Decoding the Intricate Landscape of Pancreatic Cancer: Insights into Tumor Biology, Microenvironment, and Therapeutic Interventions.
Notch signaling
PD-L1
TGF-beta signaling
cancer-associated fibroblasts
macrophages
pancreatic cancer
tumor microenvironment
tumor-associated macrophages
Journal
Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829
Informations de publication
Date de publication:
02 Jul 2024
02 Jul 2024
Historique:
received:
30
05
2024
revised:
24
06
2024
accepted:
28
06
2024
medline:
13
7
2024
pubmed:
13
7
2024
entrez:
13
7
2024
Statut:
epublish
Résumé
Pancreatic ductal adenocarcinoma (PDAC) presents significant oncological challenges due to its aggressive nature and poor prognosis. The tumor microenvironment (TME) plays a critical role in progression and treatment resistance. Non-neoplastic cells, such as cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs), contribute to tumor growth, angiogenesis, and immune evasion. Although immune cells infiltrate TME, tumor cells evade immune responses by secreting chemokines and expressing immune checkpoint inhibitors (ICIs). Vascular components, like endothelial cells and pericytes, stimulate angiogenesis to support tumor growth, while adipocytes secrete factors that promote cell growth, invasion, and treatment resistance. Additionally, perineural invasion, a characteristic feature of PDAC, contributes to local recurrence and poor prognosis. Moreover, key signaling pathways including Kirsten rat sarcoma viral oncogene (KRAS), transforming growth factor beta (TGF-β), Notch, hypoxia-inducible factor (HIF), and Wnt/β-catenin drive tumor progression and resistance. Targeting the TME is crucial for developing effective therapies, including strategies like inhibiting CAFs, modulating immune response, disrupting angiogenesis, and blocking neural cell interactions. A recent multi-omic approach has identified signature genes associated with anoikis resistance, which could serve as prognostic biomarkers and targets for personalized therapy.
Identifiants
pubmed: 39001498
pii: cancers16132438
doi: 10.3390/cancers16132438
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng