Breast Cancer Tissues 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.

A correlation study of adhesion G protein-coupled receptors as potential therapeutic targets for breast cancer.

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. UALCAN, GEPIA, Kaplan-Meier Plotter, MethSurv, cBiopportal, String, GeneMANIA, DAVID, Timer, Metascape, and qPCR were applied in this work. 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 andmetabolic energy reserves. Moreover, aGPCRs may exert influence or actively participate in the development of BRCA through their impact on immune status. aGPCRs, particularly ADGRF2 and ADGRF4, hold promise as immunotherapeutic targets and prognostic biomarkers in BRCA.

Chemopreventive effects of atractylenolide-III on mammary tumorigenesis via activation of the Nrf2/ARE pathway through autophagic degradation of Keap1

The incidence of breast cancer is increasing annually, making it a major health threat for women. Chemoprevention using natural, dietary, or synthetic products has emerged as a promising approach to address this growing burden. Atractylenolide-III (AT-III), a sesquiterpenoid present in various medicinal herbs, has demonstrated potential therapeutic effects against several diseases, including tumors, nonalcoholic fatty liver disease, and cerebral ischemic injury. However, its impact on breast cancer chemoprevention remains unexplored. In this study, we used an N-methyl-N-nitrosourea (NMU)-induced rat breast cancer model and 17β-estradiol (E2)-treated MCF-10A cells to evaluate the chemopreventive potential of AT-III on mammary tumorigenesis. AT-III inhibited mammary tumor progression, evidenced by reduced tumor volume and multiplicity, prolonged tumor latency, and the reversal of NMU-induced weight loss. Furthermore, AT-III suppressed NMU-induced inflammation and oxidative stress through the Nrf2/ARE pathway in breast cancer tissues. In vitro, AT-III effectively suppressed E2-induced anchorage-independent growth and cell migration in MCF-10A cells. Nrf2 knockdown attenuated the protective effects of AT-III, highlighting the pivotal role of Nrf2 in AT-III-mediated suppression of tumorigenesis. The mechanism involves the induction of Nrf2 expression by AT-III through the autophagic degradation of Kelch-like ECH-associated protein 1 (Keap1). Overall, the results of this study indicate that AT-III is a promising candidate for breast cancer chemoprevention and provide valuable insights into its molecular interactions and signaling pathways.

LncRNA AFAP1-AS1 mediates breast cancer cell proliferation and migration through the miR-21/PTEN axis.

LncRNAs play various effects, mostly by sponging with miRNAs. Based on public databases integrating bioinformatics analyses and further validation in breast cancer(BC) tissue and cell lines, the effect of lncRNA AFAP1-AS1 on breast cancer cell proliferation and migration was verified. It might work via the miR-21/PTEN axis. The expression of AFAP1-AS1, which was significantly upregulated in BC tissues and cell lines, was correlated with old age and lymph node metastasis of patients with BC. Knockdown of AFAP1-AS1 inhibited the proliferation and migration of BC cells in vitro and in vivo. And downregulated miR-21 expression and upregulated PTEN expression additionally. Mechanistically, the knockdown of lncRNA AFAP1-AS1 upregulated PTEN expression and consequently attenuated miR-21-mediated enhanced BC cell proliferation and migration. LncRNA AFAP1-AS1 is a potential prognostic biomarker for BC patients.

Differential expression of NAT1 pharmacogene in hormone receptor positive vs. negative female breast tumors may affect drug treatment.

Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N -acetyltransferase type 1 in estrogen receptor positive breast tumors, and this association has been linked to patient chemoresistance and response to tamoxifen. We probed the expression of NAT1 , using quantitative reverse transcription PCR to screen clinically characterized breast cancer tissue cDNA arrays. Primers detecting all NAT1 alternative transcripts were used, and the protocol and results are reported according to consensus guidelines. The clinical information about 166 tumor samples screened is provided, including tumor stage, estrogen and progesterone receptor status and HER2 expression. NAT1 was found to be significantly ( P < 0.001) upregulated in hormone receptor positive vs. negative tumors. No correlation was apparent between NAT1 and tumor stage or HER2 expression. Our findings demonstrate a strong correlation between the expression of NAT1 and steroid hormone receptors in breast tumors, supporting its possible utility as a pharmacogenetic biomarker or drug target. Of the two polymorphic NAT genes, NAT1 is the one primarily expressed in breast tissue, and is subjected to regulation by two differential promoters and more than one polyadenylation signal. Hormonal factors may enhance NAT1 gene expression at the transcriptional or epigenetic level, and tamoxifen has additionally been shown to inhibit NAT1 enzymatic activity. The outcome of tamoxifen treatment is also more favorable in patients with NAT1 overexpressing tumors. The study adds to the growing body of evidence implicating NAT1 in breast cancer and its pharmacological treatment.

Formulation of quinoa oil-alginate loaded nanoemulsion and its anticancer efficacy as a therapy for chemically induced breast cancer.

Quinoa seeds (Chenopodium quinoa Willd.) have gained interest due to their naturally occurring phytochemicals and antioxidants. They possess potent anticancer properties against human colorectal cancer. Fatty acids in quinoa oil were studied using gas chromatography-mass spectrometry. Rats were used to test the acute oral toxicity of the nanoemulsion loaded with sodium alginate. The DPPH radical scavenging method was employed to assess the nanoemulsion's ability to scavenge free radicals. It was examined the in vivo anticancer potential of quinoa oil nanoemulsion on rats with breast cancer induced by 7, 12-dimethylbenz (a) anthracene (DMBA). DMBA-breast cancer models received daily quinoa oil nanoemulsions for 30 days. The anticancer effect of the nanoemulsion was assessed by measuring ROS, protein carbonyl, gene expression of anti-oncogenes, and histopathological analysis. Supplying quinoa oil nanoemulsion significantly reduced the increase in serum ROS and PC levels induced in breast cancer tissue. The expression levels of antioncogenes in breast cancer tissue were decreased by the quinoa oil nanoemulsion. Nanoemulsions also improved the cellular morphology of breast tumors. The study results indicate that quinoa oil nanoemulsion has anticancer activity against breast cancer, effectively modulating oxidative stress markers, anti-oncogene expressions, and tissue architecture. It can be inferred from the results that quinoa oil nanoemulsion is a chemoprotective medication that may hinder breast cancer progression in rats.

Preliminary exploration of Trop2 ADC in combination with immune checkpoint inhibitors in the different molecular subtypes of invasive breast carcinoma.

e12558 Background: Human trophoblastic cell surface antigen 2 (Trop2) is a transmembrane protein overexpressed in breast cancer tissues. However, it is present at minimal levels in adult somatic tissues, making it an ideal target for treatment with antibody-drug conjugates (ADCs). Sacituzumab govitecan, an anti-Trop2 ADC, has been approved for the treatment of triple-negative breast cancer and urothelial cancer. Recent studies have demonstrated that human cytotoxic T lymphocytes can recognize Trop2. Accordingly, we aimed to assess the role of Trop2 in the tumor immune activity of different subtypes of breast cancer, and laying the foundation for further studies on the efficacy of the combination of Trop2 ADC and immune checkpoint inhibitors in breast cancer. Methods: We retrospectively retrieved tissues from 152 invasive breast carcinoma of no special type and 111 benign breast tumor tissues and undergoing surgical resection at our institution from 2018 to 2023. Immunohistochemistry was used to detect Trop2 and PD-L1 expression and lymphatic invasion in patients, and their correlations with clinicopathological factors were analyzed. Trop2 expression was evaluated using the H-score. The median as the cut-off value, a score of 0–240 indicated low expression, and 240–300 indicated high expression. Cases with CPS ≥ 1% were considered positive for PD-L1. Results: The expression was Trop2 in breast cancer tissues than in benign tumor tissues (P&lt;0.0001). Immune infiltration analysis suggested that Trop2 expression was correlated with immune cell infiltration and the abundance (P&lt;0.001). Kaplan–Meier plotter analysis demonstrated that high Trop2 expression was related to poor prognosis in patients with triple-negative breast cancer (overall survival: HR=1.53, P=0.029; relapse-free survival: HR=1.26, P=0.045). In contrast, Trop2 expression was not significantly associated with prognosis in other breast cancer subtypes. However, there was no statistically significant correlation found between PD-L1 expression and Trop-2 expression in breast cancer. Conclusions: The findings suggest that Trop2 correlates with poor prognosis and immune cell infiltration in breast cancer. This indicates the role of Trop2 as a potential prognostic biomarker, laying the foundation for further research focusing on the immune regulatory role of Trop2. [Table: see text]

Silencing PCMT1 enhances the sensitivity of breast cancer cells to paclitaxel through the PI3K/Akt/STMN1 pathway.

This study aimed to investigate whether silencing Protein L-isoaspartate (D-aspartate) O-methyltransferase (PCMT1) expression can enhance the sensitivity of breast cancer cells to paclitaxel and its possible mechanism. Tumor tissues and adjacent histologically normal tissues were collected from patients with breast cancer admitted to our hospital. Human normal breast epithelial cells MCF10A, human breast cancer cells MCF-7, and paclitaxel-resistant breast cancer cells MCF-7/PR were purchased. MCF-7/PR cells were further grouped into negative control (NC) group, si-PCMT1 group (transfected with si-PCMT1), 740Y-P group (treated with 740Y-P, an activator of phosphatidylinositol 3-kinase (PI3K)/ v-Akt Murine Thymoma Viral Oncogene (AKT) signaling pathway), and si-PCMT1 + 740Y-P group (transfected with si-PCMT1 and then treated with 740Y-P). The expression level of PCMT1 in tissues and cells was detected by quantitative real-time polymerase chain reaction (qRT-PCR). Western blot analysis was used to detect the protein expression level of PCMT1 in tissues and cells as well as the protein level of p-PI3K, PI3K, p-Akt, Akt, and Stathmin1 (STMN1) in cells. 3-(4,5)-dimethylthiahiazo(-z-y1)-3,5-di-phenytetrazoliumromide (MTT) and colony formation assays were used to determine cell viability, scratch assay was used to assess the migration ability of cells, and Transwell assay was used to assess the invasion ability of cells. The expression of PCMT1 was remarkably up-regulated in breast cancer tissues and MCF-7/PR cells. Silencing PCMT1 expression significantly inhibited the proliferation, migration, and invasion of MCF-7/PR cells, and alleviated the resistance of cancer cells to paclitaxel. Additionally, silencing PCMT1 expression also inhibited the activation of PI3K/Akt/STMN1 pathway in MCF-7/PR cells, while activating PI3K/Akt/STMN1 pathway significantly reversed the effect of silencing PCMT1 expression on MCF-7/PR cells. PCMT1 is highly expressed in breast cancer tissues and MCF-7/PR cells, and silencing PCMT1 expression can not only inhibit the development of breast cancer but also enhance paclitaxel sensitivity. Its mechanism of action may be achieved by inhibiting PI3K/Akt/STMN1 signaling.

Recombinant Human IL-32θ Induces Polarization Into M1-like Macrophage in Human Monocytic Cells.

The tumor microenvironment (TME) is formed by several immune cells. Notably, tumor-associated macrophages (TAMs) are existed in the TME that induce angiogenesis, metastasis, and proliferation of cancer cells. Recently, a point-mutated variant of IL-32θ was discovered in breast cancer tissues, which suppressed migration and proliferation through intracellular pathways. Although the relationship between cancer and IL-32 has been previously studied, the effects of IL-32θ on TAMs remain elusive. Recombinant human IL-32θ (rhIL-32θ) was generated using an Escherichia coli expression system. To induce M0 macrophage polarization, THP-1 cells were stimulated with PMA. After PMA treatment, the cells were cultured with IL-4 and IL-13, or rhIL-32θ. The mRNA level of M1 macrophage markers (IL-1β, TNFα, inducible nitric oxide synthase) were increased by rhIL-32θ in M0 macrophages. On the other hand, the M2 macrophage markers (CCL17, CCL22, TGFβ, CD206) were decreased by rhIL-32θ in M2 macrophages. rhIL-32θ induced nuclear translocation of the NF-κB via regulation of the MAPK (p38) pathway. In conclusion, point-mutated rhIL-32θ induced the polarization to M1-like macrophages through the MAPK (p38) and NF-κB (p65/p50) pathways.

Prediction of CCL2 in breast cancer based on enhanced MRI radiomics model with integrated bioinformatics analysis and machine learning.

e12509 Background: Breast cancer is the most common malignant tumor in women. According to the 2023 Cancer Statistics Report, breast cancer has surpassed lung cancer to become the most common malignant tumor. Its incidence and mortality both rank first among female malignant tumors. This study proposes non-invasive prediction of CCL2 mRNA expression in breast cancer tissue through enhanced MRI radiomics, while integrating bioinformatics analysis to explore the underlying molecular mechanisms and their association with the immune microenvironment. Methods: Excluding criteria were applied to select primary solid tumor samples with RNA-seq data (n = 840) from the TCGA-BRCA database. Enhanced MRI imaging data (n = 98) intersecting with the TCGA-BRCA data were obtained from TCIA-BRCA. The imaging data were randomly divided into training (n = 70) and testing sets (n = 28) in a 7:3 ratio. A feature subset was selected, and a model was constructed using the support vector machine (SVM) algorithm in the training set. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and the Hosmer-Lemeshow goodness-of-fit test. The calibration of the radiomics prediction model was assessed using the Brier score, and the clinical utility of the radiomics prediction model was demonstrated by drawing decision curves (DCA). External validation of the model was performed using a validation set. The radiomics score (RS) was calculated using the LR radiomics model and categorized as a binary variable (Low/High RS). Subsequently, KEGG pathway, immune-related genes, and gene mutation analysis were conducted based on the CCL2 high and low expression levels. Results: A total of 1810 radiomic features were obtained with ICC values ≥ 0.75. Subsequently, the mRMR (Maximum relevance, minimum redundancy) method, and the optimal 7 feature subsets were further identified using the RFE (Recursive feature elimination) algorithm. The SVM model demonstrated favorable predictive performance, with an AUC value of 0.822 for the training set and 0.779 for the validation set, as indicated by the ROC curve. Calibration curve and Hosmer-Lemeshow goodness-of-fit test revealed good consistency between the radiomic predictive model for the probability of high gene expression and the actual values (P &gt; 0.05). Additionally, the decision curve analysis (DCA) demonstrated high clinical utility of the model. The TNF-α signaling pathway was found to influence the occurrence and development of breast cancer. Furthermore, the degree of Plasma Cell infiltration was observed to be highest in breast cancer. Conclusions: The CCL2 model constructed using a combination of machine learning and radiomic features, can non-invasively predict the prognosis of breast cancer treatment and exhibits good generalizability.

FCM-DCS: Fuzzy C means distorted contour-based segmentation model for breast cancer detection

Breast cancer (BC) is a commonly diagnosed cancer among women nowadays. The cancer cells in the breast tissues are known as BC. Comprehensive research on early-stage BC detection helped to increase the survival rate and reduce the amortality rate associated with this disease. Mammogram scan analysis is a commonly used breast tissue visualization method. This image data is analyzed adequately for accurate BC diagnosis. Region of interest (ROI) identification is crucial in an image-based BC detection system. The ROI detection helps to segment the cancer tissues from the mammogram images by analyzing the heterogeneity among cancerous and normal breast tissues. Early-stage BC issues have homogeneous features as normal breast tissues. So, it is an open challenge for the researchers to develop a more accurate segmentation method during the automatic BC stages detection system. This study introduced fuzzy C means (FCM) distorted contour-based segmentation (FCM DCS) method to address the real detection issues in present studies. It uses the distorted contour (DC) based method to identify the contour of the cancer tissue from mammogram images. The DC method is performed with the help of FCM to identify the cancer tissues. Moreover, a histogram and adaptive equalization method were utilized to reduce image noise and preserve the edge features. The result analysis shows that the FCM-DC methods achieved a maximum accuracy rate (98.76 %) than comparison methods in BC detection.

Investigating the Role of Fat Mass and Obesity-Associated (FTO) Single Nucleotide Polymorphisms and Methylation in Breast Cancer.

Background Fat mass and obesity-associated (FTO) protein is an mRNA demethylase enzyme essential for active genome regulation. The FTO gene codes for a protein that is part of the methylosome complex and has a regulatory role in cancer development. Some studies have shown a relationship between FTO and cancer, where single nucleotide polymorphisms (SNPs) may have some impact on cancer risk. The present study aimed to evaluate the risk of FTO polymorphisms rs9939609, rs1477196, and rs9930506; analyze the methylation status of FTO promoters among Mexican women with breast cancer (BC); and investigate by in silico analysis the methylation status in the region near these polymorphisms. Methods A total of 157 BC patients and 137 healthy controls were genotyped for rs9939609, rs1477196, and rs9930506 FTO polymorphisms by TaqMan SNP Genotyping Assays. Promoter methylation was analyzed by sodium bisulfite and methylation-specific polymerase chain reaction (MSP) for 78 tissue samples. An in silico analysis using The Cancer Genome Atlas Program (TCGA) database was employed to investigate the methylation state in promoter and near polymorphism locations and its relation to survival. Results The AG genotype of FTO rs9930506 was associated with BC protection (P= 0.0025; adjusted OR, 0.27; 95% CI: 0.10-0.70). rs9939609 and rs1477196, according to the results of the present study, had no relation to BC. Promoter methylation status assays by MSP revealed no changes in methylation in BC or healthy tissues. Trying to know more about the methylation in promoters and near polymorphisms' relation to survival, we performed an in silico analysis. Bioinformatics analysis showed a correlation between poor survival and methylation near polymorphisms but not with methylation in the promoter region. Conclusions The AG genotype rs9930506 has a protective function against BC. Whereas high methylation near polymorphisms was related to lower survival, the hypomethylated promoter region does not impact survival.

A blind validation of a deep-learning solution providing HER2, ER, and PR results from H&amp;E-stained breast cancer specimens.

562 Background: Newly diagnosed breast cancer specimens are routinely tested for oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER2) status. This requires additional immunohistochemistry (IHC) +/- in situ hybridisation (ISH) assessment. This can increase laboratory/pathologist workloads and turnaround times. A computer-based approach could help to alleviate these issues. PANProfiler Breast is a deep-learning solution designed to predict ER/PR status and detect HER2 negative cases from whole slide images (WSIs) of haematoxylin and eosin (H&amp;E)-stained breast cancer tissue. Here we present a blind validation of PANProfiler Breast. Methods: Three cohorts of H&amp;E-stained archival breast cancers (400 cases, 692 WSIs) from St James’s University Hospital, Leeds, UK, were assigned for calibration (200 cases, 344 WSIs) and blind validation (200 cases, 348 WSIs). Slides were scanned at 40x magnification on an Aperio GT450 (Leica, Illinois, USA) scanner. PANProfiler returned “Positive”, “Negative” or “Indeterminate” for ER and PR, and “Negative” or “Indeterminate” for HER2. Results were compared to the ER/PR/HER2 status given in the corresponding pathology report. For calibration and blind validation, the WSI(s) corresponding to the IHC/ISH testing block was used for analysis. One case with missing HER2 status was excluded from HER2 analyses. Confusion matrices enabled analysis of concordance. While a conventional Positive/Negative confusion matrix was used for ER/PR, “Negative” results were used as the reference Positive event for HER2. Results: Case concordance for ER and PR status across the three cohorts ranged from 89.74-92.86% and 85.71-90.91% respectively. Additionally, sensitivity for ER ranged from 89.19-100%, with specificity ranging between 62.50-100%. For PR, sensitivity was between 87.50% and 93.48% and specificity between 75.00% and 83.33%. False negative rates for both ER and PR were between 0-10.81% and 6.52-12.50% respectively. Regarding HER2, sensitivity was relatively low, ranging between 30.77% and 37.04%. However, over 90% concordance was seen across all cohorts for cases PANProfiler predicted as HER2 “Negative”. Specificity and positive predictive value were also over 90% throughout the three cohorts. Additionally, false positive rates were 0.00%, 4.35% and 9.52% for HER2 across these same three cohorts. Test replacement rates varied amongst the cohorts with 70-84% for ER, 55-84% for PR and 22-27% for HER2. Conclusions: This blind validation of PANProfiler Breast shows impressive levels of performance for predicting ER and PR status in breast cancer WSIs. For HER2, the technology demonstrated a striking level of confidence for cases predicted as HER2 “Negative”. Further development and analysis are warranted to increase the number of HER2 negative BC WSIs that PANProfiler is able to identify.

LC3AB protein-based gene (PbG) signatures as an indicator of relapse even after achieving pathological complete response.

e12552 Background: The application of tissue-based quantitative protein and morphological profiling of breast cancer tissues combined with RNA sequencing provides a flexible and generally applicable and scalable method to develop Protein-based Gene (PbG) signatures with significant prognostic value. Methods: A racially and subtype diverse breast cancer cohort (N=555) with available subset of RNA-seq data was used to develop gene expression-based signatures by stratifying patients according to protein expression (IHC) based on survival information and tumor lymphocyte infiltration (TILs) using survival-derived cutoff values. The predictive value of these signatures was then compared with other popular biomarkers scoring systems such as ROR.score, and OncotypeDx (Gene 21). Here we describe the predictive value of these signatures is evaluated by logistic regression modeling of publicly available gene expression data (N=996) from patients receiving neoadjuvant chemotherapy (anthracycline +/- taxane) with a final validation in an independent cohort (N=443) receiving similar therapy. Results: A model of PbG-derived signature from Kaiso, LC3A/B IHC and quantitative TIL-measurements together with ROR score, MAPK, PTEN, Immune and Gene21 signatures show significant prediction of distant metastasis-free survival in all patients: (DMFS, AUC= 0.737, 95% CI: 0.665- 0.819); and in non-pCR patients DMSF (AUC= 0.71, 95% CI: 0.633-0.773). When examining the role of all those markers among the patients who achieved the pCR and had relapse, the LC3A/B PbG-derived score was found to be highly predictive of those patients who would not achieve pCR and ultimately have recurrent disease. Conclusions: PbG-based signatures utilizing on LC3A/B protein values offer a novel and clinically relevant predictive biomarker of response to therapy and relapse in breast cancer patients.

Nectin-4 expression in primary breast cancer and associated clinical outcomes.

570 Background: Antibody-drug conjugates (ADC) selectively deliver chemotherapy to tumor cells expressing a target antigen. Currently approved ADCs in breast cancer target HER2 or Trop-2. Enfortumab vedotin, an ADC targeting Nectin-4, a cell adhesion molecule, is approved in advanced/metastatic urothelial cancer. This study evaluated the expression landscape of Nectin-4 in breast cancer and its association with clinical outcomes. Methods: Processed mRNAseq data was assessed for expression of the gene encoding Nectin-4 in primary breast cancer tissue and adjacent normal breast tissue from The Cancer Genome Atlas (TCGA), and normal tissue from the Genotype-Tissue Expression (GTEx) Project. Low gene expression was determined as &lt;100 transcripts per million (TPM). TCGA samples had been annotated for putative copy-number alterations using GISTIC 2.0; genes with a score of 2 were marked as amplified. Multivariable Cox regression analysis was used to analyze the association of low vs medium/high gene expression with disease-free survival (DFS) and overall survival (OS), adjusting for age, stage, and subtype. Results: RNA-Seq data was available for 1086 patients with primary breast cancer, including known hormone receptor positive (HR+)/HER2- (n=530), HER2+ (n=112), and triple negative breast cancer (TNBC) (n=120). NECTIN4was amplified in 15% of cases (n=165): 15% (n=78) in HR+, 15% (n=17) in HER2+ and 21% (n=25) in TNBC. NECTIN4 expression was medium/high in 356 (33%) patients: 149 (28%) HR+/HER2- (median 77.8 TPM, IQR 50.1-116.5), 32 (29%) HER2+ (median 73.7 TPM, IQR 51.9-107.8), and 59 (49%) TNBC (median 99.7 TPM, IQR 57.8-148.3). Median expression in normal breast tissue was 47 TPM (TCGA) &amp; 16.74 TPM (GTEx), and highest in normal skin at 205 TPM. In multivariable analysis, medium/high NECTIN4 expression was associated with worse OS (HR 1.96, 95% CI 1.32-2.99, p&lt;0.001). As a continuous variable, increasing NECTIN4 expression levels were associated with worse OS. After correcting for age, stage and subtype, for each 10-unit increase in NECTIN4TPM, the risk of death increased by 5% (HR 1.0050, 95% CI 1.0028 - 1.0072, p &lt; 0.001). Conclusions: NECTIN4 expression was higher in TNBC and associated with worse overall survival. The high expression level in normal skin possibly contributes to the cutaneous toxicity associated with enfortumab vedotin approval and requires careful consideration as ADCs targeting Nectin-4 are developed to target breast cancer.

First-in-human autologous CAR-T for metastatic breast cancers to target growth factor receptor MUC1*.

TPS2683 Background: MUC1 has been one of the most important therapeutic targets for solid tumor cancers for the past 20+ years. However, no MUC1 targeted therapeutic has yet succeeded or has been granted FDA approval. Although MUC1 is overexpressed on cancer cells, it is also widely expressed on normal epithelial cells. We previously reported that a MUC1 transmembrane cleavage product, MUC1* (muk 1 star), is a Class I growth factor receptor activated by ligand-induced dimerization of its truncated extra cellular domain. We generated monoclonal antibodies that recognize the specific conformation that is created when MUC1 is cleaved by specific enzymes expressed in the tumor microenvironment. 93% of human breast cancer tissues are recognized by one of these antibodies, huMNC2, which importantly does not bind to normal MUC1. We have incorporated this antibody into two CARs, wherein one bears the “1XX” mutations in CD3z that greatly increase CAR-T cell persistence, inhibit exhaustion and enable the killing of low antigen expressing cancer cells. Methods: Phase I for huMNC2-CAR44, an autologous frozen product, opened January, 2020, but as a 1st-in-human trial was paused during COVID. All patients receive 300 mg/m2 cyclophosphamide and 30 mg/m2 fludarabine for 3 days prior to CAR-T treatment. Dose escalation from 3.3x105 – 1x107 CAR+ cells/kg follows a standard 3 + 3 design. In addition to standard organ function inclusion criteria, the trial was first open to breast cancer patients whose cancer had progressed after at least 2 or 3 prior therapies while metastatic, yet there was no limit on the number of prior therapies. A recent patient biopsy had to be at least 30% positive for MUC1* in a CLIA validated IHC assay. Importantly, there were no limits on the vein-to-vein time. Dose levels 1 and 2 for huMNC2-CAR44 were completed without DLTs. Phase I for huMNC2-CAR22, which bore the 1XX mutations in CD3z to increase persistence and increase the killing of low antigen expressing cells opened September, 2023. Based on responses of initial huMNC2-CAR44 patients, inclusion criteria were amended to an Enrichment Trial Design. The number of prior therapies was limited to less than or equal to 10. Anticipated survival at the time of product infusion should be at least 3 months. Vein-to-vein time, which historically had been 15-16 days at one site and as high as 83 days at another site, would be targeted to 16- 22 days. The tumors of eligible patients need to have a MUC1* membrane positive H-score equal to or greater than 120 out of a possible 300, defined as high MUC1* positivity. Based on IHC analysis of human breast cancer TMAs, the H-score restriction would include roughly 40% of breast cancers. The increased ability of huMNC2-CAR22 to kill low antigen expressing cancer cells may support future studies of patients expressing low levels of MUC1*. Clinical trial information: NCT04020575 .

MicroRNAs as promising biomarkers and potential therapeutic agents in breast cancer management: a comprehensive review

Breast cancer (BC), a complex and varied ailment, poses a significant global health burden. MicroRNAs (miRNAs) have emerged as vital regulators in BC progression, with potential implications for diagnosis and treatment. This review aims to synthesize current insights into miRNA dysregulation in BC. MiRNAs, small RNA molecules, govern gene expression post-transcriptionally and are implicated in BC initiation, metastasis, and therapy resistance. Differential expression of specific miRNAs in BC tissues versus normal breast tissue sheds light on underlying molecular mechanisms. MiRNAs also offer promise as diagnostic biomarkers due to their stable nature, accessibility in bodily fluids, and altered expression patterns in early-stage disease, augmenting conventional diagnostic methods. Beyond diagnosis, miRNAs also hold promise as therapeutic targets in BC. By modulating the expression of specific dysregulated miRNAs, it may be possible to restore normal cellular functions and overcome treatment resistance. However, several challenges need to be addressed before miRNA-based therapies can be translated into clinical practice, including the development of efficient delivery systems and rigorous evaluation through preclinical and clinical trials. MiRNAs represent a promising avenue in BC research, offering potential applications in diagnosis, prognosis, and therapeutic interventions. As our understanding of miRNA biology deepens and technology advances, further research and collaborative efforts are needed to fully exploit the diagnostic and therapeutic potential of miRNAs in BC management. Ultimately, the integration of miRNA-based approaches into clinical practice may lead to more personalized and effective strategies for combating this devastating disease.

Employing semi-quantitative methods to classify breast cancer markers (ER, PR, HER2, Ki67) expression, using the RT-qPCR based APIS Breast Cancer Subtyping Kit.

e13091 Background: Accurate determination of breast cancer (BC) biomarker status is crucial for guiding patient management decisions. Histopathologists commonly use semi-quantitative scoring systems to convert subjective observations of immunohistochemistry (IHC) marker expression into quantitative data, allowing a more detailed categorisation of marker status. The APIS Breast Cancer Subtyping Kit (BCSK) is an in vitro diagnostic test, detecting the relative expression of seven mRNA target genes ( ESR1, PGR, ERBB2, MKI67, CCNA2, PCNA, and KIF23) from invasive BC tissue. The APIS BCSK reports a positive/negative result for each biomarker alongside a molecular classification. Here, we demonstrate that by implementing additional RNA expression cut-off values, it is possible to generate a semi-quantitative result by further stratifying target expression into negative, low, medium, and high status using the APIS BCSK. Methods: 368 formalin-fixed paraffin-embedded (FFPE) samples of BC cases were used, obtained by core needle biopsy or resection. IHC scores were correlated with copy numbers as determined by an independently validated digital PCR (dPCR) assay and were used to set copy number cut-off values corresponding to IHC classification. The generated dPCR cut-off values were used to evaluate the corresponding ∆Ct values (RNA expression results derived from the APIS BCSK). For each target, three ΔCt cut-offs were established, facilitating classification into negative, low, medium, and high expression. Results: The semi-quantitative approach successfully classified target expression levels ( ESR1, PGR, ERBB2, MKI67). Overlap in ΔCt values was observed in central IHC categories for all targets, likely due to tumor heterogeneity and differing measurement methods for IHC and RT-qPCR. Despite these discrepancies, the derived cut-off values define a semi-quantitative scale for each target (Table). Conclusions: This study has established a methodology that utilises target copy number values and IHC protein quantification to establish ΔCt cut-off points. For each target we have defined four distinct groups as negative, low, medium, and high expression. This approach provides a semi-quantitative scale for evaluating each target with the APIS BCSK and serves as a valuable tool for classifying and understanding target expression levels. [Table: see text]

EXPRESSION OF SPP1 AND SPARC GENES IN TUMOR TISSUE OF PATIENTS WITH BREAST CANCER.

Breast cancer (BCa) is one of the most common oncological diseases in women in Ukraine and worldwide, which determines the need to search for new diagnostic and prognostic markers. In this aspect, the study of multicellular proteins, in particular osteopontin (OPN) and osteonectin (ON), in BCа tissue is relevant. The aim of the work was to investigate the expression of SPP1 and SPARC at the mRNA and protein levels in BCa tissue and to assess their relationship with the main clinicopathological BCa characteristics and the survival rates of patients. The work was based on the analysis of the results of the examination and treatment of 60 patients with stage II-III BCa and 15 patients with breast fibroadenomas. SPP1 and SPARC mRNA levels were determined by real-time PCR. The study of the expression of protein products of the SPP1 and SPARC genes was carried out by the immunohistochemical method. We have established that the BCa tissue was characterized by 3.5 (p < 0.05) and 7.4 (p < 0.05) lower levels of SPP1 and SPARC mRNA, respectively, compared to the tissue of benign neoplasms, while OPN and ON expression levels were 1.6 (p < 0.05) and 5.6 (p < 0.05) times higher, respectively, compared to fibroadenoma tissue. The analysis of the relationship between the expression of SPP1 and SPARC at the protein and mRNA levels in BCa tissue and the main clinicopathological BCa characteristics revealed its dependence on the presence of metastases in regional lymph nodes, differentiation grade, and the molecular BCa subtype. Also, high expression levels of SPP1 and OPN were associated with worse patient survival rates. The obtained results indicate the perspective of using SPP1 and SPARC expression indices in BCa tissue to assess the aggressiveness of the cancer course and optimize the tactics of treating patients.

Systematic proteomics analysis revealed different expression of laminin interaction proteins in breast cancer: lower in luminal subtype and higher in claudin-low subtype.

Breast cancer is a major public health concern. Proteomics enables identification of proteins with aberrant properties. Here, we identified proteins with abnormal expression levels in breast cancer tissues and systematically analyzed and validated the data to locate potential diagnostic and therapeutic targets. Protein expression level in breast cancer tissues and para-carcinoma tissues were detected by Isobaric Tags for Relative and Absolute Quantification (iTRAQ) technology and further screened through Gene Expression Profiling Interactive Analysis (GEPIA) database. Cellular components, protein domain and Reactome pathway analysis were performed to screen functional targets. Abnormal expression levels of functional targets were validated by Oncomine database, quantitative real time polymerase chain reaction (qRT-PCR) and proteomics detection. Protein correlation analysis was performed to explain the abnormal expression levels of potential targets in breast cancer. Overall, 207 and 207 proteins were up- and down-regulated, respectively, in breast cancer tissues, and approximately 50% were also detected in the GEPIA database. The overlapping proteins were mainly extracellular proteins containing epidermal growth factor-like domain in leukocyte adhesion molecule (EGF-Lam) domain and enriched in laminin interaction pathway. Moreover, the downregulated laminin interaction proteins could be functional targets, which were also validated through Oncomine-Richardson and Oncomine-Curtis database. However, the lower expression level of laminin interaction proteins only fit for luminal breast cancer cells with no or low metastasis ability because the proteins achieved higher expression level in more invasive claudin-low breast cancer cells. In addition, when compared with corresponding in situ carcinoma tissues, above-mentioned proteins also showed higher expression levels in invasive carcinoma tissues. Finally, we have revealed the negative correlation between the laminin interaction proteins and the claudins. The laminin interaction protein, especially for laminins with β1 and γ1 subunits and their integrin receptors with α1 and α6 subunits, showed lower expression levels in luminal breast cancer with no or lower metastatic ability, but showed higher expression levels in claudin-low breast cancer with higher metastatic ability; and their higher expression could be related to the low claudin expression.