Prognosis Of Triple-negative Breast Cancer Research Articles

Identification of TUBB2A as a Cancer-Immunity Cycle-Related Therapeutic Target in Triple-Negative Breast Cancer.

Triple negative breast cancer (TNBC) is a malignant subtype of breast cancer characterized by the absence of ER, PR, and HER2. We aimed to explore target gene from the perspective of cancer-immunity cycle, providing insights into treatment of TNBC. We obtained TNBC samples from METABRIC database and downloaded 4 datasets from GEO database, as well as an IMvigor210 dataset. WGCNA was applied to screen genes associated with cancer-immunity cycle in TNBC. GO, KEGG and GSEA analyses were performed to explore the target gene's potential functions and pathways. The binding motifs with transcription factors were predicted with FIMO. Immune infiltration analysis was conducted by CIBERSORT. TUBB2A was screened out as our target gene which was negatively correlated with T cell recruitment in cancer-immunity cycle. TUBB2A expressed higher in TNBC samples than in normal samples. High expression of TUBB2A was associated with poor prognosis of TNBC. 12 transcription factors and 5 miRNAs might regulate TUBB2A's expression. The infiltration ratios of 7 types of immune cells such as CD8+ T cells, naive CD4+ T cells and activated memory CD4+ T cells were significantly lower in TUBB2A high expression group. TUBB2A was a potential drug target. We screened a cancer-immunity cycle-related gene TUBB2A which was negatively correlated with T cell recruiting in TNBC. TUBB2A expressed higher in TNBC samples than in normal samples, associated with poor prognosis.

Opioids and immune checkpoint inhibitors differentially regulate a common immune network in triple-negative breast cancer.

Opioids are the primary analgesics for cancer pain. Recent clinical evidence suggests opioids may counteract the effect of immune checkpoint inhibition (ICI) immunotherapy, but the mechanism for this interaction is unknown. The following experiments study how opioids and immunotherapy modulate a common RNA expression pathway in triple negative breast cancer (TNBC), a cancer subtype in which immunotherapy is increasingly used. This study identifies a mechanism by which opioids may decrease ICI efficacy, and compares ketamine, a non-opioid analgesic with emerging use in cancer pain, for potential ICI interaction. Tumor RNA expression and clinicopathologic data from a large cohort with TNBC (N=286) was used to identify RNA expression signatures of disease. Various drug-induced RNA expression profiles were extracted from multimodal RNA expression datasets and analyzed to estimate the RNA expression effects of ICI, opioids, and ketamine on TNBC. We identified a RNA expression network in CD8+ T-cells that was relevant to TNBC pathogenesis and prognosis. Both opioids and anti-PD-L1 ICI regulated RNA expression in this network, suggesting a nexus for opioid-ICI interaction. Morphine and anti-PD-L1 therapy regulated RNA expression in opposing directions. By contrast, there was little overlap between the effect of ketamine and anti-PD-L1 therapy on RNA expression. Opioids and ICI may target a common immune network in TNBC and regulate gene expression in opposing fashion. No available evidence supports a similar interaction between ketamine and ICI.

C-X-C Motif Chemokine Ligand 9 Correlates with Favorable Prognosis in Triple-Negative Breast Cancer by Promoting Immune Cell Infiltration.

C-X-C motif chemokine ligand 9 (CXCL9) plays an important role in antitumor immunity through the recruitment, proliferation, and activation of immune cells (IC). Here, we evaluated the expression patterns of CXCL9 and programmed death-ligand 1 (PD-L1) in a cohort of 268 patients with triple-negative breast cancer (TNBC) by tissue microarray (TMA). The correlations between CXCL9 expression in ICs or tumor cells (TC) and clinicopathologic parameters, PD-L1 expression, tumor-infiltrating lymphocytes (TIL) and survival were analyzed in this cohort (n = 268). In addition, we analyzed a TNBC dataset (n = 138) from The Cancer Genome Atlas (TCGA) to identify correlation between CXCL9 expression and other immune gene expression, immune infiltration, and prognosis. The results of the TMA cohort (n = 268) showed that CXCL9 was expressed in 80.6% cases, with elevated expression levels in ICs relative to in TCs (median: 1% vs. 0%). CXCL9 expressed in ≥1% of ICs was categorized as the CXCL9-IC-positive group. CXCL9-IC expression was strongly and positively correlated with the PD-L1 expression, CD3+ TILs, CD4+ TILs, CD8+ TILs, and CD19+ TILs (all P < 0.0001). Survival analyses showed that the CXCL9-IC-positive group demonstrated prolonged disease-free survival (P = 0.038) and overall survival (P = 0.023) compared with the negative group. The analyses from TCGA cohort (n = 138) showed that elevated CXCL9 expression correlated with increased infiltration of B cells, macrophages, natural killer cells, monocytes and increased expression of immune checkpoint molecules and other CXCL family members, including CXCL10 and CXCL11. These findings confirm the regulatory role of CXCL9 in antitumor immunity and suggest a potential role in treatments involving immune checkpoint blockade.

A serum LncRNA signature for predicting prognosis of triple-negative breast cancer

BackgroundBreast cancer is the leading causes of cancer-associated mortality among women, and triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Long non-coding RNAs (LncRNAs) have recently been studied to predict the prognosis of various cancers, but whether it is an effective marker in TNBC is inconclusive. MethodsWe used RNA-sequencing analysis to identify differentially expressed exosomal LncRNAs, and qRT-PCR assay was performed to verify dysregulated LncRNAs in multicenter validation cohorts. A signature, which was composed of LINC00989, CEA, and CA153, was then utilized to predict the progression and recurrence of TNBC. Kaplan-Meier analysis was applied to evaluate the prognostic values of the signature. ResultsOn the basis of RNA-sequencing analysis, we found that serum exosomal LncRNA LINC00989 was significantly up-regulated in metastatic patients of TNBC. Then LINC00989, together with clinic marker CEA and CA125, were selected to construct a prognostic signature. In both training and validation cohort, higher levels of this signature were significantly related with shorter overall and progression-free survival time. Univariate and multivariate analysis shown that the signature was the independent prognosis factor of TNBC patients. ConclusionsOur results suggested that this prognostic signature might potentially predict prognosis and recurrence of TNBC, and was worth validation in future clinical trials.

Long non-coding RNA AC099850.4 correlates with advanced disease state and predicts worse prognosis in triple-negative breast cancer.

Our understanding of the function of long non-coding RNAs (lncRNAs) in health and disease states has evolved over the past decades due to the many advances in genome research. In the current study, we characterized the lncRNA transcriptome enriched in triple-negative breast cancer (TNBC, n = 42) and estrogen receptor (ER+, n = 42) breast cancer compared to normal breast tissue (n = 56). Given the aggressive nature of TNBC, our data revealed selective enrichment of 57 lncRNAs in TNBC. Among those, AC099850.4 lncRNA was chosen for further investigation where it exhibited elevated expression, which was further confirmed in a second TNBC cohort (n = 360) where its expression correlated with a worse prognosis. Network analysis of AC099850.4high TNBC highlighted enrichment in functional categories indicative of cell cycle activation and mitosis. Ingenuity pathway analysis on the differentially expressed genes in AC099850.4high TNBC revealed the activation of the canonical kinetochore metaphase signaling pathway, pyridoxal 5'-phosphate salvage pathway, and salvage pathways of pyrimidine ribonucleotides. Additionally, upstream regulator analysis predicted the activation of several upstream regulator networks including CKAP2L, FOXM1, RABL6, PCLAF, and MITF, while upstream regulator networks of TP53, NUPR1, TRPS1, and CDKN1A were suppressed. Interestingly, elevated expression of AC099850.4 correlated with worse short-term relapse-free survival (log-rank p = 0.01). Taken together, our data are the first to reveal AC099850.4 as an unfavorable prognostic marker in TNBC, associated with more aggressive clinicopathological features, and suggest its potential utilization as a prognostic biomarker and therapeutic target in TNBC.

Artificial intelligence learning landscape of triple-negative breast cancer uncovers new opportunities for enhancing outcomes and immunotherapy responses

Triple-negative breast cancer (TNBC) is a relatively aggressive breast cancer subtype due to tumor relapse, drug resistance, and multi-organ metastatic properties. Identifying reliable biomarkers to predict prognosis and precisely guide TNBC immunotherapy is still an unmet clinical need. To address this issue, we successfully constructed a novel 25 machine learning (ML) algorithms-based immune infiltrating cell (IIC) associated signature of TNBC (MLIIC), achieved by multiple transcriptome data of purified immune cells, TNBC cell lines, and TNBC entities. The TSI index was employed to determine IIC-RNAs that were accompanied by an expression pattern of upregulation in immune cells and downregulation in TNBC cells. LassoLR, Boruta, Xgboost, SVM, RF, and Pamr were utilized for further obtaining the optimal IIC-RNAs. Following univariate Cox regression analysis, LassoCox, CoxBoost, and RSF were utilized for the dimensionality reduction of IIC-RNAs from a prognostic perspective. RSF, Ranger, ObliqueRSF, Rpart, CoxPH, SurvivalSVM, CoxBoost, GlmBoost, SuperPC, StepwiseCox, Enet, LassoCox, CForest, Akritas, BlackBoost, PlsRcox, SurvReg, GBM, and CTree were used for determining the most potent MLIIC signature. Consequently, this MLIIC signature was correlated significantly with survival status validated by four independent TNBC cohorts. Also, the MLIIC signature had a superior predictive capability for TNBC prognosis, compared with 148 previously reported signatures. In addition, MLIIC signature scores developed by immunofluorescent staining of tissue arrays from TNBC patients showed a substantial prognostic value. In TNBC immunotherapy, the low MLIIC profile demonstrated significant immune-responsive efficacy in a dataset of multiple cancer types. MLIIC signature could also predict m6A epigenetic regulation which controls T cell homeostasis. Therefore, this well-established MLIIC signature is a robust predictive indicator for TNBC prognosis and the benefit of immunotherapy, thus providing an efficient tool for combating TNBC.

Role of ICAM1 in tumor immunity and prognosis of triple-negative breast cancer.

Treating triple-negative breast cancer (TNBC) is a difficult landscape owing to its short survival times and high risk of metastasis and recurrence among patients. Although involved in tumor invasion and metastasis, the mechanism of action of intercellular adhesion molecule 1 (ICAM1), a trans-membrane glycoprotein, in TNBC is ambiguous. We examined ICAM1's role in TNBC, focusing on its expression, cell survival, mutation, and tumor immunity. Then, a risk score model was created utilizing co-expressed genes associated with ICAM1. According to their respective risk scores, we divided patients into high- and low-risk groups. Immune function, drug susceptibility differences, and somatic variants were analyzed in the high-and low-risk groups. And we used the CMap database to predict potential medications. Then, TNBC cells with low expression of ICAM-1 were co-cultured with PMA-treated THP-1 cells and CD8 T cells. In addition, We detected the expression of PD-1 and CTLA4 of low ICAM-1 expressing TNBC cells when they were cocultured with CD8 T cells. ICAM1 was found to be involved in leukocyte cell adhesion, motility, and immune activation. Patients with low-ICAM1 group had shorter disease-free survival (DFS) than those with high-ICAM1 group. The group with elevated levels of ICAM1 exhibited significantly increased levels of T-cell regulation, quiescence in natural killer (NK) cells, and M1 macrophage. ICAM1 expression was correlated with immune checkpoint drugs. The prognostic ability of the risk score model was found to be superior to that of individual genes. Patients categorized as high-risk exhibited elevated clinical stages, showed higher M1 macrophage numbers, and were able to benefit better from immunotherapy. Individuals belonging to the high-risk group exhibit significantly elevated mutation rates in TP53, TTN, and SYNE1 genes, along with increased TMB and PD-L1 levels and decreased TIDE scores. These findings suggest that immunotherapy may be advantageous for the high-risk group. Furthermore, low expression of ICAM1 was found to promote polarization to M2 macrophages along with T-cell exhaustion. In conclusion, Low ICAM1 expression may be related to immune escape, leading to poor treatment response and a worse prognosis.

Advances in Medicinal Chemistry of Estrogen-related receptor alpha (ERRα) inverse agonists.

Estrogen-related receptor alpha (ERRα), a member of the nuclear receptor superfamily, is strongly expressed in breast cancer cells. Its overexpression is associated with poor prognosis in triple-negative breast cancer (TNBC). ERRα expression could be inhibited by the downregulation of upstream oncogenic growth factors mTOR, HER2, and PI3K. Low expression of ERRα could suppress the migration and angiogenesis of tumor cells by inhibiting the activity of its downstream signals VEGF and WNT11. Studies have confirmed that ERRα inverse agonists can inhibit ERRα expression to treat breast cancer. Inverse agonists of ERRα could disrupt the interactions of ERRα with its coactivators and inhibit tumor development. Existing ERRα inverse agonists have shown moderate efficacy in inhibiting the growth of breast cancer cells. Clinical inverse agonists of ERRα have not been found in the literature. This review focuses on the research progress and the structure-activity relationship of ERRα inverse agonists, providing guidance for the research and discovery of new anti-tumor compounds for TNBC.

Genomic alterations affecting tumor-infiltrating lymphocytes and PD-L1 expression patterns in triple-negative breast cancer.

Tumor-infiltrating lymphocytes (TILs) and programmed cell death 1 ligand 1 (PD-L1) remain imperfect in predicting clinical outcomes of triple-negative breast cancer because outcomes do not always correlate with the expression of these biomarkers. Genomic and transcriptomic alterations that may contribute to the expression of these biomarkers remain incompletely uncovered. We evaluated PD-L1 immunohistochemistry scores (SP142 and 28-8 assays) and TILs in our triple-negative breast cancer multiomics dataset and 2 immunotherapy clinical trial cohorts. Then, we analyzed genomic and transcriptomic alterations correlated with TILs, PD-L1 expression, and patient outcomes. Despite TILs serving as a decent predictor for triple-negative breast cancer clinical outcomes, exceptions remained. Our study revealed that several genomic alterations were correlated with unexpected events. In particular, PD-L1 expression may cause a paradoxical relationship between TILs and prognosis in certain patients. Consequently, we classified triple-negative breast cancers into 4 groups based on PD-L1 and TIL levels. The TIL-negative PD-L1-positive and TIL-positive PD-L1-negative groups were not typical "hot" tumors; both were associated with worse prognoses and lower immunotherapy efficacy than TIL-positive PD-L1-positive tumors. Copy number variation of PD-L1 and oncogenic signaling activation were correlated with PD-L1 expression in the TIL-negative PD-L1-positive group, whereas GSK3B-induced degradation may cause undetectable PD-L1 expression in the TIL-positive PD-L1-negative group. These factors have the potential to affect the predictive function of both PD-L1 and TILs. Several genomic and transcriptomic alterations may cause paradoxical effects among TILs, PD-L1 expression, and prognosis in triple-negative breast cancer. Investigating and targeting these factors will advance precision immunotherapy for patients with this disease.

Prognostic value and immune landscapes of TERT promoter methylation in triple negative breast cancer.

Treatment options for patients with triple-negative breast cancer (TNBC) remain limited to mainstay therapies owing to a lack of efficacious therapeutic targets. Accordingly, there is an urgent need to discover and identify novel molecular targets for the treatment and diagnosis of this disease. In this study, we analyzed the correlation of telomerase reverse transcriptase (TERT) methylation status with TERT expression, prognosis, and immune infiltration in TNBC and identified the role of TERT methylation in the regulation TNBC prognosis and immunotherapy. Data relating to the transcriptome, clinicopathological characteristics and methylation of TNBC patients were obtained from The Cancer Genome Atlas (TCGA) database. TERT expression levels and differential methylation sites (DMSs) were detected. The correlations between TERT expression and DMSs were calculated. Kaplan-Meier curves was plotted to analyze the relationship between the survival of TNBC patients and the DMSs. The correlations of DMSs and TERT expression with several immunological characteristics of immune microenvironment (immune cell infiltration, immunomodulators, immune-related biological pathways, and immune checkpoints) were assessed. The results were validated using 40 TNBC patients from Sun Yat-sen University Cancer Center (SYSUCC). Six DMSs were identified. Among them, four sites (cg11625005, cg07380026, cg17166338, and cg26006951) were within the TERT promoter, in which two sites (cg07380026 and cg26006951) were significantly related to the prognosis of patients with TNBC. Further validation using 40 TNBC samples from SYSUCC showed that the high methylation of the cg26006951 CpG site was associated with poor survival prognosis (P=0.0022). TERT expression was significantly correlated with pathological N stage and clinical stage, and cg07380026 were significantly associated with pathological T and N stages in the TCGA cohort. Moreover, the methylation site cg26006951, cg07380026 and TERT expression were significantly correlated with immune cell infiltration, common immunomodulators, and the level of the immune checkpoint receptor lymphocyte activation gene 3 (LAG-3) in TNBC patients. TERT promotertypermethylation plays an important role in TERT expression regulation and tumor microenvironment in TNBC. It is associated with overall survival and LAG-3 expression. TERT promoter hypermethylation may be a potential molecular biomarker for predicting response to the TERT inhibitors and immune checkpoint inhibitors in TNBC.

An EMT-Related Gene Signature to Predict the Prognosis of Triple-Negative Breast Cancer.

Epithelial-mesenchymal transition (EMT) is an important biological process in tumor invasion and metastasis, and thus a potential indicator of the progression and drug resistance of breast cancer. This study comprehensively analyzed EMT-related genes in triple-negative breast cancer (TNBC) to develop an EMT-related prognostic gene signature. With the application of The Cancer Genome Atlas (TCGA) database, Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), and the Genotype-Tissue Expression (GTEx) database, we identified EMT-related signature genes (EMGs) by Cox univariate regression and LASSO regression analysis. Risk scores were calculated and used to divide patients with TNBC into high-risk group and low-risk groups by the median value. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were applied for model validation. Independent prognostic predictors were used to develop nomograms. Then, we assessed the risk model in terms of the immune microenvironment, genetic alteration and DNA methylation effects on prognosis, the probability of response to immunotherapy and chemotherapy, and small molecule drugs predicted by The Connectivity Map (Cmap) database. Thirteen EMT-related genes with independent prognostic value were identified and used to stratify the patients with TNBC into high- and low-risk groups. The survival analysis revealed that patients in the high-risk group had significantly poorer overall survival than patients in the low-risk group. Populations of immune cells, including CD4 memory resting Tcells, CD4 memory activated Tcells, and activated dendritic cells, significantly differed between the high- and low-risk groups. Moreover, some therapeutic drugs to which the high-risk group might show sensitivity were identified. Our research identified the significant impact of EMGs on prognosis in TNBC, providing new strategies for personalizing TNBC treatment and improving clinical outcomes.

Treatment Problems In Triple Negative Breast Cancer

Background: Breast cancer ranks second on the list of common diseases worldwide. It causes many deaths in the United States and Europe, second only to lung cancer. Triple-negative breast cancer (TNBC) does not express Estrogen Receptor (ER), Progesterone Receptor (PR), and Human Epithelial Receptor (HER2). It represents 24% of new cases of all breast cancer, and its incidence increases yearly. TNBC is a hormone-resistant breast cancer, so no current standard therapy exists. This article aims to explore regimen-resistant and troubleshooting treatment responses in TNBC cases. The method of writing this article is a literature review of studies using the keywords triple-negative breast cancer treatment and regimen, which are limited to only the most recent articles, 2012-2022, using search engines from PubMed, Science Direct, and Google Scholar. Results: There is no definitive therapy for the triple-negative breast cancer subtype, in which the TNBC type has no target receptor. Chemotherapy is the SOC of TNBC for early stage treatment. For late-stage and relapsed TNBC, however, chemotherapy is no longer the first choice. Currently there is no standard chemotherapy regimen that can be given to patients who experience relapse after chemotherapy because they will have a short response and lead to metastases. Some studies have shown that chemotherapy gives a better response, but the prognosis of TNBC remains poor. TNBC has different responses to therapy. TNBC showed a good response to combination chemotherapy along with pembrolizumab, capecitabine, olaparib, and radiotherapy, compared to chemotherapy by itself. Surgical therapy, such as Breast-Conserving Surgery (BCS), does not improve better prognosis in TNBC patients. Conclusions: Combining pembrolizumab, olaparib, capecitabine, and radiotherapy with chemotherapy increased survival rates compared to chemotherapy only.

FSIP1 enhances the therapeutic sensitivity to CDK4/6 inhibitors in triple-negative breast cancer patients by activating the Nanog pathway.

CDK4/6 inhibitors are routinely recommended agents for the treatment of advanced HR+HER2- breast cancer. However, their therapeutic effectiveness in triple-negative breast cancer (TNBC) remains controversial. Here, we observed that the expression level of fibrous sheath interacting protein 1 (FSIP1) could predict the treatment response of TNBC to CDK4/6 inhibitors. High FSIP1 expression level was related to a poor prognosis in TNBC, which was associated with the ability of FSIP1 to promote tumor cell proliferation. FSIP1 downregulation led to slowed tumor growth and reduced lung metastasis in TNBC. FSIP1 knockout caused cell cycle arrest at the G0/G1 phase and reduced treatment sensitivity to CDK4/6 inhibitors by inactivating the Nanog/CCND1/CDK4/6 pathway. FSIP1 could form a complex with Nanog, protecting it from ubiquitination and degradation, which may facilitate the rapid cell cycle transition from G0/G1 to S phase and exhibit enhanced sensitivity to CDK4/6 inhibitors. Our findings suggest that TNBC patients with high FSIP1 expression levels may be suitable candidates for CDK4/6 inhibitor treatment.

Oxidative stress genes define two subtypes of triple-negative breast cancer with prognostic and therapeutic implications.

Introduction: Oxidative stress (OS)-related genes have been confirmed to be closely related to the prognosis of triple-negative breast cancer (TNBC) patients; despite this fact, there is still a lack of TNBC subtype strategies based on this gene guidance. Here, we aimed to explore OS-related subtypes and their prognostic value in TNBC. Methods: Data from The Cancer Genome Atlas (TCGA)-TNBC and Sequence Read Archive (SRA) (SRR8518252) databases were collected, removing batch effects using a combat method before analysis. Consensus clustering analysis identified two OS subtypes (clusters A and B), with cluster A showing a better prognosis. Immune infiltration characteristics were analyzed using ESTIMATE and single-sample gene set enrichment analysis (ssGSEA) algorithms, revealing higher ImmuneScore and ESTIMATEscore in cluster A. Tumor-suppressive immune cells, human leukocyte antigen (HLA) genes, and three immune inhibitors were more prevalent in cluster A. Results: An eight-gene signature, derived from differentially expressed genes, was developed and validated as an independent risk factor for TNBC. A nomogram combining the risk score and clinical variables accurately predicted patient outcomes. Finally, we also validated the classification effect of subtypes using hub markers of each subtype in the test dataset. Conclusion: Our study reveals distinct molecular clusters based on OS-related genes to better clarify the reactive oxygen species (ROS)-mediated progression and the crosstalk between the ROS and tumor microenvironment (TME) in this heterogenetic disease, and construct a risk prognostic model which could provide more support for clinical treatment decisions.

Natural killer cell-related prognostic risk model predicts prognosis and treatment outcomes in triple-negative breast cancer.

Natural killer (NK) cells are crucial to the emergence, identification, and prognosis of cancers. The roles of NK cell-related genes in the tumor immune microenvironment (TIME) and immunotherapy treatment are unclear. Triple-negative breast cancer (TNBC) is a highly aggressive malignant tumor. Hence, this study was conducted to develop a reliable risk model related to NK cells and provide a novel system for predicting the prognosis of TNBC. NK cell-related genes were collected from previous studies. Based on TCGA and GEO database, univariate and LASSO cox regression analysis were used to establish the NK cell-related gene signature. The patients with TNBC were separated to high-risk and low-risk groups. After that, survival analysis was conducted and the responses to immunotherapies were evaluated on the basis of the signature. Moreover, the drug sensitivity of some traditional chemotherapeutic drugs was assessed by using the "oncoPredict" R package. In addition, the expression levels of the genes involved in the signature were validated by using qRT-PCR in TNBC cell lines. The patients with TNBC were divided into high- and low-risk groups according to the median risk score of the 5-NK cell-related gene signature. The low-risk group was associated with a better clinical outcome. Besides, the differentially expressed genes between the different risk groups were enriched in the biological activities associated with immunity. The tumor immune cells were found to be highly infiltrated in the low-risk groups. In accordance with the TIDE score and immune checkpoint-related gene expression analysis, TNBC patients in the low-risk groups were suggested to have better responses to immunotherapies. Eventually, some classical anti-tumor drugs were shown to be less effective in high-risk groups than in low-risk groups. The 5-NK cell-related gene signature exhibit outstanding predictive performance and provide fresh viewpoints for evaluating the success of immunotherapy. It will provide new insights to achieve precision and integrated treatment for TNBC in the future.

Spatial immunophenotypes orchestrate prognosis in triple-negative breast cancer with Miller-Payne grade 4 following neoadjuvant chemotherapy

Some triple-negative breast cancer (TNBC) patients evaluated as Miller-Payne 4 with ypN0 after neoadjuvant chemotherapy (NACT) who have better prognoses should avoid escalation of therapy. We aim to identify these patients by evaluating pretherapeutic spatial distributions of immunophenotypes. Our retrospective study in patients with TNBC assessed as Miller-Payne grade 4/5 with ypN0 showed that Miller-Payne 4 with ypN0 group had poorer 5-year disease-free survival (DFS, 63.8% vs. 83.0%, p = 0.003) and the 5-year overall survival (OS, 71.0% vs. 85.5%, p = 0.007) than Miller-Payne 5 with ypN0 group. High TILs were significantly associated with better DFS and OS in patients with Miller-Payne 4 and ypN0 (both p = 0.016). Spatially, detected by multiplexed ion beam imaging by the time of flight combined with proteomics, tumors assessed as Miller-Payne 4 and ypN0 with good prognosis exhibited an inflamed phenotype, with dominant CD8+ T cells on tumor center, few scattered CD68+ myeloid-derived cells far away from T cells, and deposit of increased activated molecules of lymphocyte. While those with poor prognoses presented excluded phenotypes, with few CD8+ T cells restricted to invasive margins and a high density of CD14+CD68+CD11c+ myeloid cells. A good classifier model based on 29 spatial immunophenotypes was established by the random forest algorithm (AUC = 0.975), for identifying patients with Miller-Payne 4 and ypN0 who had favorable prognoses. We also observed similar signatures in patients with Miller-Payne 5 and ypN0. Taken together, spatial immunophenotypes may assess the prognosis in TNBC patients with Miller-Payne 4 and ypN0 after NACT.

Identification of Genes Associated with Prognosis and Immunotherapy Prediction in Triple-Negative Breast Cancer via M1/M2 Macrophage Ratio.

Background and Objectives: Triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous subtype of breast cancer, accounts for ap-proximately 10-15% of all breast cancer cases. Currently, there is no effective therapeutic target for TNBC. Tu-mor-associated macrophages (TAMs), which can be phenotypically classified into M1 and M2 subtypes, have been shown to influence the prognosis of various cancers, including ovarian cancer. This study aimed to investigate the role of M1/M2 macrophages in the TNBC tumor microenvironment (TME), with a focus on identifying prognostic genes and predicting immunotherapy response. Materials and Methods: The study employed the CIBERSORT algorithm to analyze immune cell expression in the TME. Genes associated with the M1/M2 macrophage ratio were identified using Pearson correlation analysis and used to classify patients into dis-tinct clusters. Dimensionality reduction techniques, including univariate Cox regression and Lasso, were applied to these genes. The expression of prognostic genes was validated through immunohistochemistry. Results: The study found a high prevalence of TAMs in the TME. Among the patient clusters, 109 differentially expressed genes (DEGs) were identified. Three significant DEGs (LAMP3, GZMB, and CXCL13) were used to construct the riskScores. The riskScore model effectively stratified patients based on mortality risk. Gene Set Enrichment Analysis (GSEA) associated the riskScore with several significant pathways, including mismatch repair, JAK/STAT3 signaling, VEGF signaling, antigen processing presentation, ERBB signaling, and P53 signaling. The study also predicted patient sensitivity to im-munotherapy using the riskScores. The expression of the three significant DEGs was validated through immunohisto-chemistry. Conclusions: The study concluded that the riskScore model, based on the M1/M2 macrophage ratio, is a valid prognostic tool for TNBC. The findings underscore the importance of the TME in TNBC progression and prognosis and highlight the po-tential of the riskScore model in predicting immunotherapy response in TNBC patients.

Tissue Inhibitor of Metalloproteinases-1 Overexpression Mediates Chemoresistance in Triple-Negative Breast Cancer Cells.

Triple-negative breast cancer (TNBC) is among the most aggressive breast cancer subtypes. Despite being initially responsive to chemotherapy, patients develop drug-resistant and metastatic tumors. Tissue inhibitor of metalloproteinases-1 (TIMP-1) is a secreted protein with a tumor suppressor function due to its anti-proteolytic activity. Nevertheless, evidence indicates that TIMP-1 binds to the CD63 receptor and activates noncanonical oncogenic signaling in several cancers, but its role in mediating TNBC chemoresistance is still largely unexplored. Here, we show that mesenchymal-like TNBC cells express TIMP-1, whose levels are further increased in cells generated to be resistant to cisplatin (Cis-Pt-R) and doxorubicin (Dox-R). Moreover, public dataset analyses indicate that high TIMP-1 levels are associated with a worse prognosis in TNBC subjected to chemotherapy. Knock-down of TIMP-1 in both Cis-Pt-R and Dox-R cells reverses their resistance by inhibiting AKT activation. Consistently, TNBC cells exposed to recombinant TIMP-1 or TIMP-1-enriched media from chemoresistant cells, acquire resistance to both cisplatin and doxorubicin. Importantly, released TIMP-1 reassociates with plasma membrane by binding to CD63 and, in the absence of CD63 expression, TIMP-1-mediated chemoresistance is blocked. Thus, our results identify TIMP-1 as a new biomarker of TNBC chemoresistance and lay the groundwork for evaluating whether blockade of TIMP-1 signal is a viable treatment strategy.

Construction of a prognostic model for triple-negative breast cancer based on immune-related genes, and associations between the tumor immune microenvironment and immunological therapy.

Triple-negative breast cancer (TNBC) is the subtype of breast cancer with the worst prognosis, and it is highly heterogeneous. There is growing evidence that the tumor immune microenvironment (TIME) plays a crucial role in tumor development, maintenance, and treatment responses. Notably however, the full effects of the TIME on prognosis, TIME characteristics, and immunotherapy responses in TNBC patients have not been fully elucidated. Gene Expression Omnibus and The Cancer Genome Atlas data were used to data analysis. Single-cell sequencing and tissue microarray analysis were used to investigate gene expression. The concentrations and distributions of immune cell types were determined and analyzed using the CIBERSORT strategy. Tumor immune dysfunction and exclusion score and the IMvigor210 cohort were used to estimate the sensitivity of TNBC patients with different prognostic statuses to immune checkpoint treatment. Five immune-related genes associated with TNBC prognosis (IL6ST, NR2F1, CKLF, TCF7L2, and HSPA2) was identified and a prognostic evaluation model was constructed based on those genes. The respective areas under the curve of the prognostic nomogram model at 3 and 5 years were 0.791 and 0.859. The group with a lower nomogram score, with a better prognosis survival status and clinical treatment benefit rate. A prognostic model for TNBC that was closely related to the immune landscape and therapeutic responses was constructed. This model may help clinicians to make more precise and personalized treatment decisions pertaining to TNBC patients.

CircEGFR reduces the sensitivity of pirarubicin and regulates the malignant progression of triple-negative breast cancer via the miR-1299/EGFR axis

Circular RNAs (circRNAs) have been found to be involved in cancer progression and chemotherapy sensitivity. However, the biological function of circRNAs in triple-negative breast cancer (TNBC) and its effect on the sensitivity to pirarubicin (THP) chemotherapy are still unclear. CircEGFR (hsa_circ_0080220) was screened and verified by bioinformatics analysis, proving it was highly expressed in TNBC cell lines, patient tissues, and plasma exosomes, and was associated with poor prognosis of patients. The expression level of circEGFR in patient tissue has potential diagnostic value to distinguish TNBC tissue from normal breast tissue. In vitro studies confirmed that overexpression of circEGFR promoted the proliferation, migration, invasion, and EMT of TNBC cells and decreased the sensitivity of THP treatment while silencing circEGFR showed the opposite effect. The circEGFR/miR-1299/EGFR pathway was cascaded and verified. CircEGFR regulated malignant progression of TNBC by regulating EGFR via sponging miR-1299. THP can inhibit the malignant phenotype of MDA-MB-231 cells by downregulating the expression of circEGFR. In vivo studies confirmed that overexpression of circEGFR can promote tumor growth and EMT and reduce tumor sensitivity to THP treatment. Silencing circEGFR inhibited the malignant progression of the tumor. These results revealed circEGFR is a promising biomarker for TNBC diagnosis, therapeutic and prognosis.