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Yang X, Liu J, Wang S, Al-Ameer WHA, Ji J, Cao J, Dhaen HMS, Lin Y, Zhou Y, Zheng C. Genome wide-scale CRISPR-Cas9 knockout screens identify a fitness score for optimized risk stratification in colorectal cancer. J Transl Med 2024; 22:554. [PMID: 38858785 DOI: 10.1186/s12967-024-05323-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2024] [Accepted: 05/20/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND The molecular complexity of colorectal cancer poses a significant challenge to the clinical implementation of accurate risk stratification. There is still an urgent need to find better biomarkers to enhance established risk stratification and guide risk-adapted treatment decisions. METHODS we systematically analyzed cancer dependencies of 17 colorectal cancer cells and 513 other cancer cells based on genome-scale CRISPR-Cas9 knockout screens to identify colorectal cancer-specific fitness genes. A regression model was built using colorectal cancer-specific fitness genes, which was validated in other three independent cohorts. 30 published gene expression signatures were also retrieved. FINDINGS We defined a total of 1828 genes that were colorectal cancer-specific fitness genes and identified a 22 colorectal cancer-specific fitness gene (CFG22) score. A high CFG22 score represented unfavorable recurrence and mortality rates, which was validated in three independent cohorts. Combined with age, and TNM stage, the CFG22 model can provide guidance for the prognosis of colorectal cancer patients. Analysis of genomic abnormalities and infiltrating immune cells in the CFG22 risk stratification revealed molecular pathological difference between the subgroups. Besides, drug analysis found that CFG22 high patients were more sensitive to clofibrate. INTERPRETATION The CFG22 model provided a powerful auxiliary prediction tool for identifying colorectal cancer patients with high recurrence risk and poor prognosis, optimizing precise treatment and improving clinical efficacy.
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Affiliation(s)
- Xiangchou Yang
- Department of Hematology and Medical Oncology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jieyu Liu
- Department of coloproctology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shuaibin Wang
- Department of Urology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Wail Hussein Ahmed Al-Ameer
- Department of Hematology and Medical Oncology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jingting Ji
- Department of Infectious Disease, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jiaqi Cao
- Department of Hematology and Medical Oncology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Hassan Mansour S Dhaen
- Department of Hematology and Medical Oncology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ying Lin
- Department of Hematology and Medical Oncology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yangyang Zhou
- Department of oncology, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200233, China.
| | - Chenguo Zheng
- Department of coloproctology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
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Bharadwaj HR, Aderinto N, Hasham Ali S, Kirani Tan J, Dhali A, Abbasher Hussein Mohamed Ahmed K. Call for intervention and analysis of the rise in young-onset gastrointestinal cancers in low- and middle-income countries: an editorial. Ann Med Surg (Lond) 2024; 86:2402-2404. [PMID: 38694330 PMCID: PMC11060283 DOI: 10.1097/ms9.0000000000001964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 03/06/2024] [Indexed: 05/04/2024] Open
Affiliation(s)
| | - Nicholas Aderinto
- Internal Medicine Department, LAUTECH Teaching Hospital, Oyo, Nigeria
| | - Syed Hasham Ali
- Faculty of Medicine, Dow Medical College, Dow University of Health Sciences, Karachi, Pakistan
| | | | - Arkadeep Dhali
- Academic Unit of Gastroenterology, Sheffield Teaching Hospitals, Sheffield
- School of Medicine and Population Health, The University of Sheffield, Sheffield
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Zhu M, Zhong X, Liao T, Peng X, Lei L, Peng J, Cao Y. Efficient organized colorectal cancer screening in Shenzhen: a microsimulation modelling study. BMC Public Health 2024; 24:655. [PMID: 38429684 PMCID: PMC10905924 DOI: 10.1186/s12889-024-18201-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 02/23/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is a global health issue with noticeably high incidence and mortality. Microsimulation models offer a time-efficient method to dynamically analyze multiple screening strategies. The study aimed to identify the efficient organized CRC screening strategies for Shenzhen City. METHODS A microsimulation model named CMOST was employed to simulate CRC screening among 1 million people without migration in Shenzhen, with two CRC developing pathways and real-world participation rates. Initial screening included the National Colorectal Polyp Care score (NCPCS), fecal immunochemical test (FIT), and risk-stratification model (RS model), followed by diagnostic colonoscopy for positive results. Several start-ages (40, 45, 50 years), stop-ages (70, 75, 80 years), and screening intervals (annual, biennial, triennial) were assessed for each strategy. The efficiency of CRC screening was assessed by number of colonoscopies versus life-years gained (LYG). RESULTS The screening strategies reduced CRC lifetime incidence by 14-27 cases (30.9-59.0%) and mortality by 7-12 deaths (41.5-71.3%), yielded 83-155 LYG, while requiring 920 to 5901 colonoscopies per 1000 individuals. Out of 81 screening, 23 strategies were estimated efficient. Most of the efficient screening strategies started at age 40 (17 out of 23 strategies) and stopped at age 70 (13 out of 23 strategies). Predominant screening intervals identified were annual for NCPCS, biennial for FIT, and triennial for RS models. The incremental colonoscopies to LYG ratios of efficient screening increased with shorter intervals within the same test category. Compared with no screening, when screening at the same start-to-stop age and interval, the additional colonoscopies per LYG increased progressively for FIT, NCPCS and RS model. CONCLUSION This study identifies efficient CRC screening strategies for the average-risk population in Shenzhen. Most efficient screening strategies indeed start at age 40, but the optimal starting age depends on the chosen willingness-to-pay threshold. Within insufficient colonoscopy resources, efficient FIT and NCPCS screening strategies might be CRC initial screening strategies. We acknowledged the age-dependency bias of the results with NCPCS and RS.
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Affiliation(s)
- Minmin Zhu
- Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen City, 518054, Guangdong, China.
| | - Xuan Zhong
- Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen City, 518054, Guangdong, China
| | - Tong Liao
- Harbin Institute of Technology Shenzhen, Shenzhen City, Guangdong, China
| | - Xiaolin Peng
- Shenzhen Nanshan Center for Chronic Disease Control, Shenzhen City, 518054, Guangdong, China
| | - Lin Lei
- Shenzhen Center for Chronic Disease Control, Shenzhen City, Guangdong, China
| | - Ji Peng
- Shenzhen Center for Chronic Disease Control, Shenzhen City, Guangdong, China
| | - Yong Cao
- Harbin Institute of Technology Shenzhen, Shenzhen City, Guangdong, China
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Dong X, Du L, Luo Z, Xu Y, Wang C, Wang F, Cao W, Zhao L, Zheng Y, Zhu H, Xia C, Li J, Du M, Hang D, Ren J, Shi J, Shen H, Chen W, Li N, He J. Combining fecal immunochemical testing and questionnaire-based risk assessment in selecting participants for colonoscopy screening in the Chinese National Colorectal Cancer Screening Programs: A population-based cohort study. PLoS Med 2024; 21:e1004340. [PMID: 38386617 PMCID: PMC10883529 DOI: 10.1371/journal.pmed.1004340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 12/28/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Screening reduces colorectal cancer (CRC) burden by allowing early resection of precancerous and cancerous lesions. An adequate selection of high-risk individuals and a high uptake rate for colonoscopy screening are critical to identifying people more likely to benefit from screening and allocating healthcare resources properly. We evaluated whether combining a questionnaire-based interview for risk factors with fecal immunochemical test (FIT) outcomes for high-risk assessment is more efficient and economical than a questionnaire-based interview-only strategy. METHODS AND FINDINGS In this multicenter, population-based, prospective cohort study, we enrolled community residents aged 40 to 74 years in 29 provinces across China. From 2016 to 2020, a total of 1,526,824 eligible participants were consecutively enrolled in the Cancer Screening Program in Urban China (CanSPUC) cohort, and 940,605 were enrolled in the Whole Life Cycle of Cancer Screening Program (WHOLE) cohort, with follow-up to December 31, 2022. The mean ages were 56.89 and 58.61 years in CanSPUC and WHOLE, respectively. In the WHOLE cohort, high-risk individuals were identified by combining questionnaire-based interviews to collect data on risk factors (demographics, diet history, family history of CRC, etc.) with FIT outcomes (RF-FIT strategy), whereas in the CanSPUC cohort, high-risk individuals were identified using only interview-based data on risk factors (RF strategy). The primary outcomes were participation rate and yield (detection rate of advanced neoplasm, early-stage detection rate of CRCs [stage I/II], screening yield per 10,000 invitees), which were reported for the entire population and for different gender and age groups. The secondary outcome was the cost per case detected. In total, 71,967 (7.65%) and 281,985 (18.47%) individuals were identified as high-risk and were invited to undergo colonoscopy in the RF-FIT group and RF group, respectively. The colonoscopy participation rate in the RF-FIT group was 26.50% (19,071 of 71,967) and in the RF group was 19.54% (55,106 of 281,985; chi-squared test, p < 0.001). A total of 102 (0.53%) CRCs and 2,074 (10.88%) advanced adenomas were detected by the RF-FIT, versus 90 (0.16%) and 3,593 (6.52%) by the RF strategy (chi-squared test, both p < 0.001). The early-stage detection rate using the RF-FIT strategy was significantly higher than that by the RF strategy (67.05% versus 47.95%, Fisher's exact test, p = 0.016). The cost per CRC detected was $24,849 by the RF-FIT strategy versus $55,846 by the RF strategy. A limitation of the study was lack of balance between groups with regard to family history of CRC (3.5% versus 0.7%). CONCLUSIONS Colonoscopy participation and screening yield were better with the RF-FIT strategy. The association with CRC incidence and mortality reduction should be evaluated after long-term follow-up.
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Affiliation(s)
- Xuesi Dong
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingbin Du
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Zilin Luo
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yongjie Xu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chenran Wang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fei Wang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Cao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Liang Zhao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yadi Zheng
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongting Zhu
- Yongkang Center for Disease Control and Prevention, Yongkang, China
| | - Changfa Xia
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiang Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mulong Du
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Dong Hang
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jiansong Ren
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jufang Shi
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wanqing Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie He
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Wang F, Han Q, Sun RJ, Tu HM, Yang YL, Ren YL. Analysis of the Current Status and Factors Influencing Compliance with Colonoscopic Monitoring After Endoscopic Surgery for Advanced Colorectal Adenoma. Patient Prefer Adherence 2023; 17:3195-3204. [PMID: 38090331 PMCID: PMC10712247 DOI: 10.2147/ppa.s437092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 11/07/2023] [Indexed: 01/02/2024] Open
Abstract
Background Advanced colorectal adenomas are at a risk of malignant transformation following endoscopic resection, and colonoscopic monitoring interval after polypectomy have been widely used. This study aims to investigate the prevailing state of compliance with postoperative colonoscopic surveillance among patients with advanced colorectal adenomas and its' influencing factors at Affiliated Hospital of Jiangnan University between November 2020 and April 2021. Methods A retrospective analysis was conducted on patients who underwent endoscopic treatment for ACA at Affiliated Hospital of Jiangnan University from November 2020 to April 2021. Compliance with postoperative colonoscopic surveillance was assessed based on established guidelines. Factors such as sociodemographic features, medical histories, and health beliefs were analyzed to determine their influence on compliance. Univariate analysis, survival analysis, and multi-factor Cox regression analysis were used for statistical evaluation. Results A total of 511 patients were included in the study. The compliance rate was found to be 43.2%. The univariate analysis indicated that factors such as gender, education level, work status, type of health insurance, place of residence, marital status, type of consultation, presence of gastrointestinal symptoms, number of polyps, and the maximum diameter of polyps significantly affected compliance. Multi-factor Cox regression analysis revealed that female gender, absence of gastrointestinal symptoms, outpatient endoscopic treatment, and solitary polyps were independent factors influencing compliance. Reasons for poor compliance included underestimating the severity of the disease, fear of colonoscopy, and procedural complexities. Conclusion Patients with advanced colorectal adenomas had poor compliance with postoperative colonoscopy monitoring. Tailored health education programs should be designed, targeting women, outpatients undergoing endoscopic procedures, and patients with solitary polyps to enhance their compliance with colonoscopy monitoring.
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Affiliation(s)
- Fei Wang
- Wuxi School of Medicine, Jiangnan University, Wuxi, 214122, People’s Republic of China
| | - Qian Han
- Center of Endoscopy, Affiliated Hospital of Jiangnan University, Wuxi, 214062, People’s Republic of China
| | - Ren-Juan Sun
- Department of Nutrition, Affiliated Hospital of Jiangnan University, Wuxi, 214062, People’s Republic of China
| | - Hui-Ming Tu
- Department of Gastroenterology, Affiliated Hospital of Jiangnan University, Wuxi, 214062, People’s Republic of China
| | - Yu-Ling Yang
- Department of Oncology, Affiliated Hospital of Jiangnan University, Wuxi, 214062, People’s Republic of China
| | - Yi-Lin Ren
- Department of Gastroenterology, Affiliated Hospital of Jiangnan University, Wuxi, 214062, People’s Republic of China
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