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

Abstract

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.

Combination of Immune-Related Network and Molecular Typing Analysis Defines a Three-Gene Signature for Predicting Prognosis of Triple-Negative Breast Cancer

“…Yan et al developed a risk autophagy-related prediction model that can predict the survival status of TNBC patients [ 35 ]. Yang et al constructed a risk scoring system to predict the immune activity and potential therapeutic response of TNBC [ 36 ]. Our previous work revealed an eight immune-related panel in the immunomodulatory subtype of TNBC [ 37 ].…”

Systematic evaluation of tumor microenvironment and construction of a machine learning model to predict prognosis and immunotherapy efficacy in triple-negative breast cancer based on data mining and sequencing validation

“…The essential light spot of our studies illustrated that two perfect scoring systems based on one gene signature were constructed to predict the efficacy of Frontiers in Pharmacology frontiersin.org immunotherapy, response to chemotherapy, and prognosis of TNBC patients. Previous studies related to the TRG score in TNBC (Qin et al, 2021;Yi et al, 2021;Yang et al, 2022) generally used one method to assess immune cell infiltration levels and did not consider immune-related pathway activation conditions; our study used not only numerous methods to evaluate immune cell infiltration levels but also employed different types of pathway signatures to evaluate pathway enrichment levels. These results provide mechanistic insights into the efficacy of immunotherapy, suggesting that benefits from immunotherapy are not only related to enhanced IL-2/ STAT5, IL-6/STAT3, and interferon response pathways but are also associated with inhibition of TGF-β-, NOTCH-, PI3K/ AKT-, and EMT-related pathways.…”

Perspectives for 3D-Bioprinting in Modeling of Tumor Immune Evasion

“…Therefore, immune evasion was added to the list of hallmarks of cancer in 2010 [5]. Although some of the mechanisms of immune evasion can be related to direct interactions between malignant cells and the immune effectors, there are numerous instances when TME serves for cancer as a protector against the immune system and/or immunotherapies [6][7][8].…”