Poor Survival In Breast Cancer Research Articles

Abstract PO4-05-12: High expression of SLC9A2 is correlation with lymphatic metastasis and poor survival in breast cancer

Abstract Background: SLC9A2 encodes Na+/H+ exchanger 2 which is an essential solute carrier protein on the surface of multiple cells. The prediction potentials of SLC9A2 in lymphatic metastasis and survival were unknow but explored in this study of breast cancer. Methods: Expression of SLC9A2 was determined in breast cancers (n=127) using real time quantitative polymerase chain reaction. Transcript levels of this gene was analysed in the breast cancers for the implication in lymph node involvement and survival using Mann-Whitney test with SPSS (Version 27). The relation of prognosis was also analysed by Kaplan Meier plotter in breast cancer. Results: In lymph node positive breast cancer, the expression of SLC9A2 shown an increase trend than no metastasis (n=43, median=25.9, interquartile range [IQR] [0.9-215.4] vs. n=44, median=4.9, IQR [0.2-31.8], p=0.1213). SLC9A2 expression in TNM stage Ⅱ was significantly higher than stage Ⅰ (n=31, median=42, IQR [0-195] vs. n=47, median=3.3, IQR [0.2- 31.6], p=0.0267) and also showed in the pathological type of invasive ductal carcinoma (n=27, median=42, IQR [3- 550] vs. n=35, median=3.3, IQR [0.2-31.8], p=0.0223). Kaplan Meier plotter showed over survival of SLC9A2 high expression was significantly worse than SLC9A2 low expression (66 months vs. 123.6 months, Hazard Ratio [HR]=1.57 [1.3-1.9], p=0.000), also found in estrogen receptor (ER) positive (63.8 months vs. 173.7 months, HR=2.19 [1.6-3.01], p=0.000). In patients with tamoxifen therapy, SLC9A2 high expression also had poor survival comparing to low expression (HR=2.86 [1.4-5.86], p=0.0026). Conclusions: High expression of SLC9A2 is correlation with lymph node metastasis and poor survival in breast cancer. SLC9A2 could be as a predictor for lymphatic involvement and survival and might be an indicator for detection of resistance to endocrine therapy. Citation Format: Binbin Cong, Xiaoshan Cao, Wen Jiang, Lin Ye. High expression of SLC9A2 is correlation with lymphatic metastasis and poor survival in breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-05-12.

GNPNAT1 is a Biomarker That Predicts a Poor Prognosis of Breast Cancer.

Breast cancer (BC) is increasingly becoming the primary reason for death in women, which sounded the alarm. Thus, finding a novel management target for BC is imminent. The data on gene expression and clinicopathological characteristics were downloaded from The Cancer Genome Atlas (TCGA). The expression of GNPNAT1 in 40 paired breast cancer and adjacent tissues was measured by quantitative real-time polymerase chain reaction (qRT-PCR). Univariate and Multivariate logistic regression methodology was applied to analyze the prognostic factors for lymph node metastasis (LNM). Based on the status of breast cancer-relative receptors, patients were distributed into six groups, and then the Kaplan-Meier survival analysis with a Log rank test was applied to investigate the involvement among the expression of GNPNAT1 and overall survival (OS). We found higher expression of GNPNAT1 was connected with poor survival in breast cancer by COX regulation analysis. GO, KEGG, and GSEA analysis prompted that GNPNAT1 was connected with the defense mechanism of cells, cell proliferation, and division. Immunization infiltration analysis showed that high GNPNAT1 was negatively connected with 16 immunization infiltration cell types and positively connected with four immunization infiltration cell types. As a whole, our results indicated that GNPNAT1 might be a probable biomarker for diagnosis and prognosis in breast cancer.

Digital PCR quantification of ultrahigh ERBB2 copy number identifies poor breast cancer survival after trastuzumab

HER2/ERBB2 evaluation is necessary for treatment decision-making in breast cancer (BC), however current methods have limitations and considerable variability exists. DNA copy number (CN) evaluation by droplet digital PCR (ddPCR) has complementary advantages for HER2/ERBB2 diagnostics. In this study, we developed a single-reaction multiplex ddPCR assay for determination of ERBB2 CN in reference to two control regions, CEP17 and a copy-number-stable region of chr. 2p13.1, validated CN estimations to clinical in situ hybridization (ISH) HER2 status, and investigated the association of ERBB2 CN with clinical outcomes. 909 primary BC tissues were evaluated and the area under the curve for concordance to HER2 status was 0.93 and 0.96 for ERBB2 CN using either CEP17 or 2p13.1 as reference, respectively. The accuracy of ddPCR ERBB2 CN was 93.7% and 94.1% in the training and validation groups, respectively. Positive and negative predictive value for the classic HER2 amplification and non-amplification groups was 97.2% and 94.8%, respectively. An identified biological “ultrahigh” ERBB2 ddPCR CN group had significantly worse survival within patients treated with adjuvant trastuzumab for both recurrence-free survival (hazard ratio, HR: 3.3; 95% CI 1.1–9.6; p = 0.031, multivariable Cox regression) and overall survival (HR: 3.6; 95% CI 1.1–12.6; p = 0.041). For validation using RNA-seq data as a surrogate, in a population-based SCAN-B cohort (NCT02306096) of 682 consecutive patients receiving adjuvant trastuzumab, the ultrahigh-ERBB2 mRNA group had significantly worse survival. Multiplex ddPCR is useful for ERBB2 CN estimation and ultrahigh ERBB2 may be a predictive factor for decreased long-term survival after trastuzumab treatment.

Downregulation of long noncoding RNA B4GALT1-AS1 is associated with breast cancer development

The misregulation of long non-coding RNAs (lncRNAs) is related to the progressive evolution of various human cancers, such as Breast cancer (BC). The role of lncRNA B4GALT1-AS1 has been investigated in some human cancers. Therefore, studying B4GALT1-AS1 expression was aimed for the first time in the tumor and marginal tissues of BC in this study. The cancer genome atlas (TCGA) database was utilized to evaluate the relative expression of B4GALT1-AS1 in BC and other cancers. RNA was extracted from twenty-eight paired BC and marginal tissues, and cDNA was synthesized. The quantitative expression level of B4GALT1-AS1 was evaluated using real-time PCR. The bioinformatics analyses were performed to identify co-expression genes and related pathways. B4GALT1-AS1 was significantly downregulated in BC specimens compared to tumor marginal samples. The TCGA data analysis confirmed the downregulation of B4GALT1-AS1 in BC. The bioinformatics analysis discovered the correlation between 700 genes and B4GALT1-AS1 and identified GNAI1 as the high degree gene which was positively correlated with B4GALT1-AS1 expression. It seems B4GALT1-AS1 provides its function, at least partly, in association with one of the hippo pathway components, YAP, in other cancers. This protein has the opposite role in BC and its loss of function can result in poor survival in BC. Further research is needed to investigate the interaction between B4GALT1‐AS1 and YAP in various subtypes of BC.

Identification of VWA5A as a novel biomarker for inhibiting metastasis in breast cancer by machine-learning based protein prioritization

Distant metastasis is the leading cause of death in breast cancer (BC). The timing of distant metastasis differs according to subtypes of BCs and there is a need for identification of biomarkers for the prediction of early and late metastasis. To identify biomarker candidates whose abundance level can discriminate metastasis types, we performed a high-throughput proteomics assay using tissue samples from BCs with no metastasis, late metastasis, and early metastasis, processed data with machine learning-based feature selection, and found that low VWA5A could be responsible for shorter duration of metastasis-free interval. Low expression of VWA5A gene in METABRIC cohort was associated with poor survival in BCs, especially in hormone receptor (HR)-positive BCs. In-vitro experiments confirmed tumor suppressive effect of VWA5A on BCs in HR+ and triple-negative BC cell lines. We found that expression of VWA5A can be assessed by immunohistochemistry (IHC) on archival tissue samples. Decreasing nuclear expression of VWA5A was significantly associated with advanced T stage and lymphatic invasion in consecutive BCs of all subtypes. We discovered lower expression of VWA5A as the potential biomarker for metastasis-prone BCs, and our results support the clinical utility of VWA5A IHC, as an adjunctive tools for prognostication of BCs.

Bifunctional Inhibitor Reveals NEK2 as a Therapeutic Target and Regulator of Oncogenic Pathways in Lymphoma.

Expression of the serine/threonine kinase never in mitosis gene A (NIMA)-related kinase 2 (NEK2) is essential for entry into mitosis via its role in facilitating centrosome separation. Its overactivity can lead to tumorigenesis and drug resistance through the activation of several oncogenic pathways, including AKT. Although the cancer-enabling activities of NEK2 are documented in many malignancies, including correlations with poor survival in myeloma, breast, and non-small cell lung cancer, little is known about the role of NEK2 in lymphoma. Here, in tumors from patients with diffuse large B-cell lymphoma (DLBCL), the most common, aggressive non-Hodgkin lymphoma, we found a high abundance of NEK2 mRNA and protein associated with an inferior overall survival. Using our recently developed NEK2 inhibitor, NBI-961, we discovered that DLBCL cell lines and patient-derived cells exhibit a dependency on NEK2 for their viability. This compromised cell fitness was directly attributable to efficient NEK2 inhibition and proteasomal degradation by NBI-961. In a subset of particularly sensitive DLBCL cells, NBI-961 induced G2/mitosis arrest and apoptosis. In contrast, an existing indirect NEK2 inhibitor, INH154, did not prevent NEK2 autophosphorylation, induce NEK2 proteasomal degradation, or affect cell viability. Global proteomics and phospho-proteomics revealed that NEK2 orchestrates cell-cycle and apoptotic pathways through regulation of both known and new signaling molecules. We show the loss of NEK2-sensitized DLBCL to the chemotherapy agents, doxorubicin and vincristine, and effectively suppressed tumor growth in mice. These studies establish the oncogenic activity of NEK2 in DLBCL and set the foundation for development of anti-NEK2 therapeutic strategies in this frequently refractory and relapse-prone cancer.

SOX13 is a novel prognostic biomarker and associates with immune infiltration in breast cancer.

The transcription factor, SOX13 is part of the SOX family. SOX proteins are crucial in the progression of many cancers, and some correlate with carcinogenesis. Nonetheless, the biological and clinical implications of SOX13 in human breast cancer (BC) remain rarely known. We evaluated the survival and expression data of SOX13 in BC patients via the UNLCAL, GEPIA, TIMER, and Kaplan-Meier plotter databases. Immunohistochemistry (IHC) was used to verify clinical specimens. The gene alteration rates of SOX13 were acquired on the online web cBioportal. With the aid of the TCGA data, the association between SOX13 mRNA expression and copy number alterations (CNA) and methylation was determined. LinkedOmics was used to identify the genes that co-expressed with SOX13 and the regulators. Immune infiltration and tumor microenvironment evaluations were assessed by ImmuCellAI and TIMER2.0 databases. SOX13 correlated drug resistance analysis was performed using the GDSC2 database. Higher SOX13 expression was discovered in BC tissues in comparison to normal tissues. Moreover, increased gene mutation and amplification of SOX13 were found in BC. Patients with increased SOX13 expression levels showed worse overall survival (OS). Cox analysis showed that SOX13 independently served as a prognostic indicator for poor survival in BC. Further, the expression of SOX13 was also confirmed to be correlated with tumor microenvironment and diverse infiltration of immune cells. In terms of drug sensitivity analysis, we found higher expression level of SOX13 predicts a high IC50 value for most of 198 drugs which predicts drug resistance. The present findings demonstrated that high expression of SOX13 negatively relates to prognosis and SOX13 plays an important role in cancer immunity. Therefore, SOX13 may potentially be adopted as a biomarker for predicting BC prognosis and infiltration of immune cells.

Early increase in tamoxifen dose in CYP2D6 poor metaboliser breast cancer patients and survival: A propensity score matching analysis.

Tamoxifen is a drug used for hormone receptor-positive breast cancers, primarily metabolised by the CYP2D6 enzyme into active metabolites such as endoxifen. CYP2D6 displays varying degrees of activity depending on its genotype. This study aims to analyse the effect of an early increase in tamoxifen dose in poor metabolisers (PM) on survival. We enrolled 220 patients diagnosed with breast cancer who were treated with tamoxifen. CYP2D6 polymorphisms were determined, and the phenotype was estimated according to the Clinical Pharmacogenetics Implementation Consortium. Disease-free survival (DFS) and overall survival (OS) were analysed considering the entire patient group, and a subgroup of 110 patients selected by Propensity Score Matching (PSM). All women were treated with 20mg/day of tamoxifen for 5 years, except PM, who initially received 20mg/day for 4 months, followed by 40mg/day for 4 months and 60mg/day for 4 months before returning to the standard dose of 20mg/day until completing 5 years of treatment. The analysis of the influence of CYP2D6 polymorphisms in the complete group and in the PSM subgroup revealed no significant differences for DFS or OS. Furthermore, DFS and OS were analysed in relation to various covariates such as age, histological grade, nodal status, tumour size, HER-2, Ki-67, chemotherapy, and radiotherapy. Only age, histological grade, nodal status, and chemotherapy treatment demonstrated statistical significance. An early increase in tamoxifen dose in PM patients is not associated with survival differences among CYP2D6 phenotypes.

SNRPD1 conveys prognostic value on breast cancer survival and is required for anthracycline sensitivity

BackgroundCancers harboring spliceosome mutations are highly sensitive to additional perturbations on the spliceosome that leads to the development of onco-therapeutics targeting the spliceosome and opens novel opportunities for managing aggressive tumors lacking effective treatment options such as triple negative breast cancers. Being the core spliceosome associated proteins, SNRPD1 and SNRPE have been both proposed as therapeutic targets for breast cancer management. Yet, their differences regarding their prognostic and therapeutic use as well as roles during carcinogenesis are largely unreported.MethodsWe conducted in silico analysis at gene expression and genetic levels to differentiate the clinical relevance of SNRPD1 and SNRPE, and explored their differential functionalities and molecular mechanistic associations with cancer in vitro.ResultsWe showedthat high SNRPD1 gene expression was prognostic of poor breast cancer survival whereasSNRPE was not. The SNRPD1 expression quantitative trait loci, rs6733100, was foundindependently prognostic of breast cancer survival using TCGA data. Silencing eitherSNRPD1 or SNRPE independently suppressed the growth of breast cancer cells, butdecreased migration was only observed in SNRPD1-silenced cells. Knocking down SNRPD1but not SNRPE triggers doxorubicin resistance in triple negative breast cancer cells.Gene enrichment and network analyses revealed the dynamic regulatory role of SNRPD1on cell cycle and genome stability, and the preventive role of SNRPE against cancerstemness that may neutralize its promotive role on cancer cell proliferation.ConclusionOur results differentiated the functionalities of SNRPD1 and SNRPE at both prognostic and therapeutic levels, and preliminarily explained the driving mechanism that requires additional explorations and validations.

High expression of TLR3 in triple-negative breast cancer predicts better prognosis—data from the Fudan University Shanghai Cancer Center cohort and tissue microarrays

IntroductionWe have previously reported that Toll-like receptor 3 (TLR3) acts as a suppressor gene for breast cancer initiation and progression. In this study, we evaluated the role of TLR3 in breast cancer using our original Fudan University Shanghai Cancer Center (FUSCC) datasets and breast cancer tissue microarrays.MethodsUsing FUSCC multiomics datasets on triple- negative breast cancer (TNBC), we compared the mRNA expression of TLR3 in TNBC tissue and the adjacent normal tissue. A Kaplan–Meier plotter was performed to investigate the expression of TLR3 on prognosis in the FUSCC TNBC cohort. We performed immunohistochemical staining to analyze TLR3 protein expression in the TNBC tissue microarrays. Furthermore, bioinformatics analysis was performed using the Cancer Genome Atlas (TCGA) data to verify the results of our FUSCC study. The relationship between TLR3 and clinicopathological features was analyzed with logistic regression and the Wilcoxon signed-rank test. The association between clinical characteristics and overall survival in TCGA patients was assessed using the Kaplan–Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify signaling pathways that are differentially activated in breast cancer.ResultsThe mRNA expression of TLR3 was lower in TNBC tissue than in the adjacent normal tissue in the FUSCC datasets. The TLR3 had high expression in immunomodulatory (IM) and mesenchymal-like (MES) subtypes and low expression in luminal androgen receptor (LAR) and basal-like immune-suppressed (BLIS) subtypes. High expression of TLR3 in TNBC predicted better prognosis in the FUSCC TNBC cohort. Immunohistochemical staining of the tissue microarrays showed that TLR3 had lower expression in breast cancer tissues than in the adject normal tissues. Furthermore, the TLR3 expression was positively associated with B cell, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and myeloid dendritic cells. Bioinformatic analysis using high-throughput RNA-sequencing data from the TCGA demonstrated that the reduced expression of TLR3 in breast cancer was associated with advanced clinicopathological characteristics, survival time, and poor prognosis.ConclusionsTLR3 has low expression in TNBC tissue. High expression of TLR3 in triple-negative breast cancer predicts better prognosis. TLR3 expression may be a potential prognostic molecular marker of poor survival in breast cancer.

The association between body fatness and mortality among breast cancer survivors: results from a prospective cohort study

Evidence linking body fatness to breast cancer (BC) prognosis is limited. While it seems that excess adiposity is associated with poorer BC survival, there is uncertainty over whether weight changes reduce mortality. This study aimed to assess the association between body fatness and weight changes pre- and postdiagnosis and overall mortality and BC-specific mortality among BC survivors. Our study included 13,624 BC survivors from the European Prospective Investigation into Cancer and Nutrition (EPIC) study, with a mean follow-up of 8.6 years after diagnosis. Anthropometric data were obtained at recruitment for all cases and at a second assessment during follow-up for a subsample. We measured general obesity using the body mass index (BMI), whereas waist circumference and A Body Shape Index were used as measures of abdominal obesity. The annual weight change was calculated for cases with two weight assessments. The association with overall mortality and BC-specific mortality were based on a multivariable Cox and Fine and Gray models, respectively. We performed Mendelian randomization (MR) analysis to investigate the potential causal association. Five-unit higher BMI prediagnosis was associated with a 10% (95% confidence interval: 5–15%) increase in overall mortality and 7% (0–15%) increase in dying from BC. Women with abdominal obesity demonstrated a 23% (11–37%) increase in overall mortality, independent of the association of BMI. Results related to weight change postdiagnosis suggested a U-shaped relationship with BC-specific mortality, with higher risk associated with losing weight or gaining > 2% of the weight annually. MR analyses were consistent with the identified associations. Our results support the detrimental association of excess body fatness on the survival of women with BC. Substantial weight changes postdiagnosis may be associated with poorer survival.

Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools.

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan-Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4+ T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.

Tumor senescence leads to poor survival and therapeutic resistance in human breast cancer.

Breast cancer (BRCA) is the most common malignant tumor that seriously threatens the health of women worldwide. Senescence has been suggested as a pivotal player in the onset and progression of tumors as well as the process of treatment resistance. However, the role of senescence in BRCA remains unelucidated. The clinical and transcriptomic data of 2994 patients with BRCA were obtained from The Cancer Genome Atlas and the METABRIC databases. Consensus clustering revealed senescence-associated subtypes of BRCA patients. Functional enrichment analysis explored biological effect of senescence. We then applied weighted gene co-expression network analysis (WGCNA) and LASSO regression to construct a senescence scoring model, Sindex. Survival analysis validated the effectiveness of Sindex to predict the overall survival (OS) of patients with BRCA. A nomogram was constructed by multivariate Cox regression. We used Oncopredict algorithm and real-world data from clinical trials to explore the value of Sindex in predicting response to cancer therapy. We identified two distinct senescence-associated subtypes, noted low senescence CC1 and high senescence CC2. Survival analysis revealed worse OS associated with high senescence, which was also validated with patient samples from the National Cancer Center in China. Further analysis revealed extensively cell division and suppression of extracellular matrix process, along with lower stromal and immune scores in the high senescence CC2. We then constructed a 37 signature gene scoring model, Sindex, with robust predictive capability in patients with BRCA, especially for long time OS beyond 10 years. We demonstrated that the Sene-high subtype was resistant to CDK inhibitors but sensitive to proteosome inhibitors, and there was no significant difference in paclitaxel chemotherapy and immunotherapy between patients with different senescence statuses. We reported senescence as a previously uncharacterized hallmark of BRCA that impacts patient outcomes and therapeutic response. Our analysis demonstrated that the Sindex can be used to identify not only patients at different risk levels for the OS but also patients who would benefit from some cancer therapeutic drugs.

Abstract P6-10-08: Evaluation of potent novel second-generation MELK-selective inhibitor in aggressive breast cancers

Abstract Background Inflammatory breast cancer (IBC) and triple-negative breast cancer (TNBC) are aggressive breast cancer subtypes with poor clinical outcomes due to the lack of well-validated and actionable targets and the onset of chemo-resistant metastasis. TNBC and IBC account for 15-20% and 2-4% of all breast cancer diagnoses but result in 30% and 8%–10% of breast cancer-related deaths, respectively. MELK (maternal embryonic leucine zipper kinase) is a potential therapeutic target in both TNBC and triple-negative IBC (TN-IBC). We have shown that 1) MELK expression is higher in basal tumors (mostly TNBC) and in IBC than in non-IBC, 2) high MELK expression is an independent prognostic factor for poor overall survival (P=0.0002) and poor distant metastasis-free survival (P=0.008) in breast cancer, and 3) MELK knockout leads to significantly lower metastatic burden and prolonged survival in a xenograft model of TNBC (unpublished data). MELK inhibitor (MELKi) OTS167 is in clinical trials but it lacks specificity and cross-reacts with other essential kinases. It is critical to discover novel, selective inhibitors with good bioavailability that target MELK and minimize adverse effects. We have developed a second-generation small-molecule MELK inhibitor 30e that is a highly potent and slow-binding ATP-competitive inhibitor of MELK. 30e exhibits potent cellular inhibition of MELK (IC50< 10 nM), as assessed using a live cell NanoBRET assay, and is highly selective as assessed by live-cell KiNativ profiling experiments in MDA-MB-231 TNBC cells. Methods We screened a panel of TNBC and IBC cell lines for MELK expression by western blot and qPCR analysis. We assessed the effects of MELK inhibition with the 30e on migration and invasion. The role of MELK in regulating cancer stem cell phenotypes was assessed using the mammosphere assay and flow cytometry (CD44+/CD24-/low surface marker). MELK’s protumorigenic role was determined in vitro using a soft agar assay, and the anti-tumor activity of 30e was assessed in vivo using a TN-IBC orthotopic xenograft mouse model. Results We found that TNBC had high mRNA levels of MELK (62%) compared to non-TNBC cell lines (25%), which correlated with MELK protein levels. 30e inhibited cell viability in TNBC and IBC cells in a dose-dependent manner and with IC50s ranging from 0.45 to 1.76 μM (P≤0.05). However, no significant effect was observed when normal MCF-10A breast cells were treated with 30e (IC50>20 μM). 30e also significantly reduced colony formation ability. Further, we observed that 30e reduced mammosphere formation efficiency and the CD44+/CD24-/low subpopulation in both TNBC and IBC cells in a dose-dependent manner (P≤0.05), suggesting the potential of 30e to inhibit the stem cell population in vitro. The soft agar assay also showed a significant decrease in colony formation in the TNBC and IBC cells after treatment with 30e, an indirect indicator of in vivo tumorigenicity. To assess the efficacy of 30e treatment on tumor growth, we evaluated this inhibitor as a single agent in a SUM-149 (TN-IBC) orthotopic mouse model. The mice were treated with intraperitoneal injections daily with 3 doses (2.5, 5, and 10 mg/kg) of 30e. Our data show that 30e suppressed tumor growth in a dose-dependent manner (P< 0.007). Conclusions and Future Directions Our data demonstrate that a novel, potent and specific MELK inhibitor inhibits tumor growth by suppressing the cancer stem cell phenotype. MELK is a promising target for aggressive cancers such as TNBC and IBC. We are evaluating how MELK inhibition modulates the tumor microenvironment, which is a critical component of breast cancer response to treatment. We performed a cytokine antibody array and are validating the top targets. Further, we will evaluate 30e in combination with standard-of-care treatment for toxicity and inhibition of metastasis. Citation Format: Mohd Mughees, Moises Tacam, Alex Tan, Hector Gonzalez, Emilly S. Villodre, Bisrat Debeb, Debu Tripathy, Geoffrey Bartholomeusz, Juhyeon Lee, Kevin Dalby, Chandra Bartholomeusz. Evaluation of potent novel second-generation MELK-selective inhibitor in aggressive breast cancers [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 P6-10-08.

The association of race/ethnicity in male breast cancer survival within similar comorbidity cohorts.

Concomitant disease is associated with poor breast cancer survival in women and is more prevalent in racial/ethnic minority groups than individuals who are non-Hispanic White. The purpose of this study was to determine if race/ethnicity is associated with survival among men with breast cancer when stratifying analyses by level of comorbidity. We used the California Cancer Registry to identify 1730 cases of men and 259,828 cases of women with breast cancer and documented Charlson Comorbidity Index (CCI). Kaplan-Meier survival and Cox regression analyses were used tocompare breast cancer-specific survival and risk of mortality for African American/Black, Hispanic, and Asian/Pacific Islander men with White women and White men. When compared with White women, Black men with a CCI of 0 (hazard ratio [HR],3.09; 95% CI, 1.10-1.16) and a CCI of 2+, (HR,2.51; 95% CI, 1.42-4.42) had an increased risk of mortality when compared with White women. When compared with White men, African American men with a CCI of 0 (HR,2.36; 95% CI, 1.45-3.85) and 2+ (HR,2.44; 95% CI, 1.26-4.74) had an increased unadjusted risk of mortality, but these disparities were neutralized when controlling for sociodemographic and clinical factors. Black men with both low and high levels of concomitant disease have an increased risk of mortality when compared with both White men and women, but demographic and clinical factors are contributors to this disparity.

A Novel Inflammatory and Nutritional Prognostic Scoring System for Nonpathological Complete Response Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy.

It has been demonstrated that inflammatory and nutritional variables are associated with poor breast cancer survival. However, some studies do not include these variables due to missing data. To investigate the predictive potential of the INPS, we constructed a novel inflammatory-nutritional prognostic scoring (INPS) system with machine learning. This retrospective analysis included 249 patients with malignant breast tumors undergoing neoadjuvant chemotherapy (NAC). After comparing seven potent machine learning models, the best model, Xgboost, was applied to construct an INPS system. K-M survival curves and the log-rank test were employed to determine OS and DFS. Univariate and multivariate analyses were carried out with the Cox regression model. Additionally, we compared the predictive power of INPS, inflammatory, and standard nutritional variables using the Z test. After comparing seven machine learning models, it was determined that the XGBoost model had the best OS and DFS performance (AUC = 0.865 and 0.771, respectively). For overall survival (OS, cutoff value = 0.3917) and disease-free survival (cutoff value = 0.4896), all patients were divided into two groups by the INPS. Those with low INPS had higher 5-year OS and DFS rates (77.2% vs. 50.0%, P < 0.0001; and 59.6% vs. 32.1%, P < 0.0001, respectively) than patients with high INPS. For OS and DFS, the INPS exhibited the highest AUC compared to the other inflammatory and nutritional variables (AUC = 0.615, P = 0.0003; AUC = 0.596, P = 0.0003, respectively). The INPS was an independent predictor of OS and DFS and exhibited better predictive ability than BMI, PNI, and MLR. For patients undergoing NAC for nonpCR breast cancer, INPS was a crucial and comprehensive biomarker. It could also forecast individual survival in breast cancer patients with low HER-2 expression.

The Diagnostic and Prognostic Significance of EFEMP1 in Breast Cancer: An Immunohistochemistry Study.

EGF-containing fibulin-like extracellular matrix protein 1 (EFEMP1) has been associated to a variety of malignancies. Because EFEMP1 can act as both a tumor suppressor and an oncogene, this study aimed to evaluate the expression of EFEMP1 at mRNA and protein in breast cancer and to ascertain the diagnostic and prognostic value of EFEMP1 in relation to clinical features of breast cancer. Several bioinformatics websites such as GEPIA and Oncomine databases were used to analyze the mRNA level of EFEMP1. Immunohistochemistry assay was used to detect EFEMP1 immunoexpression using tissue microarray (TMA) and clinical breast cancer samples. EFEMP1 was shown to be overexpressed in breast cancer in some study cohorts while being low expressed in others. In TMA, 86 patients (39.1%) with a high H-score and 134 patients (60.9%) with a low H-score had EFEMP1 positive for breast cancer. While HER2 breast cancer and normal breast tissues had the lowest expression of EFEMP1, it was shown to be highly expressed in Luminal B, A, and TNBC. EFEMP1 H-score is associated with tumor stage and indicates poor overall survival in breast cancer. EFEMP1 H-score was high in the clinical tumor tissues compared with adjacent normal tissue (n = 20), therefore, it would to be a sensitive biomarker for breast cancer. EFEMP1 is a key indicator for assessing the clinical prognosis and diagnosis of patients with breast cancer, as evidenced by the higher expression of EFEMP1 in tumor tissue compared to normal tissue and its association with poor overall survival.

Clinicopathologic Review of Metastatic Breast Cancer to the Gynecologic Tract.

Metastatic spread is the single most significant predictor of poor survival in breast cancer. Some of the most common metastatic sites are the bones, lungs, liver, brain, and peritoneal cavity. Clinically metastatic breast cancer to the gynecologic tract is usually asymptomatic and diagnosed as an incidental finding during a histologic examination of gynecologic specimens resected for other reasons. Cases of metastatic breast cancer to gynecologic organs diagnosed from August 1995 to January 2021 were retrieved from our institution's pathology databases, and their clinicopathologic features were reviewed. The most common site of metastasis was the ovary which was involved in about 79% (22 of 28 cases) of metastases to the gynecologic tract. Clinically, only 8 cases (36%) presented with ovarian mass detected in imaging studies and the rest of the cases were all incidental findings. Among ovarian metastasis, 59% of cases were invasive lobular carcinoma and 41% were invasive ductal carcinoma. In 5 cases, metastatic breast cancer was found in the endometrium, including 2 cases with endometrial metastasis only and 3 cases with multiple gynecologic organs involved. Metastatic breast cancer rarely involved the lower gynecologic tract, with only 7% vaginal metastasis and 4% found in the vulva. The absolute majority of metastatic breast cancer outside of the ovaries were lobular carcinoma (88%). Most of the metastatic breast carcinomas were positive for estrogen receptor on immunohistochemistry (27 of 28 cases, 96%). Her-2/neu immunostaining was positive in 4 cases only (14%). Metastatic breast cancer needs to be distinguished from gynecologic primary neoplasms and metastatic tumors from adjacent urinary and GI tracts. A careful review of the patient's history and adequate immunohistochemistry panel are helpful to render the diagnosis.

Functional regulations between genetic alteration-driven genes and drug target genes acting as prognostic biomarkers in breast cancer

Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer. We identified two mutation and copy number-driven gene pairs (PARP1-ACSL1 and PARP1-SRD5A3), three DNA methylation-driven gene pairs (PRLR-CDKN1C, PRLR-PODXL2 and PRLR-SRD5A3), six gene pairs between mutation-driven genes and drug target genes (SLC19A1-SLC47A2, SLC19A1-SRD5A3, AKR1C3-SLC19A1, ABCB1-SRD5A3, NR3C2-SRD5A3 and AKR1C3-SRD5A3), and four copy number-driven gene pairs (ADIPOR2-SRD5A3, CASP12-SRD5A3, SLC39A11-SRD5A3 and GALNT2-SRD5A3) that all served as prognostic biomarkers of breast cancer. In particular, RARP1 was found to be upregulated by simultaneous copy number amplification and gene mutation. Copy number deletion and downregulated expression of ACSL1 and upregulation of SRD5A3 both were observed in breast cancers. Moreover, copy number deletion of ACSL1 was associated with increased resistance to PARP inhibitors. PARP1-ACSL1 pair significantly correlated with poor overall survival in breast cancer owing to the suppression of the MAPK, mTOR and NF-kB signaling pathways, which induces apoptosis, autophagy and prevents inflammatory processes. Loss of SRD5A3 expression was also associated with increased sensitivity to PARP inhibitors. The PARP1-SRD5A3 pair significantly correlated with poor overall survival in breast cancer through regulating androgen receptors to induce cell proliferation. These results demonstrate that genetic alteration-driven gene pairs might serve as potential biomarkers for the prognosis of breast cancer and facilitate the identification of combination therapeutic targets for breast cancers.

Abstract 812: High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer

Abstract INTRODUCTION: Homologous recombination deficiency (HRD) is involved in breast cancer carcinogenesis, however, activation of DNA repair in cancer cells may promote its survival and progression. RAD51 plays an essential role in homologous recombination with BRCA2. Recently, RAD51 has been highlighted to play a role in resistance to DNA-damaging chemotherapy or PARP inhibitors. We hypothesized that RAD51 as a prognostic and predictive biomarker of drug sensitivity in breast cancer. MATERIALS AND METHODS: Total of 4500 primary breast cancer patients from three independent cohorts were examined. High and low expression of RAD51 were divided by median RNA expression. Response to treatments were assessed in total of 3000 patients across 11 independent cohorts of breast cancer patients that received neoadjuvant chemotherapy. RESULTS: RAD51 was upregulated in cancer compared to normal tissues in the TCGA cohort and was positively correlated with HRD. Cancer with high RAD51 group enriched DNA repair gene set in gene set enrichment analysis (GSEA) in all cohorts and had high expression of HRD-related genes including BRCA1 and BRCA2. Histological grade and Ki67 expression were positively correlated with RAD51, and all cancer proliferation gene sets from Hallmark (E2F target, G2M checkpoint, Myc Targets v1 and v2, and Mitotic Spindle) were strongly enriched in the high RAD51 expression breast cancer in all cohorts. In TCGA, tumor mutation burden and neoantigen were also higher in tumor with high RAD51 expression, but RAD51 expression was not elevated in BRCA1 or BRCA2 mutant tumors. Cytolytic activity score, a marker of cancer immunity, was elevated high RAD51 group in two cohorts, and the immune cell fraction calculated by the xCell algorithm showed increase in immune cell infiltration, including CD4 memory T cells, Th1 cells, M1 macrophages and activated dendritic cells, in all cohorts, suggesting a certain level of activation of cancer immunity in this RAD51 high breast cancer group. However, contrary to previous reports, RAD51 expression in breast cancer cell lines did not show any association between sensitivity to chemotherapy or PARP inhibitors. Neither for the breast cancer NAC cohort, RAD51 expression was not increased in the residual burden group, but conversely increase in RAD51expression was observed in pathological complete response group in some cohorts. Surprisingly, RAD51 was significantly associated with worse overall survival in all three large cohorts included in this analysis, and with worse disease-specific survival in two cohorts. CONCLUSIONS: RAD51 expression was significantly associated with worse survival, but did not with treatment-responsive, suggesting its usefulness as prognostic, but not predictive, biomarker. Citation Format: Rongrong Wu, Ankit Patel, Yoshihisa Tokumaru, Mariko Asaoka, Masanori Oshi, Li Yan, Takashi Ishikawa, Kazuaki Takabe. High RAD51 gene expression is associated with aggressive biology and with poor survival in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 812.