Title: CRUK/OHSU JOINT FUNDING AWARD - Deciphering the immune complexity in oesophageal adenocarcinoma and pre-cancerous lesions with multiplex immunostaining and Sparse Subspace Clustering (SSC) approach - CRUK and OHSU Lead Applicants contribute equally; this project will be jointly funded if successful
Funder: Cancer Research UK

Abstract: Background Oesophageal cancer is the sixth most common cause of cancer death. Oesophageal adenocarcinoma (OAC) has increased almost 6-fold in western countries in the past decades, OAC has a poor prognosis with an overall five-year survival rate of 15%. Progression of OAC follows well-defined histopathological stages: metaplastic Barrett’s oesophagus (BO), low- and high-grade dysplasia and cancer. The absolute risk of progression from BO to OAC is low, however, for some patients, the malignant transition could be rapid, and most OAC patients present with late stages. OAC also bear various mutational signatures, one subtype with high mutational load (Mutagentic), is highly infiltrated with CD8 T cells. OAC with coexisting BO also shows a significantly higher survival benefit. Although the mutational drivers of OAC are becoming clear via large scale sequencing, the evolution of various immune cell populations and their potential contribution remain largely unclear, particularly under such complex clinical and genetic contexts. The challenge lies on identification, quantification, and functional evaluation of the immune cell subsets. Comprehensive characterization typically requires assessment of 10 or more markers, which usually exceeds the limit of conventional methods; in addition, assessment of image based multi-parametric data in vast amount is also a laborious task with possible bias from the researcher. Aims i) In this study, we aimed to investigate the following hypotheses: Immune complexity in OAC evolves with cancer progression; ii) certain immune cell subsets are associated with critical changes in disease grade; iii) progression from BO to OAC can be predicted by certain features of the immune complexity; iv) certain immune cell types contribute to the better survival of OAC patients with synchronous BO; v) certain immune cell types are associated with specific OAC mutational signatures; vi) A novel automated approach can analyse high-throughput data; vii) characterization of immune complexity is independent of the multiplex methods used. Methods We will apply various multiplex methods on patient tissues slides, including sequential IHC and CyTOF, to characterize various immune populations and compare the results. Data will also be analysed by a novel automated Sparse Subspace Clustering approach to increase efficiency and seek for unknow cell subsets. How the results of this research will be used The results will significantly contribute to objective and reproducible quantitative image analysis for interpretation of immune-related biomarkers and provide guidance to the management of BO and OAC patients with respect of risk stratification, early detection, prognosis and potential immune therapy targets.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES
Health categories: CANCER AND NEOPLASMS