ReviewCancer drug resistance (Alhambra, Calif.)2021
Overview of microRNAs as liquid biopsy biomarkers for colorectal cancer sub-type profiling and chemoresistance.
Review in Cancer drug resistance (Alhambra, Calif.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 10 citations in OpenAlex.
- Colorectal cancer: a comprehensive review of carcinogenesis, diagnosis, and novel strategies for classified treatments.Cancer metastasis reviews · 2024Review
- Medical Relevance, State-of-the-Art and Perspectives of "Sweet Metacode" in Liquid Biopsy Approaches.Diagnostics (Basel, Switzerland) · 2024Review
- Tumor Suppressor MicroRNAs in Clinical and Preclinical Trials for Neurological Disorders.Pharmaceuticals (Basel, Switzerland) · 2024Review
- The Role of microRNAs in Epigenetic Regulation of Signaling Pathways in Neurological Pathologies.International journal of molecular sciences · 2023Review
- Expression of specific microRNAs in tissue and plasma in colorectal cancer.Journal of pathology and translational medicine · 2023Article
- microRNAs in Liquid Biopsy: The Way to a Simple and Rapid Test for Early Colorectal Cancer Diagnosis?Cancers · 2023Article
- Integrated Bioinformatics Analysis Reveals Novel miRNA as Biomarkers Associated with Preeclampsia.Genes · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is the third most common cancer worldwide. It has also been demonstrated that over the last ten years the incidence of CRC among younger people below the age of 50 is also increasing. Screening for colorectal cancer is of utmost importance; the rationale behind screening is to target the malignancy and reduce the incidence and mortality of the disease. Diagnostic methods to screen for incidence or relapse are therefore a requisite to detect cancer as early as possible. Scientific findings demonstrate that many deaths are due to lack of screening and therefore early identification will lead to greater survivability. In colorectal cancer, diagnostic tests include liquid biopsy biomarkers. Since the discovery of microRNAs (miRNAs), many studies have demonstrated the relationship between miRNAs and the various sub-types of CRC. Several miRNAs have been identified after analysing serum or plasma samples in patients, and such miRNAs were found to be significantly dysregulated. Such findings place the possibility of miRNAs to be at the epicentre of novel diagnostic techniques for CRC identification and sub-type stratification, including other characteristics associated with CRC development such as patient prognosis. The following review serves to underline the latest findings for miRNAs with such potential for routine diagnostic employment in CRC diagnostics and treatments.
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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.