Evidence map›Paper›PMID 41428609›Full record

ArticleOncology2026

Transcriptomic Characterization of North Queensland Hepatocellular Carcinoma.

Rhys Gillman, Miriam Wankell, Eun Jin Sun, Matan Ben David, Rozemary Karamatic, Pranavan Palamuthusingam, Matt A Field, Ulf Schmitz, Lionel Hebbard

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncology, 2026. 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. Article
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

9 authors.

Rhys GillmanDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Miriam WankellDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Eun Jin SunDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Matan Ben DavidDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Rozemary KaramaticDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Pranavan PalamuthusingamDepartment of Surgery, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
Matt A FieldDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Ulf SchmitzDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia.
Lionel HebbardDepartment of Biomedical Sciences and Molecular and Cell Biology, College of Medicine and Dentistry, College of Science and Engineering, James Cook University, Townsville, Queensland, Australia, lionel.hebbard@jcu.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

<p>Introduction: Hepatocellular carcinoma (HCC) is a growing burden, particularly in rural, regional, and remote areas, but samples from these communities are underrepresented in public cancer data repositories. It remains unclear whether the findings of large, commonly studied cohorts such as The Cancer Genome Atlas (TCGA) are applicable to these remote communities.

methodsWe profiled paired tumour and adjacent non-tumour liver biopsies from 19 patients admitted to the Townsville University Hospital in rural Australia. We used RNA-seq to characterize transcriptomic and mutational features and compared these with the TCGA Liver Hepatocellular Carcinoma (LIHC) cohort. Furthermore, we used these data to test a transcriptome-only adaptation of our TARGET-SL pipeline for low-cost drug target prediction.

resultsDifferential expression analysis identified 923 genes altered in our cohort, of which 64% overlapped with TCGA-LIHC, and the cohort-mean gene expression correlated strongly (Spearman rho = 0.96). Somatic variant calling from RNA highlighted mutational heterogeneity, with CTNNB1 (47%) and TP53 (21%) the most frequently mutated genes, consistent with TCGA findings. Copy number inference detected recurrent deletions on 8p, 6q, and 17p, congruous with known HCC patterns. We ran TARGET-SL solely on RNA-seq to identify personalized driver genes in these patients and were able to identify a drug candidate in 63% of patients.

conclusionOur results demonstrate that NQ HCC shares core molecular features with larger TCGA cohorts and that a transcriptome-based approach can feasibly support precision oncology in resource-limited regional settings. </p>.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsTranscriptomeAgedbeta CateninFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedMutationQueenslandbeta CateninCTNNB1 protein, humanDriver genesHepatocellular carcinomaLiver cancerRural areaTranscriptome

Identifiers

PMID41428609
PMCPMC12823099

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LicenceCC BY-NC
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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.