Mapping the T-cell landscape of pancreatic cancer

Pancreatic cancer has one of the worst prognoses of any cancer, with pancreatic ductal adenocarcinoma (PDAC) patients having an average survival rate of 7%.

T-cells (the lymphocytes that play a wide range of roles in shaping the body’s immune response to cancer) are known to be dysregulated in pancreas tumours. So far, checkpoint inhibitor (a type of immune-therapy that targets T-cells and have curative properties on other cancer types) trials have had minimal effect on pancreatic cancer (with a response rate of only 5-10%), and with no lasting impact on a patient’s survival chance. Additionally, current approved checkpoint therapies are focused on only two T-cell checkpoints, known as PD-1 and CTLA4.

In order to better understand why this is and understand which treatments may have a better impact on pancreatic cancer, there is a need to understand the specific sub-populations of T-cells that are involved in pancreatic cancer. Even though we know T-cells exist in the microenvironment of pancreatic cancer, not much is known about their differentiation or activation status.

A new study, currently in pre-print, from Dr Shivan Sivakumar and Dr Enas Abu-Shah has characterised the immune landscape and specifically the different T-cells, and their checkpoint expression patterns in pancreatic cancer patients in the hope of understanding the features to aid rational drug development and novel therapeutics for this disease.

The team looked at 32,000 T-cells from 8 cancer patients, to see if there was any unique T-cell subtypes in the tumour microenvironment. They made three important findings. Their observations showed an activated regulatory T-cell population, which was characterized by a highly immunosuppressive state with high TIGIT, ICOS and CD39 expression. The exhausted CD8 T-cells had lower PD1 levels but high levels of TIGIT and tim3. And the presence of a significant senescent T-cell population – this is when cells have gone down an irreversible cell cycle arrest and are no longer responsive to antigen stimuli.

This data suggests that the microenvironment of pancreatic cancer is extremely suppressive and could be a major driver of poor prognosis. The findings were validated in an independent pancreatic cancer single-cell RNA sequencing dataset using 24 patients. The team also showed that regulatory T-cells were predominantly found in the stroma of PDAC, highlighting the potential importance of tissue localisation on their function.

This means that new potential checkpoint immunotherapy avenues in TIGIT, ICOS, CD39 and Tim3, that target these populations, may have more potential to improving the prognosis of pancreatic cancer.

About the study

This study was co-authored by Dr Shivan Sivakumar (Dept of Oncology) and Dr Enas Abu-Shah (Kennedy Institute of Rheumatology). This study was a collaboration with Prof Mark Middleton (Dept of Oncology), Dr Rachael Bashford-Rodgers (Wellcome Trust Centre for Human Genomics),  Prof Michael Dustin (Kennedy Institute of Rheumatology), Mr Michael Silva (University Hospitals NHS foundations Trust) and Mr Zahir Soonawalla (University Hospitals NHS foundations Trust).

Shivan’s primary area of study is pancreatic cancer and developing novel therapeutic strategies for this recalcitrant disease. He studies the biology of the disease with a particular focus on the complex tumour microenvironment.

Enas’ work looks at the interactions between the T-cells and the APCs in the presence and absence of regulatory T-cells. Currently, using this model she is interested in investigating the mechanism of inhibition as a function of antigen affinity. The other line of investigation in the context of immune regulation is trying to understand the immune regulation in human pancreatic cancer.

In collaboration with Dr. Shivan Sivakumar, they are using mass cytometry, sequencing and multiplex imaging to characterise the immune landscape of primary treatment-naive tumours with focus on T-cell signatures of activation, dysregulation and suppression.  This work is funded by the NIHR, Celgene translation fellowship, UCB-Oxford Research Fellowship, LAP, CRUK and HIDI.