ArticleAsian Pacific journal of cancer prevention : APJCP2022
Evaluation of miRNA 223/125a and COBLL1 Expressions and ROR-1 Levels as Reliable Markers in B- chronic Lymphocytic Leukemia.
Article in Asian Pacific journal of cancer prevention : APJCP, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 4 citations in OpenAlex.
- Multiplexed single-cell transcriptomics reveals diverse phenotypic outcomes for pathogenic SHP2 variants.Science advances · 2026Article
- Prognostic Significance of miR-145, NANOG, OCT4, and KLF4 in Triple-Negative Breast Cancer.Asian Pacific journal of cancer prevention : APJCP · 2026Article
- MicroRNAs: Potential prognostic and theranostic biomarkers in chronic lymphocytic leukemia.EJHaem · 2024Review
- Gene-Nutrient Interactions in Obesity:International journal of molecular sciences · 2023Article
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundmiRNA 223 /125a and Cordon-bleu Protein Like 1 (COBLL1) are novel biomarkers that can predict prognosis and guide treatment decisions in patients with chronic lymphocytic leukemia (CLL). Also, there is a growing interest in CLL monitoring based on flow cytometry of receptor tyrosine kinase-like orphan receptor-1 (ROR-1). Objective: This study aimed to evaluate the relationship between miRNA 223 /125a and COBLL1 expressions and ROR-1 expression in patients with CLL. Also, the study evaluated the relationship between the expression of these biomarkers with tumor staging and cancer progression.
methodsOur study included 40 patients newly diagnosed with B-CLL. In peripheral blood (PB), miRNA 223/125a and COBLL1 expressions were detected by real-time polymerase chain reaction (real-time PCR) and ROR-1 percentage was detected by flow cytometry before and after treatment. Results: High level of COBLL1 expression was statistically significantly associated with high ROR-1 percentage expression (P= 0.03). However, a high level of miRNA 223/125a expression was statistically significantly associated with low ROR-1 percentage expression (P=0.002). The sensitivity and specificity of ROR-1 as a predictor of high WBCs count after treatment were 96.6 and 81.1%, respectively. There was a statistically significant reduction of ROR-1 percentage after treatment compared to before treatment (P <0.001).
conclusionROR-1 percentage expression can be considered a possible prognostic predictor in CLL along with miRNA 223/125a and COBLL1 expressions. This can be explained by the significant correlation between ROR-1 and the studied molecular biomarkers; miRNA 223/125a and COBLL1. In addition, there was a significantly higher ROR-1 percentage in patients with higher WBC counts. Moreover, there was a significant reduction in ROR-1 percentage after treatment.
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.