the advancement of BC through its interaction with 16 metabolic-related genes, and the changes in glycolysis related pathways have been validated in BC cell lines after IMMT inhibition. Consequently, this investigation furnishes compelling evidence supporting the classification of IMMT as prognostic marker in BC, and underscoring its prospective utility as a novel target for metabolic therapy.

Unveiling the complexity: Liquid biopsy-based proteomic exploration of triple-negative breast cancer in women.

e13138 Background: This groundbreaking study places a spotlight on breast cancer in women, with a specific emphasis on the challenging triple-negative breast cancer (TNBC) subtype. Delving into the intricate world of extracellular vesicles (EVs) from TNBC-diagnosed individuals, the research meticulously compares various conditions, including healthy controls, benign tumors, recurrent tumors, and those in remission. Employing cutting-edge techniques like liquid biopsy and LC-MS/MS, the study meticulously explores the proteomic profile of serum exosomes, aiming to pinpoint diagnostic and prognostic markers in breast cancer. Methods: In the initial phase, EVs were expertly isolated and characterized from blood plasma samples exclusively from women, utilizing state-of-the-art methods such as ultracentrifugation and nanoparticle tracking analysis (NTA). Despite applying rigorous statistical criteria, the study found no significant differences in EV concentrations and sizes among the diverse groups. However, the ensuing proteomic analysis uncovered 130 proteins, with Cystatin A and Histone H2A emerging as promising biomarkers for TNBC. To validate them, the study intricately tested tumor cell lines from distinct subtypes, representing luminal, triple-negative, and HER2 overexpressed. The examination of gene and protein expression through RT-qPCR and western blotting added a layer of depth to the research, unraveling the complexity of regulatory processes within cells and demonstrating a remarkable congruence between protein levels found in the proteomics from patients’ serum and in immortalized cell lines. Results: The proteomic analysis brought to light the absence of CSTA and HIST1H2A expression in benign tumor patients, varied levels in malignant tumor patients, and a substantial increase in TNBC patients pre-mastectomy. Validating these findings through western blotting further accentuated the potential of these proteins as distinguishing factors. Conclusions: In conclusion, this pioneering study not only underscores the immense potential of liquid biopsy-based proteomic analysis in identifying crucial diagnostic and prognostic markers in breast cancer but also sheds light on the intricate nuances of the challenging TNBC subtype. Our findings unveil valuable insights that pave the way for future personalized treatment strategies, marking a significant stride forward in breast cancer research.

Identification of SMC2 and SMC4 as prognostic markers in breast cancer through bioinformatics analysis.

Breast cancer (BRCA) is one of the most common malignant tumors. The structural maintenance of chromosome (SMC) gene family has been shown to play an important role in human cancers. However, the role of SMC families in BRCA is unclear. This study aimed to explore the role and potential clinical value of whole SMCs in BRCA. TIMER and UALCAN database were used to analysis the expression level. Genetic variations were analyzed by cBioPortal. Promoter methylation and protein level were analyzed by UCLCAN. GO and KEGG were analyzed by Metascape database. Prognostic value of SMCs was analyzed by Kaplan-Meier and multivariate cox regression analyses. Immune infiltration analysis was conducted by CIBERSORT. Immunotherapy outcome prediction was conducted by Cancer Immunome Atlas. Targeted drug therapy outcome prediction was taken by GDSC and R language. The cell viability was tested by CCK8 and migration was tested by wound healing assay. Xenograft model was used to investigate the in vivo role of SMC2. Expression levels of SMC1A, SMC2, SMC4, SMC5 and SMC6 mRNA were increased in BRCA tissues, and negatively correlated with promoter methylation. Overexpression of SMC2 and SMC4 was negatively correlated with survival. Function of SMCs family regulatory genes was mainly related to ATPase activity. Expression of most SMCs was negatively correlated with immunotherapy and drug therapy outcomes. Interfere SMC2 and SMC4 decreased IC50 values of 5-fluorouracil and oxaliplatin and inhibited the migration of MCF7 cells. Tumor growth and weights were significantly decreased in si-SMC2 groups. Combined bioinformatics and clinical specimen analysis verified SMC2 and SMC4 as independent prognostic factors in BRCA, suggesting their significance for the diagnosis and treatment of BRCA.

PMBC: a manually curated database for prognostic markers of breast cancer.

Breast cancer is notorious for its high mortality and heterogeneity, resulting in different therapeutic responses. Classical biomarkers have been identified and successfully commercially applied to predict the outcome of breast cancer patients. Accumulating biomarkers, including non-coding RNAs, have been reported as prognostic markers for breast cancer with the development of sequencing techniques. However, there are currently no databases dedicated to the curation and characterization of prognostic markers for breast cancer. Therefore, we constructed a curated database for prognostic markers of breast cancer (PMBC). PMBC consists of 1070 markers covering mRNAs, lncRNAs, miRNAs and circRNAs. These markers are enriched in various cancer- and epithelial-related functions including mitogen-activated protein kinases signaling. We mapped the prognostic markers into the ceRNA network from starBase. The lncRNA NEAT1 competes with 11 RNAs, including lncRNAs and mRNAs. The majority of the ceRNAs in ABAT belong to pseudogenes. The topology analysis of the ceRNA network reveals that known prognostic RNAs have higher closeness than random. Among all the biomarkers, prognostic lncRNAs have a higher degree, while prognostic mRNAs have significantly higher closeness than random RNAs. These results indicate that the lncRNAs play important roles in maintaining the interactions between lncRNAs and their ceRNAs, which might be used as a characteristic to prioritize prognostic lncRNAs based on the ceRNA network. PMBC renders a user-friendly interface and provides detailed information about individual prognostic markers, which will facilitate the precision treatment of breast cancer. PMBC is available at the following URL: http://www.pmbreastcancer.com/.

Abstract PO3-28-08: Triple Hormone Receptor Signatures as Novel Prognostic Markers in Breast Cancer

Abstract Background Tumor phenotype across various cancers, including breast cancer, is predominantly shaped by a synergy between genomic alterations and the cell-of-origin from which the tumor emerges. These elements collectively influence crucial aspects like tumor aggressiveness, treatment response, and patient prognosis. While existing research highlights that the cell-of-origin often leaves a lasting imprint on the molecular architecture of tumors, leveraging this information for actionable clinical insights has proven challenging. Specifically, in the realm of breast cancer, utilizing cellular ancestry signatures could be a key factor in tailoring effective therapeutic strategies and improving patient outcomes. Methods In this study, we developed a unique signature anchored in the expression levels of triple hormone receptors (THR)—namely androgen (AR), estrogen (ER), and vitamin D (VDR)—in normal breast cells. Building on this, we formulated two distinct mRNA markers, THR-50 and THR-70, aimed at categorizing breast tumors based on their THR expression profiles. These markers were rigorously validated across 65 independent breast cancer studies, involving a total of 6,679 patients, utilizing Kaplan-Meier survival curves, Cox proportional hazards models, and unsupervised clustering analyses. Results Our findings indicate that both THR-50 and THR-70 are robustly associated with overall survival and recurrence-free survival in breast cancer patients across all datasets evaluated. Importantly, these THR signatures demonstrate broad applicability across various breast cancer subtypes, grades, and treatment phases—unlike conventional prognostic markers that tend to be subtype-specific. Additionally, the THR signatures have revealed four unique patient clusters with divergent survival outcomes, three of which are ER-positive and one ER-negative. When augmented with an immune-based signature (i20), THR-70 identifies a specific ER-negative breast cancer subgroup with a highly favorable prognosis, comparable to ER-positive subtypes, as well as another ER-negative subgroup characterized by exceedingly poor survival outcomes. Conclusion The THR-based cellular ancestry signatures open a new avenue in understanding the intricacies of breast cancer biology. These signatures offer a robust and stable framework for developing other prognostic markers, thus providing an enhanced stratification of existing breast cancer categories as well as creating new classifications. Citation Format: Mohamed Omar, Chuck Harrell, Rulla Tamimi, Luigi Marchionni, Tan Ince. Triple Hormone Receptor Signatures as Novel Prognostic Markers in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-28-08.

Abstract LB392: Transformative pathomics in oncology: Harnessing FFPE tissue slide imagery for clinically relevant gene expression prediction in invasive breast carcinoma

Abstract Purpose: Pathologists routinely analyze H&E-stained FFPE tissue slides microscopically to arrive at diagnoses for patients. Pathomics, the study of quantitative imaging from such samples, aims to elevate diagnostic accuracy by revealing intricate tissue and cellular details. Our research evaluates how pathomic features from tissue imagery can predict gene expression, as determined by RNA sequencing, offering advancements in the molecular profiling and targeted therapy for invasive breast carcinoma (IBC). Method: We conducted an analysis of 90 regions of interest (ROIs) on FFPE tissue slide images from the TCGA registry for patients with IBC. Using HistomicsTK software, we extracted nearly 300 pathomic features depicting cell morphometry, intensity, and gradient from these regions of interest (ROIs). We then assessed the intra-correlation of the pathomic features within the ROIs of the same tissue slide to identify the most heterogeneous and highly correlating features (n=20) across categories—morphometry, intensity, and gradient—with a Pearsonʼs Correlation coefficient (r) greater than 0.9 and a FDR adjusted p-value less than 0.05. Subsequently, gene expression data in the form of FPKM were obtained for the corresponding tissues from TCGA. We trained a Multitask Elastic Net (MTEN) model on these pathomic features using an 80:20 split for the training and testing sets, with a three-fold cross-validation applied to the training set utilizing ImaGene software. The model's performance was evaluated by measuring the AUC and R² value for the predicted gene expression on the testing set. Result and Biological significance: The testing of the MTEN model using a testing set predicted the expression of three genes identified in the literature as prognostic markers in breast cancer, namely ALDH1L2, MFAP5, and MXRA8, with an AUC greater than 0.8 and an R² above 0.5 at a p-value of less than 0.002. According to the literature, expression of genes from the ALDH1 superfamily in breast cancer correlates with the stage of the disease, triple-negative status, and response to neoadjuvant therapy. The upregulation of MFAP5 in invasive breast carcinomas has been associated with high risk prognostic features, such as higher tumor grade and stage and increased angiogenesis, and poorer outcomes, such as lymph node metastasis. Furthermore, MXRA8 is involved in modulating the progression of human triple-negative breast cancer, likely through its influence on the interactions of tumor cells with their microenvironment. Conclusion: The present study predicts the expression of clinically relevant genes in IBC using a heterogeneous set of pathomic features extracted from FFPE tissue slide imagery. By linking cell and tissue-based morphometric, intensity, and gradient features with gene expression, researchers can gain insights into the molecular mechanisms underlying disease progression. Digital pathology and pathomics may reduce the need for additional genetic testing in critical patient-cases by providing predictive information from routinely acquired pathology slides. Bridging the gap between phenotypic tissue data and molecular data, the predictive capabilities of pathomic features represent a significant advancement in the field of precision medicine. Citation Format: Shrey S. Sukhadia, Digvijay Yadav, Kristen E. Muller. Transformative pathomics in oncology: Harnessing FFPE tissue slide imagery for clinically relevant gene expression prediction in invasive breast carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB392.

Expression and Significance of LINC02418 in Breast Cancer.

The complicated pathogenesis and poor prognosis of breast cancer have become a major difficulty in medical research. This study aims to explore new lncRNA as prognostic markers for breast cancer and explore their roles and molecular mechanisms to lay a foundation for the treatment of cancer patients. The expression of LINC02418 and miR-766-5p in breast cancer tissues and cells was first identified using polymerase chain reaction, and Pearson was used to examine the correlation between the two. The cancer cells activities under different transfection conditions were detected using the Transwell assay and CCK8 assay. The correlation between LINC02418 and patient prognosis was analyzed using multifactor Cox regression and Kaplan-Meier. It was shown that LINC02418 expression was upregulated in breast cancer tissues and cells. There are significant differences in lymph node metastasis and TNM stage between high and low LINC02418 expression groups. The higher the expression of LINC02418, the higher the mortality rate of breast cancer patients. miR-766-5p expression was downregulated and negatively correlated with LINC02418. There are binding sites between LINC02418 and miR-766-5p; Transfection with miR-766-5p inhibitor boosted LINC02418 luciferase activity, but transfection with miR-766-5p mimic decreased it. Knockdown of LINC02418 promoted miR-766-5p expression and inhibited cancer progression, which was alleviated to some extent by transfection with miR-766-5p inhibitors. LINC02418 has the potential to serve as a poor prognostic marker for breast cancer and plays a pro-oncogenic role by targeting miR-766-5p.

Long-Noncoding-RNA HOTAIR Upregulation is Associated with Poor Breast Cancer Outcome: A Systematic Review and Meta Analysis.

Breast cancer is the most frequent cancer among women worldwide with significant disproportionate mortality rates in developing countries. Although clinical management of breast cancer has been immensely improved, refinement in the prognostic and recurrent markers is still needed. Long non-coding RNAs (lncRNA) HOTAIR has recently been associated with poor outcome and is potentially used as a prognostic marker in breast cancer. We comprehensively reviewed studies evaluating lncRNA HOTAIR in association with overall and disease-free survivals in breast cancers. Systematic searches were performed in Pubmed, ProQuest, ScienceDirect, Scopus, Google Scholar, Semantic Scholar, Springer, Nature, Sage Journals, and Wiley databases using combination keywords "long non-coding RNA," "lncRNA," "HOX transcript antisense RNA," "HOTAIR," "breast can-cer," "carcinoma mammae," "prognosis," and "survival." Risk of bias score was used to assess quality of studies, I2 test was conducted to assess heterogeneity. Meta-analysis was performed to compare HOTAIR expression with breast cancer survival rates using STATA v.17 software. Of the total 1,504 screened studies, seven studies were included in the meta-analysis involving 533 patients. High expression of HOTAIR was associated with poor survival rates (pooled HR: 1.69; 95%CI: 1.11-2.59; p=0.015), shorter overall survival (OS) (pooled HR: 1.33; 95%CI: 0.78-2.26; p=0.455), poor disease-free survival (DFS) (pooled HR: 2.40; 95%CI: 1.63-3.53; p<0.001), poor distant metastatic-free survival (MFS) (HR: 1.75; 95%CI: 1.13-2.71; p=0.012). In addition, overexpression of HOTAIR was associated with positive lymph node infiltration (pooled OR: 2.38; 95%CI: 0.53-10.69; p=0.26) and ductal type cancer (pooled OR: 3.27; 95%CI: 1.15-9.30; p=0.03). Upregulation of lncRNA HOTAIR is associated with worse DFS aand MFS that can potentially be used as a prognostic marker in breast cancer patients.

Mitochondrial calcium uniporter as biomarker and therapeutic target for breast cancer: Prognostication, immune microenvironment, epigenetic regulation and precision medicine

IntroductionMitochondrial calcium uniporter (MCU) is a central subunit of MCU complex that regulate the levels of calcium ions within mitochondria. A comprehensive understanding the implications of MCU in clinical prognostication, biological understandings and therapeutic opportunity of breast cancer (BC) is yet to be determined. ObjectivesThis study aims to investigate the role of MCU in predictive performance, tumor progression, epigenetic regulation, shaping of tumor immune microenvironment, and pharmacogenetics and the development of anti-tumor therapy for BC. MethodsThe downloaded TCGA datasets were used to identify predictive ability of MCU expressions via supervised learning principle. Functional enrichment, mutation landscape, immunological profile, drug sensitivity were examined using bioinformatics analysis and confirmed by experiments exploiting human specimens, in vitro and in vivo models. ResultsMCU copy numbers increase with MCU gene expression. MCU expression, but not MCU genetic alterations, had a positive correlation with known BC prognostic markers. Higher MCU levels in BC showed modest efficacy in predicting overall survival. In addition, high MCU expression was associated with known BC prognostic markers and with malignancy. In BC tumor and sgRNA-treated cell lines, enrichment pathways identified the involvement of cell cycle and immunity. miR-29a was recognized as a negative epigenetic regulator of MCU. High MCU levels were associated with increased mutation levels in oncogene TP53 and tumor suppression gene CDH1, as well as with an immunosuppressive microenvironment. Sigle-cell sequencing indicated that MCU mostly mapped on to tumor cell and CD8 T-cells. Inter-databases verification further confirmed the aforementioned observation. miR-29a-mediated knockdown of MCU resulted in tumor suppression and mitochondrial dysfunction, as well as diminished metastasis. Furthermore, MCU present pharmacogenetic significance in cellular docetaxel sensitivity and in prediction of patients’ response to chemotherapeutic regimen. ConclusionMCU shows significant implication in prognosis, outcome prediction, microenvironmental shaping and precision medicine for BC. miR-29a-mediated MCU inhibition exerts therapeutic effect in tumor growth and metastasis.

Abstract 3486: Triple hormone receptor signatures as novel prognostic markers in breast cancer

Abstract Background: Tumor phenotype across various cancers, including breast cancer, is predominantly shaped by a synergy between genomic alterations and the cell-of-origin from which the tumor originates. These elements collectively influence crucial aspects like tumor aggressiveness, treatment response, and patient prognosis. While existing research highlights that the role of cell-of-origin in shaping the molecular architecture of breast cancer, leveraging this information for actionable clinical insights has proven challenging. Here, we introduce two robust models leveraging cellular ancestry signatures of breast luminal cells to improve patient stratification and outcome prediction. Methods: In this study, we developed a unique gene signature anchored in the expression levels of triple hormone receptors (THR)—namely androgen (AR), estrogen (ER), and vitamin D (VDR)—in breast cancer cells. Building on this, we formulated two distinct mRNA markers, THR-50 and THR-70, aimed at categorizing breast tumors based on their THR expression profiles. These markers were rigorously validated across 65 independent breast cancer studies, involving a total of 6,679 patients, utilizing Kaplan-Meier survival curves, Cox proportional hazards models, and unsupervised clustering analyses. Results: Our findings indicate that both THR-50 and THR-70 are robustly associated with overall survival and recurrence-free survival in breast cancer patients across all datasets evaluated. Importantly, these THR signatures demonstrate broad applicability across various breast cancer subtypes, grades, and treatment phases—unlike existing prognostic markers that tend to be subtype-specific. Additionally, the THR signatures have revealed four unique patient clusters with divergent survival outcomes, three of which are ER-positive and one is ER-negative. Additionally, we developed an immune-based signature (i20) which can further categorize patients within the ER-negative cluster into two subgroups: one with a highly favorable prognosis, comparable to the ER-positive subtypes, and another that is characterized by exceedingly poor survival outcomes. Conclusion: The THR-based cellular ancestry signatures open a new avenue in understanding the intricacies of breast cancer biology. These signatures offer a robust and stable framework for developing other prognostic markers, thus providing an enhanced stratification of existing breast cancer categories as well as creating new classifications with more distinct survival estimates. Citation Format: Mohamed Omar, J. Chuck Harrell, Rulla M. Tamimi, Luigi Marchionni, Tan Ince. Triple hormone receptor signatures as novel prognostic markers in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3486.

Multi-omics analysis reveals the unique landscape of DLD in the breast cancer tumor microenvironment and its implications for immune-related prognosis

BackgroundCuproptosis, i.e., copper-induced programmed cell death, has potential implications in cancer therapy. However, the impact of the cuproptosis-related gene (CRG) dihydrolipoyl dehydrogenase (DLD) on breast cancer (BC) prognosis remains underexplored. MethodsWe employed real-time quantitative PCR and multiplexed immunostaining techniques to quantify DLD expression in both BC and the adjacent non-cancerous tissues. Immunofluorescence analysis was employed to assess the influence of DLD on immune cells and immunological checkpoints in the BC microenvironment. DLD knockdown experiments were conducted in BC cell lines MDA-MB-468 and SK-BR-3, with knockdown efficiency validated via western blot. Subsequently, we performed the cell counting kit-8 (CCK-8) assay, clone formation assay, Transwell migration assay, and invasion assay. To construct a prognostic model, we employed a Lasso-Cox regression analysis of immune-related genes associated with DLD. Additionally, we established a competing endogenous RNA network based on CRGs to evaluate potential regulatory pathways. ResultsCompared to the adjacent tissues, BC tissues exhibited markedly elevated DLD expression levels. In vitro experiments demonstrated that DLD knockdown effectively inhibited BC cell migration, invasion, and proliferation. DLD exhibited positive correlations with CD68+ macrophages and PD-L1 in the tumor, as well as with macrophages and CD4+ T cells in the stroma. Tumor regions with high DLD expression were enriched in PD-L1 and macrophages, while stromal regions with high DLD expression contained CD4+ T cells and macrophages. The AUC values for 1-, 3-, and 5-year overall survival in TCGA-BRCA training set were 0.67, 0.66, and 0.66, respectively. A nomogram with a C-index of 0.715 indicated that risk score, tumor stage, and age could serve as independent prognostic factors for BC. ConclusionOur findings underscore the significant predictive significance of DLD in BC and its influence on the tumor microenvironment. DLD represents a promising diagnostic and prognostic marker for BC, offering novel avenues for the identification of therapeutic targets and the enhancement of immunotherapy in BC.

The Correlation between Morpho-Dynamic Contrast-Enhanced Mammography (CEM) Features and Prognostic Factors in Breast Cancer: A Single-Center Retrospective Analysis.

Breast cancer, a major contributor to female mortality globally, presents challenges in detection, prompting exploration beyond digital mammography. Contrast-Enhanced Mammography (CEM), integrating morphological and functional information, emerges as a promising alternative, offering advantages in cost-effectiveness and reduced anxiety compared to MRI. This study investigates CEM's correlation with breast cancer prognostic factors, encompassing histology, grade, and molecular markers. In a retrospective analysis involving 114 women, CEM revealed diverse lesion characteristics. Statistical analyses identified correlations between specific CEM features, such as spiculated margins and irregular shape, and prognostic factors like tumor grade and molecular markers. Notably, spiculated margins predicted lower grade and HER2 status, while irregular shape correlated with PgR and Ki-67 status. The study emphasizes CEM's potential in predicting breast cancer prognosis, shedding light on tumor behavior. Despite the limitations, including sample size and single-observer analysis, the findings advocate for CEM's role in stratifying breast cancers based on biological characteristics. CEM features, particularly spiculated margins, irregular shape, and enhancement dynamics, may serve as valuable indicators for personalized treatment decisions. Further research is crucial to validate these correlations and enhance CEM's clinical utility in breast cancer assessment.

Prognostic value of cyclin B1 and cyclin B2 expression in breast cancer: A systematic review and updated meta-analysis.

Cyclin B1 and cyclin B2 are key regulators of cell cycle progression and have been implicated in the prognostic significance of various cancers. This meta-analysis aimed to evaluate the prognostic value of cyclin B1 and B2 expression in breast cancer. A comprehensive literature search was conducted on Pubmed, Embase, MEDLINE, Web of Science, and Cochrane library. Studies with survival data and clinicopathological parameters associated with cyclin B1 and B2 or CCNB1 and CCNB2 genes were included. Survival data and clinicopathological parameters associated with cyclin B1 and B2 expression were extracted. Pooled hazard ratios and odds ratios with 95% confidence intervals were calculated. Subgroup analysis was conducted to assess heterogeneity. Publication bias was evaluated. A total of 23 studies were included in the analysis. High expression of cyclin B1 was significantly associated with worse overall survival (hazard ratio [HR] = 1.69, P < .01), disease-specific survival (HR = 1.71, P < .01), and disease-free survival (HR = 2.01, P = .01). High expression of cyclin B2 was associated with worse disease-specific survival (HR = 2.46, P = .02). Clinicopathological parameters did not show significant associations with cyclin B1 and B2 expressions. When data on cyclin B1 and B2 were combined, a significant age-related difference was found (odds ratio = 0.62, P = .04). This meta-analysis provides evidence supporting the prognostic significance of cyclin B1 and B2 expression in breast cancer. High expression of cyclin B1 and B2 is associated with worse survival, indicating their potential as prognostic markers in breast cancer.

To study the utility of tumor budding as a histopathological marker in comparison to various histopathological parameters and TNM staging in breast carcinoma

Background Breast cancer is the leading cause of death in Indian females. Detection of breast cancer in later stages leads to poorer prognosis and therefore decreases patient survival. Various new modalities such as mammography and USG guided FNACs are developed and many new markers are available to diagnose breast cancer; however, tumour budding is a cost-effective method which can be helpful in early diagnosis. Tumour buds are found to have a positive correlation with various histopathological prognostic markers in breast cancer. The present study will be conducted to evaluate tumour buds as a prognostic marker in breast cancer. This study aims to compare tumour budding with histopathological prognostic markers, TNM staging and IHC phenotypes. Methods The study will be observational, cross- sectional, and prospective, will include 60 cases and will be conducted at Jawaharlal Nehru Medical College (JNMC) Wardha in the Pathology Department. Results Data will be collected and combined together over a period of two years and will be analysed statistically for tumour budding as a marker and its correlation with breast prognosis.

Neutrophil-lymphocyte ratio reflects tumour-infiltrating lymphocytes and tumour-associated macrophages and independently predicts poor outcome in breast cancers with neoadjuvant chemotherapy.

The neutrophil-lymphocyte ratio (NLR) is a systemic reflection of cancer-associated inflammation and a prognostic marker for breast cancer. For the local tumour microenvironment, tumour-infiltrating lymphocytes (TILs) and tumour-associated macrophages (TAMs) are also highly correlated with breast cancer survival. This study aimed to explore the relationship between the circulating and local immune microenvironment, and to further delineate the prognostic role of NLR in breast cancer patients receiving neoadjuvant chemotherapy (NAC). A cohort of breast cancer patients receiving NAC with subsequent surgery was retrieved. Clinical data were reviewed. Histological slides andCD8 immunohistochemistry from biopsy (pre-chemotherapy) and excision (postchemotherapy) specimens were assessed for TILs and TAMs. A total of 146 patients were included. There was a significant positive correlation between pre- and postsurgery NLR at a cut-off of 2.6 (median pre-chemotherapy NLR) (P < 0.001). NLR pre-chemotherapy was associated positively with necrosis on biopsy (P = 0.027) and excision (P = 0.021) and TAMs on excision (P = 0.049). NLR 1 year postsurgery was associated with high tumour stage (P = 0.050) and low histological grade (P = 0.008). TIL count was lower in NLR-high cases at almost all time-points by histological assessment and CD8 immunostaining (P < 0.050). In multivariate analysis, postsurgery NLR is an independent predictor for overall survival [OS; hazard ratio (HR) = 9.524, P < 0.001], breast cancer-specific survival (BCSS) (HR = 10.059, P = 0.001) and disease-free survival (DFS; HR = 2.824, P = 0.016). The association between NLR with tumour necrosis, TAMs and TILs illustrates an interaction between the circulating and local immune microenvironment. Late NLR is a strong indicator of outcome and may be useful for prognostication and disease monitoring.

Ultrafast Dynamic Contrast‐Enhanced MRI of the Breast: From Theory to Practice

The development of ultrafast dynamic contrast‐enhanced (UF‐DCE) MRI has occurred in tandem with fast MRI scan techniques, particularly view‐sharing and compressed sensing. Understanding the strengths of each technique and optimizing the relevant parameters are essential to their implementation. UF‐DCE MRI has now shifted from research protocols to becoming a part of clinical scan protocols for breast cancer. UF‐DCE MRI is expected to compensate for the low specificity of abbreviated MRI by adding kinetic information from the upslope of the time‐intensity curve. Because kinetic information from UF‐DCE MRI is obtained from the shape and timing of the initial upslope, various new kinetic parameters have been proposed. These parameters may be associated with receptor status or prognostic markers for breast cancer. In addition to the diagnosis of malignant lesions, more emphasis has been placed on predicting and evaluating treatment response because hyper‐vascularity is linked to the aggressiveness of breast cancers. In clinical practice, it is important to note that breast lesion images obtained from UF‐DCE MRI are slightly different from those obtained by conventional DCE MRI in terms of morphology. A major benefit of using UF‐DCE MRI is avoidance of the marked or moderate background parenchymal enhancement (BPE) that can obscure the target enhancing lesions. BPE is less prominent in the earlier phases of UF‐DCE MRI, which offers better lesion‐to‐noise contrast. The excellent contrast of early‐enhancing vessels provides a key to understanding the detailed pathological structure of tumor‐associated vessels. UF‐DCE MRI is normally accompanied by a large volume of image data for which automated/artificial intelligence‐based processing is expected to be useful. In this review, both the theoretical and practical aspects of UF‐DCE MRI are summarized.Evidence Level5Technical EfficacyStage 2

A multiplex immunoprofiling approach for detecting the co-localization of breast cancer biomarkers using a combination of Alexafluor - Quantum dot conjugates and a panel of chromogenic dyes

There is a plethora of information embedded in a tissue section that the conventional IHC understands only partially. Predictive biomarkers for precision immuno-oncology heavily dependent on the spatial arrangement of cells and the co-expression patterns in the tissue sections. Here we have explored the versatility of indirect multiplex immunofluorescence (mIF) and indirect multiplex immunohistochemistry (mIHC) for the labeling of breast cancer prognostic markers in routinely processed, formalin-fixed paraffin-embedded (FFPE) tissues at high resolution. The multiplex immunohistochemistry protocol utilized sequential staining for the chromogenic immunolabelling of Estrogen Receptor α (ERα) or Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Nucleoside diphosphate kinase 1 (NM23) by multicolor chromogens in different combinations. A feasible workflow for multiplex immunofluorescence was also effectively standardized for ERα, PR, and HER2 using combinations of commercially available Alexa Fluor and Quantum dots semiconductor nanocrystal conjugated secondary antibodies. Multiplex chromogenic immunolabeling revealed differential expression of the markers on the same slide. Kappa statistics revealed perfect agreement with uniplex immunohistochemistry. For multiplex fluorescence approach, surface receptor detection using Quantum dots and Alexa fluor dyes for cytoplasmic or nuclear markers performed well for profiling multiple co-localized biomarkers on a single paraffin tissue section. The technique developed reveals additional information such as co-expression, spatial relationships, and tumor heterogeneity, providing a deeper insight into developing combinatorial therapeutic strategies in clinical care. This high throughput workflow complements the outcomes of traditional IHC while saving tissue, time, labour, and reagents.

Analysis of Interleukin-6 Gene Variants (rs1800795, rs1800796, rs1554606, rs1800797, rs2069840, rs12700386, and rs2069861) as Prognostic Markers in Breast Cancer: A Systematic Review, Meta-Analysis, and Network Analysis.

Interleukin-6 (IL-6) has obviously tumor-promoting and tumor-inhibitory effects and can induce an epithelial-mesenchymal transition phenotype in human breast cancer (BC) cells and implicate its potential to promote BC metastasis. Herein, we aimed to evaluate the association of IL-6 variants (rs1800795, rs1800796, rs1554606, rs1800797, rs2069840, rs12700386, and rs2069861) with the susceptibility to BC. The databases of PubMed/Medline, Web of Science, Scopus, and Cochrane Library were searched until December 19, 2022, without any restrictions. The quality assessment of each study was performed based on the Newcastle-Ottawa Scale tool. The Review Manager 5.3 software presented the effect sizes including odds ratio (OR) along with a 95% confidence interval (CI). Both publication bias and sensitivity analyses were carried out by the Comprehensive Meta-Analysis version 2.0 software. A total of 2,508 records were identified among databases and at last, 27 articles were entered into the meta-analysis. Seven polymorphisms of IL-6 were entered into the analyses. Just rs1800797 polymorphism in the dominant model (OR = 1.51; 95% CI = 1.15-2.00; P = 0.003) and rs2069840 polymorphism in heterozygous (OR = 0.89; 95% CI = 0.81-0.97; P = 0.008) and dominant (OR = 0.91; 95% CI = 0.84-0.99; P = 0.02) models had a significant association with the BC risk. In conclusion, among 7 polymorphisms and despite a few included cases, the present meta-analysis recommended that the AA+GA genotype of rs1800797 polymorphism had a significantly elevated risk and the GC and the CC+GC genotypes of rs2069840 polymorphism had a protective role in the BC patients.

The p53/ZEB1-PLD3 feedback loop regulates cell proliferation in breast cancer

Breast cancer is the most prevalent cancer globally, endangering women’s physical and mental health. Phospholipase D3 (PLD3) belongs to the phosphodiesterase family (PLD). PLD3 is related to insulin-mediated phosphorylation of the AKT pathway, suggesting that it may play a role in the occurrence and development of malignant tumors. This study may further explore the molecular mechanism of PLD3 inhibiting breast cancer cell proliferation. In this study, we demonstrated that PLD3 and miR-6796 are co-expressed in breast cancer. PLD3 can bind with CDK1 and inhibit its expression, leading to mitotic arrest and inhibiting breast cancer proliferation. Wild-type p53 regulates PLD3 and miR-6796 expression by competitively binding to the PLD3 promoter with ZEB1. DNMT3B, as the target gene of miR-6796, is recruited into the PLD3 promoter by combining with ZEB1 to regulate the DNA methylation of the PLD3 promoter and ultimately affect PLD3 and miR-6796 expression. In conclusion, we revealed the role and molecular mechanism of PLD3 and its embedded miR-6796 in breast cancer proliferation, providing clues and a theoretical foundation for future research and development of therapeutic targets and prognostic markers for breast cancer.

Development of lymph node metastasis-related prognostic markers in breast cancer

BackgroundLymph node metastasis (LNM) from Breast cancer (BC) is commonly seen in BC progression. Currently, the identification of genes linked with LNM in BC remains in mystery. MethodsGenes related to BC LNM were screened, and a risk model was constructed based on LASSO-Cox analysis. Combined with the Kaplan-Meier curve, the ability of riskscore to distinguish different baseline characteristics was evaluated, and model was verified by the receiver operating characteristic (ROC) curve. The expression levels of prognostic marker genes were analyzed by qRT-PCR and western blot (WB). ResultsA higher survival rate and longer survival time in low-risk BC patients. The 1, 3 and 5 year AUC values of the training set were 0.79, 0.74, and 0.73, respectively. Results for the validation set was similar to the training set. The differentially expressed genes between the high- and low-risk groups were significantly enriched in immune pathways. In addition, the low-risk group had higher levels of immune infiltration. qRT-PCR and WB results showed that in BC, CDH10, SMR3A, POU3F2, and FABP7 were down-regulated, and LHX1 was up-regulated. ConclusionsWe built a prognostic model of BC based on LNM-related genes, proffering evaluation for prognosis and precise cure of BC. SignificanceAt present, the genes related to lymph node metastasis in BC are still largely unknown and need to be further explored. Searching for potential lymph node metastasis-related genes of BC will provide meaningful biomarkers for BC treatment. Based on TCGA-BRCA data, we established an effective 11-gene prognostic risk model that could predict patient outcomes independently. Our model could classify BC patients and distinguish patients with poor prognosis effectively. Besides, the feature genes we identified might exert a predictive function in immunotherapy. The results of this study provide a new reference for the prognosis and treatment of BC patients with lymph node metastasis.