Mitochondrial Metabolism in Pancreatic Ductal Adenocarcinoma: From Mechanism-Based Perspectives to Therapy

Abstract

Pancreatic ductal adenocarcinoma (PDAC), the fourteenth most common malignancy, is a major contributor to cancer-related death with the utmost case fatality rate among all malignancies. Functional mitochondria, regardless of their complex ecosystem relative to normal cells, are essential in PDAC progression. Tumor cells’ potential to produce ATP as energy, despite retaining the redox potential optimum, and allocating materials for biosynthetic activities that are crucial for cell growth, survival, and proliferation, are assisted by mitochondria. The polyclonal tumor cells with different metabolic profiles may add to carcinogenesis through inter-metabolic coupling. Cancer cells frequently possess alterations in the mitochondrial genome, although they do not hinder metabolism; alternatively, they change bioenergetics. This can further impart retrograde signaling, educate cell signaling, epigenetic modifications, chromatin structures, and transcription machinery, and ultimately satisfy cancer cellular and nuclear demands. To maximize the tumor microenvironment (TME), tumor cells remodel nearby stromal cells and extracellular matrix. These changes initiate polyclonality, which is crucial for growth, stress response, and metastasis. Here, we evaluate all the intrinsic and extrinsic pathways drawn by mitochondria in carcinogenesis, emphasizing the perspectives of mitochondrial metabolism in PDAC progression and treatment.

Extracellular Matrix Collagen I Differentially Regulates the Metabolic Plasticity of Pancreatic Ductal Adenocarcinoma Parenchymal Cell and Cancer Stem Cell

“…The large increase in ATP production in the CSCs could indicate an increasing dependence on glutamine uptake and its use in glutamine-driven oxidative phosphorylation (glutaminolysis), as recently reported in pluripotent stem cells [77,78], leukemia CSCs [33,34] and in PDAC cells, where the primary amino acid taken up was glutamine [35,36,59,79,80], including PDAC-initiating cells [25]. However, while PDAC is characterized by high levels of glutamine uptake, the role of the increasing collagen I during the desmoplastic reaction in driving this glutamine uptake/usage has not been described.…”

“…Even if glucose is considered to be the main metabolite used by CSCs, they can use it to fuel different metabolic pathways [16] and there are studies showing CSCs to be particularly reliant on amino acid metabolism for oxidative phosphorylation, especially in leukemia stem cells, which are completely dependent on metabolizing amino acids for energy [33,34]. While PDAC is characterized by high levels of glutamine uptake [35][36][37][38][39], neither the tumor cell type involved nor the role of the desmoplastic reaction in driving this glutamine uptake have been described. Many studies have revealed that CSCs identified in some types of cancer, such as PDAC [40], ovarian [41] and gliomas [42], rely mainly on oxidative metabolism with a higher mitochondrial mass content and higher oxygen consumption levels [43][44][45][46].…”

A Novel Perspective on Genes Driving Metastatic Pancreatic Cancer Revealed by Single-cell RNA Sequencing

“…Several RPs are overexpressed in various human tumors, including prostate, colon, hepatic, pancreatic, gastric, lung, and breast cancers, among others (2,3). Interestingly, nearly all the downregulated genes are associated with the mitochondrially encoded NADH gene family and mitochondrially encoded cytochrome C and B (4,5). The top 10 upregulated and downregulated genes in metastatic cells compared to primary cells in PDAC.…”

Therapeutic Approaches in Pancreatic Cancer: Recent Updates

“…The use of drugs destroys cancerous cells while sparing the surrounding healthy cells, allowing them to be combined with other cancer treatments to maximize their effectiveness [ 14 , 15 ]. Existing treatment possibilities for patients with advanced pancreatic cancer include chemotherapy, immunotherapy, targeted therapies, and surgery [ 4 , 16 , 17 ].…”