ArticleOncoTargets and therapy2021
HS3ST2 and Its Related Molecules as Potential Biomarkers for Predicting Lymph Node Metastasis in Patients with Colorectal Cancer.
Article in OncoTargets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 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
2 citing papers in PubMed, 2 citations in OpenAlex.
- Identification and verification of microRNA signature and key genes in the development of osteosarcoma with lung metastasis.Medicine · 2022Article
- COL3A1 and Its Related Molecules as Potential Biomarkers in the Development of Human Ewing's Sarcoma.BioMed research international · 2021Article
Corrections and comments
- Retraction · 2022-09-23Duplication of/in Article · Lack of Approval from Author ·
- Retracted
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLymph node metastasis is a major cause of cancer-related death in patients with colorectal cancer (CRC), but current strategies are limited to predicting this clinical behavior. Our study aims to establish a lymph node metastasis prediction model based on miRNA and mRNA to improve the accuracy of prediction.
methodsGSE56350, GSE70574, and GSE95109 were downloaded from the Gene Expression Omnibus (GEO) database and 569 colorectal cancer statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs were calculated by using R software. Besides, gene ontology and enriched pathway analysis of target mRNAs were analyzed by using FunRich. Furthermore, the mRNA-miRNA network was constructed using Cytoscape software. Gene expression level was also detected by performing qRT-PCR (quantitative real-time PCR) in colorectal cancer and lymph node tissues.
resultsIn total, 5 differentially expressed miRNAs were selected, and 34 mRNAs were identified after filtering. The research of KEGG indicated that mRNAs are enriched in many cancer pathways. Differentially expressed miRNAs were most enriched in the cytoplasm, nucleoside, transcription factor activity, and RNA binding. KEGG pathway analysis of these target genes was mainly enriched in 5 pathways including fatty acid elongation, MAPK signaling pathway, autophagy, signaling pathways regulating pluripotency of stem cells, and Th17 cell differentiation. The results of qRT-PCR indicated that hsa-miR-100 and hsa-miR-99a were differentially expressed in lymph node metastatic colorectal cancer tissues and lymph node non-metastasis tissues which all target HS3ST2. Besides, we also found they have a significant difference in colorectal cancer tissues compared with normal tissues.
conclusionBy using microarray and bioinformatics analyses, differentially expressed miRNAs were identified and a complete gene network was constructed. To our knowledge, HS3ST2 and related molecules including hsa-miR-100 and hsa-miR-99a were firstly identified as potential biomarkers in the development of lymph node metastatic colorectal cancer.
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.