Recurrence risk assessment for stage III colorectal cancer based on five methylation biomarkers in plasma cell-free DNA.

For stage III colorectal cancer (CRC) patients with a high risk of recurrence, intensified adjuvant chemotherapy can improve overall survival. We aimed to develop a circulating tumor DNA (ctDNA) methylation marker model for predicting the relapse risk of stage III CRC patients. Differentially methylated markers identified between 53 normal mucosa samples and 165 CRC tissue samples, as well as between plasma samples from 75 stage I/II (early-stage) CRC patients and 55 stage IV (late-stage) CRC patients, were analyzed using Student's t-tests. The overlapping methylation markers shared by plasma and tissue samples were used to establish a methylation marker model to evaluate the tumor burden in the peripheral blood of CRC patients using the random forest method. This model was verified in the validation cohort (n = 44) and then applied to predict recurrence risk in 50 stage III CRC patients and monitor the clinical disease course in serial samples from four CRC patients. We built a five-marker-based ctDNA methylation model that had high sensitivity (84.21%) and specificity (84%) in identifying late-stage CRC in a validation cohort containing 24 stage I/II CRC patients and 20 stage IV CRC patients. The model achieved high sensitivity (87.5%) and specificity (94.12%) in predicting tumor relapse in an independent cohort of 50 stage III CRC patients and could be an independent recurrence risk factor for stage III patients [Hazard ratio (HR), 60.4; 95% confidence interval (CI): 7.68-397; p = 9.73e-5]. Analysis of serial blood samples of CRC showed that the model could monitor disease relapse earlier than imaging examination and serum carcinoembryonic antigen (CEA) and so may provide an opportunity for the early adjustment of therapeutic strategies. Moreover, the model could potentially monitor the clinical course and treatment response dynamically. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Assessment of Rumen Microbiota from a Large Dairy Cattle Cohort Reveals the Pan and Core Bacteriomes Contributing to Varied Phenotypes.

Currently, knowledge on the extent to which rumen microbiota differ in a large population of cattle fed the same diet and whether such differences are associated with animal performance is limited. This study was conducted to characterize the rumen microbiota of a large cohort of lactating Holstein dairy cows (n = 334) that were fed the same diet and raised under the same environment, aiming to uncover linkages between core and pan rumen microbiomes and host phenotypes. Amplicon sequencing of the partial 16S rRNA gene identified 391 bacterial genera in the pan bacteriome and 33 genera in the core bacteriome. Interanimal variation existed in the pan and core bacteriomes, with the effect of lactation stage being more prominent than that of parity (the number of pregnancies, ranging from 2 to 7) and sire. Spearman's correlation network analysis revealed significant correlations among bacteria, rumen short-chain fatty acids, and lactation performance, with the core and noncore genera accounting for 53.9 and 46.2% of the network, respectively. These results suggest that the pan rumen bacteriome together with the core bacteriome potentially contributes to variations in milk production traits. Our findings provide an understanding of the potential functions of noncore rumen microbes, suggesting the possibility of enhancing bacterial fermentation using strategies to manipulate the core and noncore bacteriomes for improved cattle performance.IMPORTANCE This study revealed the rumen bacteriome from a large dairy cattle cohort (n = 334) raised under the same management and showed the linkages among the rumen core and pan bacteriomes, rumen short-chain fatty acids, and milk production phenotypes. The findings from this study suggest that the pan rumen bacteriome, together with the core bacteriome, potentially contributes to variations in host milk production traits. Fundamental knowledge on the rumen core and pan microbiomes and their roles in contributing to lactation performance provides novel insights into future strategies for manipulating rumen microbiota to enhance milk production in dairy cattle.