The adaptive immune and immune checkpoint landscape of neoadjuvant treated esophageal adenocarcinoma using digital pathology quantitation

Abstract

Background: Limited studies examine the immune landscape in Esophageal Adenocarcinoma (EAC). We aim to identify novel associations, which may inform immunotherapy treatment stratification. Methods: Three hundred twenty-nine EAC cases were available in Tissue Microarrays (TMA) format. A discovery cohort of 166 EAC cases were stained immunohistochemically for range of adaptive immune (CD3, CD4, CD8 and CD45RO) and immune checkpoint biomarkers (ICOS, IDO-1, PD-L1, PD-1). A validation cohort of 163 EAC cases was also accessed. A digital pathology analysis approach was used to quantify biomarker density. Results: CD3, CD4, CD8, CD45RO, ICOS and PD-1 were individually predictive of better overall survival (OS) (Log rank p = < 0.001; p = 0.014; p = 0.001; p = < 0.001; p = 0.008 and p = 0.026 respectively). Correlation and multivariate analysis identified high CD45RO/ICOS patients with significantly improved OS which was independently prognostic (HR = 0.445, (0.223-0.886), p = 0.021). Assessment of CD45RO and ICOS high cases in the validation cohort revealed an associated with improved OS (HR = 0.601 (0.363-0.996), p = 0.048). Multiplex IHC identified cellular co-expression of high CD45RO/ICOS. High CD45RO/ICOS patients have significantly improved OS. Conclusions: Multiplexing identifies true cellular co-expression. These data demonstrate that co-expression of immune biomarkers are associated with better outcome in EAC and may provide evidence for immunotherapy treatment stratification.

PD-L1 Multiplex and Quantitative Image Analysis for Molecular Diagnostics

“…Following a method of TMA dearraying, a rigorous quality control process was undertaken by an experienced image analyst to remove necrosis, tissue folds and normal epithelium that may confound the analysis. This was confirmed by a second reviewer with frequent consultations with an experienced pathologist prior to analysis, as previously reported [ 4 , 9 , 13 , 17 , 24 , 25 ].…”

“…Studies are emerging that increasingly show that immune profiling and biomarker co-localisation may greatly improve immunotherapeutic strategies and these can be achieved largely by employing mIF methods [ 11 , 12 , 13 ]. Advancements in multiplexing technology bring the potential to deploy mIF in a clinical setting [ 4 , 14 , 15 ].…”

Immune cell infiltrates as prognostic biomarkers in pancreatic ductal adenocarcinoma: a systematic review and meta‐analysis

“…Our findings have also suggested an important role for the immune system in PDAC and further research in this area may yield an important therapeutic breakthrough. Advances in multiplex IHC platforms are enabling the analysis of multiple immune markers simultaneously, and have been investigated in pancreatic, gastric and oesophageal cancer [76–79]. Multiplex staining and advanced immunoprofiling enable the investigation of biomarker expression and immune cell infiltration, whilst preserving the special organisation of tumour tissue [80].…”

QuPath: The global impact of an open source digital pathology system

“…QuPath has undoubted utility in the quantification of ‘routine’ DAB biomarkers [9] , [10] , [54] , [55] , [56] , [57] , including RNAScope [28] , [58] , [59] , [60] , and the ability to handle complex quantification of multiple immunofluorescence biomarkers [16] , [23] , [51] , [61] . As we have seen in the examples above, QuPath provides a framework for the training, provision and application of advanced AI, beyond that of the inbuilt machine learning methodologies.…”