癌症是全球主要死因之一，免疫細胞在腫瘤微環境中扮演著重要角色，影響腫瘤生長、轉移及治療反應。理解免疫細胞與臨床特徵及患者存活的關係對優化治療策略至關重要。本研究利用癌症基因組圖譜（TCGA）數據庫中的RNA測序數據，採用CIBERSORT演算法估算不同癌症樣本中的免疫細胞組成比例。CIBERSORT能精確解析腫瘤樣本中各種免疫細胞的比例，提供腫瘤免疫環境的詳細資訊。在估算完免疫細胞比例後，本研究使用ESTIMATE 演算法來估計腫瘤純度，並根據腫瘤純度調整免疫細胞比例，提高估算準確性，更精確地反映腫瘤微環境中的免疫狀況。
本研究首先運用Wilcoxon排序和檢定(Wilcoxon rank-sum test)和配對T 檢定(Paired t test)比較不同癌症樣本中各類免疫細胞比例的差異，辨別不同癌症類型中的免疫細胞特徵。在存活分析方面，本研究採用Cox比例風險模型，評估免疫細胞比例對患者存活時間的影響，幫助理解特定免疫細胞類型的存在和比例如何與患者存活相關，為臨床決策提供依據。最後，透過中介分析，本研究推斷了免疫細胞比例作為中介變數，影響患者臨床特徵與存活狀態、存活時間的關係。

Cancer is one of the leading causes of death globally, and immune cells play a crucial role in the tumor microenvironment, influencing tumor growth, metastasis, and treatment response. Understanding the relationship between immune cells, clinical characteristics, and patient prognosis is vital for optimizing treatment strategies. This study utilizes RNA sequencing data from The Cancer Genome Atlas (TCGA) database and employs the CIBERSORT algorithm to estimate the composition ratios of immune cells in different cancer samples. CIBERSORT accurately parses the proportions of various immune cells within tumor samples, providing detailed information about the tumor immune environment. After estimating the proportions of immune cells, this study further uses the ESTIMATE Algorithm to assess tumor purity and adjust immune cell proportions based on tumor purity, enhancing the accuracy of the estimations and more precisely reflecting the immune status within the tumor microenvironment.
First, this study employs the Wilcoxon rank-sum test and Paired t test to compare the differences in immune cell proportions across various cancer samples, identifying immune cell characteristics in different cancer types. For survival analysis, this study uses the Cox proportional hazards model to evaluate the impact of immune cell proportions on patient survival time, aiding in the understanding of how the presence and proportion of specific immune cell types affect patient prognosis, providing a basis for clinical decision-making. Finally, through mediation analysis, this study infers the role of immune cell proportions as mediating variables influencing the relationship between clinical characteristics and survival status, survival time.

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