Tumour genotype shapes blood biomarker expression for use in pancreatic cancer detection and diagnosis.
Canel, M.; Lonergan, D. W.; Ferguson, C.; Gautier, P.; Morton, j. P.; Kriegsheim, A. v.; Serrels, A.
Show abstract
Typically diagnosed late, when systemic metastasis has already occurred, pancreatic ductal adenocarcinoma (PDAC) has one of the worst 5-year survival rates of any cancer type. For many patients with advanced disease, current chemotherapy regimens offer only modest benefit despite significant toxicity and surgical resection, the only treatment option with curative potential, is not possible. Therefore, while new treatments are much needed, diagnosing patients at an earlier disease stage when surgery remains possible and the window of opportunity for treatment response is longer will be critical to improving patient outcomes. In this regard, the identification of biomarkers from biospecimens that can be easily sampled from patients remains the focus of considerable research, however success has not been forthcoming. Using a suite of novel genetically defined murine isogenic models of early PDAC, engineered using CRISPR-Cas9 gene editing, we sought to address whether loss-of-function mutations in common driver genes, and thus the genetic heterogeneity inherent to the disease, may represent an important confounding factor in the identification of a one-size-fits-all biomarker suitable for early detection. Focussing on the multi-omics analysis of blood, we show that both loss of Cdkn2a and / or Smad4 on the background of a KrasG12D Trp53-/- genotype has profound effects on the profile of differentially expressed RNA species including protein coding RNAs, lncRNAs, snoRNAs, scRNAs, snRNAs and miRNAs, and on plasma protein expression, when compared to both healthy controls and chemically induced pancreatitis. In addition, we find that loss of Smad4, a genomic event that occurs following progression from PanIN to PDAC, substantially limits the availability of blood biomarkers. These findings identify the need to move towards genotype-specific biomarker signatures and uncover a potential role for Smad4 loss in limiting opportunities for the early detection of pancreatic cancer.
Matching journals
The top 13 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Digital Spatial Profiling of Intraductal Papillary Mucinous Neoplasms: Towards a Molecular Framework for Risk Stratification 95%
- HIRA loss transforms FH-deficient cells 95%
- Multiplexed Glycan Immunofluorescence Identification of Pancreatic Cancer Cell Subpopulations in Both Tumor and Blood Samples 95%
Similar papers in this journal
Similar papers in this journal
- AXL is a key factor for cell plasticity and promotes metastasis in pancreatic cancer 95%
- MYC hyperactivates WNT signaling in APC/CTNNB1-mutated colorectal cancer cells through miR-92a-dependent repression of DKK3 93%
- Insulin Resistance Increases TNBC Aggressiveness and Brain Metastasis via Adipocyte-derived Exosomes 93%
Similar papers in this journal
- Netrin G1 promotes pancreatic tumorigenesis through cancer associated fibroblastdriven nutritional support and immunosuppression 96%
- Mesenchymal Lineage Heterogeneity Underlies Non-Redundant Functions of Pancreatic Cancer-Associated Fibroblasts 95%
- ROR2 regulates cellular plasticity in pancreatic neoplasia and adenocarcinoma 95%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.