ReviewCancers2023
Amino Acid Profiles in the Biological Fluids and Tumor Tissue of CRC Patients.
Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Spatially Resolved Metabolomic Profiling Reveals Progression-Associated Metabolic Reprogramming in Colorectal Liver Metastasis.Metabolites · 2026Article
- Characteristics of gut microbiota and metabolites in patients with metabolic dysfunction-associated steatotic liver disease and colorectal adenoma.Scientific reports · 2026Article
- From exposure to oncogenesis: a review on the multifaceted roles of microplastics in tumor initiation and progression.Journal of translational medicine · 2025Review
- Identification of Salivary Biomarkers in Colorectal Cancer by Integrating Olink Proteomics and Metabolomics.Journal of proteome research · 2025Article
- Advances in colorectal cancer screening: technological innovations, guideline discrepancies, and individualized strategies.Frontiers in oncology · 2025Review
- Integrating multi-omics and machine learning methods reveals the metabolism of amino acids and derivatives-related signature in colorectal cancer.Frontiers in oncology · 2025Article
- Exploration of the application potential of serum multi-biomarker model in colorectal cancer screening.Scientific reports · 2024Article
- Current Advances of Nanomaterial-Based Oral Drug Delivery for Colorectal Cancer Treatment.Nanomaterials (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Amino acids are the building blocks of proteins and essential players in pathways such as the citric acid and urea cycle, purine and pyrimidine biosynthesis, and redox cell signaling. Therefore, it is unsurprising that these molecules have a significant role in cancer metabolism and its metabolic plasticity. As one of the most prevalent malign diseases, colorectal cancer needs biomarkers for its early detection, prognostic, and prediction of response to therapy. However, the available biomarkers for this disease must be more powerful and present several drawbacks, such as high costs and complex laboratory procedures. Metabolomics has gathered substantial attention in the past two decades as a screening platform to study new metabolites, partly due to the development of techniques, such as mass spectrometry or liquid chromatography, which have become standard practice in diagnostic procedures for other diseases. Extensive metabolomic studies have been performed in colorectal cancer (CRC) patients in the past years, and several exciting results concerning amino acid metabolism have been found. This review aims to gather and present findings concerning alterations in the amino acid plasma pool of colorectal cancer patients.
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.