Table 1_Integrative transcriptomic analysis reveals miR-26a-5p downregulation and a potent

A 1.1 MB Excel dataset from figshare, last updated April 20, 2026, by author Andrei Sorop. It contains integrative transcriptomic analysis results linking miR-26a-5p downregulation to the progression from metabolic liver disease to hepatocellular carcinoma. The data includes a proposed predictive gene signature based on EpCAM, DTNA, and KPNA2.

Use Cases

• Validate the proposed miR-26a-5p-associated gene signature for stratifying metabolic liver disease patients based on the description.
• Investigate the relationship between miR-26a-5p expression and antitumor immunity in hepatocellular carcinoma samples as suggested by the in silico analysis.
• Correlate transcriptomic signatures with oncogenic signaling via the β-catenin/c-Myc/EpCAM axis described in the mechanistic findings.
• Benchmark new predictive models for liver disease progression against the identified gene signature (EpCAM, DTNA, KPNA2).

Strengths

• Data integrates findings from mouse models, public transcriptomic datasets, and in vitro experiments, as described.
• Dataset is licensed under CC-BY-4.0, permitting open sharing and adaptation.
• File size is 1.1 MB, making it quick to download and inspect.

Limitations

• Row count and column-level documentation are unknown, which may limit suitability assessment.
• The dataset's specific sample composition and preprocessing steps are not detailed in the provided metadata.

Provenance

Source

figshare, author Andrei Sorop.

Collection Method

Integrative bioinformatics analysis of public transcriptomic datasets and experimental validation, as described.

Time Range

Temporal coverage of the underlying data is not specified.

Freshness

Last updated 2026-04-20 05:23:30; freshness should be verified.

Geography

Spatial coverage is not specified.