Luminal Breast Cancer Subtypes Research Articles

Abstract PO3-13-10: Proteogenomic characterization of primary invasive breast tumors from young women compared to matched tumors from older women

Abstract Introduction: Breast cancer (BC) in women < 40 years old accounts for ~5% of BC diagnosed in the U.S. However, young women have more aggressive tumors and worse outcomes, including higher rates of recurrence and lower disease-free and overall survival, compared to older women. To better understand mechanisms for these disparities, an integrated proteogenomic study of tumors from young (< 40) and older (≥ 60) women was performed through the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) program. Methods: 34 pairs of retrospectively collected, untreated primary breast tumors from young and older women, matched by immunohistochemistry (IHC) subtype and race, were selected from the Clinical Breast Care Project. Median patient follow-up was 7 years. Tumor cells were enriched by laser microdissection and analyzed using RNA sequencing, whole genome sequencing, global proteomics, phosphoproteomics, and reverse phase protein array (RPPA). Molecular and clinical data from tumors from young and old patients in the TCGA-BC and METABRIC studies, matched by IHC subtype and race, were used to corroborate findings from our cohort. Results are presented comparing young women and their tumors to their older counterparts. Results: Young women have worse clinical outcome measured by progression-free interval. Despite matching for IHC subtypes, tumors from young women are enriched for intrinsic basal-like subtype, BRCA1/2 germline mutations, and had fewer invasive lobular BCs. Differentially enriched molecules and pathways: A number of significantly differentially expressed genes (DEGs) and proteins were detected, which were able to separate luminal subtypes of BC by patient age. IRS1 and IRS2 were enriched at both transcript and protein levels; IRS1 has been reported to promote tamoxifen resistance. We observed limited overlap of DEGs between the APOLLO, TCGA, and METABRIC datasets. In contrast, 14 of the 28 significantly upregulated Cancer Hallmark pathways were also enriched in TCGA-BC and METABRIC datasets; suggesting targeting pathways, vs genes, may be more effective for therapeutic intervention. Integrated pathway/network analysis: Integrated pathway analysis of RNA and protein levels identified 5 Hallmark pathways upregulated in younger women, including ER response and proliferative pathways, and 6 downregulated immune-response pathways; 10 of the 11 were supported by the public datasets. Immune scores were also lower. Kinase substrate enrichment analysis identified 4 kinases with increased activity in tumors from young women. ESR1/ER: We identified for the first time a significant reduction of ER protein expression while confirming previously reported lower ESR1 gene expression and copy number variations. Surprisingly, integrated pathway analysis identified elevation of early and late estrogen responses in young women. ER activation, indicated by phosphorylated ER (pS118) normalized to total ER protein, was elevated in LumA tumors from young women. Conclusions: This first-ever integrated proteogenomic study shows that BC in young women is enriched for more aggressive molecular subtypes and for genes that promote tamoxifen resistance, exhibits lower immune pathways and immune scores, and shows enhanced ER responses despite lower gene and protein expression of ER. These findings may contribute to the understanding of the molecular mechanisms underlying worse outcomes of BC in young women, and offer new insight to therapeutic strategies. Disclaimer: The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions or policies of USUHS, HJF, the DoD or the Departments of the Army, Navy or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government. Citation Format: Praveen Kumar Raj Kumar, Jianfang Liu, Anthony Soltis, Nicholas Bateman, Qingrong Chen, Lori Sturtz, Brenda Deyarmin, Mariaelena Pierobon, Tamara Abulez, Anupama Praveen-Kumar, Xijun Zhang, Trinh Nguyen, Chunhua Yan, Ying Hu, Kate Guion, Jeffrey Hooke, Albert Kovatich, Leigh Fantacone-Campbell, Brad Mostoller, Leonid Kvecher, Stella Somiari, Patricia Steeg, Sheila Rajagopal, Kathleen Darcy, Jerry Lee, Clifton Dalgard, Thomas Conrads, Emanuel Petricoin, Daoud Meerzaman, Matthew Wilkerson, APOLLO Research Network, Xiaoying Lin, Craig Shriver, Stanley Lipkowitz, Hai Hu. Proteogenomic characterization of primary invasive breast tumors from young women compared to matched tumors from older women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-13-10.

CORONet: A Cross-Sequence Joint Representation and Hypergraph Convolutional Network for Classifying Molecular Subtypes of Breast Cancer Using Incomplete DCE-MRI.

Breast cancer, the predominant malignancy among women, is characterized by significant heterogeneity, leading to the emergence of distinct molecular subtypes. Accurate differentiation of these molecular subtypes holds paramount clinical significance, owing to substantial variations in prognosis, therapeutic strategies, and survival outcomes. In this study, we propose a cross-sequence joint representation and hypergraph convolution network (CORONet) for classifying molecular subtypes of breast cancer using incomplete DCE-MRI. Specifically, we first build a cross-sequence joint representation (COR) module to integrate image imputation and feature representation into a unified framework, encouraging effective feature extraction for subsequent classification. Then, we fuse multiple COR features and applied feature selection to reduce the redundant information between sequences. Finally, we deploy hypergraph structures to model high-order correlation among different subjects and extracted high-level semantic features by hypergraph convolutions for molecular subtyping. Extensive experiments on incomplete DCE-MRIs of 395 patients from the TCIA repository showed a significant improvement of our CORONet over state of the arts, with the area under the curve (AUC) of 0.891 and 0.903 for luminal and triple-negative (TN) subtype prediction, respectively. Similar advantages of CORONet were also confirmed in partial complete DCE-MRIs of 144 patients, achieving an AUC of 0.858 and 0.832 for predicting luminal and TN subtypes of breast cancer, respectively. Nevertheless, both of these values were lower compared to the scenario where DCE-MRIs from all 395 patients were utilized. Our study contributes to the precise molecular subtyping using incomplete multi-sequence DCE-MRI, thereby offering promising prospects for future risk stratification of breast cancer patients.

Molecular Characterization and Subtyping of Breast Cancer Cell Lines Provide Novel Insights into Cancer Relevant Genes.

Continuous cell lines are important and commonly used in vitro models in breast cancer (BC) research. Selection of the appropriate model cell line is crucial and requires consideration of their molecular characteristics. To characterize BC cell line models in depth, we profiled a panel of 29 authenticated and publicly available BC cell lines by mRNA-sequencing, mutation analysis, and immunoblotting. Gene expression profiles separated BC cell lines in two major clusters that represent basal-like (mainly triple-negative BC) and luminal BC subtypes, respectively. HER2-positive cell lines were located within the luminal cluster. Mutation calling highlighted the frequent aberration of TP53 and BRCA2 in BC cell lines, which, therefore, share relevant characteristics with primary BC. Furthermore, we showed that the data can be used to find novel, potential oncogenic fusion transcripts, e.g., FGFR2::CRYBG1 and RTN4IP1::CRYBG1 in cell line MFM-223, and to elucidate the regulatory circuit of IRX genes and KLF15 as novel candidate tumor suppressor genes in BC. Our data indicated that KLF15 was activated by IRX1 and inhibited by IRX3. Moreover, KLF15 inhibited IRX1 in cell line HCC-1599. Each BC cell line carries unique molecular features. Therefore, the molecular characteristics of BC cell lines described here might serve as a valuable resource to improve the selection of appropriate models for BC research.

Abstract C031: ABCD3 expression is upregulated Caucasian and Asian breast cancer patients and is associated with non-responsiveness to endocrine therapy in luminal breast cancers

Abstract The ABC transporters represent the largest family of transmembrane proteins. They also serve in protective roles whereby many transporters act as efflux pumps for xenobiotics. And subsequently, several members; most notably of the A, B and C subfamilies, have been implicated in cancer chemoresistance; however, D family members have not been extensively studies with regards to cancer biology and treatment. Here we report that ABCD3 transporter expression is upregulated in breast cancer (p<0.001). The gene was also upregulated across cancer stages (p<0.05). Analysis of histological subtypes revealed that ABCD3 was expressed infiltrating ductal carcinoma (IDC). Immunohistochemistry (IHC) analysis confirmed that ABCD3 protein is expressed IDC (p<0.001). Moreover, ABCD3 expression was elevated in White (p<0.001) and Asian (p<0.05) breast cancer patients but not in African-American patients. Analysis of molecular subtypes revealed that ABCD3 expression was significantly higher in the Luminal breast cancer subtype (p<0.001). Furthermore, ROC analysis of gene expression in relationship in response to treatment revealed that ABCD3 is a moderate predictor (AUC=0.644, p=0.003) of response to endocrine therapy (tamoxifen and aromatase inhibitors) and a strong predictor (AUC=08, p=0.026) to chemotherapy in luminal breast cancers. Taken collectively, ABCD3 represents a biomarker which may be important for determining therapeutic response. Citation Format: Romonia Renee Reams, Simone Heyliger, Marilyn Saulsbury. ABCD3 expression is upregulated Caucasian and Asian breast cancer patients and is associated with non-responsiveness to endocrine therapy in luminal breast cancers [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr C031.

Epigenetic Dysregulation and Its Correlation with the Steroidogenic Machinery Impacting Breast Pathogenesis: Data Mining and Molecular Insights into Therapeutics.

Breast cancer (BC) is a heterogeneous condition and comprises molecularly distinct subtypes. An imbalance in the levels of epigenetic histone deacetylases (HDACs), modulating estrogen accumulation, especially 17β-estradiol (E2), promotes breast tumorigenesis. In the present study, analyses of The Cancer Genome Atlas (TCGA) pan-cancer normalized RNA-Seq datasets revealed the dysregulation of 16 epigenetic enzymes (among a total of 18 members) in luminal BC subtypes, in comparison to their non-cancerous counterparts. Explicitly, genomic profiling of these epigenetic enzymes displayed increases in HDAC1, 2, 8, 10, 11, and Sirtuins (SIRTs) 6 and 7, and decreases in HDAC4-7, -9, and SIRT1-4 levels, respectively, in TCGA breast tumors. Kaplan-Meier plot analyses showed that these HDACs, with the exception of HDAC2 and SIRT2, were not correlated with the overall survival of BC patients. Additionally, disruption of the epigenetic signaling in TCGA BC subtypes, as assessed using both heatmaps and boxplots, was associated with the genomic expression of factors that are instrumental for cholesterol trafficking/utilization for accelerating estrogen/E2 levels, in which steroidogenic acute regulatory protein (STAR) mediates the rate-limiting step in steroid biosynthesis. TCGA breast samples showed diverse expression patterns of a variety of key steroidogenic markers and hormone receptors, including LIPE, CYP27A1, STAR, STARD3, CYP11A1, CYP19A1, ER, PGR, and ERBB2. Moreover, regulation of STAR-governed steroidogenic machinery was found to be influenced by various transcription factors, i.e., CREB1, CREM, SF1, NR4A1, CEBPB, SREBF1, SREBF2, SP1, FOS, JUN, NR0B1, and YY1. Along these lines, ingenuity pathway analysis (IPA) recognized a number of new targets and downstream effectors influencing BCs. Of note, genomic, epigenomic, transcriptional, and hormonal anomalies observed in human primary breast tumors were qualitatively similar in pertinent BC cell lines. These findings identify the functional correlation between dysregulated epigenetic enzymes and estrogen/E2 accumulation in human breast tumors, providing the molecular insights into more targeted therapeutic approaches involving the inhibition of HDACs for combating this life-threatening disease.

Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome.

The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome. A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer. The best accuracy for discriminating HER2 + versus HER2 - breast cancers was obtained considering nine predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 88% on validation set). The best accuracy for discriminating HR + versus HR - breast cancers was obtained considering nine predictors by T2-weighted subtraction images and a decision tree (accuracy of 90% on validation set). The best accuracy for discriminating G1 + G2 versus G3 breast cancers was obtained considering 16 predictors by early phase T1-weighted subtraction images in a linear regression model with an accuracy of 75%. The best accuracy for discriminating luminal versus non-luminal breast cancers was obtained considering 27 predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 94% on validation set). The combination of radiomics analysis and artificial intelligence techniques could be used to support physician decision-making in prediction of Breast Cancer Histological Outcome.

MAF1 is a predictive biomarker in HER2 positive breast cancer.

RNA polymerase III transcription is pivotal in regulating cellular growth and frequently deregulated in various cancers. MAF1 negatively regulates RNA polymerase III transcription. Currently, it is unclear if MAF1 is universally deregulated in human cancers. Recently, MAF1 expression has been demonstrated to be altered in colorectal and liver carcinomas and Luminal B breast cancers. In this study, we analyzed clinical breast cancer datasets to determine if MAF1 alterations correlate with clinical outcomes in HER2-positive breast cancer. Using various bioinformatics tools, we screened breast cancer datasets for alterations in MAF1 expression. We report that MAF1 is amplified in 39% of all breast cancer sub-types, and the observed amplification co-occurs with MYC. MAF1 amplification correlated with increased methylation of the MAF1 promoter and MAF1 protein expression is significantly decreased in luminal, HER2-positive, and TNBC breast cancer subtypes. MAF1 protein expression is also significantly reduced in stage 2 and 3 breast cancer compared to normal and significantly decreased in all breast cancer patients, regardless of race and age. In SKBR3 and BT474 breast cancer cell lines treated with anti-HER2 therapies, MAF1 mRNA expression is significantly increased. In HER2-positive breast cancer patients, MAF1 expression significantly increases and correlates with five years of relapse-free survival in response to trastuzumab treatment, suggesting MAF1 is a predictive biomarker in breast cancer. These data suggest a role for MAF1 alterations in HER2-positive breast cancer. More extensive studies are warranted to determine if MAF1 serves as a predictive and prognostic biomarker in breast cancer.

Untargeted LC-MS/MS Metabolomics Study of HO-AAVPA and VPA on Breast Cancer Cell Lines.

Breast cancer (BC) is one of the biggest health problems worldwide, characterized by intricate metabolic and biochemical complexities stemming from pronounced variations across dysregulated molecular pathways. If BC is not diagnosed early, complications may lead to death. Thus, the pursuit of novel therapeutic avenues persists, notably focusing on epigenetic pathways such as histone deacetylases (HDACs). The compound N-(2-hydroxyphenyl)-2-propylpentanamide (HO-AAVPA), a derivative of valproic acid (VPA), has emerged as a promising candidate warranting pre-clinical investigation. HO-AAVPA is an HDAC inhibitor with antiproliferative effects on BC, but its molecular mechanism has yet to be deciphered. Furthermore, in the present study, we determined the metabolomic effects of HO-AAVPA and VPA on cells of luminal breast cancer (MCF-7) and triple-negative breast cancer (MDA-MB-231) subtypes. The LC-MS untargeted metabolomic study allowed for the simultaneous measurement of multiple metabolites and pathways, identifying that both compounds affect glycerophospholipid and sphingolipid metabolism in the MCF-7 and MDA-MB-231 cell lines, suggesting that other biological targets were different from HDACs. In addition, there are different dysregulate metabolites, possibly due to the physicochemical differences between HO-AAVPA and VPA.

Relationship of The Characteristic Imaging Findings of Breast Cancer with Molecular Subtypes in Young Women.

The characteristic imaging findings of breast cancer in young women are not yet fully understood. It causes a delay in diagnosis by mixing with benign findings. To evaluate the relationship between the imaging and histopathological features of breast cancer in women aged under 40 years. In our center, 537 suspicious lesions were detected in a total of 15,223 adult female patients under 40 years who were evaluated by breast ultrasonography (US). As a result of the mammographic, histopathological, and immunohistochemical analysis, 101 lesions meeting the study criteria were included in the sample. The luminal subtypes of breast cancer mostly visualized as irregularly shaped spiculated lesions with calcification and architectural distortion mammography and presented as masses that were sometimes accompanied by increased echogenicity in the surrounding tissue on US. The human epidermal growth factor receptor 2 (HER2) enriched subtypes mostly had microlobulated or indistinct margins with heterogeneous echoes accompanied by high calcification on mammography. The triple-negative (TN) subtypes generally appeared as microlobulated lesions with angular or indistinct margins, hypo echogenicity, posterior enhancement or shadowing, and vascularization. Some radiological features of breast cancer in young women were found to be associated with molecular subtypes similar to other age groups in the literature. However, unlike other age groups, the incidences of the HER2-enriched subtype presenting with only calcification, TN subtypes presenting with circumscribed masses, and calcification were found to be low among the young women in our study.

FUNDC2, a mitochondrial outer membrane protein, mediates triple-negative breast cancer progression via the AKT/GSK3β/GLI1 pathway.

Triple-negative breast cancer (TNBC) lacks effective therapeutic targets and has a poor prognosis, easy recurrence and metastasis. It is urgent and important to explore TNBC treatment targets. Through mass spectrometry combined with qRT-PCR validation in luminal A cells and TNBC cells, high-content screening and clinical sample analysis, FUNDC2 was discovered as a novel target. The function of the outer mitochondrial membrane protein FUNDC2 in breast cancer is still unclear. In this study, we find that FUNDC2 expression in TNBC tissues is significantly higher than that in luminal subtype breast cancer tissues. FUNDC2 silencing in TNBC cells significantly reduces cell proliferation, migration and invasion. As demonstrated in vivo using subcutaneous tumor xenografts in mice, FUNDC2 suppression significantly inhibits tumor growth. The underlying mechanism might be mediated by inactivating its downstream signal AKT/GSK3β and GLI1, a key factor of the Hedgehog signaling pathway. Therefore, FUNDC2 may promote TNBC progression and provide a therapeutic target for treating TNBC.

Importance of endocrine treatment adherence and persistence in breast cancer survivorship: a systematic review

PurposeAdjuvant endocrine treatment is essential for treating luminal subtypes of breast cancer, which constitute 75% of all breast malignancies. However, the detrimental side effects of treatment make it difficult for many patients to complete the guideline-required treatment. Such non-adherence may jeopardize the lifesaving ability of anti-estrogen therapy. In this systematic review, we aimed to assess the consequences of non-adherence and non-persistence from available studies meeting strict statistical and clinical criteria.MethodsA systematic literature search was performed using several databases, yielding identification of 2,026 studies. After strict selection, 14 studies were eligible for systematic review. The review included studies that examined endocrine treatment non-adherence (patients not taking treatment as prescribed) or non-persistence (patients stopping treatment prematurely), in terms of the effects on event-free survival or overall survival among women with non-metastatic breast cancer.ResultsWe identified 10 studies measuring the effects of endocrine treatment non-adherence and non-persistence on event-free survival. Of these studies, seven showed significantly poorer survival for the non-adherent or non-persistent patient groups, with hazard ratios (HRs) ranging from 1.39 (95% CI, 1.07 to 1.53) to 2.44 (95% CI, 1.89 to 3.14). We identified nine studies measuring the effects of endocrine treatment non-adherence and non-persistence on overall survival. Of these studies, seven demonstrated significantly reduced overall survival in the groups with non-adherence and non-persistence, with HRs ranging from 1.26 (95% CI, 1.11 to 1.43) to 2.18 (95% CI, 1.99 to 2.39).ConclusionThe present systematic review demonstrates that non-adherence and non-persistence to endocrine treatment negatively affect event-free and overall survival. Improved follow-up, with focus on adherence and persistence, is vital for improving health outcomes among patients with non-metastatic breast cancer.

GATA3 mediates doxorubicin resistance by inhibiting CYB5R2-catalyzed iron reduction in breast cancer cells.

Neoadjuvant chemotherapy (NAC) is the primary preoperative therapy for breast cancer. The luminal subtype of breast cancer shows less NAC response than the basal subtype, with an inefficient NAC treatment effect. Understanding of the molecular and cellular mechanisms responsible for this chemoresistance is an important issue when determining optimal treatment. Doxorubicin-induced apoptosis and ferroptosis was investigated using cytotoxicity, western blotting, and flow cytometry assays. The role of GATA3 in modulating doxorubicin-induced cell death was investigated both in vitro and in vivo. RNA-seq, qPCR, ChIP, and luciferase assay and association analyses were performed to investigate the regulation of CYB5R2 by GATA3. The function of GATA3 and CYB5R2 in regulating doxorubicin-induced ferroptosis was evaluated with iron, ROS, and lipid peroxidation detection assays. Immunohistochemistry was performed for results validation. Doxorubicin-induced basal breast cancer cell death is dependent on iron-mediated ferroptosis. Overexpression of the luminal signature transcriptional factor GATA3 mediates doxorubicin resistance. GATA3 promotes cell viability by decreasing ferroptosis-related gene CYB5R2 expression and by maintaining iron homeostasis. Analyzing data from the public and our cohorts demonstrates that GATA3 and CYB5R2 are associated with NAC response. GATA3 promotes doxorubicin resistance by inhibiting CYB5R2-mediated iron metabolism and ferroptosis. Therefore, patients with breast cancer who display high GATA3 expression do not benefit from doxorubicin-based NAC regimens.

Identification of circRNA-miRNA-mRNA network in luminal breast cancers by integrated analysis of microarray datasets.

Introduction: Circular RNAs (circRNAs) regulatory network is important in human cancer. We, therefore, mapped the regulatory networks driven by circRNA in luminal-subtype breast cancer. Methods: Breast cancer-related microarray datasets from GEO database were analyzed for the differentially expressed circRNAs, miRNAs, and mRNAs. The potential downstream RNAs were collected using Circular RNA Interactome or Targetscan database. Protein-protein interaction (PPI) analysis was performed for the filtered genes to identify hub genes. The functions were annotated by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. CircRNA-miRNA-mRNA networks were mapped using Cytoscape software. Hsa_circ_0086735-miR-1296-5p-STAT1 axis was used for verification. The expression levels of hsa_circ_0086735, miR-1296-5p, and STAT1 mRNA were confirmed by qRT-PCR in luminal-subtype tissues and cell lines. The interactions among them were verified by Luciferase reporter assay and RNA pull-down assay. Cell proliferation and apoptosis were assayed. Overall and distant metastasis-free survival was analyzed. Results: A total of 70 genes were finally targeted and enriched in multi-process and multi-pathway. Networks containing 96 circRNA-miRNA-mRNA axes were constructed. Hsa_circ_0086735 and STAT1 mRNA was upregulated in luminal breast cancer, while miR-1296-5p was downregulated. Hsa_circ_0086735-miR-1296-5p-STAT1 axis promotes breast cancer progression and contributes to tamoxifen resistance. High hsa_circ_0086735 was associated with poor overall and distant metastasis-free survival. Discussion: This study identified the hsa_circ_0086735-miR-1296-5p-STAT1 as an important regulatory axis in luminal-subtype breast cancer, aiding to determine potential therapeutic targets.

Regulation of ERα-dependent breast cancer metastasis by a miR-29a signaling

Malignant breast cancer (BC) remains incurable mainly due to the cancer cell metastasis, which is mostly related to the status of Estrogen receptor alpha (ERα). However, our understanding of the mechanisms through which ERα regulates cancer cell metastasis remains limited. Here we identified a miR-29a-PTEN-AKT axis as a downstream signaling pathway of ERα governing breast cancer progression and metastasis. Two estrogen response element (ERE) half sites were identified in the promoter and enhancer regions of miR-29a, which mediated transcriptional regulation of miR-29a by ERα. Low level of miR-29a showed association with reduced metastasis and better survival in ERα+ luminal subtype of BC. In contrast, high level of miR-29a was detected in ERα- triple negative breast cancer (TNBC) in association with distant metastasis and poor survival. miR-29a overexpression in BC tumors increased the number of circulating tumor cells and promoted lung metastasis in mice. Targeted knockdown of miR-29a in TNBC cells in vitro or administration of a nanotechnology-based anti-miR-29a delivery in TNBC tumor-bearing mice in vivo suppressed cellular invasion, EMT and lung metastasis. PTEN was identified as a direct target of miR-29a, inducing EMT and metastasis via AKT signaling. A small molecular inhibitor of AKT attenuated miR-29a-induced EMT. These findings demonstrate a novel mechanism responsible for ERα-regulated breast cancer metastasis, and reveal the combination of ERα status and miR-29a levels as a new risk indicator in BC.

Abstract 1143: Development of a CDK2-selective small molecule inhibitor INCB123667 for the treatment of CCNE1hi breast cancers

Abstract Cyclin-dependent kinases 4 and 6 (CDK4/6) inhibitors have been approved for treatment of metastatic ER+ HER2− breast cancer as monotherapy or in combination with endocrine therapy. However, many patients become resistant to CDK4/6 therapy due to various mechanisms such as loss of tumor suppressor Rb, hyperactivation of CDK4/6, and/or CDK2/Cyclin E1 expression and activity, resulting in a highly unmet clinical need. Triple-negative breast cancers (TNBC), owing to a lack of hormone receptor (HR) expression and extensive heterogeneity, remain notoriously aggressive and unresponsive to current therapies. CCNE1 overexpression or amplification has been shown to be an oncogenic driver associated with poor clinical outcomes in ovarian, gastric, endometrial, and HR+ breast cancers. CCNE1hi cancers are dependent on CDK2 for growth and survival. CDK2 in complex with CCNE1 phosphorylates Rb, resulting in E2F target gene expression and G1 to S-phase cell cycle progression. Using a potent and selective CDK2 inhibitor, INCB123667, we demonstrate the efficacy of CDK2 inhibition in CCNE1hi breast cancer models. Analysis of genome-wide CRISPR screen data identified a subset of CCNE1hi breast cancer models dependent on CDK2 comprised of basal and luminal breast cancer subtypes, including TNBC, ER+ HER2−, and HR− HER2+ models. Two CCNE1hi cell lines, HCC1569 and MDAMB157, were evaluated in cell assays monitoring pRb, S-phase, and growth inhibition, and found to be sensitive to treatment with INCB123667 and insensitive to multiple CDK4/6 inhibitors. Through extensive biochemical studies, INCB123667 was observed to be potently active against CDK2 at subnanomolar range and inactive against other CDKs (CDK1, CDK4, CDK6, CDK7, and CDK9). INCB123667 also selectively induced senescence in CCNE1hi HCC1569 cells. In contrast, CCNE1 nonamplified cell lines, MCF7 and T47D, were inactive in pRb, S-phase, and growth inhibition assays when treated with INCB123667. Significant tumor growth inhibition was observed in CCNE1hi PDX and xenograft models with minimal body weight loss. We also observed dose-dependent inhibition of CDK2 substrates, including pRb S780, both in vitro and in vivo. To further characterize downstream signaling and transcriptional changes with CDK2 inhibition, we identified a discrete gene signature associated with cell cycle regulation, which was notably distinct from CDK4/6 responsive target genes. In conclusion, we have demonstrated CDK2 activity in CCNE1hi breast cancers using INCB123667, a potent and selective small molecule inhibitor of CDK2 currently in clinical development. Treatment resulted in cell growth inhibition and antitumor activity in vitro and in vivo. Our data demonstrate the therapeutic potential of CDK2 inhibition in CCNE1hi HR+ HER2− and TNBC breast cancer models. Acknowledgments: R&D services provided by Pharmaron, Crown Bioscience, and Champions Oncology Citation Format: Saswati Chand, Michael Hansbury, Yvonne Lo, Pat Feldman, Justine Carl, Cynthia Timmers, Joshua Hummel, Susan Wee, Sunkyu Kim. Development of a CDK2-selective small molecule inhibitor INCB123667 for the treatment of CCNE1hi breast cancers [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 1143.

Cross-attention multi-branch CNN using DCE-MRI to classify breast cancer molecular subtypes.

The aim of this study is to improve the accuracy of classifying luminal or non-luminal subtypes of breast cancer by using computer algorithms based on DCE-MRI, and to validate the diagnostic efficacy of the model by considering the patient's age of menarche and nodule size. DCE-MRI images of patients with non-specific invasive breast cancer admitted to the Second Affiliated Hospital of Dalian Medical University were collected. There were 160 cases in total, with 84 cases of luminal type (luminal A and luminal B and 76 cases of non-luminal type (HER 2 overexpressing and triple negative). Patients were grouped according to thresholds of nodule sizes of 20 mm and age at menarche of 14 years. A cross-attention multi-branch net CAMBNET) was proposed based on the dataset to predict the molecular subtypes of breast cancer. Diagnostic performance was assessed by accuracy, sensitivity, specificity, F1 and area under the ROC curve (AUC). And the model is visualized with Grad-CAM. Several classical deep learning models were included for diagnostic performance comparison. Using 5-fold cross-validation on the test dataset, all the results of CAMBNET are significantly higher than the compared deep learning models. The average prediction recall, accuracy, precision, and AUC for luminal and non-luminal types of the dataset were 89.11%, 88.44%, 88.52%, and 96.10%, respectively. For patients with tumor size <20 mm, the CAMBNET had AUC of 83.45% and ACC of 90.29% for detecting triple-negative breast cancer. When classifying luminal from non-luminal subtypes for patients with age at menarche years, our CAMBNET model achieved an ACC of 92.37%, precision of 92.42%, recall of 93.33%, F1of 92.33%, and AUC of 99.95%. The CAMBNET can be applied in molecular subtype classification of breasts. For patients with menarche at 14 years old, our model can yield more accurate results when classifying luminal and non-luminal subtypes. For patients with tumor sizes ≤20 mm, our model can yield more accurate result in detecting triple-negative breast cancer to improve patient prognosis and survival.

Cell State Transitions and Phenotypic Heterogeneity in Luminal Breast Cancer Implicating MicroRNAs as Potential Regulators.

Luminal breast cancer subtypes respond poorly to endocrine and trastuzumab treatments due to cellular heterogeneity arising from the phenotype transitions, accounted for mainly by the loss of receptor expression. The origins of basal-like and human epidermal growth factor receptor 2 (HER2)-overexpressing breast cancer subtypes have been attributed to genetic and protein modifications in stem-like cells and luminal progenitor cell populations, respectively. The post-transcriptional regulation of protein expression is known to be influenced by microRNAs (miRNAs) that are deemed to be master regulators of several biological processes in breast tumorigenesis and progression. Our objective was to identify the fractions of luminal breast cancer cells that share stemness potentials and marker profiles and to elucidate the molecular regulatory mechanism that drives transitions between fractions, leading to receptor discordances. Established breast cancer cell lines of all prominent subtypes were screened for the expression of putative cancer stem cell (CSC) markers and drug transporter proteins using a side population (SP) assay. Flow-cytometry-sorted fractions of luminal cancer cells implanted in immunocompromised mice generated a pre-clinical estrogen receptor alpha (ERα+) animal model with multiple tumorigenic fractions displaying differential expression of drug transporters and hormone receptors. Despite an abundance of estrogen receptor 1 (ESR1) gene transcripts, few fractions transitioned to the triple-negative breast cancer (TNBC) phenotype with a visible loss of ER protein expression and a distinct microRNA expression profile that is reportedly enriched in breast CSCs. The translation of this study has the potential to provide novel therapeutic miRNA-based targets to counter the dreaded subtype transitions and the failure of antihormonal therapies in the luminal breast cancer subtype.

Chalcone-3 Inhibits the Proliferation of Human Breast Cancer MDA-MB-231 Cell Line.

Chalcone-3 has been shown to be cytotoxic and selective against luminal subtype breast cancer cell lines, which are suspected to occur through the mechanism of epidermal growth factor receptors (EGFR) inhibition. However, the cytotoxic effect has never been tested on cell strains from patients with triple negative breast cancer (TNBC), where EGFR expression is known to increase. This study aimed to identify the role of chalcone-3 in one of the downstream targets of EGFR as an antiproliferative agent. Chalcone-3 was examined for its effect on proliferation in human breast cancer MDA-MB-231 cell lines. The percentage of proliferation inhibition was analyzed using methyl-thiazol tetrazolium assay. Flow cytometry was used to analyze the population of cell cycle distribution and the expression of cyclin-D1 and pEGFR. Chalcone-3 inhibited the proliferation of MDA-MB-231 cells in a dose and time-dependent manner with an IC50 value of 17.98±6.36 µg/mL by inducing cell cycle arrest at the G2/M phase. Flow cytometry assays showed that chalcone-3 significantly reduced the expression of pEGFR and cyclin-D1, contributing to cell cycle arrest. Chalcone-3 might have potential as an anti-proliferative drug to treat TNBC.

Unique sphingolipid signature identifies luminal and triple-negative breast cancer subtypes.

Breast cancer (luminal and triple-negative breast cancer [TNBC]) is the most common cancer among women in India and worldwide. Altered sphingolipid levels have emerged as a common phenomenon during cancer progression. However, these alterations are yet to be translated into robust diagnostic and prognostic markers for cancer. Here, we present the quantified sphingolipids of tumor and adjacent-normal tissues from patients of luminal (n=70) and TNBC (n=42) subtype from an Indian cohort using targeted liquid chromatography mass spectrometry. We recorded unique sphingolipid profiles that distinguished luminal and TNBC tumors in comparison to adjacent normal tissue by six-sphingolipid signatures. Moreover, systematic comparison of the profiles of luminal and TNBC tumors provided a unique five-sphingolipid signature distinguishing the two subtypes. We further identified key sphingolipids that can stratify grade II and grade III tumors of luminal and TNBC subtype as well as their lymphovascular invasion status. Therefore, we provide the right evidence to develop these candidate sphingolipids as widely acceptable marker/s capable of diagnosing luminal vs TNBC subtype of breast cancer, and predicting the disease severity by identifying the tumor grade.

Dual Function of CCAT2 in Regulating Luminal Subtype of Breast Cancer Depending on the Subcellular Distribution.

Breast cancer is the most common cancer in women around the world. Emerging evidence has indicated the important roles that non-coding RNAs play in regulating tumor development and progression in breast cancer. Herein, we found a dual function of long non-coding RNA (LncRNA) CCAT2 in the luminal subtype of breast cancer, depending on its subcellular distribution. CCAT2 showed an overall downregulation in the tumor tissues from luminal breast cancer patients. Transient overexpression of CCAT2 in the luminal subtype of breast cancer cell MCF-7 or T47D significantly suppressed cell proliferation in vitro and inhibited tumor growth in vivo. Gene expression analysis of cancer stem cell markers including OCT4, NANOG, h-TERT, SOX2 and KLF4; flow cytometry analysis of breast cancer stem cell population, and mammosphere formation assay demonstrated inhibition of cancer cell stemness with transient transfection of CCAT2 in which exogenous CCAT2 mainly distributed in the cytoplasm and regulated miR-221-p27 signaling via RNA sequence interaction. However, overexpression of CCAT2 in MCF-7 cells through pMX retroviral nuclear expression vector accumulated CCAT2 in the nucleus, leading to upregulation of OCT4-PG1, a pseudogene of stem gene OCT4, thereby promoting the cancer cell stemness. In conclusion, the current study, for the first time, revealed a dual function of lncRNA CCAT2 as a tumor suppressor or oncogene depending upon its subcellular distribution. It also demonstrated the regulatory mechanism of cytoplasmic CCAT2 in suppressing tumorigenesis in the luminal subtype of breast cancer.