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Background: Circulating tumor DNA (ctDNA) has emerged as a biomarker that can define the risk of recurrence after curative-intent surgery for patients with colorectal cancer (CRC). However, beyond the predictive power of postoperative ctDNA detection, the efficacy and potential limitations of ctDNA detection urgently need to be fully elucidated in a large cohort of CRC. Objectives: To define potentially cured CRC patients through ctDNA monitoring following surgery. Design: A prospective, multicenter, observational study. Methods: We enrolled 309 patients with stages I–IV CRC who underwent definitive surgery. Tumor tissues were sequenced by a custom-designed next-generation sequencing panel to identify somatic mutations. Plasma was analyzed using a ctDNA-based molecular residual disease (MRD) assay which integrated tumor-genotype-informed and tumor-genotype-naïve ctDNA analysis. The turnaround time of the assay was 10–14 days. Results: Postoperative ctDNA was detected in 5.4%, 13.8%, 15%, and 30% of patients with stage I, II, III, and IV disease, respectively, and in 17.5% of all longitudinal samples. Patients with positive postsurgery MRD had a higher recurrence rate than those with negative postsurgery MRD [hazard ratio (HR), 13.17; p < 0.0001], producing a sensitivity of 64.6%, a specificity of 94.8%, a positive predictive value (PPV) of 75.6%, and a negative predictive value (NPV) of 91.5%. Furthermore, patients with positive longitudinal MRD also had a significantly higher recurrence rate (HR, 14.44; p < 0.0001), with increased sensitivity (75.0%), specificity (94.9%), PPV (79.6%), and NPV (93.4%). Subgroup analyses revealed that adjuvant therapy did not confer superior survival for patients with undetectable or detectable MRD. In addition, MRD detection was less effective in identifying lung-only and peritoneal metastases. Conclusion: Postoperative ctDNA status is a strong predictor of recurrence independent of stage and microsatellite instability status. Longitudinal undetectable MRD could be used to define the potentially cured population in CRC patients undergoing curative-intent surgery. [ABSTRACT FROM AUTHOR]

The sensitive detection of trace biomarkers in exhaled breath for lung cancer diagnosis represents a critical area of research in life analytical chemistry, with profound implications for early disease detection, therapeutic intervention, and prognosis monitoring. Despite its potential, the analytical process faces significant challenges due to the ultratrace levels of disease biomarkers present and the complex, high-humidity composition of exhaled breath. This study introduces a highly sensitive method for detecting aldehyde biomarkers in exhaled breath by integrating the use of amino-functionalized microporous organic networks (NH 2 -MON) as a solid-phase microextraction (SPME) fiber coating with gas chromatography-triple quadrupole mass spectrometry (GC-MS/MS) analysis. The method innovatively combines sample collection and extraction, achieving a dual-step enrichment process that significantly enhances both the enrichment efficiency and reproducibility of biomarker detection while effectively mitigating the interference caused by water vapor in exhaled breath. The NH 2 -MON, utilized as an SPME fiber coating, demonstrates exceptional enrichment capacity for five key aldehyde biomarkers, facilitating the development of a highly sensitive detection approach for these biomarkers in exhaled breath. Compared to previously reported methods, the proposed technique exhibits significantly lower limits of quantification, ranging from 0.77 to 11.89 pg mL -1 , and achieves substantially higher enrichment factors, ranging from 9156- to 35723-fold. The practicality and feasibility of the method were validated through the analysis of exhaled breath samples from lung cancer patients, underscoring its potential application in the early diagnosis and monitoring of lung cancer.

Background: Endometrial Cancer (EC) is a highly heterogeneous cancer comprising both histological and molecular subtypes. Using a non-invasive modality method to trigger these subtypes as early as possible can aid clinicians in establishing individualized treatment., Purpose: The study aimed to clarify the value of the Apparent Diffusion Coefficient (ADC) of EC MRI in determining molecular subtypes., Material and Methods: We retrospectively recruited 109 patients with pathologically proven EC (78 endometrioid cancers and 31 non-endometrioid cancers) with available molecular classification from a tertiary centre. MRI was prospectively performed a month prior to surgery; images were blindly interpreted by two experienced radiologists with consensus reading. The ADC value was measured by an experienced radiologist on the commercially available processing workstation. Interoperator measurement consistency was calculated., Results: Our sample comprised 17 PLOE, 32 MSI-H, 31 NSMP, and 29 P53abn ECs. Clinical information did not differ significantly among the groups. The maximum diameter and volume of the lesions differed among the groups. The ADC value in the maximal area (ADCarea) or region of interest (ROI, ADCroi) in the P53abn group was higher than that in the other groups (894.0 ±12.6 and 817.5 ± 83.3 x10-6 mm2/s). The ADC mean values were significantly different between the P53abn group and the other groups (P = 0.000). The nomogram showed the highest discriminative ability to distinguish P53abn EC from other types (AUC: 0.859)., Conclusion: Our results have suggested the quantitative MR characteristics (ADC values) derived from preoperative EC MRI to provide useful information in preoperatively determining P53abn cancer.