Avoiding futile chemotherapy in metastatic pancreatic ductal adenocarcinoma (PDAC) patients by monitoring response to treatment is of utmost importance. A novel biomarker for monitoring treatment response in PDAC, using mutant circulating tumor DNA (ctDNA), is proposed. Results, although limited by small sample numbers, suggest that ctDNA can be an effective marker for disease monitoring and that ctDNA level over time is a better predictor of survival than the dynamics of the commonly used biomarker CA19-9. Therefore, ctDNA analysis can be a useful tool for monitoring PDAC treatment response. These results should be further validated in larger sample numbers.

Genetic sub-clonality has been described in multiple malignancies, however the presence of sub-clonality for major drivers in lung adenocarcinoma and its clinical significance is a subject under debate. Using molecular and morphometric approach, 347 lung adenocarcinoma samples were analyzed for KRAS and EGFR sub-clonality, which was further correlated with clinical and pathological variables.KRAS and EGFR mutations were identified in 100 (29%) and 82 (23%) cases, respectively. One hundred and forty four KRAS or EGFR positive cases were also available for morphometric analysis, among which 37 (26%) were defined as sub-clonal. The presence of sub-clonality was associated with shorter survival time (p=0.02). Interestingly, cases with sub-clonality were also associated with earlier disease stage (89% vs 66% stage I disease in sub-clonal vs clonal cases, respectively, p=0.01) and less lymph node involvement (8% vs 25% in sub-clonal vs clonal cases, respectively, p=0.02). Our findings demonstrate the presence of sub-clonality for mutations in common drivers in lung adenocarcinoma and link it both to earlier disease stage and to poor survival. These findings are in line with the different evolutionary models that can present with genetic sub-clonality.

Objective:Circulating tumor DNA is a promising noninvasive tool for cancer monitoring. One of the challenges in applying this tool is the detection of low-frequency mutations. The detection limit of these mutations varies between different molecular methods. The aim of this study is to characterize the factors affecting the limit of detection for epidermal growth factor receptor p.T790M mutation in circulating tumor DNA of patients with lung adenocarcinoma.Methods:DNA was extracted from plasma samples of 102 patients. For sequencing the DNA, we used 2 different next-generation sequencing–based platforms: Ion Torrent Personal Genome Machine (56 cases) and Roche/454 (46 cases). Serially diluted synthetic DNA samples carrying the p.T790M mutation were sequenced using the Ion Torrent Personal Genome Machine for validation. Limit of detection was determined through the analysis of non-hot-spot nonreference reads, which were regarded as sequencing artifacts.Results:The frequency of the non-hot-spot nonreference reads was higher in Ion Torrent Personal Genome Machine compared to Roche/454 (0.07% ± 0.08% and 0.03% ± 0.06%, respectively, P < .001). We found that different base type substitutions occur with different frequency. Since the base substitution leading to p.T790M mutation is C>T transition, its frequency was used to determine the limit of detection for the assay. Based on the C>T non-hot-spot nonreference allele frequency, we found that the limit of detection is 0.18% in Ion Torrent Personal Genome Machine and 0.1% in Roche/454. Based on these values, 48% and 56% of the cases were positive for T790M mutation in Ion Torrent Personal Genome Machine and Roche/454 groups, respectively. Agreement between duplicates was 76% in Ion Torrent Personal Genome Machine and 72% in Roche/454. Using serially diluted synthetic DNA samples carrying the p.T790M mutation, we could identify mutations with allele frequency of 0.18% or more using the Ion Torrent Personal Genome Machine, supporting our approach to determine the detection limit.Conclusion:Both the sequencing platform and the specific nucleotide change affect the limit of detection and should therefore be determined in the validation process of new assays.