ArticleBiomarkers in medicine2009
Approaches to biomarkers in human colorectal cancer: looking back, to go forward.
Article in Biomarkers in medicine, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Identification of interconnected markers for T-cell acute lymphoblastic leukemia.BioMed research international · 2013Pooled it
- Hypermethylation of ITGA4, TFPI2 and VIMENTIN promoters is increased in inflamed colon tissue: putative risk markers for colitis-associated cancer.Journal of cancer research and clinical oncology · 2015Article
- Proteomics for discovery of candidate colorectal cancer biomarkers.World journal of gastroenterology · 2014Review
- Identification of novel mouse genes conferring posthypoxic pauses.Journal of applied physiology (Bethesda, Md. : 1985) · 2012Article
- Cell surface markers in colorectal cancer prognosis.International journal of molecular sciences · 2010Review
- Restructuring proteomics through verification.Biomarkers in medicine · 2010Review
- Reconstructing the pipeline by introducing multiplexed multiple reaction monitoring mass spectrometry for cancer biomarker verification: an NCI-CPTC initiative perspective.Proteomics. Clinical applications · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Like all human cancers, colorectal cancer is a complicated disease. While a mature body of research involving colorectal cancer has implicated the putative sequence of genetic alterations that trigger the disease and sustain its progression, there is a surprising paucity of well-validated, clinically useful diagnostic markers of this disease. For prognosis or guiding therapy, single gene-based markers of colorectal cancer often have limited specificity and sensitivity. Genome-wide analyses (microarrays) have been used to propose candidate patterns of gene expression that are prognostic of outcome or predict the tumor's response to a therapy regimen; however, these patterns frequently do not overlap, and this has raised questions concerning their use as biomarkers. The limitation of gene-expression approaches to marker discovery occurs because the change in mRNA expression across tumors is highly variable and, alone, accounts for a limited variability of the phenotype, such as with cancer. More robust and accurate markers of cancer will result from integrating all the information we have about the cell: genomics, proteomics and interactomics. This article will discuss traditional markers in colorectal cancer, both genomic and proteomic, including their respective approaches and limitations, then conclude with examples of systems biology-based approaches for candidate marker discovery, and discuss how this approach is reshaping our view of a biomarker.
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.