Department of Epidemiology and Ministry of Education Key Laboratory of Public Health Safety, School of Public Health, Fudan University, Shanghai, China.
State Key Laboratory of Genetic Engineering, Human Phenome Institute, School of Life Sciences, Fudan University, Shanghai, China.
Aging (Albany NY). 2024 Jul 5;16(13):11027-11061. doi: 10.18632/aging.205999.
Adenocarcinoma of the esophagogastric junction (AEGJ) with a specific pathological profile and poor prognosis has limited therapeutic options. Previous studies have found that TILs exhibit distinct characteristics in different tumors and are correlated with tumor prognosis. We established cellular training sets to obtain auto-quantified TILs in pathological images. And we compared the characteristics of TILs in AEGJ with those in esophageal squamous cell carcinoma (ESCC) and gastric adenocarcinoma (GAC) to gain insight into the unique immune environments of these three tumors and investigate the prognostic value of TILs in these three tumors.
Utilizing a case-control study design, we analyzed 214 AEGJ, 256 GAC, and 752 ESCC cases. The TCGA dataset was used to validate prognostic value of auto-quantified TILs. The specific cellular training sets were established by experienced pathologists to determine TILs counts. Kruskal-Wallis test and multi-variable linear regression were conducted to explore TILs characteristics. Survival analyses were performed with Kaplan-Meier method and Cox proportional hazards model.
The three cellular training sets of these cancers achieved a classification accuracy of 87.55 at least. The median auto-quantified TILs of AEGJ, GAC, and ESCC cases were 4.82%, 1.92%, and 0.12%, respectively. The TILs demonstrated varied characteristics under distinctive clinicopathological traits. The higher TILs proportion was associated with better prognosis in esophagogastric cancers (all < 0.05) and was an independent prognostic biomarker on AEGJ in both datasets (Taixing: HR = 0.965, 95% CI = 0.938-0.994; TCGA: HR = 0.811, 95% CI = 0.712-0.925).
We found variations in TILs across ESCC, GAC, and AEGJ, as assessed by image processing algorithms. Additionally, TILs in these three cancers are an independent prognostic factor. This enhances our understanding of the unique immune characteristics of the three tumors, improving patient outcomes.
具有特定病理特征和预后不良的食管胃结合部腺癌（AEGJ）治疗选择有限。先前的研究发现，TIL 在不同的肿瘤中表现出不同的特征，并与肿瘤预后相关。我们建立了细胞训练集，以从病理图像中获得自动量化的 TIL。我们比较了 AEGJ、食管鳞状细胞癌（ESCC）和胃腺癌（GAC）中 TIL 的特征，以深入了解这三种肿瘤的独特免疫环境，并研究 TIL 在这三种肿瘤中的预后价值。
利用病例对照研究设计，我们分析了 214 例 AEGJ、256 例 GAC 和 752 例 ESCC 病例。使用 TCGA 数据集验证自动量化的 TIL 的预后价值。经验丰富的病理学家建立了特定的细胞训练集来确定 TIL 的计数。采用 Kruskal-Wallis 检验和多变量线性回归分析来探讨 TIL 的特征。采用 Kaplan-Meier 法和 Cox 比例风险模型进行生存分析。
这三种癌症的三个细胞训练集的分类准确率至少达到了 87.55%。AEGJ、GAC 和 ESCC 病例的中位数自动量化 TIL 分别为 4.82%、1.92%和 0.12%。TIL 在不同的临床病理特征下表现出不同的特征。较高的 TIL 比例与食管胃癌症的较好预后相关（均<0.05），并且在两个数据集的 AEGJ 中均为独立的预后生物标志物（泰兴：HR=0.965，95%CI=0.938-0.994；TCGA：HR=0.811，95%CI=0.712-0.925）。
我们发现，通过图像处理算法，ESCC、GAC 和 AEGJ 之间的 TIL 存在差异。此外，这三种癌症中的 TIL 是独立的预后因素。这增强了我们对这三种肿瘤独特免疫特征的理解，改善了患者的预后。
