Triple-negative Breast Cancer Samples Research Articles

Exploring the association of POSTN+ cancer-associated fibroblasts with triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis. Cancer-associated fibroblasts (CAFs) play a critical role in regulating TNBC tumor development. This study aimed to identify and characterize a specific subtype of CAFs associated with TNBC. Initially, using high-throughput bulk transcriptomic data in two cohorts, we identified three CAF-related subtypes (CS1, CS2, CS3) in TNBC samples. These three CAFs subtypes were closely linked to the tumor microenvironment. The CS1 subtype exhibited a relatively immune-rich microenvironment and a favourable prognosis, whereas the CS3 subtype displayed an immune-deprived tumor microenvironment and an unfavourable prognosis. Through WGCNA analysis, POSTN was identified as a key biomarker for CAFs associated with TNBC. Then, POSTN+CAFs was identified and characterized. Both POSTN and POSTN+CAFs showed significant positive correlations with stromal molecules HGF and MET at both the transcriptional and protein levels. Specifically co-localized with CAFs in the tumor stromal area, POSTN, produced by POSTN+CAFs, could modulate the HGF-MET axis, serving as a bypass activation pathway to regulate tumor cell proliferation in response to EGFR inhibitor and MET inhibitor. This study underscores the significance of POSTN and POSTN+CAFs as crucial targets for the diagnosis and treatment of TNBC.

Abstract LB312: Subtype- and race-specific differences in immune landscape of breast cancer

Abstract Tumor mass comprises of not just the tumor cells but a variety of stromal cells. Immune cells residing within the tumor microenvironment modulate the growth and behavior of the tumor cells through a bi-directional crosstalk and affect the outcomes of cancer therapies. Breast cancer (BC) is a highly heterogeneous disease having four major molecular subtypes. Triple-negative breast cancer (TNBC) is the most aggressive subtype and has limited available therapeutic options. Further, it disproportionately affects African American (AA) women, with nearly two times higher incidence as compared to Caucasian American (CA) women. It is associated with an earlier onset and overall higher mortality of BC. Here, we investigated the differences in the immune landscape between TNBC and non-TNBC subtypes and examined if there existed any race-specific patterns. A total of 81 breast cancer samples with a distribution of 55 non-TNBC (28 CA and 27 AA) and 26 TNBC (12 CA and 14 AA) were selected after histopathologic analysis. Tissues were analysis using the NanoString nCounter® pancancer immune panel to determine tissue-specific immune cell populations. We observed a significantly higher presence of tumor-infiltrating lymphocytes in TNBC compared to non-TNBC, with a higher immune score for CD45+ (total lymphocytes), T-cells, B-cells and tumor-associated macrophages. Specifically, among the T-cell population, Treg cells, Th1 cells, and CD8+ cells were higher in TNBC samples. The pathway prediction indicated 'primary immunodeficiency' and 'cancer immunotherapy by PD-1 blockade' pathways being significantly up-regulated in TNBC samples. Overexpression of CTLA4, IDO1, PDL1 and PDL2 as well as Treg marker genes, such as FOXP3 and LAG3, which are involved in immunosuppressive pathways, was observed in TNBC. In race-wise comparisons of non-TNBC and TNBC sample between CA and AA patients, we found that AA non-TNBC tumors had higher Treg cell scores. On the other hand, CA TNBC samples had higher Th1 and CD8+ T-cell scores compared to AA TNBC. The pathway prediction from differentially expressed genes between CA and AA non-TNBC samples showed complement activation pathway to be down-regulated in AA patients, which could be associated with an increased presence of Treg cells. Further, when comparing CA vs AA TNBC samples, we found significant up-regulation of oncogene BMI1 and down-regulation of genes involved in T-cell activation such as CD47, CD44, FOS, and S100A8 in AA TNBC, supporting their more aggressive nature. In conclusion, our data show that TNBC patients have a higher infiltration of immune cells, which remain suppressed due to the presence of Treg cells and PD1 signaling pathway. The presence of higher Treg cells in AA non-TNBC and lower Th1 and CD8+ T-cells in AA TNBC samples suggests an overall immune suppressed microenvironment in AA patients compared to CA patients. Overall, our data suggest that TNBC could be good candidate for immune therapy. Citation Format: Amod Sharma, Kunwar Somesh Vikramdeo, Sarabjeet Kour Sudan, Mohammad Aslam Khan, Mohammad Tahir, James Elliot Carter, Cindy Nelson, Ajay P Singh, Seema Singh. Subtype- and race-specific differences in immune landscape of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB312.

Therapeutic potential of LINS01 histamine H3 receptor antagonists as antineoplastic agents for triple negative breast cancer

The aims of this work were to evaluate the expression of histamine H3 receptor (H3R) in triple negative breast cancer (TNBC) samples and to investigate the antitumoral efficacy and safety of the LINS01 series of H3R antagonists, through in silico, in vitro, and in vivo approaches. Antitumor activity of LINS01009, LINS01010, LINS01022, LINS01023 was assayed in vitro in 4T1 and MDA-MB-231 TNBC cells (0.01–100 μM), and in vivo in 4T1 tumors orthotopically established in BALB/c mice (1 or 20 mg/kg). Additionally, H3R expression was assessed in 50 human TNBC samples. We have described a higher H3R mRNA expression in basal-like/TNBC tumors vs. matched normal tissue using TCGA Pan-Cancer Atlas data, and a higher H3R expression in human tumor samples vs. peritumoral tissue evidenced by immunohistochemistry associated with poorer survival. Furthermore, while all the essayed compounds showed antitumoral properties, LINS01022 and LINS01023 exhibited the most potent antiproliferative effects by: i) inducing cell apoptosis and suppressing cell migration in 4T1 and MDA-MB-231 TNBC cells, and ii) inhibiting cell growth in paclitaxel-resistant 4T1 cells (potentiating the paclitaxel antiproliferative effect). Moreover, 20 mg/kg LINS01022 reduced tumor size in 4T1 tumor-bearing mice, exhibiting a safe toxicological profile and potential for druggability estimated by ADME calculations. We conclude that the H3R is involved in the regulation of TNBC progression, offering promising therapeutic potential for the novel LINS01 series of H3R antagonists.

Identification of cuproptosis-related miRNAs in triple-negative breast cancer and analysis of the miRNA–mRNA regulatory network

IntroductionThe close association between cuproptosis and tumor immunity in triple-negative breast cancer (TNBC) allows its monitoring for predicting the prognosis of patients with TNBC. Nevertheless, the biological function and prognostic value of cuproptosis-related miRNAs and their target genes have not been reported. PurposeTo construct the miRNA and mRNA-based risk models associated with cuproptosis for patients with TNBC. MethodsComparison of expression levels for genes associated with cuproptosis was executed between patients in the normal individuals and the TCGA-TNBC cohort. Conducting differential analysis resulted in the identification of differentially expressed miRNA (DE-miRNAs) and differentially expressed genes (DEGs) between the TNBC and Control samples. Screening for prognostic miRNAs and biomarkers involved employing univariate Cox analysis and least absolute shrinkage and selection operator regression analyses. These methods were utilized to construct risk models aimed at predicting the survival of patients with TNBC. Based on the median value of risk scores, patients were then stratified into low- and high-risk groups. Functional enrichment analysis was employed to explore the potential function and pathways of prognostic genes. Additionally, independent prognostic analysis was performed through univariate and multivariate Cox regression. Immune infiltration analysis was performed to examine disparities in the infiltration of immune cells between the two risk groups. Finally, the prognostic gene expression was mined in key cell types of TNBC. ResultsWe obtained 5213 DEGs and 204 DE-miRNAs related to cuproptosis between TNBC and Control samples. Five prognostic miRNAs (miR-203a-3p, miR-1277–3p, miR-135b-5p, miR-200c-3p, and miR-592) and three biomarkers (DENND5B, IGF1R, and MEF2C) were closely associated with TNBC. Significant differences in the functions of prognostic genes between the two risk groups were observed, encompassing adipogenesis, inflammatory response, and hormone metabolic process. The prognostic gene regulatory network revealed that miR200C-3p regulated ZFPM2 and CFL2, and miR-1277–3p regulated BMP2 and RORA. A nomogram was created based on riskScore, cancer status, and pathologic stage to predict 1/3/5-year survival of patients with TNBC. Immune infiltration analysis indicated that the immune microenvironment may be associated with the progression of TNBC. Interestingly, prognostic genes exhibited higher expression levels in T cells, fibroblasts, endothelial cells, and monocytes compared to other cells. ConclusionsFive prognostic miRNA (miR-203a-3p, miR-1277–3p, miR-135b-5p, miR-200c-3p, and miR-592) and three biomarkers (DENND5B, IGF1R, and MEF2C) were significantly associated with TNBC, it provides new therapeutic targets for the treatment and prognosis of TNBC.

Abstract 1149: Spatial transcriptomic analysis of tumor microenvironment in patients with triple negative breast cancer with residual disease after neoadjuvant chemotherapy with immune checkpoint inhibitor

Abstract Recent advance of treatment strategy for triple negative breast cancer (TNBC) including immune checkpoint inhibitor improved survival outcome. Especially, adding pembrolizumab on neoadjuvant chemotherapy (NAC) increased pathologic complete response (pCR) rate at the time of curative surgery. Previous studies suggested that PD-L1 expression in both tumor and immune cells was associated with the response of pembrolizumab in TNBC, but PD-L1 expression state were not associated with pembrolizumab response in NAC setting. In addition, neoadjuvant pembrolizumab increased event-free survival (DFS) rate after NAC even though they had not achieved pCR. However, there were no biomarker for EFS increasement of using pembrolizumab. We designed prospective translational research for evaluating tumor microenvironment (TME) of residual TNBC which had treated with NAC followed by curative surgery. We collected formalin fixed paraffin embedded (FFPE) surgical specimens after NAC with or without pembrolizumab. TNBC samples were used for spatial transcriptomics (ST) analysis, with H&E staining and inspection by an experienced pathologist. Libraries were prepared using Visium Spatial Gene Expression Reagent Kit protocol for FFPE (10x Genomics). Sequencing was conducted on the NovaSeq 6000 System (Illumina). From February 2023 to October 2023, 23 TNBC specimens from 22 patients were collected. Twenty specimens were breast tissues and three were lymph nodes, 18 TNBCs had been treated with NAC with pembrolizumab and four with only NAC, and five had residual cancer burden(RCB) class I, 11 of RCB class II and one of RCB class III. We collected BC and LN samples from BC with class III. Of 23 samples, we performed spatial transcriptomic analysis in 12 samples. In intrinsic subtyping, eight specimens were categorized into normal like, two of basal like and two of luminal A BC subtypes. In TNBC subtyping, mesenchymal stem cell like (MSL) were in six specimens, three of stem cell like (SL), two of luminal androgen receptor (LAR) and one of immunomodulatory (IM). We also performed cell type annotation with unsupervised method and categorized into 11 cell types; three cancer cell types, two macrophages, B and T cells, adipocytes, normal epithelium and perivascular-like and cancer associated fibroblasts. Among these 11 cell types, increasement of immune cells including B cells, T cells and macrophage proportions was associated with pembrolizumab treatment in NAC setting. In our study, we evaluated TME state of TNBC after NAC with or without pembrolizumab. We suggested that MSL or SL TNBC subtypes were associated with residual disease after NAC regardless of pembrolizumab use and pembrolizumab may recruit more immune cells in TME of TNBC. For concreating our suggestion, further analyses would be warranted. Citation Format: Ji-Yeon Kim, Kyunghee Park, Yoon La Choi, Jeong Eon Lee, Byung Joo Chae, Jonghan Yu, Seok Won Kim, Seok Jin Nam, Jin Seok Ahn, Woong-Yang Park, Yeon Hee Park. Spatial transcriptomic analysis of tumor microenvironment in patients with triple negative breast cancer with residual disease after neoadjuvant chemotherapy with immune checkpoint inhibitor [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1149.

Abstract 1986: Acquisition of carboplatin resistance corresponds with reduced sacituzumab govitecan efficacy in triple negative breast cancer patient derived xenografts

Abstract Sacituzumab Govitecan (SG) is an antibody drug conjugate that targets the epithelial glycoprotein Trop-2. SG has been approved for the treatment of patients with triple negative breast cancer (TNBC) or estrogen receptor positive (ER+) breast cancer after they have received at least two previous systemic treatments. The objectives of this study were to identify biomarkers of SG response using breast cancer patient-derived xenografts (PDXs) and determine if SG efficacy changes when cells become carboplatin resistant (CR). Analysis of transcriptomic and proteomic levels of Trop2 using bulk RNAseq, scRNA-seq, and tandem mass tag spectrometry found that overall ER+ PDXs had significantly lower RNA (p-value less than 0.001) and protein (p-value less than 0.001) expression of Trop-2 than TNBC PDXs. Immunohistochemical assessment of 42 TNBC and 27 ER+ patient tumor samples identified variation in Trop-2 expression; within each cohort, expression varied from highly positive to completely negative. To test the association of Trop-2 with drug responsiveness, cells from 19 different PDXs were cultured in vitro and administered increasing doses of SG. TNBC cells were more responsive to SG treatments compared to ER+ cells (p-value equaling 0.005). Correlation analysis identified a positive relationship of drug response with protein abundance which was stronger in TNBC samples. In vivo studies with 7 TNBC PDXs found that over 70% were highly susceptible to SG treatments, with some tumors being completely eradicated or exhibiting a total inhibition of tumor growth which resulted in a long-term durable response after 10 weeks of treatment. In vivo across all the PDXs, Trop-2 expression alone did not strongly correlate with SG treatment success. Interestingly, CR sublines derived from 2 carboplatin sensitive PDXs were significantly less responsive to SG than their parental PDXs (p-value less than 0.001). These two CR sublines were also significantly less sensitive to the majority of 555 other drugs identified by the NCI compared to their parental PDXs. Ongoing studies are defining mechanisms of reduced SG efficacy in CR models. Overall, these studies find that SG is highly effective in many TNBC PDX models and should be utilized earlier in treatment protocols, especially in metastatic patients. Citation Format: Carson J. Walker, Julia E. Altman, Emily K. Zboril, Rachel K. Myrick, Nicole S. Hairr, David C. Boyd, Bin Hu, Mikhail G. Dozmorov, J. Chuck Harrell. Acquisition of carboplatin resistance corresponds with reduced sacituzumab govitecan efficacy in triple negative breast cancer patient derived xenografts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1986.

Abstract 5487: Improved spatial biology analysis of the tumor microenvironment with the next generation of the MultiOmyxTMplatform

Abstract Multiplexed Immunofluorescence is a powerful tool for spatially characterizing and phenotyping cells within the tumor microenvironment. MultiOmyx has been one of the leading platforms for generating multiplexed immunofluorescence data to support translational and clinical research for more than 10 years. However, MultiOmyx and other similar platforms are often hampered by a limited imaging area due to either restricted staining areas or being cost prohibitive due to excessive imaging times. Here, we demonstrate the capabilities of an improved MultiOmyx platform which can be used to generate whole-tissue data from the iterative MultiOmyx multiplexing process using the CyteFinder® II microscope and a customized software package developed by RareCyte, Inc. The new NeoLYTX image analysis pipeline in conjunction with the whole-tissue image output allows for improved interaction with pathologists, better histological context, and unbiased spatial analysis. In this study we utilized a 16-marker panel consisting of CD3, CD4, CD8, FoxP3, CD20, CD68, CD163, HLA-DR, PD-1, PD-L1, CTLA-4, CD34, Vimentin, SOX10, Ki67, and PanCK to generate immune profiles for colorectal carcinoma, prostate carcinoma, non-Small cell lung cancer, and triple negative breast cancer samples. We showed concordance with the current MultiOmyx imager - the IN Cell 2200 - for each of the markers in the panel. Additionally, we demonstrated that the updates made to the proprietary NeoLYTX image analysis pipeline are able to facilitate the significantly larger data sets that will be generated with the new MultiOmyx platform. This study successfully demonstrates the capability of the improved MultiOmyx system to characterize the distribution of T-cell and myeloid phenotypes in the tumor microenvironment using the proven MultiOmyx workflow, now enhanced by whole slide images and analysis. Citation Format: Michael Lazare, Harry Nunns, Fatemeh Jelvhei Moghaddam, Xiaowei Jin, Courtney Todorov, Eric Leones, Marianne Thio, Flora Sahafi, Erinn Parnell, Qingyan Au. Improved spatial biology analysis of the tumor microenvironment with the next generation of the MultiOmyxTMplatform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5487.

Abstract 6604: Spatial transcriptomics delineates tumor heterogeneity in NACT triple-negative breast cancer

Abstract BACKGROUND: Triple-Negative Breast Cancer (TNBC) is a highly aggressive subtype of breast cancer and only ~40% of TNBC patients achieve a pathological complete response (pCR) following neoadjuvant chemotherapy (NACT). Since molecular heterogeneity of TNBC may contribute to variable responses to NACT, we aimed to deconvolute TNBC’s histological and spatial transcriptomics (ST) patterns. METHODS: In total, 90 pre-treatment biopsies were collected from NACT-treated TNBC patients from archival samples and the ongoing FORCE (NCT03238144) clinical trial at Guy’s Hospital, London, UK. Of these, 38 achieved pCR (Responder), 46 had residual disease (Non-Responder) whilst 6 are currently undergoing NACT; 46 post-treatment surgical resections were collected from Non-Responders.Each sample was H&E stained, imaged, and annotated by a pathologist. A 6-digit classifier was designed to capture the histology of each region of interest (ROI), characterizing the tumour region, epithelial type and immune cell localization, population, distribution, and abundance.H&Es were used to guide ST profiling of serial sections which was performed on the GeoMx Digital Spatial Profiler. Tissues were stained with fluorescent antibodies against PanCK and CD45 to visualize the tissue, select ROIs and illuminate spatially resolved tumor and immune-enriched compartments, defined as PanCK+/CD45- and PanCK-/CD45+, respectively.Data analysis was performed in R 4.3.1 using the limma, dplyr, EdgeR, GeoMx Tools, GeoMx Workflows, RUV4, Spatial Experiment, SpatialDecon and GSVA packages, facilitating quality control, batch correction, differential and topographical gene expression, immune cell deconvolution and gene set enrichment analysis (GSEA), respectively. RESULTS: To date, we have performed ST profiling of 120 TNBC samples from 82 patients (46 Non-Responders; 36 Responders), totaling 3917 tumor or immune-cell enriched regions. Preliminary analyses revealed KEGG pathways involved in tissue adhesion are upregulated in tumor compartments of Non-Responders compared to Responders, whilst those involved in genomic integrity are suppressed. Unsupervised clustering of PanCK+CD45- regions in Non-Responders identified tumor clusters present in both pre- and post-NACT samples, suggesting potential chemo-resistant properties. Moreover, immune cell deconvolution of the PanCK-/CD45+ regions revealed spatially distinct patters of immune cell composition mapped to histological annotations identified by our ROI classifier. CONCLUSION: (S)Large scale ST of TNBC before and after NACT reveals novel patterns associated with response to treatment. We have designed a novel ROI classifier to spatially resolved transcriptomes of histological features, as such provide an in-depth characterization of the histo-genomics of TNBC. Citation Format: Isobelle Wall, Jelmar Quist, Sarah Pinder, KCL Cancer Biobank, Sheeba Irshad, Cheryl Gillet, Victoria Seewaldt, Kavitha Mukund, David Frankhouser, Shankar Subramaniam, Maddy Parsons, Anita Grigoriadis. Spatial transcriptomics delineates tumor heterogeneity in NACT triple-negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6604.

Quantitative Pattern of hPTMs by Mass Spectrometry-Based Proteomics with Implications for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is known for its aggressive nature, and TNBC management is currently challenging due to the lack of effective targets. Despite the importance of histone post-translational modifications (hPTMs) in breast cancer, their associations with molecular subtypes of breast cancer, especially TNBC, are poorly understood. In this study, a combination of untargeted and targeted proteomics approaches, supplemented by a derivatization method, was applied to breast cancer cells and tissue samples. Untargeted proteomics of eight breast cancer cell lines belonging to different molecular subtypes revealed 36 modified peptides with 12 lysine modification sites in histone H3, and the most frequently reported top 5 histone H3 methylation and acetylation sites were covered. Then, targeted proteomics was carried out to quantify the total 20 target hPTMs at the covered modification sites (i.e., mono-, di-, trimethylation, and acetylation for each site), indicating the difficulty in distinguishing TNBC cells from normal cells. Subsequently, the analysis in TNBC patients revealed significant expression differences in 4 specific hPTMs (H3K14ac, H3K27me1, H3K36me2, and H3K36me3) between TNBC and adjacent normal tissue samples. These unique hPTM patterns allowed for the differentiation of TNBC from normal cases. This finding provides promising implications for advancing targeted treatment strategies for TNBC in the future.

YB-1 Targeted by miR-509-3-5p Affects Migration and Invasion of Triple‑Negative Breast Cancer by Regulating Cellular Epithelial‑Mesenchymal Transition.

The epithelial-mesenchymal transition (EMT) process is closely linked to metastasis of breast cancer. This article elucidates the role of Y-box binding protein-1 (YB-1) on the migration and invasion of triple-negative breast cancer (TNBC) cells by regulating EMT, and the related mechanism. The expression data of YB-1 and miR-509-3-5p in TNBC samples and normal samples were downloaded from the GEO database. The proliferation, migration, invasion, and EMT of TNBC cells were detected by CCK-8 assay, colony formation assay, wound-healing assay, transwell assay, and immunoblotting analyses. The targeted binding of YB-1 and miR-509-3-5p was validated by luciferase reporter experiment. A xenograft mouse model was constructed to investigate the influence of the miR-509-3-5p/YB-1 axis on TNBC tumor growth in vivo. YB-1 was overexpressed, while miR-509-3-5p was underexpressed in TNBC tumor tissues and various cell lines. Silencing YB-1 depressed cell viability, proliferation, motility, and EMT in vitro, and miR-509-3-5p upregulation exerted the same effects. YB-1 was targeted by miR-509-3-5p. The suppressive effects on the phenotypes of TNBC cells caused by overexpressed miR-509-3-5p were attenuated by YB-1 upregulation. In addition, miR-509-3-5p overexpression restrained TNBC tumor growth and downregulated the YB-1-mediated EMT process in vivo. YB-1 targeted by miR-509-3-5p affects motility of TNBC cells by regulating cellular EMT.

The Role of CD8A in the Immune Microenvironment of Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer (BC), and it is often associated with a high tumor grade, a younger age at diagnosis, and a low survival rate. Conventional endocrine and anti-HER-2 therapies are usually ineffective against TNBC, creating treatment challenges and resulting in a poor prognosis. Hence, new targets and treatment strategies for TNBC are urgently required. The GSE102818 dataset was used to identify differentially expressed genes (DEGs) between primary BC and metastatic BC lesions. The Cancer Genome Atlas and the cBioPortal platform were employed to explore mutations in candidate genes. Utilizing the Tumor IMmune Estimation Resource (TIMER), the relationship between the expression of candidate genes and immune cell infiltration was assessed. Additionally, the cell-specific expression of the candidate genes was examined in the immune microenvironment of primary BC and metastatic BC lesions using the single-cell RNA sequencing (scRNA-seq) datasets GSE118389 and GSE202695. Finally, the protein expression of the candidate genes in clinical TNBC samples was evaluated. CD8A was identified as a hub gene in the DEG network and was found to be down-regulated in metastatic BC lesions. CD8A expression was highly correlated with the infiltration of CD8+ T cells, and elevated CD8A expression was correlated with improved survival. Interestingly, scRNA-seq data revealed that CD8A was down-regulated in CD8+ T cells in the immune microenvironment of metastatic BC lesions. Finally, the evaluation of clinical samples confirmed the down-regulation of CD8A in the immune microenvironment of BC lung metastases. In patients with metastatic TNBC, high levels of CD8A (especially in the immune microenvironment) are associated with a good prognosis.

Identification of Subtypes in Triple-negative Breast Cancer Based on Shared Genes Between Immunity and Cancer Stemness.

The correlation between triple-negative breast cancer (TNBC) and genes related to immunity and cancer stemness, particularly shared genes, remains unclear. This study aimed to investigate the correlation of immunity and cancer stemness with the molecular subtyping and survival rates in TNBC using bioinformatics approaches. Differential gene analysis was conducted to identify TNBC-associated differentially expressed genes (DEGs). Cancer stem cell (CSC)-related genes were obtained using weighted gene coexpression network analysis. Immune-related gene sets were retrieved from the literature. Venn analysis was performed to identify the shared DEGs between immunity and cancer stemness in TNBC. Cluster analysis and survival analysis based on the expression of these genes were conducted to identify TNBC subtypes with significant survival differences. A total of 5259 TNBC-associated DEGs, 2214 CSC-related genes, 1793 immune-related genes, and 44 shared DEGs between immunity and cancer stemness were obtained. Among them, 3 shared DEGs were closely associated with TNBC survival rates ( P <0.05). Cluster and survival analyses revealed that among 3 subtypes, cluster2 exhibited the best survival rate, and cluster3 showed the worst survival rate ( P <0.05). Dendritic cells were highly infiltrated in cluster2, while plasma cells and resting mast cells were highly infiltrated in cluster3 ( P <0.05). Genes shared by immunity and cancer stemness were capable of classifying TNBC samples. TNBC patients of different subtypes exhibited significant differences in immune profiles, genetic mutations, and drug sensitivity. These findings could provide new insights into the pathogenesis of TNBC, the immune microenvironment, and the selection of therapeutic targets for drug treatment.

Expression of cell surface zinc transporter LIV1 in triple negative breast cancer is an indicator of poor prognosis and therapy failure.

Triple negative breast cancers (TNBC) are an aggressive molecular subtype of breast carcinoma (BC) identified by the lack of receptor expression for estrogen, progesterone, & human epidermal growth factor receptor-2. Lack of tangible drug targets warrants further research in TNBC. LIV1, is a zinc (Zn) transporter known to be overexpressed in few cancer types including BCs. Recently, in the United States of America, FDA approved the use of a new drug targeting LIV1, antibody drug conjugate SGN-LIV1A for treatment of TNBC patients. Though LIV1 also has a role in modulating immune cells by its differential transport of Zn, a correlation between the tumor cell expression of LIV1 and immune cell infiltrations were scantily reported. Further adequate baseline data on LIV1 expression in other populations have not been documented. Our objective was to screen a large Indian cohort of TNBC patient samples for LIV1, categorize the immune cell infiltration using CD4/CD8 expression and correlate the findings with therapy outcomes. Further, we also investigated for LIV1 expression in matched samples of primary & secondary tumors; pre & postchemotherapy in TNBC patients. Results showed an elevated expression of LIV1 in TNBC samples as compared to adjacent normal, the mean Q scores being 183.06 ± 6.39 and 120.78 ± 7.37 (p < 0.0001), respectively. Similarly, LIV1 levels were elevated in secondary tumors than primary & in patient samples postchemotherapy as compared to naïve. In the TNBC cohort, using automated method, cell morphology parameters were computed and analysis showed LIV1 levels were elevated in grade 3 TNBC samples presenting with altered cell morphology parameters namely cell size, cell perimeter, & nucleus size. Thus indicating LIV1 expressing TNBC samples portrayed an aggressive phenotype. Finally, TNBC patients with 3+ staining intensity showed poor survival (4.44 year) as compared to patients with 2+LIV1 expression (5.47 year), emphasizing that LIV1 expression is a poor prognostic factor in TNBC. In conclusion, the study reports elevated expression of LIV1 in a large Indian TNBC cohort; high expression is a poor prognostic factor and correlated with aggressive disease and indicating the need for LIV1 targeted therapies.

Personalized differential expression analysis in triple-negative breast cancer.

Identification of individual-level differentially expressed genes (DEGs) is a pre-step for the analysis of disease-specific biological mechanisms and precision medicine. Previous algorithms cannot balance accuracy and sufficient statistical power. Herein, RankCompV2, designed for identifying population-level DEGs based on relative expression orderings, was adjusted to identify individual-level DEGs. Furthermore, an optimized version of individual-level RankCompV2, named as RankCompV2.1, was designed based on the assumption that the rank positions of genes and relative rank differences of gene pairs would influence the identification of individual-level DEGs. In comparison to other individualized analysis algorithms, RankCompV2.1 performed better on statistical power, computational efficiency, and acquired coequal accuracy in both simulation and real paired cancer-normal data from ten cancer types. Besides, single sample GSEA and Gene Set Variation Analysis analysis showed that pathways enriched with up-regulated and down-regulated genes presented higher and lower enrichment scores, respectively. Furthermore, we identified 16 genes that were universally deregulated in 966 triple-negative breast cancer (TNBC) samples and interacted with Food and Drug Administration (FDA)-approved drugs or antineoplastic agents, indicating notable therapeutic targets for TNBC. In addition, we also identified genes with highly variable deregulation status and used these genes to cluster TNBC samples into three subgroups with different prognoses. The subgroup with the poorest outcome was characterized by down-regulated immune-regulated pathways, signal transduction pathways, and apoptosis-related pathways. Protein-protein interaction network analysis revealed that OAS family genes may be promising drug targets to activate tumor immunity in this subgroup. In conclusion, RankCompV2.1 is capable of identifying individual-level DEGs with high accuracy and statistical power, analyzing mechanisms of carcinogenesis and exploring therapeutic strategy.

Construction and validation of immune-associated lncRNA model for predicting immune status and therapeutic reactions of triple-negative breast cancer.

The immune status of the tumor microenvironment significantly impacts the clinical prognosis of triple-negative breast cancer (TNBC). The involvement of long noncoding RNAs (lncRNAs) in tumor immune infiltration is widely acknowledged. Therefore, it is crucial to explore the role of significant immune-related lncRNAs in TNBC. We acquired RNA, single-cell sequencing, and clinical information on TNBC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. To identify immune-related lncRNAs, immune infiltration subgroups were determined and verified using single-sample gene-set enrichment analysis, non-negative matrix factorization, and weighted gene co-expression network analysis. CIBERSORTx, deconvolution, drug sensitivity, and Scissor analyses revealed that differences in cell type and drug efficacy were associated with immune grouping. TNBC samples were classified into immune-desert (cold) and immune-inflamed (hot) subgroups based on a lncRNA model (including LINC01550, LY86-AS1, LINC00494, LINC00877, CHRM3-AS2, HCP5, MIR155HG, and PIK3CD-AS1). Furthermore, using in vitro experiments, we found that LINC01550 promoted malignant phenotypes, including proliferation, survival, and migration of TNBC. The immune-inflamed subgroup exhibited significantly lower half-maximal inhibitory concentration values for common anti-tumor drugs, including palbociclib, ribociclib, mitoxantrone, and sorafenib (T-test, P < 0.001). This may be related to the fact that the immune-inflamed subgroup has more plasmacytoid dendritic cells (pDCs) and B cells than those in immune-desert subgroups (P < 0.001). Differences in specific cell infiltration can lead to increased sensitivity of the immune-inflamed subgroup to anti-tumor drugs. The proposed lncRNA model holds great promise to assess the immune landscapes and therapeutic reactions of TNBC patients.

A novel Fc-engineered cathepsin D-targeting antibody enhances ADCC, triggers tumor-infiltrating NK cell recruitment, and improves treatment with paclitaxel and enzalutamide in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) prognosis is poor. Immunotherapies to enhance the antibody-induced natural killer (NK) cell antitumor activity are emerging for TNBC that is frequently immunogenic. The aspartic protease cathepsin D (cath-D), a tumor cell-associated extracellular protein with protumor activity and a poor prognosis marker in TNBC, is a prime target for antibody-based therapy to induce NK cell-mediated antibody-dependent cellular cytotoxicity (ADCC). This study investigated whether Fc-engineered anti-cath-D antibodies trigger ADCC, their impact on antitumor efficacy and tumor-infiltrating NK cells, and their relevance for combinatory therapy in TNBC. Cath-D expression and localization in TNBC samples were evaluated by western blotting, immunofluorescence, and immunohistochemistry. The binding of human anti-cath-D F1M1 and Fc-engineered antibody variants, which enhance (F1M1-Fc+) or prevent (F1M1-Fc-) affinity for CD16a, to secreted human and murine cath-D was analyzed by ELISA, and to CD16a by surface plasmon resonance and flow cytometry. NK cell activation was investigated by flow cytometry, and ADCC by lactate dehydrogenase release. The antitumor efficacy of F1M1 Fc-variants was investigated using TNBC cell xenografts in nude mice. NK cell recruitment, activation, and cytotoxic activity were analyzed in MDA-MB-231 cell xenografts by immunophenotyping and RT-qPCR. NK cells were depleted using an anti-asialo GM1 antibody. F1M1-Fc+ antitumor effect was assessed in TNBC patient-derived xenografts (PDXs) and TNBC SUM159 cell xenografts, and in combination with paclitaxel or enzalutamide. Cath-D expression on the TNBC cell surface could be exploited to induce ADCC. F1M1 Fc-variants recognized human and mouse cath-D. F1M1-Fc+ activated NK cells in vitro and induced ADCC against TNBC cells and cancer-associated fibroblasts more efficiently than F1M1. F1M1-Fc- was ineffective. In the MDA-MB-231 cell xenograft model, F1M1-Fc+ displayed higher antitumor activity than F1M1, whereas F1M1-Fc- was less effective, reflecting the importance of Fc-dependent mechanisms in vivo. F1M1-Fc+ triggered tumor-infiltrating NK cell recruitment, activation and cytotoxic activity in MDA-MB-231 cell xenografts. NK cell depletion impaired F1M1-Fc+ antitumor activity, demonstrating their key role. F1M1-Fc+ inhibited growth of SUM159 cell xenografts and two TNBC PDXs. In combination therapy, F1M1-Fc+ improved paclitaxel and enzalutamide therapeutic efficacy without toxicity. F1M1-Fc+ is a promising immunotherapy for TNBC that could be combined with conventional regimens, including chemotherapy or antiandrogens.

Tumor infiltrating lymphocytes (TILs) in triple negative breast cancer

Tumor infiltrating lymphocytes (TILs) are a promising inexpensive prognostic and predictive biomarker in breast cancer. High levels of TILs are associated with improved survival and higher probability to achieve pathological complete response in triple-negative breast cancer (TNBC). To assess the level of TILs in TNBC samples and analyze the association between the level of TILs and the main pathological parameters, to identify their impact on long-term results. The study included information on 140 patients with I-III stage TNBC and estrogen receptors <10%. Tumor tissue samples at baseline biopsies were evaluated the histological type, HER2 expression, estrogen expression levels, Ki-67 and TILs. The pathological response was evaluated according to the ypTNM, Miller-Payne, and RCB classifications. The average level of TILs in biopsy specimens before NACT was 29.3±23.1%. Low levels of TILs (<10%) were defined in 21% of cases, intermediate levels (≥10% to ≤40%) in 55% of cases, and high levels (>40%) in 24% of cases. Using the two-tiered system, low TILs (≤40%) were defined in 76% and high TILs (>40%) in 24% of cases. The level of TILs was correlated with histological grade (R=0.187; p=0.027) and estrogen receptor expression level (R=0.211; p=0.012). There were no significant differences depending on the level of TILs and other pathological parameters. Three-year event-free survival (EFS) in patients with high TILs levels was 95% versus 65% in the low TILs group (p=0.037). Stromal TILs are an important prognostic biomarker in TNBC. Using a cutoff of 40%, high TILs are significantly associated with longer EFS.

Integrating Bulk and Single-cell RNA-seq to Construct a Macrophage-related Prognostic Model for Prognostic Stratification in Triple-negative Breast Cancer.

Background: Triple-negative breast cancer (TNBC) is a poor prognostic subtype of breast cancer due to limited treatment. Macrophage plays a critical role in tumor growth and survival. Our study intends to explore the heterogeneity of macrophage in TNBC and establish a macrophage-related prognostic model for TNBC prognostic stratification. Materials and Methods: Seurat package was conducted to analyze the single-cell RNA expression profilers. The cell types were identified by the markers derived from public research and online database. The cell-cell interactions were calculated by the CellChat package. Monocle package was used to visualize the cell trajectory of macrophages. The prognostic model was constructed by six macrophage-related genes after a series of selections. The expression of six genes were validated in normal and TNBC tissues. And several potential agents for high-risk TNBC patients were analyzed by Connectivity Map analysis. Results: Nine cell types were identified, and the macrophages were highly enriched in TNBC samples. five distinct subgroups of macrophage were identified. Notably, SPP1+ tumor-associated macrophages exhibited a poor prognosis. The prognostic model was constructed by HSPA6, LPL, IDO1, ALDH2, TK1, and QPCT with good predictive accuracy at 3-, 5- years overall survival for TNBC patients in both training and external test cohorts. Finally, several drugs were identified for the high-risk TNBC patients decided by model. Conclusion: Our study provides a valuable source for clarifying macrophage heterogeneity in TNBC, and a promising tool for prognostic risk stratification of TNBC.

Identification of new subtypes and potential genetic signatures in triple-negative breast cancer using weighted gene co-expression network analysis.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with aggressive behavior and poor prognosis. Here, we used gene expression profiling to define new subtypes of TNBC, which may improve prevention and treatment through personalized medicine. Gene expression profiles from the public datasets GSE76250, GSE61724, GSE61723, and GES76275 were subjected to co-expression analysis to identify differentially expressed genes (DEGs) between TNBC and non-TNBC tissues. Consistency clustering was used to define TNBC subtypes, whose correlation with gene modules was analyzed. Enrichment analysis was used to identify module genes' biological functions and pathways. Single-sample gene set enrichment analysis was used to assess immune cell infiltration in the different TNBC subtypes, and the ChAMP package was used to examine methylation sites in TNBC. A total of 4,958 DEGs in TNBC were identified, which showed the same expression differences across all datasets as in the dataset GSE76250 and clustered into 9 co-expression modules. TNBC samples clustered into two subtypes based on nine hub genes from the modules. Class I showed the most significant correlation with module 1, whose genes were related mainly to interleukin-1 response, while class II showed the most significant correlation with module 6, whose genes were related mainly to the transforming growth factor-β pathway. Class I was significantly enriched in cell cycle and DNA replication, and tumors of this subtype showed lower immune cell infiltration than class II tumors. Tumor infiltration by Th2 cells correlated positively with the expression of MCM10 and negatively with the expression of PREX2. A greater methylation of CIDEC, DLC1, EDNRB, EGR2 and SRPK1 correlated with better prognosis. Class I TNBC, for which a useful biomarker is MCM10, may be associated with a worse prognosis than class II TNBC, for which PREX2 may serve as a biomarker.

Estrogen receptor beta suppresses the androgen receptor oncogenic effects in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive type of breast cancer associated with poor prognosis and limited treatment options. The androgen receptor (AR) has emerged as a potential therapeutic target for luminal androgen receptor (LAR) TNBC. However, multiple studies have claimed that anti-androgen therapy for AR-positive TNBC only has limited clinical benefits. This study aimed to investigate the role of AR in TNBC and its detailed mechanism. Immunohistochemistry and TNBC tissue sections were applied to investigate AR and nectin cell adhesion molecule 4 (NECTIN4) expression in TNBC tissues. Then, in vitro and in vivo assays were used to explore the function of AR and estrogen receptor beta (ERβ) in TNBC. Chromatin immunoprecipitation sequencing (ChIP-seq), co-immunoprecipitation (co-IP), molecular docking method, and luciferase reporter assay were performed to identify key molecules that affect the function of AR. Based on the TNBC tissue array analysis, we revealed that ERβ and AR were positive in 21.92% (32/146) and 24.66% (36/146) of 146 TNBC samples, respectively, and about 13.70% (20/146) of TNBC patients were ERβ positive and AR positive. We further demonstrated the pro-tumoral effects of AR on TNBC cells, however, the oncogenic biology was significantly suppressed when ERβ transfection in LAR TNBC cell lines but not in AR-negative TNBC. Mechanistically, we identified that NECTIN4 promoter -42bp to -28bp was an AR response element, and that ERβ interacted with AR thus impeding the AR-mediated NECTIN4 transcription which promoted epithelial-mesenchymal transition in tumor progression. This study suggests that ERβ functions as a suppressor mediating the effect of AR in TNBC prognosis and cell proliferation. Therefore, our current research facilitates a better understanding of the role and mechanisms of AR in TNBC carcinogenesis.