Classification of Pancreatic Cancer: Ready for Practical Application?

Theranostic nanoparticles enabling the release of phosphorylated gemcitabine for advanced pancreatic cancer therapy

Gemcitabine (GEM) has been the recommended first-line drug for patients with pancreatic ductal adenocarcinoma cancer (PDAC) for the last twenty years. However, GEM-based treatment has failed in many patients because of the drug resistance acquired during tumorigenesis and development. To override resistance to GEM in pancreatic cancer, we developed a visualisable, photothermally controlled, drug release nanosystem (VPNS). This nanosystem has NaLuF4:Nd@NaLuF4 nanoparticles as the luminescent core, octabutoxyphthalocyanine palladium(ii) (PdPc) as the photothermal agent, and phosphorylated gemcitabine (pGEM) as the chemodrug. pGEM, one of the active forms of GEM, can circumvent the insufficient activation of GEM in cancer cell metabolism. The NaLuF4:Nd@NaLuF4 nanoparticles were employed to visualise the tumor lesion in vivo by their near-infrared luminescence. The near-infrared light-triggered photothermal effect from PdPc could trigger the release of pGEM loaded in a thermally responsive ligand and simultaneously enable photothermal cancer treatment. This work presents an effective method that suppresses the growth of tumour cells with dual-mode treatment and enables the improved treatment of orthotopic nude mice afflicted with pancreatic cancer.

Preclinical models of pancreatic ductal adenocarcinoma: challenges and opportunities in the era of precision medicine

Pancreatic ductal adenocarcinoma (PDAC) is an extremely lethal malignancy, with an average 5-year survival rate of 9% (Siegel RL, Miller KD, Jemal A. Ca Cancer J Clin. 2019;69(1):7-34). The steady increase in mortality rate indicates limited efficacy of the conventional regimen. The heterogeneity of PDAC calls for personalized treatment in clinical practice, which requires the construction of a preclinical system for generating patient-derived models. Currently, the lack of high-quality preclinical models results in ineffective translation of novel targeted therapeutics. This review summarizes applications of commonly used models, discusses major difficulties in PDAC model construction and provides recommendations for integrating workflows for precision medicine.

The m6A-Related mRNA Signature Predicts the Prognosis of Pancreatic Cancer Patients

N⁶-methyladenosine (m⁶A) has an important epitranscriptomic modification that controls cancer self-renewal and cell fate. The addition of m⁶A to mRNA is a reversible modification. The deposition of m⁶A is encoded by a methyltransferase complex involving three homologous factors, jargonized as "writers," "erasers," and "readers." However, their roles in pancreatic adenocarcinoma (PAAD) are underexploited. With the use of The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases, we provided an mRNA signature that may improve the prognostic prediction of PAAD patients based on the genetic status of m⁶A regulators. PAAD patients with genetic alteration of m⁶A regulators had worse disease-free and overall survival. After comparing PAAD groups with/without genetic alteration of m⁶A regulators, we identified 196 differentially expressed genes (DEGs). Then, we generated a 16-mRNA signature score system through least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Multivariate cox regression analysis demonstrated that a high-risk score significantly correlates with poor prognosis. Moreover, time-dependent receiver operating characteristic (ROC) curves revealed it was effective in predicting the overall survival in both training and validation sets. PAH, ZPLD1, PPFIA3, and TNNT1 from our signature also exhibited an independent prognostic value. Collectively, these findings can improve the understanding of m⁶A modifications in PAAD and potentially guide therapies in PAAD patients.