Background: A high percentage of patients diagnosed with localized colon cancer (CC) will relapse after curative treatment. Although pathological staging currently guides our treatment decisions, there are no biomarkers determining minimal residual disease (MRD) and patients are at risk of being undertreated or even overtreated with chemotherapy in this setting. Circulatingtumor DNA (ctDNA) can to be a useful tool to better detect risk of relapse.Patients and methods: One hundred and fifty patients diagnosed with localized CC were prospectively enrolled in our study. Tumor tissue from those patients was sequenced by a custom-targeted next-generation sequencing (NGS) panel to characterize somatic mutations. A minimum variant allele frequency (VAF) of 5% was applied for variant filtering. Orthogonal droplet digital PCR (ddPCR) validation was carried out. We selected known variants with higher VAF to track ctDNA in the plasma samples by ddPCR.Results: NGS found known pathological mutations in 132 (88%) primary tumors. ddPCR showed high concordance with NGS (r ¼ 0.77) for VAF in primary tumors. Detection of ctDNA after surgery and in serial plasma samples during follow-up were associated with poorer disease-free survival (DFS) [hazard ratio (HR), 17.56; log-rank P ¼ 0.0014 and HR, 11.33; log-rank P ¼ 0.0001, respectively]. Tracking at least two variants in plasma increased the ability to identify MRD to 87.5%. ctDNA was the only significantly independent predictor of DFS in multivariable analysis. In patients treated with adjuvant chemotherapy, presence of ctDNA after therapy was associated with early relapse (HR 10.02; log-rank P < 0.0001). Detection of ctDNA at followup preceded radiological recurrence with a median lead time of 11.5 months.Conclusions: Plasma postoperative ctDNA detected MRD and identified patients at high risk of relapse in localized CC. Mutation tracking with more than one variant in serial plasma samples improved our accuracy in predicting MRD.

BackgroundLocally advanced head and neck squamous cell carcinoma (LAHNSCC) is a heterogeneous disease in which better predictive and prognostic factors are needed. Apart from TNM stage, both systemic inflammation and poor nutritional status have a negative impact on survival.MethodsWe retrospectively analysed two independent cohorts of a total of 145 patients with LAHNSCC treated with induction chemotherapy followed by concurrent chemoradiotherapy at two different academic institutions. Full clinical data, including the Prognostic Nutritional Index (PNI), neutrophil to lymphocyte ratio and derived neutrophil to lymphocyte ratio, were analysed in a training cohort of 50 patients. Receiver operating characteristic curve analysis was used to establish optimal cut-off. Univariate and multivariate analyses of prognostic factors for overall survival (OS) were performed. Independent predictors of OS identified in multivariate analysis were confirmed in a validation cohort of 95 patients.ResultsIn the univariate analysis, low PNI (PNI<45) (p=0.001), large primary tumour (T4) (p=0.044) and advanced lymph node disease (N2b-N3) (p=0.025) were significantly associated with poorer OS in the validation cohort. The independent prognostic factors in the multivariate analysis for OS identified in the training cohort were dRNL (p=0.030) and PNI (p=0.042). In the validation cohort, only the PNI remained as independent prognostic factor (p=0.007).ConclusionsPNI is a readily available, independent prognostic biomarker for OS in LAHNSCC. Adding PNI to tumour staging could improve individual risk stratification of patients with LAHNSCC in future clinical trials.