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

Abstract

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.

The Desmoplastic Stroma of Pancreatic Cancer: Multilayered Levels of Heterogeneity, Clinical Significance, and Therapeutic Opportunities

“…Research is underway to understand the complicated signaling networks between tumor cells, fibroblast subtypes, and immune cells to develop stroma-modifying therapies against PDACs [121][122][123][124][125]. Moreover, spatial analyses have revealed significant differences in the tumor−immune microenvironment using different intratumoral locations and organ sites [126,127]. This section discusses the geographical/spatial heterogeneity of PDAC stroma at niche, locoregional, and organ levels.…”

“…For example, Lenk et al, have demonstrated that the hepatic stromal microenvironment is essential for dictating tumor cell dormancy in liver metastases of PDACs [153]. In addition, immune-regulatory pathways in the tumor microenvironment of metastatic PDACs appear to differ in the liver and lung [127]. On the other hand, pancreatic cancers can easily disseminate into the abdominal cavity to develop peritoneal implants with a similar desmoplastic stroma to primary tumors.…”

Integrated T cell cytometry metrics for immune-monitoring applications in immunotherapy clinical trials

“…Additionally, using 3 independent CyTOF data sets from patients with PDAC, HCC, and melanoma and our transfer learning software projectR ( 33 ), we demonstrated that CyTOF-derived integrated signatures with clinical correlations can be used for transfer learning across data sets, despite discordance in antibody panels and distinct disease contexts. We have previously illustrated the wide applicability of projectR in cross-data set and cross-species transfer learning of single-cell and bulk transcriptomic data in multiple biological contexts ( 34 , 37 ). Our current work also implicates the utility of our approach in CyTOF-based translational applications, such as comparing immunological states of patients learned from NMF across several clinical trials, evaluating relatively uncommon events such as clinical response to immunotherapy in patients with PDAC, and validating specific T cell signatures in a data set of limited scale by projecting robust signatures identified in another well-established data set.…”

Deconstructing Pancreatic Cancer Using Next Generation-Omic Technologies–From Discovery to Knowledge-Guided Platforms for Better Patient Management

“…Single cell data also demonstrates that immune checkpoint receptors are heterogeneously expressed between patients (N. G. Steele et al, 2020 ). In addition, recent studies have established that primary tumour and metastatic lesions support distinct immune infiltrates, which is largely heterogeneous between patients and also shaped by the metastatic niche (C. W. Steele et al, 2016 ; Lin et al, 2020 ; Raghavan et al, 2021 ; Ho et al, 2021 ). These data highlight the complexity of individual patient immune microenvironments and suggest that therapeutic approaches targeting immune checkpoints may need to be tailored to individual PDAC patients (N. G. Steele et al, 2020 ).…”