Evaluating the tumor immune profile based on a three-gene prognostic risk model in HER2 positive breast cancer

Abstract

To date, there have not been great breakthroughs in immunotherapy for HER2 positive breast cancer (HPBC). This study aimed to build a risk model that might contribute to predicting prognosis and discriminating the immune landscape in patients with HPBC. We analyzed the tumor immune profile of HPBC patients from the TCGA using the ESTIMATE algorithm. Thirty survival-related differentially expressed genes were selected according to the ImmuneScore and StromalScore. A prognostic risk model consisting of PTGDR, PNOC and CCL23 was established by LASSO analysis, and all patients were classified into the high- and low-risk score groups according to the risk scores. Subsequently, the risk model was proven to be efficient and reliable. Immune related pathways were the dominantly enriched category. ssGSEA showed stronger immune infiltration in the low-risk score group, including the infiltration of TILs, CD8 T cells, NK cells, DCs, and so on. Moreover, we found that the expression of immune checkpoint genes, including PD-L1, CTLA-4, TIGIT, TIM-3 and LAG-3, was significantly upregulated in the low-risk score group. All the results were validated with corresponding data from the GEO database. In summary, our investigation indicated that the risk model composed of PTGDR, PNOC and CCL23 has potential to predict prognosis and evaluate the tumor immune microenvironment in HPBC patients. More importantly, HPBC patients with a low-risk scores are likely to benefit from immune treatment.

Characterization of immune checkpoints expression and lymphocyte densities of iranian breast cancer patients; the co-expression status and clinicopathological associates

“…Likewise, by grouping breast cancer based on tumor-infiltrating immune cells, a group noticed that compared to the regulatory T-cells and M0 and M2 macrophages group, samples with higher CD8 + T-cells and memory-activated CD4 + T-cells harbor higher expressions of a wide range of immunomodulators (including LAG-3 and PD-L1), and have a significantly higher overall survival [ 43 ]. Similar findings are reported for HER2-positive tumors, as a group noted that higher expression of PD-L1, CTLA-4, TIGIT, TIM-3, and LAG-3 genes is a feature of low-risk patients [ 44 ]. Such findings have also been implicated by another study on TNBC [ 45 ].…”

Characterization of immune checkpoints expression and lymphocyte densities of Iranian breast cancer patients; the co-expression status and clinicopathological associates

“…Likewise, by grouping breast cancer based on tumor-in ltrating immune cells, a group noticed that compared to the regulatory T-cells and M0 and M2 macrophages group, samples with higher CD8 + T-cells and memory-activated CD4 + T-cells harbor higher expressions of a wide range of immunomodulators (including LAG-3 and PD-L1), and have a signi cantly higher overall survival (43). Similar ndings are reported for HER2-positive tumors, as a group noted that higher expression of PD-L1, CTLA-4, TIGIT, TIM-3, and LAG-3 genes is a feature of low-risk patients (44). Such ndings have also been implicated by another study on TNBC (45).…”

Identifying prognostic characteristics of m6A-related glycolysis gene and predicting the immune infiltration landscape in bladder cancer

“…Following this, Spearman’s correlations were performed between biomarkers and differentially immune cells, biomarkers and differentially immune functions, and risk score and differentially immune cells. The inter-group differences between the eight immune checkpoints, 24 immune checkpoint inhibitors, and 38 immune factors were calculated and compared using “wilcox.test” [ 17 , 18 ]. Furthermore, immune phenotype scores (IPS) in different risk groups were calculated, and a Spearman’s correlation was performed to determine the relationship between IPS and risk score.…”