Evidence map›Paper›PMID 41216224›Full record

ArticleExploration of targeted anti-tumor therapy2025

Racial disparities in hepatocellular carcinoma: a TCGA-based gene expression study of Caucasian and Asian populations.

Muhammad Rezki Rasyak, Sri Jayanti, Cyrollah Disoma, Bens Pardamean, Caecilia Sukowati

Abstract read
In one paragraph

Article in Exploration of targeted anti-tumor therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Muhammad Rezki RasyakBioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta 11480, Indonesia.ORCID https://orcid.org/0000-0002-4016-4072
Sri JayantiEijkman Research Center for Molecular Biology, National Research and Innovation Agency (BRIN), Central Jakarta 10340, Indonesia.ORCID https://orcid.org/0000-0003-4554-504X
Cyrollah DisomaLiver Cancer Unit, Fondazione Italiana Fegato ONLUS, AREA Science Park, Campus Basovizza, 34149 Trieste, Italy.ORCID https://orcid.org/0000-0002-7916-6606
Bens PardameanBioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta 11480, Indonesia.ORCID https://orcid.org/0000-0002-7404-9005
Caecilia SukowatiEijkman Research Center for Molecular Biology, National Research and Innovation Agency (BRIN), Central Jakarta 10340, Indonesia.ORCID https://orcid.org/0000-0001-9699-7578

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Hepatocellular carcinoma (HCC) displays both shared and ethnicity-specific molecular characteristics. Using transcriptomic data from The Cancer Genome Atlas (TCGA), we compared gene expression profiles between Asian and Caucasian HCC patients. Methods: Gene expression profiles were analyzed using the PyDESeq2 implementation of DESeq2, applying size factor normalization and dispersion estimation. Differentially expressed genes (DEGs) were identified with thresholds of false discovery rate (FDR) of < 0.05 and |log Results: A total of 387 and 250 genes were commonly upregulated and downregulated, respectively, in both populations, including the upregulations of Conclusions: These findings highlight key molecular differences in HCC across ethnicities and emphasize the value of TCGA data for identifying both shared targets and population-specific therapeutic strategies. Understanding these differences is crucial for advancing precision oncology and developing tailored interventions.

Indexed as

gene expressionhepatocellular carcinomapopulationsTCGA

Identifiers

PMID41216224
PMCPMC12597399

What OpenQuestion holds

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Registered trials

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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.