ArticleBioscience reports2020
Time series expression pattern of key genes reveals the molecular process of esophageal cancer.
Article in Bioscience reports, 2020. 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 It has been retracted, and should not be counted.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 1 paper.
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
1 citing paper in PubMed, 3 citations in OpenAlex.
- VIVA1: a more invasive subclone of MDA-MB-134VI invasive lobular carcinoma cells with increased metastatic potential in xenograft models.British journal of cancer · 2022Article
Corrections and comments
- Retracted
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEsophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease is still elusive.
aimTo investigate the molecular process of esophageal cancer comprehensively and deeply.
methodsDifferential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer. Then exacting gene interaction modules and hub genes were identified in module interaction network. Further, though survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related function or pathway were identified to elucidate potential mechanism in esophageal cancer.
resultsA total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding and other biological processes (BPs), as well as p53 signaling pathway, ERBB signaling pathway and epidermal growth factor receptor (EGFR) signaling pathway. Then, transcription factors (TFs) (including HIF1A) and ncRNAs (including CRNDE and hsa-mir-330-3p) significantly regulate dysfunction modules were identified. Further, survival analysis showed that GNGT2 was closely related to survival of esophageal cancer. And DEGs with strong methylation regulation ability were identified, including SST and SH3GL2.
conclusionThese works not only help us to reveal the potential regulatory factors in the development of disease, but also deepen our understanding of its deterioration mechanism.
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.