Activation of ERß hijacks the splicing machinery to trigger R-loop formation in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with aggressive behavior and poor prognosis. Current therapeutic options available for TNBC patients are primarily chemotherapy. With our evolving understanding of this disease, novel targeted therapies, including poly ADP-ribose polymerase (PARP) inhibitors, antibody-drug conjugates, and immune-checkpoint inhibitors, have been developed for clinical use. Previous reports have demonstrated the essential role of estrogen receptor ß (ERß) in TNBC, but the detailed molecular mechanisms downstream ERß activation in TNBC are still far from elucidated. In this study, we demonstrated that a specific ERß agonist, LY500307, potently induces R-loop formation and DNA damage in TNBC cells. Subsequent interactome experiments indicated that the residues 151 to 165 of U2 small nuclear RNA auxiliary factor 1 (U2AF1) and the Trp439 and Lys443 of ERß were critical for the binding between U2AF1 and ERß. Combined RNA sequencing and ribosome sequencing analysis demonstrated that U2AF1-regulated downstream RNA splicing of 5-oxoprolinase (OPLAH) could affect its enzymatic activity and is essential for ERß-induced R-loop formation and DNA damage. In clinical samples including 115 patients from The Cancer Genome Atlas (TCGA) and 32 patients from an in-house cohort, we found a close correlation in the expression of ESR2 and U2AF1 in TNBC patients. Collectively, our study has unraveled the molecular mechanisms that explain the therapeutic effects of ERß activation in TNBC, which provides rationale for ERß activation-based single or combined therapy for patients with TNBC.

A second-generation eIF4A RNA helicase inhibitor exploits translational reprogramming as a vulnerability in triple-negative breast cancer.

In this study, we aimed to address the current limitations of therapies for macro-metastatic triple-negative breast cancer (TNBC) and provide a therapeutic lead that overcomes the high degree of heterogeneity associated with this disease. Specifically, we focused on well-documented but clinically underexploited cancer-fueling perturbations in mRNA translation as a potential therapeutic vulnerability. We therefore developed an orally bioavailable rocaglate-based molecule, MG-002, which hinders ribosome recruitment and scanning via unscheduled and non-productive RNA clamping by the eukaryotic translation initiation factor (eIF) 4A RNA helicase. We demonstrate that MG-002 potently inhibits mRNA translation and primary TNBC tumor growth without causing overt toxicity in mice. Importantly, given that metastatic spread is a major cause of mortality in TNBC, we show that MG-002 attenuates metastasis in pre-clinical models. We report on MG-002, a rocaglate that shows superior properties relative to existing eIF4A inhibitors in pre-clinical models. Our study also paves the way for future clinical trials exploring the potential of MG-002 in TNBC and other oncological indications.

Proteomic Analysis Revealed the Potential Role of MAGE-D2 in the Therapeutic Targeting of Triple-Negative Breast Cancer.

Among all the molecular subtypes of breast cancer, triple-negative breast cancer (TNBC) is the most aggressive one. Currently, the clinical prognosis of TNBC is poor because there is still no effective therapeutic target. Here, we carried out a combined proteomic analysis involving bioinformatic analysis of the proteome database, label-free quantitative proteomics, and immunoprecipitation (IP) coupled with mass spectrometry (MS) to explore potential therapeutic targets for TNBC. The results of bioinformatic analysis showed an overexpression of MAGE-D2 (melanoma antigen family D2) in TNBC. In vivo and in vitro experiments revealed that MAGE-D2 overexpression could promote cell proliferation and metastasis. Furthermore, label-free quantitative proteomics revealed that MAGE-D2 acted as a cancer-promoting factor by activating the PI3K-AKT pathway. Moreover, the outcomes of IP-MS and cross-linking IP-MS demonstrated that MAGE-D2 could interact with Hsp70 and prevent Hsp70 degradation, but evidence for their direct interaction is still lacking. Nevertheless, MAGE-D2 is a potential therapeutic target for TNBC, and blocking MAGE-D2 may have important therapeutic implications.

Purinergic signaling promotes premature senescence.

Extracellular ATP activates P2 purinergic receptors. Whether purinergic signaling is functionally coupled to cellular senescence is largely unknown. We find that oxidative stress induced release of ATP and caused senescence in human lung fibroblasts. Inhibition of P2 receptors limited oxidative stress-induced senescence, while stimulation with exogenous ATP promoted premature senescence. Pharmacological inhibition of P2Y11 receptor (P2Y11R) inhibited premature senescence induced by either oxidative stress or ATP, while stimulation with a P2Y11R agonist was sufficient to induce cellular senescence. Our data show that both extracellular ATP and a P2Y11R agonist induced calcium (Ca++) release from the endoplasmic reticulum (ER) and that either inhibition of phospholipase C or intracellular Ca++ chelation impaired ATP-induced senescence. We also find that Ca++ that was released from the ER, following ATP-mediated activation of phospholipase C, entered mitochondria in a manner dependent on P2Y11R activation. Once in mitochondria, excessive Ca++ promoted the production of reactive oxygen species in a P2Y11R-dependent fashion, which drove development of premature senescence of lung fibroblasts. Finally, we show that conditioned medium derived from senescent lung fibroblasts, which were induced to senesce through the activation of ATP/P2Y11R-mediated signaling, promoted the proliferation of triple-negative breast cancer cells and their tumorigenic potential by secreting amphiregulin. Our study identifies the existence of a novel purinergic signaling pathway that links extracellular ATP to the development of a protumorigenic premature senescent phenotype in lung fibroblasts that is dependent on P2Y11R activation and ER-to-mitochondria calcium signaling.

Novel markers of MCL1 inhibitor sensitivity in triple-negative breast cancer cells.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer sub-type with limited treatment options and poor prognosis. Currently, standard treatments for TNBC include surgery, chemotherapy, and anti-PDL1 therapy. These therapies have limited efficacy in advanced stages. Myeloid-cell leukemia 1 (MCL1) is an anti-apoptotic BCL2 family protein. High expression of MCL1 contributes to chemotherapy resistance and is associated with a worse prognosis in TNBC. MCL1 inhibitors are in clinical trials for TNBC, but response rates to these inhibitors can vary and predictive markers are lacking. Currently, we identified a 4-member (AXL, ETS1, IL6, EFEMP1) gene signature (GS) that predicts MCL1 inhibitor sensitivity in TNBC cells. Factors encoded by these genes regulate signaling pathways to promote MCL1 inhibitor resistance. Small molecule inhibitors of the GS factors can overcome resistance and sensitize otherwise resistant TNBC cells to MCL1 inhibitor treatment. These findings offer insights into potential therapeutic strategies and tumor stratification for MCL1 inhibitor use in TNBC.

Development and validation of AI/ML derived splice-switching oligonucleotides.

Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identification of functional, verifiable, and therapeutic SSOs. We trained XGboost tree models using splicing factor (SF) pre-mRNA binding profiles and spliceosome assembly information to identify modulatory SSO binding sites on pre-mRNA. Using Shapley and out-of-bag analyses we also predicted the identity of specific SFs whose binding to pre-mRNA is blocked by SSOs. This step adds considerable transparency to AI/ML-driven drug discovery and informs biological insights useful in further validation steps. We applied this approach to previously established functional SSOs to retrospectively identify the SFs likely to regulate those events. We then took a prospective validation approach using a novel target in triple negative breast cancer (TNBC), NEDD4L exon 13 (NEDD4Le13). Targeting NEDD4Le13 with an AI/ML-designed SSO decreased the proliferative and migratory behavior of TNBC cells via downregulation of the TGFß pathway. Overall, this study illustrates the ability of AI/ML to extract actionable insights from RNA-seq data.

Suppression of AGRN enhances CD8+ T cell recruitment and inhibits breast cancer progression.

Breast cancer (BC) stands as a prominent contributor to global cancer-related mortality, with an increasing incidence annually. This study aims to investigate AGRN gene expression in BC, as well as explore its influence on the tumor immune microenvironment. AGRN displayed a pronounced upregulation in BC tissues relative to paracancerous tissues. Single-cell RNA analysis highlighted AGRN-specific elevation within cancer cell clusters and also showed expression expressed in stromal as well as immune cell clusters. AGRN upregulation was positively correlated with clinicopathological stage and negatively correlated with BC prognosis. As revealed by the in vitro experiment, AGRN knockdown effectively hinders BC cells in terms of proliferation, invasion as well as migration. AGRN protein, which may interact with EXT1, LRP4, RAPSN, etc., was primarily distributed in the cell cytoplasm. Notably, immune factors might interact with AGRN in BC, evidenced by its discernible associations with immunofactors like IL10, CD274, and PVRL2. Mass spectrometry and immunohistochemistry revealed that the reduction of AGRN led to an increase in CD8+ T cells with triple-negative breast cancer (TNBC). Mechanistically, the connection between TRIM7 and PD-L1 is improved by AGRN, acting as a scaffold, thereby facilitating the accelerated degradation of PD-L1 by TRIM7. Downregulation of AGRN inhibits BC progression and increases CD8+ T cell recruitment. Targeting AGRN may contribute to BC treatment. The biomarker AGRN, serving as a therapeutic target for BC, emerges as a prospective avenue for enhancing both diagnosis and prognosis in BC cases.

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer.

BACKGROUND: Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach. METHODS: In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels. RESULTS: There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965. CONCLUSION: This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Fluvastatin prevents lung metastasis in triple-negative breast cancer by triggering autophagy via the RhoB/PI3K/mTOR pathway.

Triple-negative breast cancer is more common among younger than older women and is associated with the poorest survival outcomes of all breast cancer types. Fluvastatin inhibits tumour progression and induces the autophagy of breast cancer cells; however, the role of autophagy in fluvastatin-induced inhibition of breast cancer metastasis is unknown. Therefore, this study aimed to determine this mechanism. The effect of fluvastatin on human hormone receptor-negative breast cancer cells was evaluated in vitro via migration and wound healing assays, western blotting, and morphological measurements, as well as in vivo using a mouse xenograft model. Chloroquine, a prophylactic medication used to prevent malaria in humans was used as an autophagy inhibitor. We found that fluvastatin administration effectively prevented the migration/invasion of triple-negative breast cancer cells, an effect that was largely dependent on the induction of autophagy. Administration of the autophagy inhibitor chloroquine prevented the fluvastatin-induced suppression of lung metastasis in the nude mouse model. Furthermore, fluvastatin increased Ras homolog family member B (RhoB) expression, and the autophagy and anti-metastatic activity induced by fluvastatin were predominantly dependent on the regulation of RhoB through the protein kinase B-mammalian target of rapamycin (Akt-mTOR) signaling pathway. These results suggest that fluvastatin inhibits the metastasis of triple-negative breast cancer cells by modulating autophagy via the up regulation of RhoB through the AKT-mTOR signaling pathway. Fluvastatin may be a promising therapeutic option for patients with triple-negative breast cancer.

Methylation of GPRC5A promotes liver metastasis and docetaxel resistance through activating mTOR signaling pathway in triple negative breast cancer.

AIMS: This study aims to explore the function and mechanism of G Protein-coupled receptor class C group 5 member A (GPRC5A) in docetaxel-resistance and liver metastasis of breast cancer. METHODS: Single-cell RNA transcriptomic analysis and bioinformatic analysis are used to screen relevant genes in breast cancer metastatic hepatic specimens. MeRIP, dual-luciferase analysis and bioinformation were used to detect m6A modulation. Mass spectrometry (MS), co-inmunoprecipitation (co-IP) and immunofluorescence colocalization were executed to explore the mechanism of GPRC5A in breast cancer cells. RESULT: GPRC5A was upregulated in triple-negative breast cancer (TNBC) and was associated with a poor prognosis. In vitro and in vivo experiments demonstrated that knockdown of GPRC5A alleviated metastasis and resistance to docetaxel in TNBC. Overexpression of GPRC5A had the opposite effects. The m6A methylation of GPRC5A mRNA was modulated by METTL3 and YTHDF1, which facilitates its translation. GPRC5A inhibited the ubiquitination-dependent degradation of LAMTOR1, resulting in the recruitment of mTORC1 to lysosomes and activating the mTORC1/p70s6k signaling pathway. CONCLUSION: METTL3/YTHDF1 axis up-regulates GPRC5A expression by m6A methylation. GPRC5A activates mTORC1/p70s6k signaling pathway by recruiting mTORC1 to lysosomes, consequently promotes docetaxel-resistance and liver metastasis.

FOXCUT regulates the malignant phenotype of triple-negative breast Cancer via the miR-337-3p/ANP32E Axis.

BACKGROUND: The lack of specific molecular targets and the rapid spread lead to a worse prognosis of triple-negative breast cancer (TNBC). Therefore, identifying new therapeutic and prognostic biomarkers helps to develop effective treatment strategies for TNBC. METHODS: Through preliminary bioinformatics analysis, FOXCUT was found to be significantly overexpressed in breast cancer, especially in TNBC. Tissue samples were collected from 15 TNBC patients, and qRT-PCR was employed to validate the expression of FOXCUT in both TNBC patient tissues and TNBC cell lines. We also carried out the GSEA analysis and KEGG enrichment analysis of FOXCUT. Additionally, the effects of FOXCUT knockdown on TNBC cell malignant behaviors, and aerobic glycolysis were assessed by methods including CCK-8, Transwell, western blot, and Seahorse XF 96 analyses. Moreover, utilizing databases predicting interactions between ceRNAs, corresponding lncRNA-miRNA binding relationships, and miRNA-mRNA interactions were predicted. These predictions were subsequently validated through RNA immunoprecipitation and dual-luciferase reporter assays. RESULTS: FOXCUT exhibited high expression in both TNBC tissues and cell lines, fostering cell malignant behaviors and glycolysis. FOXCUT was found to sponge miR-337-3p, while miR-337-3p negatively regulated the expression of ANP32E. Consequently, FOXCUT ultimately facilitated the malignant phenotype of TNBC by upregulating ANP32E expression. CONCLUSION: This study elucidated the role of FOXCUT in elevating aerobic glycolysis levels in TNBC and driving malignant cancer cell development via the miR-337-3p/ANP32E regulatory axis.

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.

Single-cell transcriptome sequencing reveals SPP1-CD44-mediated macrophage-tumor cell interactions drive chemoresistance in TNBC.

Triple-negative breast cancer (TNBC) is often considered one of the most aggressive subtypes of breast cancer, characterized by a high recurrence rate and low overall survival (OS). It is notorious for posing challenges related to drug resistance. While there has been progress in TNBC research, the mechanisms underlying chemotherapy resistance in TNBC remain largely elusive. We collect single-cell RNA sequencing (scRNA-seq) data from five TNBC patients susceptible to chemotherapy and five resistant cases. Comprehensive analyses involving copy number variation (CNV), pseudotime trajectory, cell-cell interactions, pseudospace analysis, as well as transcription factor and functional enrichment are conducted specifically on macrophages and malignant cells. Furthermore, we performed validation experiments on clinical samples using multiplex immunofluorescence. We identified a subset of SPP1+ macrophages that secrete SPP1 signals interacting with CD44 on malignant cell surfaces, potentially activating the PDE3B pathway within malignant cells via the integrin pathway, leading to chemotherapy resistance. The abnormally enhanced SPP1 signal between macrophages and malignant cells may serve as a factor promoting chemotherapy resistance in TNBC patients. Therefore, SPP1+ macrophages could potentially serve as a therapeutic target to reduce chemotherapy resistance.

METTL14/miR-29c-3p axis drives aerobic glycolysis to promote triple-negative breast cancer progression though TRIM9-mediated PKM2 ubiquitination.

The energy metabolic rearrangement of triple-negative breast cancer (TNBC) from oxidative phosphorylation to aerobic glycolysis is a significant biological feature and can promote the malignant progression. However, there is little knowledge about the functional mechanisms of methyltransferase-like protein 14 (METTL14) mediated contributes to TNBC malignant progression. Our study found that METTL14 expression was significantly upregulated in TNBC tissues and cell lines. Silencing METTL14 significantly inhibited TNBC cell growth and invasion in vitro, as well as suppressed tumour growth. Mechanically, METTL14 was first found to activate miR-29c-3p through m6A and regulate tripartite motif containing 9 (TRIM9) to promote ubiquitination of pyruvate kinase isoform M2 (PKM2) and lead to its transition from tetramer to dimer, resulting in glucose metabolic reprogramming from oxidative phosphorylation to aerobic glycolysis to promote the progress of TNBC. Taken together, these findings reveal important roles of METTL14 in TNBC tumorigenesis and energy metabolism, which might represent a novel potential therapeutic target for TNBC.

Exploring the interplay between triple-negative breast cancer stem cells and tumor microenvironment for effective therapeutic strategies.

Triple-negative breast cancer (TNBC) is a highly aggressive and metastatic malignancy with poor treatment outcomes. The interaction between the tumor microenvironment (TME) and breast cancer stem cells (BCSCs) plays an important role in the development of TNBC. Owing to their ability of self-renewal and multidirectional differentiation, BCSCs maintain tumor growth, drive metastatic colonization, and facilitate the development of drug resistance. TME is the main factor regulating the phenotype and metastasis of BCSCs. Immune cells, cancer-related fibroblasts (CAFs), cytokines, mesenchymal cells, endothelial cells, and extracellular matrix within the TME form a complex communication network, exert highly selective pressure on the tumor, and provide a conducive environment for the formation of BCSC niches. Tumor growth and metastasis can be controlled by targeting the TME to eliminate BCSC niches or targeting BCSCs to modify the TME. These approaches may improve the treatment outcomes and possess great application potential in clinical settings. In this review, we summarized the relationship between BCSCs and the progression and drug resistance of TNBC, especially focusing on the interaction between BCSCs and TME. In addition, we discussed therapeutic strategies that target the TME to inhibit or eliminate BCSCs, providing valuable insights into the clinical treatment of TNBC.

Overcoming doxorubicin resistance in triple-negative breast cancer using the class I-targeting HDAC inhibitor bocodepsin/OKI-179 to promote apoptosis.

BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with a poor prognosis. Doxorubicin is part of standard curative therapy for TNBC, but chemotherapy resistance remains an important clinical challenge. Bocodepsin (OKI-179) is a small molecule class I histone deacetylase (HDAC) inhibitor that promotes apoptosis in TNBC preclinical models. The purpose of this study was to investigate the combination of bocodepsin and doxorubicin in preclinical TNBC models and evaluate the impact on terminal cell fate, including apoptosis and senescence. METHODS: TNBC cell lines were treated with doxorubicin and CellTiter-Glo was used to assess proliferation and determine doxorubicin sensitivity. Select cell lines were treated with OKI-005 (in vitro version of bocodepsin) and doxorubicin and assessed for proliferation, apoptosis as measured by Annexin V/PI, and cell cycle by flow cytometry. Immunoblotting was used to assess changes in mediators of apoptosis, cell cycle arrest, and senescence. Senescence was measured by the senescence-associated ß-galactosidase assay. An MDA-MB-231 xenograft in vivo model was treated with bocodepsin, doxorubicin, or the combination and assessed for inhibition of tumor growth. shRNA knockdown of p53 was performed in the CAL-51 cell line and proliferation, apoptosis and senescence were assessed in response to combination treatment. RESULTS: OKI-005 and doxorubicin resulted in synergistic antiproliferative activity in TNBC cells lines regardless of p53 mutation status. The combination led to increased apoptosis and decreased senescence. In vivo, the combination resulted in increased tumor growth inhibition compared to either single agent. shRNA knock-down of p53 led to increased doxorubicin-induced senescence that was decreased with the addition of OKI-005 in vitro. CONCLUSION: The addition of bocodepsin to doxorubicin resulted in synergistic antiproliferative activity in vitro, improved tumor growth inhibition in vivo, and promotion of apoptosis which makes this a promising combination to overcome doxorubicin resistance in TNBC. Bocodepsin is currently in clinical development and has a favorable toxicity profile compared to other HDAC inhibitors supporting the feasibility of evaluating this combination in patients with TNBC.

Targeting tumor-stromal interactions in triple-negative breast cancer using a human vascularized micro-tumor model.

Triple-negative breast cancer (TNBC) is highly aggressive with limited available treatments. Stromal cells in the tumor microenvironment (TME) are crucial in TNBC progression; however, understanding the molecular basis of stromal cell activation and tumor-stromal crosstalk in TNBC is limited. To investigate therapeutic targets in the TNBC stromal niche, we used an advanced human in vitro microphysiological system called the vascularized micro-tumor (VMT). Using single-cell RNA sequencing, we revealed that normal breast tissue stromal cells activate neoplastic signaling pathways in the TNBC TME. By comparing interactions in VMTs with clinical data, we identified therapeutic targets at the tumor-stromal interface with potential clinical significance. Combining treatments targeting Tie2 signaling with paclitaxel resulted in vessel normalization and increased efficacy of paclitaxel in the TNBC VMT. Dual inhibition of HER3 and Akt also showed efficacy against TNBC. These data demonstrate the potential of inducing a favorable TME as a targeted therapeutic approach in TNBC.

The novel phosphatase NUDT5 is a critical regulator of triple-negative breast cancer growth.

BACKGROUND: The most aggressive form of breast cancer is triple-negative breast cancer (TNBC), which lacks expression of the estrogen receptor (ER) and progesterone receptor (PR), and does not have overexpression of the human epidermal growth factor receptor 2 (HER2). Treatment options for women with TNBC tumors are limited, unlike those with ER-positive tumors that can be treated with hormone therapy, or those with HER2-positive tumors that can be treated with anti-HER2 therapy. Therefore, we have sought to identify novel targeted therapies for TNBC. In this study, we investigated the potential of a novel phosphatase, NUDT5, as a potential therapeutic target for TNBC. METHODS: The mRNA expression levels of NUDT5 in breast cancers were investigated using TCGA and METABRIC (Curtis) datasets. NUDT5 ablation was achieved through siRNA targeting and NUDT5 inhibition with the small molecule inhibitor TH5427. Xenograft TNBC animal models were employed to assess the effect of NUDT5 inhibition on in vivo tumor growth. Proliferation, death, and DNA replication assays were conducted to investigate the cellular biological effects of NUDT5 loss or inhibition. The accumulation of 8-oxo-guanine (8-oxoG) and the induction of γH2AX after NUDT5 loss was determined by immunofluorescence staining. The impact of NUDT5 loss on replication fork was assessed by measuring DNA fiber length. RESULTS: In this study, we demonstrated the significant role of an overexpressed phosphatase, NUDT5, in regulating oxidative DNA damage in TNBCs. Our findings indicate that loss of NUDT5 results in suppressed growth of TNBC both in vitro and in vivo. This growth inhibition is not attributed to cell death, but rather to the suppression of proliferation. The loss or inhibition of NUDT5 led to an increase in the oxidative DNA lesion 8-oxoG, and triggered the DNA damage response in the nucleus. The interference with DNA replication ultimately inhibited proliferation. CONCLUSIONS: NUDT5 plays a crucial role in preventing oxidative DNA damage in TNBC cells. The loss or inhibition of NUDT5 significantly suppresses the growth of TNBCs. These biological and mechanistic studies provide the groundwork for future research and the potential development of NUDT5 inhibitors as a promising therapeutic approach for TNBC patients.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer.

BACKGROUND: Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment in NAC response in patients with TNBC remains unclear. In this study, we developed a machine learning-based two-step pipeline to distinguish between various histological components in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of TNBC tissue biopsies and to identify histological features that can predict NAC response. METHODS: H&E-stained WSIs of treatment-naïve biopsies from 85 patients (51 with pCR and 34 with RD) of the model development cohort and 79 patients (41 with pCR and 38 with RD) of the validation cohort were separated through a stratified eightfold cross-validation strategy for the first step and leave-one-out cross-validation strategy for the second step. A tile-level histology label prediction pipeline and four machine-learning classifiers were used to analyze 468,043 tiles of WSIs. The best-trained classifier used 55 texture features from each tile to produce a probability profile during testing. The predicted histology classes were used to generate a histology classification map of the spatial distributions of different tissue regions. A patient-level NAC response prediction pipeline was trained with features derived from paired histology classification maps. The top graph-based features capturing the relevant spatial information across the different histological classes were provided to the radial basis function kernel support vector machine (rbfSVM) classifier for NAC treatment response prediction. RESULTS: The tile-level prediction pipeline achieved 86.72% accuracy for histology class classification, while the patient-level pipeline achieved 83.53% NAC response (pCR vs. RD) prediction accuracy of the model development cohort. The model was validated with an independent cohort with tile histology validation accuracy of 83.59% and NAC prediction accuracy of 81.01%. The histological class pairs with the strongest NAC response predictive ability were tumor and tumor tumor-infiltrating lymphocytes for pCR and microvessel density and polyploid giant cancer cells for RD. CONCLUSION: Our machine learning pipeline can robustly identify clinically relevant histological classes that predict NAC response in TNBC patients and may help guide patient selection for NAC treatment.