不同分子型態乳癌的腫瘤浸潤淋巴細胞反應以及不同種族流行病學研究

Abstract

惡性腫瘤自民國71年起即位列十大死因的第1名，乳癌則是從民國92年起首度超越子宮頸癌拿下國人女性惡性腫瘤發生率的第1名，中華民國107年癌症登記報告指出乳癌為女性癌症發生率的第1名，死亡率則是第2名，顯見乳癌對國人婦女所造成的威脅，近年來隨著分子生物科技的發展，乳癌已被視為是一種異質性的疾病，不同亞型的乳癌有不同的癌症治療計畫，如何讓罹癌婦女依據自身的健康情形，打造獨一無二的治療計畫，則仰賴於對乳癌亞型更深入的認識。 本研究旨在探討種族對不同乳癌亞型間腫瘤浸潤淋巴細胞的影響暨乳癌亞型、種族、年齡、腫瘤浸潤淋巴細胞對乳癌復發與死亡的影響，分別使用了ESTIMATE和CIBERSORT方法，前者得到了免疫分數用來推估免疫細胞的浸潤程度，免疫分數愈高代表免疫浸潤淋巴細胞愈多，後者獲得了22種免疫細胞的相對比例。資料來自基因表達資料庫(Gene Expression Omnibus ,GEO)獲得原發性乳癌的基因表達微陣列，一共分析7個資料集的資料，分別是西方資料集4個(GSE58644、GSE6532、GSE21653、GSE25066)和東方資料集3個(GSE20685、GSE131769、GSE102484)。 在這項研究發現東方乳癌患者相較於西方乳癌患者更為年輕(p值< 2.2E-16)、免疫分數較高(p值=4.36E-02)、具有較長的復發時間(p值=1.50E-02)。東西方乳癌的免疫分數除了受到乳癌亞型的影響外，年齡也會產生交互作用，在≦50歲的Luminal A亞型可看到西方乳癌的免疫分數高於東方乳癌(p值=2.40E-02)，這可能是年輕的乳癌在種族上受到環境因素的影響，才導致此一相反的結果。東西方的免疫細胞組成在記憶B細胞、漿細胞、CD8 T細胞、濾泡輔助T細胞、Treg細胞、活化的自然殺手細胞、單核球、M1巨噬細胞、M2巨噬細胞、休眠樹突細胞和嗜中性白血球之間有顯著差異(q值介於：4.72E-15~6.41E-136)。休眠記憶CD4 T細胞量(HR=0.77 ,95% CI:0.63~0.94)和休眠肥大細胞(HR=0.73 ,95% CI:0.59~0.90)在乳癌病人浸潤愈多愈不容易復發，活化肥大細胞在乳癌病人浸潤愈多愈容易復發(HR=1.37 ,95% CI:1.13~1.66)，Gamma delta T細胞浸潤愈多愈不容易死亡(HR=0.51 ,95% CI: 0.33~0.78)。 在乳癌的治療上若能考慮各乳癌亞型、種族、年齡、免疫細胞組成的不同，找出真正可以從治療中受益的病人，減少過度治療或療效不足的問題，減少藥物的副作用，給予病人更準確有效的治療策略，以達個人化醫療的目標，相信可以減少醫療浪費並把握黃金治療時間。

Malignant tumor is the leading cause of death in Taiwan for 39 years. Breast cancer have become the most common cancer among women, and have exceeded cervical cancer in Taiwan since 2003. Furthermore, the mortality of breast cancer ranks second in cancer among women. Breast cancer is regarded as a heterogeneous disease because of development of molecular biotechnology in recent years. Breast cancer with different subtypes has different responses to systemic and local therapies. Therefore, unique treatments can be designed for individual based on expanding our understanding of disease. This study aimed to assess the TILs influence on breast cancer with different molecular subtypes. Additionally, we expected to explore the prognosis or recurrence contribution of breast cancer subtype, race, age and tumor-infiltrating lymphocytes among patients with breast cancer.This study analysis was applied to gene expression microarray data from primary breast tumors , which were obtained from the Gene Expression Omnibus (GEO), including four data sets from cohorts of Western patients (GSE58644, GSE6532, GSE21653, and GSE25066), and three data sets from a cohort of Asian patients (GSE20685, GSE131769, and GSE102484). ESTIMATE and CIBERSORT were used in this study. Immune score which calculated with ESTIMATE indicates the amount of tumor-infiltrating immune cells. There was a positive correlation between immune scores and tumor-infiltrating lymphocytes. The proportions of 22 immune cell subsets from tumor transcriptomes were calculated with CIBERSORT. The results showed that Eastern patients were younger (p value< 2.2e-16), higher immune score (p value=4.36E-02) and longer DFS (p value=1.50E-02) than Western patients. The immune scores of breast cancer were affected by breast cancer subtypes, age, both of Eastern and Western patients. Moreover, there is interaction between race and immune scores. Younger (≤50 years) Western patients with breast cancer had a significantly higher immune score in the Luminal A subtype (p value =2.40E-02). Environment factor is likely to be the reason. Statistical analysis was significant that memory B cells,plasma cells,CD8 T cells,follicular helper T cells,regulatory T cells, activated NK cells,monocytes,M1 macrophages,M2 macrophages,resting dendritic cells,and neutrophils had different percentage between races(q value：4.72E-15~6.41E-136). Higher resting CD4 T cell (HR=0.77 ,95% CI:0.63~0.94) and resting mast cell (HR=0.73 ,95% CI:0.59~0.90) were associated with longer DFS. Higher activated mast cell was associated with shorter DFS (HR=1.37 ,95% CI:1.13~1.66). Higher gamma delta T cell was associated with longer OS HR=0.51 ,95% CI: 0.33~0.78). Treatment strategies should be considered for subtype, race, age, the composition of tumor-infiltrating lymphocytes. Hence, it may discover patients who could have benefit from therapies, and reduce occurrence of overtreatment, insufficient efficacy, and side effects of medicine. More accurate and effective treatment strategies to achieve the goal of personalized medical treatment are believed to reduce medical waste and grasp the golden treatment time.