ArticleNature communications2024
Plasma proteomic and polygenic profiling improve risk stratification and personalized screening for colorectal cancer.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed.
- Colorectal Cancer: Epidemiology, Risk Factors, Signaling Pathways, Clinical Features, Screening, Diagnosis, and Management.MedComm · 2026Review
- Defining Age to Screen and Real-World Effectiveness for Early-Onset Colorectal Cancer.Cancer science · 2026Article
- Large-scale plasma proteomics improves prediction of heart failure among MASLD individuals: A prospective cohort study.American journal of preventive cardiology · 2026Article
- Article
- Decoding the human gut bacterial plasmids in colorectal cancer.Communications biology · 2026Article
- Early-onset colorectal cancer: a comprehensive review reframing hypotheses and defining research priorities.International journal of colorectal disease · 2026Review
- Knowledge, Symptom Awareness, and Referral Practices of Primary Care Providers in Early-Onset Colorectal Cancer.Population health management · 2026Article
- Global research trends in diagnostic biomarkers for colorectal cancer: a bibliometric and visualization analysis.Annals of medicine and surgery (2012) · 2026Article
- Gut fungal landscape in colorectal cancer and its cross-kingdom interplay with gut microbial ecology.iScience · 2026Article
- Plasma Proteomic Signatures for Diverticulitis Risk Stratification.The Journal of surgical research · 2026Article
- Polygenic risk score-guided personalized osteoporosis screening: a population-based study.BMC medicine · 2026Article
- AI-enabled multi-omics integration in colorectal cancer: from molecular stratification to clinical translation.Frontiers in cell and developmental biology · 2026Review
- GDF15-integrated blood biomarker panel for risk stratification of digestive malignancies: a multicenter retrospective study.Frontiers in pharmacology · 2026Article
- Integrative Machine Learning and Experimental Validation Identify MYBL2 as a Prognostic Biomarker and Therapeutic Target in Hepatocellular Carcinoma.Oncology research · 2026Article
- Tailored Therapeutic Strategies for Fetuses, Neonates, Pediatrics, Geriatrics, Athletes, and Critical Cases in the Era of Personalized Medicine.Diseases (Basel, Switzerland) · 2025Review
- Dynamic screening initiation using 16 plasma protein biomarkers with polygenic risk and PLCOm2012: a precision prevention framework for lung cancer.Journal of translational medicine · 2025Article
- Emerging hallmarks and the rise of complexities and heterogeneity of tumor.Biochemistry and biophysics reports · 2025Review
- Plasma-derived exosomal tRF-3004a as a diagnostic biomarker for colorectal cancer.Scientific reports · 2025Article
- Integrating prognosis-related genes with immune-related gene signature for development and validation of a survival stratification model for early-stage colorectal cancer.Translational cancer research · 2025Article
- Review
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
This study aims to identify colorectal cancer (CRC)-related proteomic profiles and develop a prediction model for CRC onset by integrating proteomic profiles with genetic and non-genetic factors (QCancer-15) to improve the risk stratification and estimate of personalized initial screening age. Here, using a two-stage strategy, we prioritize 15 protein biomarkers as predictors to construct a protein risk score (ProS). The risk prediction model integrating proteomic profiles with polygenic risk score (PRS) and QCancer-15 risk score (QCancer-S) shows improved performance (C-statistic: 0.79 vs. 0.71, P = 4.94E-03 in training cohort; 0.75 vs 0.69, P = 5.49E-04 in validation cohort) and net benefit than QCancer-S alone. The combined model markedly stratifies the risk of CRC onset. Participants with high ProS, PRS, or combined risk score are proposed to start screening at age 46, 41, or before 40 years old. In this work, the integration of blood proteomics with PRS and QCancer-15 demonstrates improved performance for risk stratification and clinical implication for the derivation of risk-adapted starting ages of CRC screening, which may contribute to the decision-making process for CRC screening.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.