RESUMEN
Immune response which involves distinct immune cells is associated with prognosis of breast cancer. Nonetheless, less study have determined the associations of different types of immune cells with patient survival and treatment response. In this study, A total of 1,502 estrogen receptor(ER)-negative breast cancers from public databases were used to infer the proportions of 22 subsets of immune cells. Another 320 ER-negative breast cancer patients from Guangdong Provincial People's Hospital were also included and divided into the testing and validation cohorts. CD8+ T cells, CD4+ T cells, B cells, and M1 macrophages were associated with favourable outcome (all p <0.01), whereas Treg cells were strongly associated with poor outcome (p = 0.005). Using the LASSO model, we classified patients into the stromal immunotype A and B subgroups according to immunoscores. The 10 years OS and DFS rates were significantly higher in the immunotype A subgroup than immunotype B subgroup. Stromal immunotype was identified as an independent prognostic indicator in multivariate analysis in all cohorts and was also related to pathological complete response(pCR) after neoadjuvant chemotherapy. The nomogram that integrated the immunotype and clinicopathologic features showed good predictive accuracy for pCR and discriminatory power. The stromal immunotype A subgroup had higher expression levels of immune checkpoint molecules (PD-L1, PD-1, and CTLA-4) and cytokines (IL-2, INF-γ, and TGF-ß). In addition, patients with immunotype A and B diseases had distinct mutation signatures. Therefore, The stromal immunotypes could predict survival and responses of ER-negative breast cancer patients to neoadjuvant chemotherapy.
RESUMEN
The overall risk of developing a second primary cancer is increasing. The purpose of this study was to analyze the survival of patients with breast cancer diagnosed after a prior cancer and identify risk factors of breast cancer death in this population. Using the SEER database, we identified 1,310 woman diagnosed with breast cancer between 2010 and 2015 after a prior cancer as the primary cohort. Clinicopathological characteristics were compared using the Student t-test and chi-square test. Fine and Gray's regression was used to evaluate the effect of treatments on breast cancer death. After propensity score matching (PSM), 9,845 pairs of patients with breast cancer as the prior or second cancer diagnosed between 2010 and 2011 were included as a second cohort. PSM-adjusted Kaplan-Meier and Cox hazards models were used to evaluate the impact of prior cancer on survival. The results showed that survivors of gynecologic cancers (e.g., ovarian cancer) had a higher risk of developing breast cancer than survivors of gastrointestinal and urinary tract cancers. More patients died of breast cancer than of prior urinary cancer (53.3% vs. 40%, P < 0.05) and melanoma (66.7% vs. 33.3%, P < 0.05). The ratio of breast cancer deaths to prior cancer deaths was significantly higher in patients with diagnoses interval ≥ 3 years than in those with the interval < 3 years (2.67 vs. 0.69, P < 0.001). Breast cancer-specific survival and overall survival rates were significantly lower in women with breast cancer as the second primary cancer than in those with breast cancer as the prior cancer, especially among hormone receptor-positive women. However, breast cancer treatment decreased the risk of breast cancer -specific death (hazard ratio = 0.695, 95% confidence interval: 0.586-0.725, P < 0.001). Breast cancer patients with prior cancers must be carefully considered for clinical trials.
