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Objectives: The project intended to analyze the impact of burden and related risk factors of late-onset colorectal cancer (LOCRC) and early-onset colorectal cancer (EOCRC) in China, thus offering essential references for optimizing prevention and control strategies., Method: Global Burden of Disease Study was employed to describe burden changes of EOCRC and LOCRC in China during 1990-2019, containing the numbers of incidence, deaths, prevalence, and disability-adjusted life years (DALYs), and to compare attributable deaths and DALYs risk factors in varying age and sex segments., Results: The numbers and corresponding crude rates of incidence, deaths, prevalence, and DALYs of EOCRC and LOCRC in China during 1990-2019 demonstrated an upward trend across all age categories, with males being dramatically predominant. Overall, over time, the impact of a low-calcium diet and a low-fiber diet on mortality and DALY rates decreased, while the impact of other risk factors increased. In terms of gender, the risk factors affecting males changed greatly, with smoking, inadequate milk intake, and the low whole-grain diet being the main factors in 2019, while in 1990, the main factors were the low-calcium diet, smoking, and inadequate milk intake., Conclusion: The burden of colorectal cancer in China is concerning. Patients grouped by diagnostic age exhibit different characteristics, indicating the need for high-quality research in the future to achieve personalized medicine tailored to different population characteristics., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: This study intended to develop a new immunogenic cell death (ICD)-related prognostic signature for colorectal cancer (CRC) patients., Research Design and Methods: The Non-Negative Matrix Factorization (NMF) algorithm was adopted to cluster tumor samples based on ICD gene expression to obtain ICD-related subtypes. Survival analysis and immune microenvironment analysis were conducted among different subtypes. Regression analysis was used to construct the model. Based on riskscore median, cancer patients were classified into high and low risk groups, and independent prognostic ability of the model was analyzed. The CIBERSORT algorithm was adopted to determine the immune infiltration level of both groups., Results: We analyzed the differential genes between cluster 4 and cluster 1-3 and obtained 12 genes with the best prognostic features finally (NLGN1, SLC30A3, C3orf20, ADAD2, ATOH1, ATP6V1B1, KCNQ2, MUCL3, RGCC, CLEC17A, COL6A5, and INSL4). In addition, patients with lower risk had higher levels of infiltration of most immune cells, lower Tumor Immune Dysfunction and Exclusion (TIDE) level and higher immunophenscore (IPS) level than those with higher risk., Conclusions: This study constructed and validated the ICD feature signature predicting CRC prognosis and provide a reference criteria for guiding the prognosis and immunotherapy of CRC cancer patients.