Clinical Outcome In Breast Cancer Research Articles

Upregulated SAE1 Drives Tumorigenesis and Is Associated with Poor Clinical Outcomes in Breast Cancer

Background. The purpose of this study was to analyze SUMO activating enzyme subunit 1 (SAE1) expression in breast cancer (BC). Through bioinformatics analysis and in vitro experiments, the biological function and possibly associated signal pathways of SAE1 in BC were further analyzed. Methods. Bioinformatics analysis was applied to analyze SAE1 expression in BC and normal breast tissues, its relationship with clinicopathologic characteristics and prognosis in BC patients, and data from the Cancer Genome Atlas database and Gene Expression Omnibus dataset. We performed immunohistochemistry to analyze SAE1 expression in BC tissues and para‐cancer tissues in 79 breast cancer patients. BC cell proliferation was detected with the Cell Counting Kit‐8 and by the colony formation assay. Cell cycle progression was analyzed by flow cytometry, and the expression of cell cycle‐related proteins (E2F1, cyclin D3, and cyclin‐dependent kinase 2) was determined by western blots in SAE1 small interfering RNA (siRNA) transfected cells. The GSE1456 dataset was used to analyze possible signal pathways associated with SAE1 by gene set enrichment analysis (GSEA), and the expression of PI3K/AKT/mTOR pathway‐related proteins (such as p‐PI3K, p‐AKT, and mTOR) in SAE1‐siRNA cells was detected by western blots. Results. The bioinformatics and immunohistochemical results showed that SAE1 mRNA and protein expression in BC tissues were significantly higher than those in normal tissues. The SAE1 overexpression was significantly associated with the tumor size, tumor‐node‐metastasis stage, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and whether or not it was a triple‐negative BC. Patients with SAE1 overexpression had a worse overall survival (OS), recurrence‐free survival (RFS), and distant metastasis‐free survival compared with lower expression patients. Multivariate Cox regression analysis showed that SAE1 may be an independent prognostic factor for OS of BC patients. The proliferation and cell cycle process of BC cells were inhibited by SAE1‐siRNA in vitro. The result of GSEA showed that SAE1 was significantly associated with 12 gene sets, including unfolded protein reaction, DNA repair, oxidative phosphorylation, and cell cycle, among others. Additionally, two signal pathways, mTORC1 and PI3K/Akt/mTOR, were significantly correlated with SAE1 overexpression. Western blots confirmed that the expression of PI3K/Akt/mTOR pathway‐related proteins (p‐PI3K, p‐AKT, and mTOR) in BC cells was decreased after knocking down SAE1. Conclusion. SAE1 was highly expressed in BC. Its overexpression was associated with poor BC prognosis. Additionally, it was an independent prognostic factor for BC patients. We demonstrated that in vitro SAE1 knockdown effectively inhibited BC proliferation and its cell cycle process. Furthermore, the biological function of SAE1 may be associated with the PI3K/Akt/mTOR pathway. SAE1 will be a potential target for BC treatment.

Influence of H19 polymorphisms on breast cancer: risk assessment and prognostic implications via LincRNA H19/miR-675 and downstream pathways.

Breast cancer, as the most prevalent malignancy among women globally, continues to exhibit rising incidence rates, particularly in China. The disease predominantly affects women aged 40 to 60 and is influenced by both genetic and environmental factors. This study focuses on the role of H19 gene polymorphisms, investigating their impact on breast cancer susceptibility, clinical outcomes, and response to treatment. We engaged 581 breast cancer patients and 558 healthy controls, using TaqMan assays and DNA sequencing to determine genotypes at specific loci (rs11042167, rs2071095, rs2251375). We employed in situ hybridization and immunohistochemistry to measure the expression levels of LincRNA H19, miR-675, MRP3, HOXA1, and MMP16 in formalin-fixed, paraffin-embedded samples. Statistical analyses included chi-squared tests, logistic regression, and Kaplan-Meier survival curves to evaluate associations between genetic variations, gene expression, and clinical outcomes. Genotypes AG at rs11042167, GT at rs2071095, and AC at rs2251375 were significantly associated with increased risk of breast cancer. Notably, the AA genotype at rs11042167 and TT genotype at rs2071095 were linked to favorable prognosis. High expression levels of LincRNA H19, miR-675, MRP3, HOXA1, and MMP16 in cancer tissues correlated with advanced disease stages and poorer survival rates. Spearman correlation analysis revealed significant positive correlations between the expression of LincRNA H19 and miR-675 and specific genotypes, highlighting their potential regulatory roles in tumor progression. The study underscores the critical roles of LincRNA H19 and miR-675 as prognostic biomarkers in breast cancer, with their overexpression associated with disease progression and adverse outcomes. The H19/LincRNA H19/miR-675/MRP3-HOXA1-MMP16 axis offers promising targets for new therapeutic strategies, reflecting the complex interplay between genetic markers and breast cancer pathology. The findings confirm that certain H19 SNPs are associated with heightened breast cancer risk and that the expression profiles of related genetic markers can significantly influence prognosis and treatment response. These biomarkers hold potential as targets for personalized therapy and early detection strategies in breast cancer, underscoring the importance of genetic research in understanding and managing this disease.

GREB1L overexpression is associated with good clinical outcomes in breast cancer

BackgroundBreast cancer is the most common malignant tumor among women worldwide. GREB1L is a protein-coding gene. Previous studies have shown that GREB1L plays a vital role in lung and gastric adenocarcinoma. Currently, there is no relevant report about its role in breast cancer.MethodsThe Cancer Genome Atlas database was used to compare the expression level of GREB1L between tumor and normal tissues. The TISIDB website was used for prognosis analysis. The LinkedOmics database was used to predict the potential biological mechanism of GREB1L in breast cancer. Immunohistochemistry was used to detect the GREB1L expression level in breast tissue. Western blotting was used to detect the GREB1L expression level in cell lines. Transwell assays, CCK-8 cell proliferation assays, and colony formation assays were used to detect the migration, invasion, proliferation, and colony formation abilities of cells. Subcutaneous xenograft models were used to detect the in vivo tumor formation abilities of cells.ResultsGREB1L is highly expressed in breast cancer tissues and breast cancer cells. KEGG enrichment analysis suggested that GREB1L participates in the regulation of the Hedgehog signaling pathway; changes in GREB1L expression affected the migration and invasion abilities of MCF7 and MDA-MB-231 cells. Although changes in GREB1L expression did not affect their proliferation and colony formation abilities in vitro and in vivo, they affected the expression of tumor metastasis-related genes in vivo. The overexpression of GREB1L in breast cancer predicted a favorable prognosis.ConclusionThese results showed that GREB1L is involved in the development of breast cancer, and it may be a potential molecular marker for predicting the prognosis of breast cancer.

Prognostic value analysis of cholesterol and cholesterol homeostasis related genes in breast cancer by Mendelian randomization and multi-omics machine learning.

The high incidence of breast cancer (BC) prompted us to explore more factors that might affect its occurrence, development, treatment, and also recurrence. Dysregulation of cholesterol metabolism has been widely observed in BC; however, the detailed role of how cholesterol metabolism affects chemo-sensitivity, and immune response, as well as the clinical outcome of BC is unknown. With Mendelian randomization (MR) analysis, the potential causal relationship between genetic variants of cholesterol and BC risk was assessed first. Then we analyzed 73 cholesterol homeostasis-related genes (CHGs) in BC samples and their expression patterns in the TCGA cohort with consensus clustering analysis, aiming to figure out the relationship between cholesterol homeostasis and BC prognosis. Based on the CHG analysis, we established a CAG_score used for predicting therapeutic response and overall survival (OS) of BC patients. Furthermore, a machine learning method was adopted to accurately predict the prognosis of BC patients by comparing multi-omics differences of different risk groups. We observed that the alterations in plasma cholesterol appear to be correlative with the venture of BC (MR Egger, OR: 0.54, 95% CI: 0.35-0.84, p<0.006). The expression patterns of CHGs were classified into two distinct groups(C1 and C2). Notably, the C1 group exhibited a favorable prognosis characterized by a suppressed immune response and enhanced cholesterol metabolism in comparison to the C2 group. In addition, high CHG score were accompanied by high performance of tumor angiogenesis genes. Interestingly, the expression of vascular genes (CDH5, CLDN5, TIE1, JAM2, TEK) is lower in patients with high expression of CHGs, which means that these patients have poorer vascular stability. The CAG_score exhibits robust predictive capability for the immune microenvironment characteristics and prognosis of patients(AUC=0.79). It can also optimize the administration of various first-line drugs, including AKT inhibitors VIII Imatinib, Crizotinib, Saracatinib, Erlotinib, Dasatinib, Rapamycin, Roscovitine and Shikonin in BC patients. Finally, we employed machine learning techniques to construct a multi-omics prediction model(Risklight),with an area under the feature curve (AUC) of up to 0.89. With the help of CAG_score and Risklight, we reveal the signature of cholesterol homeostasis-related genes for angiogenesis, immune responses, and the therapeutic response in breast cancer, which contributes to precision medicine and improved prognosis of BC.

Occupational exposure to pesticides dysregulates systemic Th1/Th2/Th17 cytokines and correlates with poor clinical outcomes in breast cancer patients

Pesticides are compounds known to cause immunetoxicity in exposed individuals, which have a potential to substantially modify the prognosis of pathologies dependent on an efficient immune response, such as breast cancer. In this context, we examined the circulating cytokine profile of Th1/Th2/Th17 patterns in women occupationally exposed to pesticides and their correlation with worse prognostic outcomes. Peripheral blood samples were collected from 187 rural working women with breast cancer, occupationally exposed or not to pesticides, to quantify the levels of cytokines IL-1β, IL-12, IL-4, IL-17-A, and TNF -α. Data on the disease profile and clinical outcomes were collected through medical follow-up. IL-12 was reduced in exposed women with tumors larger than 2 cm and in those with lymph node metastases. Significantly reduced levels of IL-17A were observed in exposed patients with Luminal B subtype tumors, with high ki67 proliferation rates, high histological grade, and positive for the progesterone receptor. Reduced IL-4 was also seen in exposed women with lymph node invasion. Our data show that occupational exposure to pesticides induces significant changes in the levels of cytokines necessary for tumor control and correlates with poor prognosis clinical outcomes in breast cancer.

The heterogeneity of tumour immune microenvironment revealing the CRABP2/CD69 signature discriminates distinct clinical outcomes in breast cancer.

It has been acknowledged that the tumour immune microenvironment (TIME) plays a critical role in determining therapeutic responses and clinical outcomes in breast cancer (BrCa). Thus, the identification of the TIME features is essential for guiding therapy and prognostic assessment for BrCa. The heterogeneous cellular composition of the TIME in BrCa by single-cell RNA sequencing (scRNA-seq). Two subtype-special genes upregulated in the tumour-rich subtype and the immune-infiltrating subtype were extracted, respectively. The CRABP2/CD69 signature was established based on CRABP2 and CD69 expression, and its predictive values for the clinical outcome and the neoadjuvant chemotherapy (NAT) responses were validated in multiple cohorts. Moreover, the oncogenic role of CRABP2 was explored in BrCa cells. Based on the heterogeneous cellular composition of the TIME in BrCa, the BrCa samples could be divided into the tumour-rich subtype and the immune-infiltrating subtype, which exhibited distinct prognosis and chemotherapeutic responses. Next, we extracted CRABP2 as the biomarker for the tumour-rich subtype and CD69 as the biomarker for the immune-infiltrating subtype. Based on the CRABP2/CD69 signature, BrCa samples were re-divided into three subtypes, and the CRABP2highCD69low subtype exhibited the worst prognosis and the lowest chemotherapeutic response, while the CRABP2lowCD69high subtype showed the opposite results. Furthermore, CARBP2 functioned as a novel oncogene in BrCa, which promoted tumour cell proliferation, migration, and invasion, and CRABP2 inhibition triggered the activation of cytotoxic T lymphocytes (CTLs). The CRABP2/CD69 signature is significantly associated with the TIME features and could effectively predict the clinical outcome. Also, CRABP2 is determined to be a novel oncogene, which could be a therapeutic target in BrCa.

CRISPR screen identifies GATAD1 as a synthetic lethal target with CDK4/6 inhibitors in estrogen receptor-positive breast cancer.

Estrogen receptor-positive (ER+) breast cancer represents approximately two-thirds of all breast cancers and has a sustained risk of late disease recurrence. Combining cyclin-dependent kinase 4/6 (CDK4/6) inhibitors with anti-estrogen therapies significantly improves ER+ advanced breast cancer clinical outcomes. Despite promising clinical outcomes, intrinsic or acquired resistance to CDK4/6 inhibitors has limited their success. We used CRISPR to screen MCF-7 cells to explore the targets whose inhibition is synthetic lethal with CDK4/6 inhibitors in ER+ breast cancer cells. We found that GATA zinc finger domain containing 1 (GATAD1) is a new synthetic lethal target with CDK4/6 inhibitors in ER+ breast cancer cells. Mechanistically, GATAD1 promotes cell proliferation by transcriptionally inhibiting p21 in ER+ breast cancer cells. GATAD1 depletion decreased the phosphorylation of CDK2/4 and RB transcriptional corepressor 1 (RB1), inducing cell cycle arrest. P21 overexpression abolished the enhanced proliferation induced by GATAD1 overexpression. Our results identify GATAD1 as a therapeutic target in ER+ breast cancer, which is beneficial to provide a novel treatment strategy.

Genomic alterations affecting tumor-infiltrating lymphocytes and PD-L1 expression patterns in triple-negative breast cancer.

Tumor-infiltrating lymphocytes (TILs) and programmed cell death 1 ligand 1 (PD-L1) remain imperfect in predicting clinical outcomes of triple-negative breast cancer because outcomes do not always correlate with the expression of these biomarkers. Genomic and transcriptomic alterations that may contribute to the expression of these biomarkers remain incompletely uncovered. We evaluated PD-L1 immunohistochemistry scores (SP142 and 28-8 assays) and TILs in our triple-negative breast cancer multiomics dataset and 2 immunotherapy clinical trial cohorts. Then, we analyzed genomic and transcriptomic alterations correlated with TILs, PD-L1 expression, and patient outcomes. Despite TILs serving as a decent predictor for triple-negative breast cancer clinical outcomes, exceptions remained. Our study revealed that several genomic alterations were correlated with unexpected events. In particular, PD-L1 expression may cause a paradoxical relationship between TILs and prognosis in certain patients. Consequently, we classified triple-negative breast cancers into 4 groups based on PD-L1 and TIL levels. The TIL-negative PD-L1-positive and TIL-positive PD-L1-negative groups were not typical "hot" tumors; both were associated with worse prognoses and lower immunotherapy efficacy than TIL-positive PD-L1-positive tumors. Copy number variation of PD-L1 and oncogenic signaling activation were correlated with PD-L1 expression in the TIL-negative PD-L1-positive group, whereas GSK3B-induced degradation may cause undetectable PD-L1 expression in the TIL-positive PD-L1-negative group. These factors have the potential to affect the predictive function of both PD-L1 and TILs. Several genomic and transcriptomic alterations may cause paradoxical effects among TILs, PD-L1 expression, and prognosis in triple-negative breast cancer. Investigating and targeting these factors will advance precision immunotherapy for patients with this disease.

Loss of ANCO1 Expression Regulates Chromatin Accessibility and Drives Progression of Early-Stage Triple-Negative Breast Cancer.

Mutations in the gene ankyrin repeat domain containing 11 (ANKRD11/ANCO1) play a role in neurodegenerative disorders, and its loss of heterozygosity and low expression are seen in some cancers. Here, we show that low ANCO1 mRNA and protein expression levels are prognostic markers for poor clinical outcomes in breast cancer and that loss of nuclear ANCO1 protein expression predicts lower overall survival of patients with triple-negative breast cancer (TNBC). Knockdown of ANCO1 in early-stage TNBC cells led to aneuploidy, cellular senescence, and enhanced invasion in a 3D matrix. The presence of a subpopulation of ANCO1-depleted cells enabled invasion of the overall cell population in vitro and they converted more rapidly to invasive lesions in a xenograft mouse model. In ANCO1-depleted cells, ChIP-seq analysis showed a global increase in H3K27Ac signals that were enriched for AP-1, TEAD, STAT3, and NFκB motifs. ANCO1-regulated H3K27Ac peaks had a significantly higher overlap with known breast cancer enhancers compared to ANCO1-independent ones. H3K27Ac engagement was associated with transcriptional activation of genes in the PI3K-AKT, epithelial-mesenchymal transition (EMT), and senescence pathways. In conclusion, ANCO1 has hallmarks of a tumor suppressor whose loss of expression activates breast-cancer-specific enhancers and oncogenic pathways that can accelerate the early-stage progression of breast cancer.

1422-P: The Impact of Type 2 Diabetes Mellitus on the Clinical Outcome of Breast Cancer

Objectives: Women with breast cancer and diabetes have worse outcomes than those with breast cancer without diabetes. The objective of this study was to investigate the impact of pre-existing diabetes on breast cancer prognosis. Methods and Materials: This was a retrospective observational study using Cancer database from a single tertiary center. The study population included women aged ≥20 years with breast cancer diagnosed between 1 January 2014 and 31 December 2018. Patients were categorized by diabetes status (T2D: n=111, non-T2D: n= 889). The clinicopathological features and outcomes were collected and compared between women with and without diabetes. Cox proportional hazard regression was used to estimate adjusted hazard ratios for overall mortality. Results: Compared to non-T2D patients, T2D patients were significantly older, had higher BMI, were more post-menopausal state at breast cancer diagnosis, had more comorbid conditions, and were in lower educational states. There were no statistically significant differences in tumor characteristics, including metastasis, lymph nodes, grade, and extent of surgery. Women with T2D had a significantly increased risk of overall mortality after adjusting for demographic and traditional risk factors for breast cancer (HR=2.15; 95%CI=1.10-4.20). Compared to patients with pre-existing T2D (n=111), patients with newly diagnosed T2D after receiving a breast cancer diagnosis (n=34) had a lower risk of breast cancer recurrence (HR=0.30; 95%CI=0.10-0.94). Conclusion: Our study showed that pre-existing T2D and T2D itself increase the risk of recurrence and total mortality among patients with breast cancer. These findings provide important prognostic information for the treatment of women with both T2D and breast cancer. Therefore, diabetes deserves additional attention to assess possible causal relationships that potentially could be modified to improve outcomes. Disclosure Y.Kim: None. I.Goak: None. H.Jin: None. T.Park: None. K.Lee: None.

HER2Δ16 Engages ENPP1 to Promote an Immune-Cold Microenvironment in Breast Cancer.

The tumor-immune microenvironment (TIME) is a critical determinant of therapeutic response. However, the mechanisms regulating its modulation are not fully understood. HER2Δ16, an oncogenic splice variant of the HER2, has been implicated in breast cancer and other tumor types as a driver of tumorigenesis and metastasis. Nevertheless, the underlying mechanisms of HER2Δ16-mediated oncogenicity remain poorly understood. Here, we show that HER2∆16 expression is not exclusive to the clinically HER2+ subtype and associates with a poor clinical outcome in breast cancer. To understand how HER2 variants modulated the tumor microenvironment, we generated transgenic mouse models expressing either proto-oncogenic HER2 or HER2Δ16 in the mammary epithelium. We found that HER2∆16 tumors were immune cold, characterized by low immune infiltrate and an altered cytokine profile. Using an epithelial cell surface proteomic approach, we identified ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) as a functional regulator of the immune cold microenvironment. We generated a knock-in model of HER2Δ16 under the endogenous promoter to understand the role of Enpp1 in aggressive HER2+ breast cancer. Knockdown of Enpp1 in HER2Δ16-derived tumor cells resulted in decreased tumor growth, which correlated with increased T-cell infiltration. These findings suggest that HER2Δ16-dependent Enpp1 activation associates with aggressive HER2+ breast cancer through its immune modulatory function. Our study provides a better understanding of the mechanisms underlying HER2Δ16-mediated oncogenicity and highlights ENPP1 as a potential therapeutic target in aggressive HER2+ breast cancer.

Infiltrating myeloid cell diversity determines oncological characteristics and clinical outcomes in breast cancer

BackgroundBreast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown.MethodsMyeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner.ResultsWe dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients.ConclusionsOur study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification.Graphical

CtDNA Dynamics Can Predict Clinical Outcomes in Early-Stage Breast Cancer.

ctDNA dynamics during neoadjuvant chemotherapy can predict clinical outcomes in breast cancer.

High leukocyte mitochondrial DNA copy number contributes to poor prognosis in breast cancer patients

BackgroundCompelling evidence has indicated a significant association between leukocyte mitochondrial DNA copy number (mtDNAcn) and prognosis of several malignancies in a cancer-specific manner. However, whether leukocyte mtDNAcn can predict the clinical outcome of breast cancer (BC) patients has not been well investigated.MethodsThe mtDNA copy number of peripheral blood leukocytes from 661 BC patients was measured using a Multiplex AccuCopy™Kit based on a multiplex fluorescence competitive PCR principle. Kaplan–Meier curves and Cox proportional hazards regression model were applied to investigate the association of mtDNAcn with invasive disease-free survival (iDFS), distant disease-free survival (DDFS), breast cancer special survival (BCSS), and overall survival (OS) of patients. The possible mtDNAcn-environment interactions were also evaluated by the Cox proportional hazard regression models.ResultsBC patients with higher leukocyte mtDNA-CN exhibited a significantly worse iDFS than those with lower leukocyte mtDNAcn (5-year iDFS: fully-adjusted model: HR = 1.433[95%CI 1.038–1.978], P = 0.028). Interaction analyses showed that mtDNAcn was significantly associated with hormone receptor status (adjusted p for interaction: 5-year BCSS: 0.028, 5-year OS: 0.022), so further analysis was mainly in the HR subgroup. Multivariate Cox regression analysis demonstrated that mtDNAcn was an independent prognostic factor for both BCSS and OS in HR-positive patients (HR+: 5-year BCSS: adjusted HR (aHR) = 2.340[95% CI 1.163–4.708], P = 0.017 and 5-year OS: aHR = 2.446 [95% CI 1.218–4.913], P = 0.011).ConclusionsFor the first time, our study demonstrated that leukocyte mtDNA copy number might influence the outcome of early-stage breast cancer patients depending on intrinsic tumor subtypes in Chinese women.

Abstract 3596: EMG1 is an rRNA-modifying protein that contributes to breast cancer progression

Abstract The ribosome, a multi-subunit RNA-protein complex, is essential for translation in all cells. Variation in ribosome composition and characteristics has been observed between cell types and under different metabolic conditions; this phenomenon is referred to as "ribosome heterogeneity." Ribosome heterogeneity has been linked to carcinogenesis and cancer progression. One of the major layers of ribosome heterogeneity is the diverse rRNA modifications. To study the impact of rRNA modifications on cancer, we performed a systematic literature search and identified 22 rRNA modifying proteins (RRMPs) that are involved in mediating different modifications of rRNA. We next examined the RRMPs' expression levels and frequency of mutation in different cancer types, with a focus on breast cancer. We see that most malignancies show alterations in RRMPs' expression levels and frequent mutations. Our analysis of gene expression patterns and clinical outcomes in breast cancer has shown that several RRPMs are strongly linked to an aggressive phenotype and a poor prognosis. Our analysis also revealed that EMG1, a N1-specific psuedouridine methyltransferase, is a RRMP with potential roles in cancer progression and metastasis. Our findings pave the way for further research into the role of RRMPs in different cancers as well as the development of therapies that specifically target RRMPs involved in cancer progression. Citation Format: Amr R. Elhamamsy, Heba A. Alsheikh, Rajeev S. Samant, Lalita A. Shevde. EMG1 is an rRNA-modifying protein that contributes to breast cancer progression. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3596.

Correlation of androgen receptor with ultrasound, clinicopathological features and clinical outcomes in breast cancer

BackgroundThis study aimed to explore whether there is an association between androgen receptor (AR) expression and ultrasound, clinicopathological features and prognosis of breast cancer.MethodsA total of 141 breast cancer patients were included in this retrospective study. AR expression was analyzed by immunohistochemistry. The images of B-mode, color Doppler and strain elastography from 104 patients were collected continuously, and the corresponding ultrasound characteristics were obtained. The differences in ultrasound and clinicopathological features in different AR status were analyzed. Progression-free survival (PFS) of patients was obtained through up to 90 months of follow-up; then, the effect of AR on PFS was analyzed. Subsequently, a nomogram was constructed to predict the AR status. The predictive accuracy was calculated using C-index.ResultsThe positive expression of AR (AR +) was associated with lower histological grade (p = 0.034) and lower Ki-67 level (p = 0.029). Triple-negative breast cancer (TNBC) had the lowest probability of AR + (p < 0.001). The AR + group mostly showed unsmooth margin (p < 0.001), posterior acoustic shadowing (p = 0.002) and higher elasticity score (p = 0.022) on ultrasound. The echo pattern of most tumors with AR + was heterogeneous (p = 0.024) in Luminal A subtype. AR + could be a sign of a better prognosis in overall breast cancer (p < 0.001), as well as in human epidermal growth factor receptor 2 (HER2) overexpression and Luminal B subtypes (p = 0.001 and 0.025). The nomogram showed relatively reliable performance with a C-index of 0.799.ConclusionOur research demonstrated that AR expression was closely related to ultrasound, clinicopathological features and prognosis of breast cancer.

Abstract PD1-10: Impact of Race on Clinical, Socioeconomic, and Genomic Characteristics, Clinical Trial Participation, and Receipt of Genotype-matched Therapy Among Patients with Metastatic Breast Cancer

Abstract Background: Clinical outcomes in breast cancer differ across racial and ethnic populations. We have previously demonstrated that receipt of genotype-matched therapy targeted to an actionable mutation may potentially improve patient outcomes (Vidula, CCR, 2021). We evaluated the impact of race on clinical, socioeconomic, and genomic characteristics, clinical trial participation, and receipt of genotype-matched therapy among patients with metastatic breast cancer (MBC). Methods: We conducted a retrospective study of patients with MBC at an academic institution who underwent cell-free DNA testing (cfDNA, Guardant360, 74 gene panel) as part of routine clinical care from 11/29/2016-11/2/2020. Patient demographics (including self-reported race and ethnicity) and clinical trial enrollment (at same institution) were determined by retrospective data collection. Mutations identified in cfDNA were characterized as actionable based on the variant interpretation performed by Guardant360 using vetted genomic databases, and receipt of genotype-matched therapy targeted to an actionable mutation was determined as previously described (Vidula, CCR, 2021). Pearson’s chi-squared and Wilcoxon rank-sum tests were used to compare categorical and continuous variables between groups, with p&amp;lt; 0.05 indicating statistical significance. Results: Four hundred and twenty-five patients with MBC and cfDNA results were identified, of which 369 were White (87%), 27 Black (6.4%), 15 Hispanic (3.5%), and 14 Asian (3.3%). There were no significant differences in median age at MBC diagnosis (p=0.064), disease subtype distribution (p=0.74), proportions of de-novo/recurrent MBC (p=0.95), presence of visceral metastases (p=0.84), Charleston comorbidity index (p=0.93), menopausal status (p=0.3), and level of education (p=0.44) across racial groups. Higher proportions of non-primary English speakers were seen in Hispanic (80%) and Asian (29%) races (p&amp;lt; 0.001). Median distance traveled to the institution also varied based on race, with White patients traveling further (White: 39.1 miles, Black: 21.8 miles, Hispanic 9.4 miles, Asian 9.1 miles, p&amp;lt; 0.001). In addition, type of insurance varied based on race, with White patients having the highest rates of commercial insurance and Medicare, Black patients having the highest rate of state-supported insurance, and Asian patients having the highest uninsured rates (p&amp;lt; 0.001). Clinical trial enrollment rates did not significantly differ by race (White: 44%, Black: 37%, Hispanic: 47%, and Asian 21%, p=0.34), but patients without insurance were significantly less likely to be enrolled on a trial than those with commercial insurance (p=0.03). The proportion of patients with ≥1 actionable mutation in cfDNA did not vary significantly by race (White: 78%, Black: 56%, Hispanic: 73%, Asian 86%, p=0.18) and the median number of actionable mutations found in cfDNA was similar across races (p=0.31). However, receipt of genotype-matched therapy targeted to an actionable mutation varied by race, with the highest rates of matched therapy in White patients (White: 28%, Black: 11%, Hispanic 13%, Asian 14%, p&amp;lt; 0.001). After multivariable logistic regression adjusting for subtype, commercial insurance versus other insurance types, and proximity to the center, White patients remained significantly more likely to receive matched therapy (p=0.029). Conclusions: We observed significant race-based differences in non-English speaking status, insurance type, and median distance traveled to the institution. Racial/ethnic minority patients were less likely to receive genotype-matched therapy than White patients. Further research is needed to identify barriers and reduce disparities in access to precision medicine. Citation Format: Rupali Sood, Lianne Ryan, Andrzej Niemierko, Laura M. Spring, Dejan Juric, Steven J. Isakoff, Seth A. Wander, Jennifer Shin, Naomi Ko, Leif Ellisen, Beverly Moy, Aditya Bardia, Neelima Vidula. Impact of Race on Clinical, Socioeconomic, and Genomic Characteristics, Clinical Trial Participation, and Receipt of Genotype-matched Therapy Among Patients with Metastatic Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD1-10.

Impact of the 21-gene expression assay on treatment decisions and clinical outcomes in breast cancer with one to three positive lymph nodes.

To assess the practice patterns of the recurrence score (RS) based on the 21-gene expression assay on adjuvant chemotherapy recommendations and survival outcomes in estrogen receptor-positive (ER+)/HER2- breast cancer (BC) with one to three positive lymph nodes (N1). We included patients with T1-2N1M0 and ER+/HER2- BC diagnosed between 2010 and 2015 in the Surveillance, Epidemiology, and End Results Oncotype DX Database. Breast cancer-specific survival (BCSS) and overall survival (OS) were assessed. We included 35,137 patients in this study. There were 21.2% of patients who had RS testing in 2010, which was significantly increased to 36.8% in 2015 (P < 0.001). Performance of the 21-gene testing was associated with older age, lower tumor grade, T1 stage, lower number of positive lymph nodes, and progesterone receptor-positive disease (all P < 0.05). In those without 21-gene testing, age was the main factor significantly related to the receipt of chemotherapy, whereas RS was the main factor significantly related to chemotherapy receipt in those with 21-gene testing. The probability of chemotherapy receipt in those without 21-gene testing was 64.1% and was decreased to 30.8% in those with 21-gene testing. On multivariate prognostic analysis, the performance of 21-gene testing was associated with better BCSS (P < 0.001) and OS (P < 0.001) compared with those without 21-gene testing. Similar results were found after propensity score matching. The 21-gene expression assay is frequently and increasingly used for chemotherapy decision-making in ER+/HER2- BC with N1 disease. Performance of the 21-gene testing is associated with improved survival outcomes. Our study supports the routine use of 21-gene testing in the clinical practice of this population.

UBE2S and UBE2C confer a poor prognosis to breast cancer via downregulation of Numb.

Ubiquitin-conjugating enzymes E2S (UBE2S) and E2C (UBE2C), which mediate the biological process of ubiquitination, have been widely reported in various cancers. Numb, the cell fate determinant and tumor suppressor, was also involved in ubiquitination and proteasomal degradation. However, the interaction between UBE2S/UBE2C and Numb and their roles in the clinical outcome of breast cancer (BC) are not widely elucidated. Oncomine, Cancer Cell Line Encyclopedia (CCLE), the Human Protein Atlas (HPA) database, qRT-PCR, and Western blot analyses were utilized to analyze UBE2S/UBE2C and Numb expression in various cancer types and their respective normal controls, breast cancer tissues, and breast cancer cell lines. The expression of UBE2S, UBE2C, and Numb in BC patients with different ER, PR, and HER2 status, grades, stages, and survival status was compared. By Kaplan-Meier plotter, we further evaluated the prognostic value of UBE2S, UBE2C, and Numb in BC patients. We also explored the potential regulatory mechanisms underlying UBE2S/UBE2C and Numb through overexpression and knockdown experiments in BC cell lines and performed growth and colony formation assays to assess cell malignancy. In this study, we showed that UBE2S and UBE2C were overexpressed while Numb was downregulated in BC, and in BC of higher grade, stage, and poor survival. Compared to hormone receptor negative (HR-) BC cell lines or tissues, HR+ BC demonstrated lower UBE2S/UBE2C and higher Numb, corresponding to better survival. We also showed that increased UBE2S/UBE2C and reduced Numb predicted poor prognosis in BC patients, as well as in ER+ BC patients. In BC cell lines, UBE2S/UBE2C overexpression decreased the level of Numb and enhanced cell malignancy, while knocking down UBE2S/UBE2C demonstrated the opposite effects. UBE2S and UBE2C downregulated Numb and enhanced BC malignancy. The combination of UBE2S/UBE2C and Numb could potentially serve as novel biomarkers for BC.

Exploring the role of sphingolipid-related genes in clinical outcomes of breast cancer.

Despite tremendous advances in cancer research, breast cancer (BC) remains a major health concern and is the most common cancer affecting women worldwide. Breast cancer is a highly heterogeneous cancer with potentially aggressive and complex biology, and precision treatment for specific subtypes may improve survival in breast cancer patients. Sphingolipids are important components of lipids that play a key role in the growth and death of tumor cells and are increasingly the subject of new anti-cancer therapies. Key enzymes and intermediates of sphingolipid metabolism (SM) play an important role in regulating tumor cells and further influencing clinical prognosis. We downloaded BC data from the TCGA database and GEO database, on which we performed in depth single-cell sequencing analysis (scRNA-seq), weighted co-expression network analysis, and transcriptome differential expression analysis. Then seven sphingolipid-related genes (SRGs) were identified using Cox regression, least absolute shrinkage, and selection operator (Lasso) regression analysis to construct a prognostic model for BC patients. Finally, the expression and function of the key gene PGK1 in the model were verified by in vitro experiments. This prognostic model allows for the classification of BC patients into high-risk and low-risk groups, with a statistically significant difference in survival time between the two groups. The model is also able to show high prediction accuracy in both internal and external validation sets. After further analysis of the immune microenvironment and immunotherapy, it was found that this risk grouping could be used as a guide for the immunotherapy of BC. The proliferation, migration, and invasive ability of MDA-MB-231 and MCF-7 cell lines were dramatically reduced after knocking down the key gene PGK1 in the model through cellular experiments. This study suggests that prognostic features based on genes related to SM are associated with clinical outcomes, tumor progression, and immune alterations in BC patients. Our findings may provide insights for the development of new strategies for early intervention and prognostic prediction in BC.