[HTML][HTML] Multi-omic profiling of lung and liver tumor microenvironments of metastatic pancreatic cancer reveals site-specific immune regulatory pathways

WJ Ho, R Erbe, L Danilova, Z Phyo, E Bigelow… - Genome biology, 2021 - Springer
Genome biology, 2021Springer
Background The majority of pancreatic ductal adenocarcinomas (PDAC) are diagnosed at
the metastatic stage, and standard therapies have limited activity with a dismal 5-year
survival rate of only 8%. The liver and lung are the most common sites of PDAC metastasis,
and each have been differentially associated with prognoses and responses to systemic
therapies. A deeper understanding of the molecular and cellular landscape within the tumor
microenvironment (TME) metastasis at these different sites is critical to informing future …
Background
The majority of pancreatic ductal adenocarcinomas (PDAC) are diagnosed at the metastatic stage, and standard therapies have limited activity with a dismal 5-year survival rate of only 8%. The liver and lung are the most common sites of PDAC metastasis, and each have been differentially associated with prognoses and responses to systemic therapies. A deeper understanding of the molecular and cellular landscape within the tumor microenvironment (TME) metastasis at these different sites is critical to informing future therapeutic strategies against metastatic PDAC.
Results
By leveraging combined mass cytometry, immunohistochemistry, and RNA sequencing, we identify key regulatory pathways that distinguish the liver and lung TMEs in a preclinical mouse model of metastatic PDAC. We demonstrate that the lung TME generally exhibits higher levels of immune infiltration, immune activation, and pro-immune signaling pathways, whereas multiple immune-suppressive pathways are emphasized in the liver TME. We then perform further validation of these preclinical findings in paired human lung and liver metastatic samples using immunohistochemistry from PDAC rapid autopsy specimens. Finally, in silico validation with transfer learning between our mouse model and TCGA datasets further demonstrates that many of the site-associated features are detectable even in the context of different primary tumors.
Conclusions
Determining the distinctive immune-suppressive features in multiple liver and lung TME datasets provides further insight into the tissue specificity of molecular and cellular pathways, suggesting a potential mechanism underlying the discordant clinical responses that are often observed in metastatic diseases.
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