Gastric and oesophageal (OG) cancers are the leading causes of cancer mortality worldwide. In OG cancers, recent studies have showed that PDL1 immune checkpoint inhibitors (ICI) in combination with chemotherapy improves patient survival. However, our understanding of the tumour immune microenvironment in OG cancers remains limited. In this study, we interrogate multiplex immunofluorescence (mIF) images taken from patients with advanced Oesophagogastric Adenocarcinoma (OGA) who received first-line fluoropyrimidine and platinum-based chemotherapy in the PLATFORM trial (NCT02678182) to predict the efficacy of the treatment and to explore the biological basis of patients responding to maintenance durvalumab (PDL1 inhibitor). Our proposed Artificial Intelligence (AI) based marker successfully identified responder from non-responder (p < 0.05) as well as those who could potentially benefit from ICI with statistical significance (p < 0.05) for both progression free and overall survival. Our findings suggest that T cells that express FOXP3 seem to heavily influence the patient treatment response and survival outcome. We also observed that higher levels of CD8+PD1+ cells are consistently linked to poor prognosis for both OS and PFS, regardless of ICI.

翻译：胃癌和食管癌是全球癌症死亡的主要原因。在食管胃癌中，近期研究表明PDL1免疫检查点抑制剂联合化疗可提高患者生存率。然而，我们对食管胃癌肿瘤免疫微环境的了解仍然有限。本研究通过对PLATFORM试验（NCT02678182）中接受一线氟尿嘧啶和铂类化疗的晚期食管胃腺癌患者的多重免疫荧光图像进行分析，以预测治疗效果并探索维持性度伐利尤单抗（PDL1抑制剂）治疗应答的生物学基础。我们提出的基于人工智能的标志物成功区分了应答者与非应答者（p < 0.05），并识别出可能从ICI治疗中获益的患者（p < 0.05），在无进展生存期和总生存期方面均具有统计学显著性。研究结果表明，表达FOXP3的T细胞似乎对患者治疗应答和生存结局产生重大影响。我们还观察到，无论是否使用ICI，更高水平的CD8+PD1+细胞始终与更差的总生存期和无进展生存期预后相关。