ArticleCells2023
Using Single-Cell RNA Sequencing and MicroRNA Targeting Data to Improve Colorectal Cancer Survival Prediction.
Article in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Survival prediction landscape: an in-depth systematic literature review on activities, methods, tools, diseases, and databases.Frontiers in artificial intelligence · 2024Pooled it
- Artificial intelligence models for survival prediction in colorectal cancer: a systematic review of time-to-event approaches.Annals of medicine and surgery (2012) · 2026Article
- Diagnostic and Therapeutic Potential of Selected microRNAs in Colorectal Cancer: A Literature Review.Cancers · 2025Review
- Application of single-cell sequencing in the study of immune cell infiltration in inflammatory bowel disease and colorectal cancer.World journal of gastrointestinal oncology · 2025Review
- Application of single cell sequencing technology in ovarian cancer research (review).Functional & integrative genomics · 2024Review
- Single-cell transcriptomics reveals stage- and side-specificity of gene modules in colorectal cancer.Research square · 2024Article
- The Demographic Profile of Colorectal Cancer Patients in Indonesia: Insights from a Single Center Experience and Exploration of Immune Response and Survival Outcomes.F1000Research · 2024Article
- Deciphering colorectal cancer progression features and prognostic signature by single-cell RNA sequencing pseudotime trajectory analysis.Biochemistry and biophysics reports · 2023Article
- Regulatory Roles of Non-Coding RNAs in Cancer.Cells · 2023Article
- Dynamics of Epithelial-Mesenchymal Plasticity: What Have Single-Cell Investigations Elucidated So Far?ACS omega · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Colorectal cancer has proven to be difficult to treat as it is the second leading cause of cancer death for both men and women worldwide. Recent work has shown the importance of microRNA (miRNA) in the progression and metastasis of colorectal cancer. Here, we develop a metric based on miRNA-gene target interactions, previously validated to be associated with colorectal cancer. We use this metric with a regularized Cox model to produce a small set of top-performing genes related to colon cancer. We show that using the miRNA metric and a Cox model led to a meaningful improvement in colon cancer survival prediction and correct patient risk stratification. We show that our approach outperforms existing methods and that the top genes identified by our process are implicated in NOTCH3 signaling and general metabolism pathways, which are essential to colon cancer progression.
Indexed as
Identifiers
What OpenQuestion holds
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.