An AI based Digital Score of Tumour-Immune Microenvironment Predicts
  Benefit to Maintenance Immunotherapy in Advanced Oesophagogastric
  Adenocarcinoma
Quoc Dang Vu Caroline Fong Anderley Gordon Tom Lund Tatiany L Silveira Daniel Rodrigues Katharina von Loga Shan E Ahmed Raza David Cunningham Nasir Rajpoot
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.