Mutant KRAS Circulating Tumor DNA Is an Accurate Tool for Pancreatic Cancer Monitoring.

BACKGROUND: Many new pancreatic cancer treatment combinations have been discovered in recent years, yet the prognosis of pancreatic ductal adenocarcinoma (PDAC) remains grim. The advent of new treatments highlights the need for better monitoring tools for treatment response, to allow a timely switch between different therapeutic regimens. Circulating tumor DNA (ctDNA) is a tool for cancer detection and characterization with growing clinical use. However, currently, ctDNA is not used for monitoring treatment response. The high prevalence of KRAS hotspot mutations in PDAC suggests that mutant KRAS can be an efficient ctDNA marker for PDAC monitoring. SUBJECTS, MATERIALS, AND METHODS: Seventeen metastatic PDAC patients were recruited and serial plasma samples were collected. CtDNA was extracted from the plasma, and KRAS mutation analysis was performed using next-generation sequencing and correlated with serum CA19-9 levels, imaging, and survival. RESULTS: Plasma KRAS mutations were detected in 5/17 (29.4%) patients. KRAS ctDNA detection was associated with shorter survival (8 vs. 37.5 months). Our results show that, in ctDNA positive patients, ctDNA is at least comparable to CA19-9 as a marker for monitoring treatment response. Furthermore, the rate of ctDNA change was inversely correlated with survival. CONCLUSION: Our results confirm that mutant KRAS ctDNA detection in metastatic PDAC patients is a poor prognostic marker. Additionally, we were able to show that mutant KRAS ctDNA analysis can be used to monitor treatment response in PDAC patients and that ctDNA dynamics is associated with survival. We suggest that ctDNA analysis in metastatic PDAC patients is a readily available tool for disease monitoring. IMPLICATIONS FOR PRACTICE: 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 KRAS 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.

Clinically significant sub-clonality for common drivers can be detected in 26% of KRAS/EGFR mutated lung adenocarcinomas.

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.

Variation in KRAS driver substitution distributions between tumor types is determined by both mutation and natural selection.

Different tumor types vary greatly in their distribution of driver substitutions. Here, we analyzed how mutation and natural selection contribute to differences in the distribution of KRAS driver substitutions between lung, colon and pancreatic adenocarcinomas. We were able to demonstrate that both differences in mutation and differences in selection drive variation in the distribution of KRAS driver substitutions between tumor types. By accounting for the effects of mutation on the distribution of KRAS driver substitutions, we could identify specific KRAS driver substitutions that are more favored by selection in specific tumor types. Such driver substitutions likely improve fitness most when they occur within the context of the tumor type in which they are preferentially favored. Fitting with this, we found that driver substitutions that are more favored by natural selection in a specific type of tumor tend to associate with worse clinical outcomes specifically in that type of tumor.