Transcriptomic Profiling of Immune Cell-Enriched Regions in Triple-Negative Breast Cancer Using Targeted RNA Sequencing
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE305953 | GEO | 2025/08/21
REPOSITORIES: GEO
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Project description:Triple-negative breast cancer (TNBC) has a highly aggressive nature and distinct molecular characteristics from other subtypes of breast cancer and lacks effective targeted therapy. The molecular and genetic basis of cysteine/cystine dependency in TNBC is complex. We found that cysteine addiction associates with the expression of a set of Claudin genes in TNBC. The Claudin-high TNBCs are independent on cystine, while the Claudin-low TNBCs undergo rapid ferroptosis upon cystine deprivation or inhibition of cystine transport by erastin. To overcome the resistance of Claudin-high TNBC and luminal breast cancer to the potential targeted cystine-addiction therapy, we explored the synthetic lethality of cysteine by an epigenetic compound library screen. Several potent HDAC6 inhibitors were identified and rendered the Claudin-high TNBCs and luminal cancer cells dependent on extracellular cystine and undergoing ferroptosis upon cystine deprivation. The transcriptomic profiling showed that the HDAC6 inhibitor tubacin in combination with erastin activates a synthetic-lethal transcriptional program. Together, we have identified the HDAC6 inhibitors as potent therapy-sensitizers to revive the targeted cysteine-addiction therapy for various subtypes of breast cancer, not limit in the Claudin-low TNBC.
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Project description:Current prognostic gene expression profiles for breast cancer mainly reflect proliferation status and are most useful in ER-positive cancers. Triple-negative breast cancers (TNBCs) are clinically heterogeneous, and prognostic markers and biology-based therapies are needed to better treat this disease. We assembled Affymetrix gene expression data for 579 TNBCs and performed unsupervised analysis to define metagenes that distinguish molecular subsets within TNBC. We used n=394 cases for discovery and n=185 cases for validation. Sixteen metagenes emerged that identified basal-like, apocrine and claudin-low molecular subtypes, or reflected various non-neoplastic cell populations including immune cells, blood, adipocytes, stroma, angiogenesis, and inflammation within the cancer. The expressions of these metagenes were correlated with survival and multivariate analysis was performed including routine clinical and pathological variables. 73% of TNBCs displayed basal-like molecular subtype that correlated with high histological grade and younger age. Survival of basal-like TNBC was not different from non-basal-like TNBC. High expression of immune cell metagenes was associated with good and high expression of inflammation and angiogenesis-related metagenes were associated with poor prognosis. A ratio of high B-cell and low IL-8 metagenes identified 32% of TNBC with good prognosis (HR 0.37, 95% CI 0.22-0.61; P<0.001) and was the only significant predictor in multivariate analysis including routine clincopathological variables. We describe a ratio of high B-cell presence and low IL-8 activity as a powerful new prognostic marker for TNBC. Inhibition of the IL-8 pathway also represents an attractive novel therapeutic target for this disease. Analysis of primary breast cancer biopsies from patients before treatment. No replicates. No control or reference samples are included. The set of 579 TNBCs includes: (1) 67 new GEO Samples (GSM782523-GSM782589), (2) 489 re-analyzed GEO Samples (see 'Relation' links below), and (3) 23 re-analyzed ArrayExpress Samples. Cohorts: HH = University of Hamburg FRA = University of Frankfurt, adjuvant chemotherapy FRA-2 = University of Frankfurt, neoadjuvant chemotherapy FRA-3 = University of Frankfurt, no adjuvant chemotherapy Data processing of the 579 TNBC Samples: MAS5 values were taken from GEO if available. For samples with no MAS5 values, CEL files were downloaded from GEO and the affy package from Bioconductor was used to generate MAS5 values. Next, MAS5 values corresponding only to the 22283 probesets from the U133A array were compiled. Subsequently, normalization of MAS5 data was performed using the command line version of the program CLUSTER 3.0 (Michael Eisen; updated by Michiel de Hoon; http://bonsai.hgc.jp/~mdehoon/software/cluster/command.txt). The following three steps were performed in the following order: 1. log2 transformation of MAS5 values 2. median centering of arrays 3. magnitude normalization of arrays These three steps correspond to the following commands: cluster.com filename -l cluster.com filename -ca m cluster.com filename -na The resulting dataset, which is linked below as a supplementary file, was used for the subsequent analyses.
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Project description:Breast cancer, particularly triple-negative breast cancer (TNBC), evades the body's immune defences, in part by fostering an immunosuppressive tumour microenvironment. We present evidence that suppressing local steroidogenesis can enhance anti-tumour immunity against TNBC. Through targeted metabolomics of steroids alongside immunohistochemistry techniques, we initially profiled the presence of various steroids in TNBC patient tumours and identified steroidogenic activity in regions with immune infiltration. In mice, genetic inhibition of immune cell steroidogenesis limited TNBC tumour progression, significantly reducing immunosuppressive components such as tumour-associated macrophages, as revealed by single-cell RNA sequencing. Crucially, inhibiting steroidogenesis seems to strengthen anti-tumour immune responses in dendritic cells and T cells by obstructing glucocorticoid signalling, according to RNA sequencing insights. By undertaking metabolic modelling of the single-cell transcriptomics and targeted tumour steroidomics, we identified mast cells and basophils as the primary steroidogenic agents in TNBC, offering pathways for enhanced therapeutic precision.
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