Deciphering the transcriptomic landscape of cancer-associated fibroblasts in pancreatic cancer – an exploratory clinical study

Completed · 2018 until 2018

Fundamental Research
Monocentric project at KSSG
Start Date
End Date
Brief description/objective

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancer types with a 5-year survival of only 7% 1. While surgical resection of localized disease offers a moderate increase in survival, patients with metastatic pancreas cancer are still left without curative treatment options 2. The current chemotherapeutical approaches in clinical practice offer a small to moderate survival benefit and recent clinical trials have failed to demonstrate improved efficacy 2. Currently, the immunosuppressive nature of the tumor microenvironment (TME) in PDAC is seen as the main obstacle because different cell populations appear to collaborate and promote tumor growth and metastasis 3. The TME of pancreatic cancer is characterized by a profound desmoplastic reaction with accumulation of cancer-associated fibroblasts (CAF) and pancreatic stellate cells (PSC) that contribute to the deposition of extracellular matrix proteins and thereby block access of therapeutic agents to the tumor cells 4. However, ablation of tumor stroma in experimental models of PDAC fostered tumor growth and led to decreased overall survival 5, 6 suggesting that certain cell types within the PDAC stroma inhibit tumor growth.
Tumors are proposed to be wounds that do not heal 7. However, the recent advances in immunotherapy have revealed that unleashing of antitumor immunity responses can lead to complete remission. Despite numerous studies investigating the contribution of fibroblasts to the progression of carcinomas 8, the identity and heterogeneity of fibroblasts that contribute to the immune-stimulating tumor stromal cell compartment has not been adequately defined. While some of the transcriptional profiles dictating positional identity of fibroblasts have been identified 9, few, if any studies have linked specific fibroblast cell types to distinct functions such enforcement of antitumor immunity during cancer stroma formation. Cumulatively, these findings suggest that the identity of immune-stimulating tumor fibroblasts needs to be unveiled because these cells can crucially contribute to the resolution of the cancer wound.
Studies on the non-transformed compartments of the TME have revealed that the cellular structures supporting tumor growth could function as universal targets for tumor therapy 10, 11. Indeed, almost all tumors, including PDAC, show robust accumulation of fibroblastic stromal cells that secrete extracellular matrix proteins and soluble mediators, all of which influence tumor progression, local angiogenesis and antitumor immunity 12. Since tumor growth depends on a supportive TME provided by tumor-associated fibroblasts 13-15, recent efforts have focused on the functional characterization and targeting of the fibroblastic tumor stroma. Surprisingly, these studies revealed the presence of both tumor-supportive and tumor-suppressive fibroblastic cell types 12, 16. Notably, the depletion of tumor-suppressive fibroblasts is associated with a decreased accumulation of highly active T cells, suggesting that circumvented antitumor immunity correlates with clinical outcome in stromal cell therapies 12, 17. Thus, identification of means to selectively foster the development and activity of immune-stimulating fibroblasts in tumors may significantly enlarge the repertoire of treatment options in PDAC.
Unraveling cell identity in the context of the tumor microenvironment by single-cell RNA-sequencing
The identity of cells and their putative origin can be analyzed at high resolution through recording of the transcriptomic landscape of well-defined cell cohorts 18 or single cells 19. The method of choice for these analyses is high-throughput sequencing of cDNA (RNA-seq) 20, 21, a technology that has almost completely supplanted the use of earlier analog technologies, such as DNA microarrays. The rapid uptake of RNA-seq was driven by two critical features: (i) a wider dynamic range of measurement; (ii) an open system, facilitating the characterization of genetic variation, new transcripts and unannotated RNA species. Until recently, RNA-seq studies were largely based on thousands (or millions) of cells pooled to obtain the necessary amount of material to build a library. In contrast, single-cell RNA sequencing technology opens up many opportunities, such as studying the heterogeneity in a cell population, detecting and characterizing rare and previously unknown cell types or associating transcriptional changes across specific cell subpopulations. Thus, single cell RNA-seq permits the comprehensive study of fibroblasts in the context of the tumor ecosystem.