Development and verification of a novel immunogenic cell death-related signature for predicting the prognosis and immune infiltration in triple-negative breast cancer.

Insufficient understanding of the pathogenesis and tumor immunology of triple-negative breast cancer (TNBC) has limited the development of immunotherapy. The importance of tumor microenvironment (TME) in immunotyping, prognostic assessment and immunotherapy efficacy of cancer has been emphasized, however, potential immunogenic cell death (ICD) related genes function in TME of TNBC has been rarely investigated. To initially explore the role and related mechanisms of ICD in TNBC, especially the role played in the TME of TNBC, and to identify different relevant subtypes based on ICD, and then develop an ICD-related risk score to predict each TNBC patient TME status, prognosis and immunotherapy response. In this study, we identified distinct ICD-related modification patterns based on 158 TNBC cases in the TCGA-TNBC cohort. We then investigated the possible correlation between ICD-related modification patterns and TME cell infiltration characteristics in TNBC. By using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analysis, we created a risk scoring system (ICD score) to quantifiably evaluate the impact of ICD-related modification patterns in individual TNBC patient. Two different ICD-related modification patterns were found with significant differences in immune infiltration. Lower ICD score was correlated with higher immune infiltration, tumor mutational burden and significantly enriched in immune-related pathways, indicating a strong ability to activate immune response, which might account for relatively favorable prognosis of TNBC patients and could serve as a predictor to select suitable candidates for immunotherapy. We used two independent cohorts, GSE58812 cohort and Metabric cohort to validate prognosis and immunohistochemistry for preliminary in vitro validation. This study evidenced that the ICD-related modification patterns might exert pivotal roles in the immune infiltration landscape of TNBC and ICD score might act as potential predictors of prognostic assessment and immunotherapy response. This research provides unique insights for individualize immune treatment strategies and promising immunotherapy candidates screening.

Li J ，Li Z ，Yang W ，Pan J ，You H ，Yang L ，Zhang X ... -  《Cancer Reports》

A novel fatty-acid metabolism-based classification for triple negative breast cancer.

Yang X ，Tang W ，He Y ，An H ，Wang J ... -  《Aging-US》

Identification of m6A modification patterns and development of m6A-hypoxia prognostic signature to characterize tumor microenvironment in triple-negative breast cancer.

N6-methylation (m6A) modification of RNA has been found to have essential effects on aspects of the tumor microenvironment (TME) including hypoxia status and mobilization of immune cells. However, there are no studies to explore the combined effect of m6A modification and hypoxia on molecular heterogeneity and TME of triple-negative breast cancer (TNBC). We collected The Cancer Genome Atlas (TCGA-TNBC, N=139), the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC-TNBC, N=297), the GSE103091, GSE21653, and GSE135565 series from the Gene Expression Omnibus (GEO-TNBC, N=247), and FUSCCTNBC (N=245) for our study. The non-negative matrix factorization algorithm was used to cluster TNBC samples. Immune cell infiltration was analyzed by the CIBERSORT algorithm. The enrichment scores were calculated by single-sample gene set enrichment analysis(ssGSEA) to characterize TME in TNBC samples. Immunohistochemistry (IHC) and qRT-PCR were performed to detect the gene expression. Based on the expression of m6A-related genes, we identified three distinct m6A clusters (denoted A, B, and C) in TNBC samples. Comparing the TME characteristics among the three clusters, we observed that cluster C was strongly related to hypoxia status and immune suppression, whereas clusters A and B displayed more immune cell infiltration. Therefore, we combine m6A and hypoxia related genes to classify two m6A-hypoxia clusters of TNBC and screened six prognostic genes by LASSO-Cox regression to construct a m6A-hypoxia signature(MHPS), which divided TNBC samples into high- and low-risk groups. We identified different TME features, immune cell infiltration between the two groups, and a better immunotherapy response was observed in the low-risk group. A nomogram was constructed with tumor size, lymph node, and risk score to improve clinical application of MHPS. We identified distinct TME characteristics of TNBC based on three different m6A modification patterns. Then, we constructed a specific m6A-hypoxia signature for TNBC to evaluate risk and predict immunotherapy response of patients, to enable more accurate treatment in the future.

Shen X ，Zhong J ，He J ，Han J ，Chen N ... -  《Frontiers in Immunology》

A novel model associated with tumor microenvironment on predicting prognosis and immunotherapy in triple negative breast cancer.

Triple negative breast cancer (TNBC) is the most aggressive and malignant subtype in breast cancer. Immunotherapy is a currently promising and effective treatment for TNBC, while not all patients are responsive. Therefore, it is necessary to explore novel biomarkers to screen sensitive populations for immunotherapy. All mRNA expression profiles of TNBC from The Cancer Genome Atlas (TCGA) database were clustered into two subgroups by analyzing tumor immune microenvironment (TIME) with single sample gene set enrichment analysis (ssGSEA). A risk score model was constructed based on differently expressed genes (DEGs) identified from two subgroups using Cox and Least Absolute Shrinkage and Selector Operation (LASSO) regression model. And it was validated by Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) analysis in Gene Expression Omnibus (GEO) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Multiplex immunofluorescence (mIF) and Immunohistochemical (IHC) staining were performed on clinical TNBC tissue samples. The relationship between risk score and immune checkpoint blockades (ICB) related signatures was further investigated, as well as the biological processes were performed by gene set enrichment analysis (GSEA). We obtained three DEGs positively related to prognosis and infiltrating immune cells in TNBC. Our risk score model could be an independent prognostic factor and the low risk group exhibited a prolonged overall survival (OS). Patients in low risk group were more likely to present a higher immune infiltration and stronger response to immunotherapy. GSEA revealed the model was associated with immune-related pathways. We constructed and validated a novel model based on three prognostic genes related to TIME in TNBC. The model contributed a robust signature that could predict the prognosis in TNBC, especially for the efficacy of immunotherapy.

Zhang J ，Zhang M ，Tian Q ，Yang J ... -  《-》

The molecular subtypes of triple negative breast cancer were defined and a ligand-receptor pair score model was constructed by comprehensive analysis of ligand-receptor pairs.

Intercellular communication mediated by ligand-receptor interactions in tumor microenvironment (TME) has a profound impact on tumor progression. This study aimed to explore the molecular subtypes mediated by ligand-receptor (LR) pairs in triple negative breast cancer (TNBC), identify the most important LR pairs to construct a prognostic risk model, and study their effect on TNBC immunotherapy. LR pairs subclasses of TNBC were categorized by consensus clustering based on LR Pairs in METABRIC dataset. Least absolute shrinkage and selection operator (LASSO) Cox regression and stepwise Akaike information criterion (stepAIC) were conducted to build a LR pairs score model. The relationship between LR pairs score and immune cell infiltration, stromal score and immune score associated with TME was analyzed, and the prediction of drug therapy and immunotherapy efficacy by LR pairs score was evaluated. According to the expression pattern of 145 TNBC prognostic LR pairs, the samples were divided into three subclasses with different survival outcomes, copy number variation (CNV), TME immune cell infiltration, stromal score and immune score. The LR pairs score model constructed in the METABRIC dataset was composed of four LR pairs, and its predictive significance for TNBC prognosis was verified in GSE58812 and GSE21653 cohorts. In addition, LR pairs score was negatively correlated with several immune pathways regulating immunity and immune score, and related to the sensitivity of anti-neoplastic drugs and the effect of anti-PD-L1 therapy. Our study confirmed the impact of LR pairs on the molecular heterogeneity of TNBC, characterized three LR pairs subtypes with different survival outcomes and TME patterns, and proposed a LR pairs score system with predictive significance for TNBC prognosis and anti-PD-L1 therapeutic effect, which provides a potential evaluation scheme for TNBC management.

Pan W ，Song K ，Zhang Y ，Yang C ，Zhang Y ，Ji F ，Zhang J ，Shi J ，Wang K ... -  《Frontiers in Immunology》