ReviewCells2021
Prognostic Cancer Gene Expression Signatures: Current Status and Challenges.
Review in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.
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
62 citing papers in PubMed.
- Improved prognostic survival models for pediatric medulloblastoma using high dimensional gene expression data.BMC medical genomics · 2026Article
- Transcriptomic Evidence of Immune-Tumor Uncoupling Defines a High-Risk State in Uterine Corpus Endometrial Carcinoma.International journal of molecular sciences · 2026Article
- Article
- Comprehensive Landscape of Diagnostic, Prognostic and Predictive Biomarkers in Colorectal Cancer: From Genomics to Multi-Omics Integration in Precision Medicine.Journal of personalized medicine · 2026Review
- Article
- Whole tumor transcriptome: a possibility for diagnosis, prognosis, and therapy in precision oncology using computational analysis.Frontiers in medicine · 2026Article
- Genomic and Epigenomic Signatures Can Distinguish Aggressive Chromophobe Renal Cell Carcinoma from Indolent Renal Oncocytic Tumors in Clinical-grade Samples.European urology oncology · 2025Article
- Toward the Best Generalizable Performance of Machine Learning in Modeling Omic and Clinical Data.Laboratory investigation; a journal of technical methods and pathology · 2025Article
- A parametric survival model with bayesian structural equation based on multi-omics integration.BMC bioinformatics · 2025Article
- The Emerging Role of FAM171A2 in Gynecological Malignancies: Bioinformatic Insights from UCEC and Ovarian Cancer.International journal of molecular sciences · 2025Article
- Molecular Prognosticators Guiding Fertility-Sparing Surgery in Early-Stage Endometrial Cancer: A Comprehensive Review.Cancers · 2025Review
- Machine learning analysis reveals tumor heterogeneity and stromal-immune niches in breast cancer.NPJ digital medicine · 2025Article
- Emerging therapeutics targeting tumor-associated macrophages for the treatment of solid organ cancers.Expert opinion on emerging drugs · 2025Review
- Comprehensive Analysis of Granzymes and Perforin Family Genes in Multiple Cancers.Biomedicines · 2025Article
- A Narrative Review of Prognostic Gene Signatures in Oral Squamous Cell Carcinoma Using LASSO Cox Regression.Biomedicines · 2025Review
- Article
- Mapping the state-of-the-art of the barriers for personalized preventive approaches worldwide: A scoping review of reviews.PloS one · 2025Article
- Article
- Identification of Prognostic and Diagnostic Biomarkers for Glioma Utilizing Immune System Gene Profiling.Medical journal of the Islamic Republic of Iran · 2025Article
- Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.International journal of molecular sciences · 2024Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Current staging systems of cancer are mainly based on the anatomical extent of disease. They need refinement by biological parameters to improve stratification of patients for tumor therapy or surveillance strategies. Thanks to developments in genomic, transcriptomic, and big-data technologies, we are now able to explore molecular characteristics of tumors in detail and determine their clinical relevance. This has led to numerous prognostic and predictive gene expression signatures that have the potential to establish a classification of tumor subgroups by biological determinants. However, only a few gene signatures have reached the stage of clinical implementation so far. In this review article, we summarize the current status, and present and future challenges of prognostic gene signatures in three relevant cancer entities: breast cancer, colorectal cancer, and hepatocellular carcinoma.
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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.