A risk scoring system based on tumor microenvironment cells to predict prognosis and immune activity in triple-negative breast cancer.

The tumor microenvironment (TME) interacting with the malignant cells plays a vital role in cancer development. Herein, we aim to establish and verify a scoring system based on the characteristics of TME cells for prognosis prediction and personalized treatment guidance in patients with triple-negative breast cancer (TNBC). 158 TNBC samples from The Cancer Genome Atlas (TCGA) were included as the training cohort, and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (N = 297), as well as GSE58812 (N = 107), were included as the validation cohort. The enrichment scores of 64 immune and stromal cells were estimated by the xCell algorithm. In the training cohort, cells with prognostic significance were found out using univariate Cox regression analysis and further applied to the random survival forest (RSF) model. Based on the scores of M2 macrophages, CD8+ T cells, and CD4+ memory T cells, a risk scoring system was constructed, which divided TNBC patients into 4 phenotypes (M2low, M2highCD8+ThighCD4+Thigh, M2highCD8+ThighCD4+Tlow, and M2highCD8+Tlow). Furthermore, types 1 and 2 patients were merged into the low-risk group, while types 3 and 4 patients were in the high-risk group. The low-risk group had superior survival outcomes than the high-risk one, which was further confirmed in the validation cohort. Moreover, in the low-risk group, immune-related pathways were significantly enriched, and a higher level of antitumoral immune cells and immune checkpoint molecules, including PD-L1, PD-1, and CTLA-4, could be observed. Additionally, consistent results were achieved in the SYSUCC cohort when the scoring system was applied. In summary, this novel scoring system might predict the survival and immune activity of patients and might serve as a potential index for immunotherapy.

Yang A ，Wu M ，Ni M ，Zhang L ，Li M ，Wei P ，Yang Y ，Xiao W ，An X ... -  《-》

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

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

A combined hypoxia and immune gene signature for predicting survival and risk stratification in triple-negative breast cancer.

Yang X ，Weng X ，Yang Y ，Zhang M ，Xiu Y ，Peng W ，Liao X ，Xu M ，Sun Y ，Liu X ... -  《Aging-US》

Development and validation of a stromal immune phenotype classifier for predicting immune activity and prognosis in triple-negative breast cancer.

Our study aims to construct a prognosis-related immune phenotype classifier for predicting clinical prognosis and immune activity in triple-negative breast cancer (TNBC). A total of 237 patients with TNBC from Sun Yat-sen University Cancer Center (SYSUCC) and 533 patients with TNBC from public datasets were included in our study. A stromal immune quantified index was generated with a LASSO Cox regression model based on five prognosis-related immune cells evaluated by CIBERSORT or IHC and was used to determine immune phenotypes. Immune features were evaluated in the samples before chemotherapy. A total of 119 patients in the SYSUCC training cohort were classified into immune Phenotypes A and B according to the density of stromal CD4+ T cells, γδ T cells, monocytes, M1 macrophages and M2 macrophages. Phenotype A predicted better survival than Phenotype B, and the classification was further validated in the testing cohort of 118 patients and the validation cohort of 533 patients. In the combined cohort, significant differences were found in Phenotype A compared to Phenotype B for the 5-year overall survival (83.5% vs 65.8%, respectively, P < .01) and the 5-year disease-free survival (87.3% vs 76.0%, respectively, P < .01). In Phenotype A, immune-related pathways were significantly enriched, and a higher level of immune checkpoint molecules, including PD-L1, PD-1 and CTLA-4, could be observed. The immune phenotype classification was an independent prognostic indicator for TNBC and might serve as a potential predictor for immune activity within the tumor microenvironment.

Zheng S ，Zou Y ，Xie X ，Liang JY ，Yang A ，Yu K ，Wang J ，Tang H ，Xie X ... -  《-》

Identification and validation of a combined hypoxia and immune index for triple-negative breast cancer.

The interaction between hypoxia and immune status has been confirmed in various cancer settings, and corresponding treatments have been investigated. However, reliable biomarkers are needed for individual treatment, so we sought to develop a novel scoring system based on hypoxia and immune status. Prognostic hypoxia-immune status-related signatures of patients with triple-negative breast cancer (TNBC) were identified in The Cancer Genome Atlas (TCGA) (N = 158), Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (N = 297), and GSE58812 (N = 107). LASSO Cox regression was used for model construction. Hypoxia and immune status expression profiles were analyzed, and infiltrating immune cells were compared. Quantitative real-time PCR (qRT-PCR) was used for validation in the Sun Yat-sen University Cancer Center (SYSUCC) cohort, and immunofluorescence was applied for the detection of hypoxia and immune markers in cancer tissues. Ten cross-cohort prognostic hypoxia-immune signatures were included to construct the comprehensive index of hypoxia and immune (CIHI) in the METABRIC cohort. Two subgroups of patients with distinct hypoxia-immune status conditions were identified using CIHI: hypoxiahigh /immunelow and hypoxialow /immunehigh , with a significantly better overall survival (OS) rate in the latter (P < 0.01). The prognostic value of CIHI was further validated in the TCGA, GSE58812, and SYSUCC cohorts (P < 0.01). Hypoxia-immune signatures were significantly differentially expressed between the two groups, and more active immune responses were observed in the hypoxialow /immunehigh group. Cytotoxic lymphocytes were inversely correlated with CIHI in silico. Differentially expressed CA-IX and stromal PD-L1 were detected between subgroups of the SYSUCC cohort. A hypoxia-immune-based cross-cohort classifier for predicting prognosis was developed and validated, which may guide hypoxia modifier treatment and immunotherapy for TNBC.

Zheng S ，Zou Y ，Liang JY ，Xiao W ，Yang A ，Meng T ，Lu S ，Luo Z ，Xie X ... -  《-》