Marker In Breast Cancer Research Articles

An institutional analysis of the correlation between KI 67 index and other prognostic markers in invasive breast cancer in northern province, Sri Lanka

An institutional analysis of the correlation between KI 67 index and other prognostic markers in invasive breast cancer in northern province, Sri Lanka

Measuring of serum taurine and beta endorphin in women as a pre-early marker for diagnosis of cancer breast

Objective: Uses of serum level of taurine and beta endorphin as early marker for diagnostic of breast cancer. Method: We selected our patients from Bahia hospital and cancer institute of Cairo university mainly suffered from positive family history of cancer breast ,acute and chronic mastitis and all women presented with benign mass (fibroma/lipoma) and different stages of cancer breast. We measure serum beta endorphin and taurine, beside complete blood picture, liver function ,kidney function and glucose in blood in all of our patients. Result: The data showed highly significant change in liver &kidney function between frank control and stages of cancer(p>0.05) that are clearly at latest stages after doses of chemotherapy, but there are slightly change between inflammation and benign. After we finished all result, we found that there were slightly change of beta-endorphin and taurine at inflammation and benign but further change at stage 1,2 that are continuously change to latest stage Conclusion: Decreasing of serum taurine level &increasing of serum beta endorphin level considered as a highly sensitive per early marker for breast cancer.

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.

TRPS1 is a highly sensitive marker for breast cancer: A tissue microarray study evaluating more than 19,000 tumors from 152 different tumor entities

Abstract Introduction/Objective TRPS1 (Trichorhinophalangeal syndrome 1) is a nuclear protein expressed in breast epithelial cells. TRPS1 immunohistochemistry (IHC) has thus been suggested as a marker for breast cancer. However, reports on TRPS1 positivity in other cancer types are piling up. Methods/Case Report To comprehensively determine the diagnostic utility of TRPS1 IHC, tissue microarrays containing 19,201 samples from 152 different tumor types and subtypes were analyzed. GATA3 IHC data were available from 11,891 of these tumors from a previous study. Results (if a Case Study enter NA) TRPS1 positivity occurred in 86 of 152 tumor categories of which 36 contained at least one strongly positive case. TRPS1 staining predominated in various types of breast carcinomas (51%-100%) and was also seen in various subtypes of soft tissue tumors (up to 100%), salivary gland tumors (up to 46%), squamous cell carcinomas (up to 35%), and gynecological cancers (up to 40%) as well as in other tumors. TRPS1 positivity occurred in only 1.8% of 1,083 urothelial neoplasms. Positivity for both TRPS1 and GATA3 occurred in 47.4%-100% of breast cancers, up to 30% of salivary gland tumors, but in only 29 (0.3%) of 9,835 tumors from 134 other cancer entities. Conclusion Although TRPS1 expression can be seen in many different tumor types, TRPS1 Immunohistochemistry has high utility for the identification of cancers of breast or salivary gland origin, especially in combination with GATA3. The virtual absence of TRPS1 positivity in urothelial neoplasms is useful for the distinction of GATA3 positive urothelial carcinoma from breast cancer.

Compartmental Syndecan-1 (CD138) expression as a novel prognostic marker in triple-negative metaplastic breast cancer

BackgroundMetaplastic breast cancer (MpBC) is rare, aggressive, and mostly triple-negative (TN) subtype of BC. We aimed to investigate the potential prognostic significance of Syndecan-1 (SDC1/CD138) expression in this unique tumor. MethodsArchived charts of 50 TNBC patients [21 MpBC and 29 invasive ductal carcinoma (IDC)] were retrospectively evaluated. Corresponding paraffin blocks were used for immunohistochemical (IHC) staining of SDC1. Compartmental (epithelial membranous, stromal, and cytoplasmic) staining scores were expressed in quartiles (Q) and correlated with disease-free survival (DFS) and overall survival (OS). ResultsThe median follow-up period was 54.6 months (range: 2.2–112.7). MpBC patients showed significantly worse DFS and OS than IDC (p = 0.007 and 0.004, respectively). MpBC demonstrated significantly higher Q4 stromal and membranous SDC1 compared to IDC (p = 0.016 and 0.021, respectively), whereas IDC exhibited significantly higher cytoplasmic Q4 SDC1 than MpBC (p = 0.015). Stromal Q4 SDC1 expression was found to be an independent factor associated with MpBC relative to IDC (OR: 6.7, 95% CI: 1.24–36.90; p = 0.028). Stromal Q4 SDC1 expression was also an independent prognostic parameter for worse DFS and OS compared to Q1–3 in the whole cohort (HR: 4.2, 95% CI: 1.6–10.5; p = 0.003 and HR: 5.8; 95% CI: 2.2–15.3; p < 0.001, respectively). In MpBC, cytoplasmic Q1–3 SDC1 expression was an independent prognostic indicator for worse OS compared with their IDC counterparts (HR: 2.837, 95% CI: 1.048–7.682; p = 0.04). ConclusionThis study suggests, for the first time, that differential expression and localization of SDC1 may contribute to the pathogenesis and prognosis of TN-MpBC. Therefore, targeting SDC1 (CD138) could emerge as a novel therapeutic approach for this devastating disease.

A Prognostic Model of Genetic Markers for Triple-Negative Breast Cancer Based on Machine Learning and Bioinformatics Analysis.

Triple negative breast cancer (TNBC) that has low survival rate and prognosis due to its heterogeneity and lack of reliable molecular targets for effective targeted therapy. Therefore, finding new biomarkers is crucial for the targeted treatment of TNBC. The experimental data from the Cancer Genome Atlas database (TCGA).First, key genes associated with TNBC prognosis were screened and used for survival analysis using a single-factor COX regression analysis combined with three algorithms: LASSO, RF and SVM-RFE. Multi-factor COX regression analysis was then used to construct a TNBC risk prognostic model. Four key genes associated with TNBC prognosis were screened as TENM2, OTOG, LEPR and HLF. Among them, OTOG is a new biomarker. Survival analysis showed a significant effect of four key genes on OS in TNBC patients (P<0.05). The experiment showed that four key genes could provide new ideas for targeting therapy for TNBC patients and improved prognosis and survival.

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.

Unravelling heterogeneous effects of cancer‑associated fibroblasts on poor prognosis markers in breast cancer EM‑G3 cell line: Invitro‑targeted treatment (anti‑IL-6, anti‑VEGF-A, anti‑MFGE8) based on transcriptomic profiling.

Breast cancer is the most frequently diagnosed cancer in women worldwide. Although dramatically increased survival rates of early diagnosed cases have been observed, late diagnosed patients and metastatic cancer may still be considered fatal. The present study's main focus was on cancer‑associated fibroblasts (CAFs) which is an active component of the tumor microenvironment (TME) regulating the breast cancer ecosystem. Transcriptomic profiling and analysis of CAFs isolated from breast cancer skin metastasis, cutaneous basal cell carcinoma, and squamous cell carcinoma unravelled major gene candidates such as IL6, VEGFA and MFGE8 that induced co‑expression of keratins‑8/‑14 in the EM‑G3 cell line derived from infiltrating ductal breast carcinoma. Western blot analysis of selected keratins (keratin‑8, ‑14, ‑18, ‑19) and epithelial‑mesenchymal transition‑associated markers (SLUG, SNAIL, ZEB1, E‑/N‑cadherin, vimentin) revealed specific responses pointing to certain heterogeneity of the studied CAF populations. Experimental invitro treatment using neutralizing antibodies against IL-6, VEGF‑A and MFGE8 attenuated the modulatory effect of CAFs on EM‑G3 cells. The present study provided novel data in characterizing and understanding the interactions between CAFs and EM‑G3 cells invitro. CAFs of different origins support the pro‑inflammatory microenvironment and influence the biology of breast cancer cells. This observation potentially holds significant interest for the development of novel, clinically relevant approaches targeting the TME in breast cancer. Furthermore, its implications extend beyond breast cancer and have the potential to impact a wide range of other cancer types.

AI-enabled routine H&E image based prognostic marker for early-stage luminal breast cancer

Breast cancer (BC) grade is a well-established subjective prognostic indicator of tumour aggressiveness. Tumour heterogeneity and subjective assessment result in high degree of variability among observers in BC grading. Here we propose an objective Haematoxylin & Eosin (H&E) image-based prognostic marker for early-stage luminal/Her2-negative BReAst CancEr that we term as the BRACE marker. The proposed BRACE marker is derived from AI based assessment of heterogeneity in BC at a detailed level using the power of deep learning. The prognostic ability of the marker is validated in two well-annotated cohorts (Cohort-A/Nottingham: n = 2122 and Cohort-B/Coventry: n = 311) on early-stage luminal/HER2-negative BC patients treated with endocrine therapy and with long-term follow-up. The BRACE marker is able to stratify patients for both distant metastasis free survival (p = 0.001, C-index: 0.73) and BC specific survival (p < 0.0001, C-index: 0.84) showing comparable prediction accuracy to Nottingham Prognostic Index and Magee scores, which are both derived from manual histopathological assessment, to identify luminal BC patients that may be likely to benefit from adjuvant chemotherapy.

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.

Exploring Neoadjuvant Chemotherapy, Predictive Models, Radiomic, and Pathological Markers in Breast Cancer: A Comprehensive Review

Breast cancer retains its position as the most prevalent form of malignancy among females on a global scale. The careful selection of appropriate treatment for each patient holds paramount importance in effectively managing breast cancer. Neoadjuvant chemotherapy (NACT) plays a pivotal role in the comprehensive treatment of this disease. Administering chemotherapy before surgery, NACT becomes a powerful tool in reducing tumor size, potentially enabling fewer invasive surgical procedures and even rendering initially inoperable tumors amenable to surgery. However, a significant challenge lies in the varying responses exhibited by different patients towards NACT. To address this challenge, researchers have focused on developing prediction models that can identify those who would benefit from NACT and those who would not. Such models have the potential to reduce treatment costs and contribute to a more efficient and accurate management of breast cancer. Therefore, this review has two objectives: first, to identify the most effective radiomic markers correlated with NACT response, and second, to explore whether integrating radiomic markers extracted from radiological images with pathological markers can enhance the predictive accuracy of NACT response. This review will delve into addressing these research questions and also shed light on the emerging research direction of leveraging artificial intelligence techniques for predicting NACT response, thereby shaping the future landscape of breast cancer treatment.

Prognostic value of lncRNA AFAP1-AS1 in breast cancer: a meta-analysis and validated study in Chinese population.

Long non encoding RNA (lncRNA) plays a crucial role in breast cancer. However, the prognostic role of AFAP1-AS1 in breast cancer remains unclear. To investigate the relationship between the expression of long non-coding RNA actin filament-associated protein1 antisense RNA1 (AFAP1-AS1) and prognosis of breast cancer. Meta-analysis was performed to explore the correlation between AFAP1-AS1 and breast cancer. The AFAP1-AS1expression in patients with breast cancer tissue and adjacent normal tissue from 153 patients was determined by qRT-PCR. Bioinformatics and Cox proportional-hazards risk model were used to explore the relationship between expression of AFAP1-AS1 and prognosis. The combined analysis revealed a significant correlation between AFAP1-AS1 expression and both overall survival (hazard ratios, HR = 2.33, 95%Cl: 1.94-2.81, p < 0.001) as well as disease-free survival/progression-free survival (HR = 2.94, 95%CI: 2.35-3.67, p < 0.001). The relation between expression of AFAP1-AS1 and breast cancer was determined in 153 breast cancer and adjacent normal tissues. The findings revealed a significantly higher AFAP1-AS1expression levels in breast cancer tissues compared to adjacent normal tissues (p < 0.001). Additionally, patients exhibiting heightened levels of AFAP1-AS1 expression were correlated with an unfavorable prognosis (HR = 2.35, 95%CI: 1.47-3.74, p < 0.001), which aligns consistently with the findings of the pooled analysis. The subgroup analysis of clinical characteristics revealed a significant association between high expression of AFAP1-AS1 and TNM stage (HR = 1.72, 95%CI: 1.11-2.65, p = 0.015). This study demonstrated that AFAP1-AS1 acts as an oncogene and may serve as a novel prognostic marker for breast cancer, particularly in the Chinese population.

Assessing the relationship between tumor proliferation and prognosis in breast cancer patients: A pathological analysis

Background: Tumor proliferation is a key prognostic factor in breast cancer, but the relationship between tumor proliferation and prognosis remains unclear. Aims and Objectives: To investigate the association between tumor proliferation and prognosis in breast cancer patients using a pathological analysis. Materials and Methods: A retrospective cohort study was conducted, including 100 breast cancer patients who underwent surgical resection between January 2021 and December 2022.Tumor proliferation was assessed using Ki-67 immunostaining and evaluated patient prognosis based on disease-free survival (DFS) and overall survival (OS). We performed statistical analyses to examine the association between tumor proliferation and prognosis. Results: Our results showed a significant correlation between tumor proliferation and prognosis in breast cancer patients. High Ki-67 expression was associated with shorter DFS and OS, while low Ki-67 expression was associated with longer DFS and OS. The difference in DFS and OS between high and low Ki-67 expression groups was statistically significant. Conclusion: Tumor proliferation is a valuable prognostic marker in breast cancer and could be used to guide treatment decisions. Our findings suggest that patients with high Ki-67 expression may benefit from more aggressive treatment options, while patients with low Ki-67 expression may be able to avoid unnecessary treatment and its associated side effects. The accurate assessment of tumor proliferation using Ki-67 immunostaining could potentially improve patient outcomes and reduce the burden of breast cancer treatment.

Cancer and the Vasopressin Gene: Radioimmunoassay Values and Commentary on Copeptin as a Plasma Marker.

Vasopressin gene expression has been demonstrated to be a common feature of all small-cell lung cancer (SCLC) and breast cancer. Provasopressin (ProVP) is a component of the cancer cell membrane and a likely target for treatment. However, a measurable fraction of this cancer provasopressin is also normally processed and products are released into the circulation. Vasopressin (VP) and vasopressin-associated human neurophysin (VP-HNP), two of three products of processing, were earlier shown to be reliable plasma markers for determining the presence of SCLC and monitoring response to treatment. In this study, copeptin, the third product of provasopressin processing, was preliminarily evaluated as a plasma marker for SCLC or breast cancer using radioimmunoassay (RIA). Antibodies directed against the 18 residue C-terminal peptide fragment of copeptin were used to avoid interference from the large-carbohydrate component of this endogenous glycopeptide. The levels of copeptin in 8 male and 6 female patients with SCLC before treatment ranged from 16 to 319 pmol/L, and these levels were elevated (>2.5 times) in 10 of 14 cases (70%) when compared with healthy volunteers (normal mean, 18 ± 6 pmol/L). Volunteer values for males were smaller than for females (15± 4 pmol/L and 20± 9 pmol/L), but numbers were small. Patients with breast cancer had plasma levels ranging from 12 to 68 pmol/L, with only three of the six elevated. While cancer patients displayed a wide range of plasma copeptin levels over 70% with SCLC and 50% with breast cancer had clearly elevated levels. This finding indicates that for such patients, plasma copeptin, like plasma VP and VP-HNP, could be used to detect disease. The control values found for healthy volunteers using our RIA were in a range predictable from established normal plasma levels of both VP and VP-HNP.

Potential Role of Zinc Finger 365 rs10822013 and rs10995190 in Mammographic Density, Sporadic Breast Cancer Risk, and Prognosis.

Despite suggesting many genetic risk markers as the outcome of Genome-wide association studies (GWAS) for breast cancer, replicating the results in different populations has remained the main issue. In this regard, this study assessed the association of two variations in Zinc Finger 365 (ZNF365) in an Iranian population. In a case-control study conducted at Mashhad University of Medical Sciences, Mashhad, Iran, between 2017 and 2020, ZNF365-rs10822013 and rs10995190 were genotyped using Allele-Specific PCR (AS-PCR). Breast density was assessed using mammography images. PHASE software module version 2 and SPSS version 16.0 were used for haplotype and statistical analyses. Quantitative and qualitative variables were compared between groups using independent t tests and Chi square tests, respectively. Binary logistic regression analysis was performed to calculate odds ratios. Multivariate analysis was then undertaken for the baseline variables, with a P<0.05 in the univariate analysis. The survival analysis was performed using the Kaplan-Meier method and the log-rank test. In this survey, 732 females, including 342 breast cancer patients and 390 healthy subjects, were enrolled. rs10822013-T allele (P=0.014), rs10995190-G allele (P=0.003), and TG haplotype (P=0.002) were significantly associated with the increased risk of breast cancer. Moreover, rs10995190-GG genotype (P=0.042) and C-G haplotype (P=0.019) revealed a significant association with better overall survival. However, considered polymorphisms and their haplotypes indicated no association with breast density and clinical features of breast cancer. ZNF365 variants might be a potential risk marker of breast cancer in the Iranian population. The interaction between alleles in haplotypes may modulate the amount of the risk conferred by these variants. Further studies on different ethnic groups can validate these results.

Direct competitive assay for HER2 detection in human plasma using Bloch surface wave-based biosensors

The overexpression and/or amplification of the HER2/neu oncogene has been proposed as a prognostic marker in breast cancer. The detection of the related peptide HER2 remains a grand challenge in cancer diagnosis and for therapeutic decision-making. Here, we used a biosensing device based on Bloch Surface Waves excited on a one-dimensional photonic crystal (1DPC) as valid alternative to standard techniques. The 1DPC was optimized to operate in the visible spectrum and the biosensor optics has been designed to combine label-free and fluorescence operation modes. This feature enables a real-time monitoring of a direct competitive assay using detection mAbs conjugated with quantum dots for an accurate discrimination in fluorescence mode between HER2-positive/negative human plasma samples. Such a competitive assay was implemented using patterned alternating areas where HER2-Fc chimera and reference molecules were bio-conjugated and monitored in a multiplexed way. By combining Label-Free and fluorescence detection analysis, we were able to tune the parameters of the assay and provide an HER2 detection in human plasma in less than 20 min, allowing for a cost-effective assay and rapid turnaround time. The proposed approach offers a promising technique capable of performing combined label-free and fluorescence detection for both diagnosis and therapeutic monitoring of diseases.

Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.

Ki-67 Index and Its Correlation with Clinical and Pathological Variables in Breast Cancer.

The role of the Ki-67 index as a prognostic marker in breast cancer is controversial. This study was undertaken to assess the association of Ki-67 index with other clinicopathological factors in breast cancer. The prospectively conducted study included 127 female patients with clinical tumor stage 1-3 and nodal stage 0 or 1 treated between March 2015 and March 2017. Ki-67 index was correlated with age, tumor size, lymph node status, histological grade, ER, PR, HER2, and molecular subtypes using Chi-square or Fisher's exact test. Mean age of the patients was 53.28 years (range, 25-86 years). Mean Ki-67 index was 33.59 (range, 2.5-95). Ki-67 index showed a positive correlation with pathological stage (p=0.025), grade (p=0.0001), and molecular subtype (p=0.0001) of the tumor. It was inversely associated with ER (p=0.0001) and PR status (p=0.0001). Its association with pathological nodal status (p=0.06) and size (p=0.08) of the tumor was not statistically significant. There was no correlation with age (p=0.892) and HER2 status (p=0.287). Association of the Ki-67 index with common prognostic factors such as grade, stage, ER, PR, and molecular subtype suggests its role as a prognostic factor in breast cancer.

THU559 3D Immuno-smFISH Reveals ER-responsive Cells At The Single-cell Level In ER+ Breast Cancer

Abstract Disclosure: L.G. Kammel: None. R.N. Wine: None. J. Rodriguez: None. Abstract: The current guidelines by the American Society of Clinical Oncology/College of American Pathologists recommend that breast tumors with ≥1% nuclear estrogen receptor (ER) expression by immunohistochemistry be classified as ER+ based on evidence that these tumors are clinically responsive to endocrine therapy (1). However, this recommendation has been challenged by in vitro data from ER+ breast cancer cells showing that the cellular response to ER is not directly correlated to the expression of ER or the activation of ER per cell, but rather the allelic state of ER target genes among individual cells (2, 3). In parallel, single-cell RNA sequencing of ER+ breast cancer cells revealed that the steroid hormone receptor-induced response of individual genes varies widely from cell-to-cell and that in the average individual cell, less than a third of hormone-regulated genes show a transcriptional response (4). Together, these findings suggest that the clinical outcome of an ER+ breast tumor to endocrine therapy would be better predicted by a measure of the induced response to ER than ER status alone, but such a strategy does not exist. Here, we developed an approach based on single molecule fluorescent in situ hybridization (smFISH) combined with immunohistochemistry (immuno-smFISH) to simultaneously determine ER expression and the ER transcriptional response at single-cell resolution in the 3D context of a tissue or tumor. Briefly, we adapted a protocol for hybridization chain reaction to label multiple RNAs in thick fixed tissues followed by traditional immunohistochemistry. We then optically cleared tissues and imaged them by lightsheet microscopy. We quantified RNA and protein expression in the 3D space by integrating the open-source cell segmentation software Cell Pose with a fluorescent spot detection pipeline. Using this quantification, we calculated the RNA distributions of ER target genes in individual cells from a mouse mammary gland. We then used the colocalization of intronic and exonic RNA to identify active transcription sites and used this value to calculate the fraction of cells transcribing ER-target genes among the ER+ population. This fractional response represents the percent of cells expected to show a response to ER-targeted therapy, and applying this measurement in 3D allows for accurate analysis of complex tissues and tumors. In summary, we developed a comprehensive immuno-smFISH based-approach to characterize both ER expression and the cells responsive to ER at the single-cell level in 3D and we speculate that integrating these outcomes will improve the utility of ER as a predictive marker in breast cancer.

SAT426 Long-term Nanomolar Bisphenol A (BPA) Exposure of MCF7 Cells Induces DNA Methylation Changes

Abstract Disclosure: S.L. Dela Cruz: None. M.C. Velarde: None. P.D. Bagamasbad: None. Breast cancer (BCa) has the highest worldwide prevalence and mortality rate among cancers. For ER-positive luminal BCa, hormone deprivation therapy using drugs that inhibit the estrogen signaling axis is commonly employed. However, activation of ER may persist due to the presence of endocrine disrupting chemicals (EDCs) that are structurally similar to endogenous estrogens. Bisphenol A (BPA) is a known EDC found in consumer products and has been associated with increased BCa risk in various animal models. Mechanistically, BPA weakly binds and activates ER resulting in transcriptional changes. In addition, studies show that BPA potentially reprograms the epigenome through changes in DNA methylation. While methylome studies on BPA-exposed cancer models have been conducted, to the best of our knowledge, this has not been done on luminal BCa cells chronically exposed to environmentally relevant doses of BPA. The use of a chronic, nanomolar-dose treatment paradigm is significant as it more accurately reflects non-occupational environmental exposure. In this study, we investigated the epigenetic effects of chronic (8 weeks) nanomolar doses (10 nM) of BPA on the ER-positive BCa cell line MCF7. We probed single gene-level DNA methylation through Bisulfite Sequencing PCR (BSP) and genome-wide methylation through Reduced Representation Bisulfite PCR (RRBS). In silico analysis of publicly available data identified potential differentially methylated regions (DMRs) upon chronic BPA treatment. BSP showed minimal changes in methylation levels of CpGs within the target DMRs, while gene expression analysis via RT-qPCR did not find significant changes in mRNA levels of genes encompassing the target regions. Methylome-wide profiling of chronically treated cells identified DMRs that fall under gene promoters (DMPs) and gene coding regions (DMGs). Pathway analysis of DMPs indicated an association with death receptor signaling, with an overall predicted effect in inhibiting apoptosis. Network analysis revealed genes encompassing DMPs that interact with the BCa markers ESR1/2, BRCA1, and PGR. Based on the pathway and network analyses, we selected 8 genes for gene expression analysis and found that the expression of all 8 genes are unchanged following chronic BPA treatment. Taken together, our results show that chronic BPA exposure of MCF7 can induce subtle changes in DNA methylation. Although initial validation did not reveal changes in gene expression associated with differential methylation, we speculate that the incremental DNA methylation changes could accumulate over time resulting in further ER signaling dysregulation, exacerbating the BCa phenotype. Presentation: Saturday, June 17, 2023