Therapeutic drug monitoring of neoadjuvant mFOLFIRINOX in resected pancreatic ductal adenocarcinoma.

BACKGROUND: Despite a potentially curative treatment, the prognosis after upfront surgery and adjuvant chemotherapy for patients with resectable pancreatic ductal adenocarcinoma (PDAC) is poor. Modified FOLFIRINOX (mFOLFIRINOX) is a cornerstone in the systemic treatment of PDAC, including the neoadjuvant setting. Pharmacokinetic-guided (PKG) dosing has demonstrated beneficial effects in other tumors, but scarce data is available in pancreatic cancer. METHODS: Forty-six patients with resected PDAC after mFOLFIRINOX neoadjuvant approach and included in an institutional protocol for anticancer drug monitoring were retrospectively analyzed. 5-Fluorouracil (5-FU) dosage was adjusted throughout neoadjuvant treatment according to pharmacokinetic parameters and Irinotecan (CPT-11) pharmacokinetic variables were retrospectively estimated. RESULTS: By exploratory univariate analyses, a significantly longer progression-free survival was observed for patients with either 5-FU area under the curve (AUC) above 28 mcg·h/mL or CPT-11 AUC values below 10 mcg·h/mL. In the multivariate analyses adjusted by age, gender, performance status and resectability after stratification according to both pharmacokinetic parameters, the risk of progression was significantly reduced in patients with 5-FU AUC ≥28 mcg·h/mL [HR = 0.251, 95% CI 0.096-0.656; p = 0.005] and CPT-11 AUC <10 mcg·h/mL [HR = 0.189, 95% CI 0.073-0.486, p = 0.001]. CONCLUSIONS: Pharmacokinetically-guided dose adjustment of standard chemotherapy treatments might improve survival outcomes in patients with pancreatic ductal adenocarcinoma.

Omics Approaches in Pancreatic Adenocarcinoma.

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal-around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.

Use of Machine-Learning Algorithms in Intensified Preoperative Therapy of Pancreatic Cancer to Predict Individual Risk of Relapse.

BACKGROUND: Although surgical resection is the only potentially curative treatment for pancreatic cancer (PC), long-term outcomes of this treatment remain poor. The aim of this study is to describe the feasibility of a neoadjuvant treatment with induction polychemotherapy (IPCT) followed by chemoradiation (CRT) in resectable PC, and to develop a machine-learning algorithm to predict risk of relapse. METHODS: Forty patients with resectable PC treated in our institution with IPCT (based on mFOLFOXIRI, GEMOX or GEMOXEL) followed by CRT (50 Gy and concurrent Capecitabine) were retrospectively analyzed. Additionally, clinical, pathological and analytical data were collected in order to perform a 2-year relapse-risk predictive population model using machine-learning techniques. RESULTS: A R0 resection was achieved in 90% of the patients. After a median follow-up of 33.5 months, median progression-free survival (PFS) was 18 months and median overall survival (OS) was 39 months. The 3 and 5-year actuarial PFS were 43.8% and 32.3%, respectively. The 3 and 5-year actuarial OS were 51.5% and 34.8%, respectively. Forty-percent of grade 3-4 IPCT toxicity, and 29.7% of grade 3 CRT toxicity were reported. Considering the use of granulocyte colony-stimulating factors, the number of resected lymph nodes, the presence of perineural invasion and the surgical margin status, a logistic regression algorithm predicted the individual 2-year relapse-risk with an accuracy of 0.71 (95% confidence interval [CI] 0.56-0.84, p = 0.005). The model-predicted outcome matched 64% of the observed outcomes in an external dataset. CONCLUSION: An intensified multimodal neoadjuvant approach (IPCT + CRT) in resectable PC is feasible, with an encouraging long-term outcome. Machine-learning algorithms might be a useful tool to predict individual risk of relapse. A small sample size and therapy heterogeneity remain as potential limitations.