探討晚期卵巢癌病人周邊血內免疫細胞亞群之臨床意義與角色

Abstract

目的: 卵巢癌在所有婦科惡性腫瘤中佔據最重要的地位，同時也是造成死亡的主要原因。卵巢癌的主要(標準)治療包括了減積手術及化療。由於早期無特異性症狀，因此診斷困難、腫瘤標記的準確度不夠與缺乏卵巢癌全面的腫瘤生物學資訊均導致了預後不良的情形。研究顯示宿主的免疫機制對癌症的進展以及預後有很重要的影響，並且近年對於表達免疫檢查點之免疫細胞的相關研究越來越多且深入。免疫檢查點已被證實與T細胞的表現和毒殺腫瘤的能力有高度相關，因此在預測病人預後狀況時可能會扮演重要的角色。本研究旨在了解病人的免疫細胞亞群上免疫檢查點表現與疾病預後狀況兩者之間的相關性，期望能找到能夠作為預測病人預後狀況的指標及改善免疫檢查點阻斷的使用。 方法: 本研究收集了69位上皮性卵巢癌患者之周邊血單核細胞(peripheral blood mononuclear cell, PBMCs)，利用多色流式細胞儀收集數據與使用Flowjo軟體分析周邊血單核細胞中各免疫細胞比例以及免疫檢查點的表現量，再藉由軟體內模組及演算法將細胞進行分群，篩選出潛在之免疫細胞亞群後觀察和病人預後之間的關聯性。卵巢癌患者依臨床資料分為三組: 初次治療完成後6個月內復發(≤ 6個月)、初次治療完成後6個月後復發(> 6個月)及從未復發，先利用復發時間≤ 6個月和從未復發兩組病人比較，尋找出具統計意義之免疫細胞亞群後，在復發時間> 6個月組別中進行與臨床病理特徵和存活情況（包括無疾病存活期DFS和整體存活期OS）的相關性分析。

結果: 經分析後篩選出具統計意義之免疫細胞亞群包括 CD3+CD4+BTLA+PD-1+、CD3+CD8+PD-1+、CD56+HVEM+TIM-3+CTLA-4+細胞，接著透過分析篩選出來的細胞亞群與初次治療完成後6個月後復發之患者的無疾病存活期和整體存活期之間的相關性，得到結果為在整體淋巴細胞中被篩選出來的細胞亞群比例和患者的DFS及OS沒有觀察到顯著關聯；但若進一步將CD3+CD4+T細胞群中CD3+CD4+BTLA+PD-1+細胞亞群的比例與整體存活期做相關性分析時，能觀察到負相關的結果；將CD56+自然殺手細胞群中CD56+HVEM+TIM-3+CTLA-1+細胞亞群的比例與無疾病存活期做相關性分析時，則可以觀察到正相關的結果。 結論: 上皮性卵巢癌患者若是在其周邊血單核細胞中具有較高的CD3+CD4+BTLA+PD-1+細胞亞群比例，就有可能會有較短的整體存活期；若有較高的CD56+HVEM+TIM-3+CTLA-4+細胞亞群比例則有可能會有較長的無疾病存活期。因此，利用高參數流式細胞儀技術區分出之病人免疫細胞亞群對於卵巢癌治療來說，是一個具有發展潛力的預後因子及用以評估標靶治療可行性的指標。

Objectives: Epithelial ovarian cancer (EOC) holds a crucial position among all gynecologic malignancies and is also a leading cause of death. The primary (standard) treatment of ovarian cancer includes cytoreductive surgery and chemotherapy. The lack of specific early symptoms makes diagnosis challenging, and the insufficient accuracy of tumor markers and lack of comprehensive tumor biology information of disease contribute to poor prognosis. Studies have shown that the host immune mechanisms have a significant impact on cancer progression and prognosis. In recent years, research on immune cells expressing immune checkpoints has become increasingly extensive and in-depth. Immune checkpoints have been proven to be highly correlated with tumor-killing ability of T cells, and may play an important role on predicting patient prognosis. This study aims to investigate the correlation between the expression of immune checkpoints on the subsets of immune cell and patient prognosis, proposing to validate the novel subsets for predict patient outcomes and optimize the usage of immune checkpoint blockade.

Methods: Peripheral blood mononuclear cells (PBMCs) from 69 patients with epithelial ovarian cancer was collected for this study. Flowcytometric data was collected using multicolor flow cytometry and then analyzed with FlowJo software to determine the proportions of various immune cells and the expression levels of immune checkpoints in PBMCs. Additionally, the software's modules and algorithms were used to cluster cells and identify potential immune cell subsets, which were then examined for their relationship with patient prognosis. The ovarian cancer patients were divided into three groups based on clinical data: recurrence within 6 months of completion of primary treatment (≤ 6 months), recurrence after 6 months of completion of primary treatment (>6 months), and no recurrence. Initially, a comparison was made between the groups with recurrence within 6 months and those with no recurrence to identify statistically significant immune cell subsets. Subsequently, the group with recurrence after 6 months was analyzed for correlations with clinical pathological characteristics and survival outcomes, including disease-free survival (DFS) and overall survival (OS).

Result: There were three immune cell subsets were identified including CD3+CD4+BTLA+PD-1+, CD3+CD8+PD-1+, and CD56+HVEM+TIM-3+CTLA-4+ cells. The correlation between these validated subsets and the DFS or OS of patients with a recurrence after 6 months of completion of primary treatment was analyzed. The results showed no significant correlation between these validated cell subsets in total lymphocytes and the DFS and OS of patients. However, when further analyzing the correlation between the CD3+CD4+BTLA+PD-1+ subset in the CD3+CD4+ T cell population and patient OS, a negative correlation was observed. In addition, a positive correlation was noted between the CD56+HVEM+TIM-3+CTLA-4+ subset in the CD56+ natural killer cell population and patient DFS.

Conclusion: EOC patients with a higher proportion of CD3+CD4+BTLA+PD-1+ cell subsets in their PBMCs may experience shorter OS. However, those with a higher proportion of CD56+HVEM+TIM-3+CTLA-4+ cell subsets may have longer DFS. Therefore, utilizing high-parameter flow cytometry to validate immune cell subsets in patients holds significant potential as a prognostic factor and as an indicator for evaluating the feasibility of immune checkpoint blockade for EOC treatment.