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Record W4322154777 · doi:10.1016/j.jhepr.2023.100715

A genomic enhancer signature associates with hepatocellular carcinoma prognosis

2023· article· en· W4322154777 on OpenAlex
Ah‐Jung Jeon, Chukwuemeka George Anene-Nzelu, Yue-Yang Teo, Shay Lee Chong, Karthik Sekar, Lingyan Wu, Sin-Chi Chew, Jianbin Chen, Raden Indah Kendarsari, Hannah Lai, Wen Huan Ling, Neslihan Arife Kaya, Jia Qi Lim, Alexander Yaw Fui Chung, Peng Chung Cheow, Juinn Huar Kam, Krishnakumar Madhavan, Alfred Wei Chieh Kow, Shridhar Ganpathi Iyer, Tony Kiat Hon Lim, Wei Qiang Leow, Shihleone Loong, Tracy Jiezhen Loh, Wei Wan, Gwyneth Shook Ting Soon, Yin Huei Pang, Boon Koon Yoong, Diana Bee‐Lan Ong, Jasmine Lim, Vanessa H. de Villa, Rouchelle D.dela Cruz, Rawisak Chanwat, Jidapa Thammasiri, Glenn Kunnath Bonney, Brian K. P. Goh, Roger Foo, Pierce K. H. Chow

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJHEP Reports · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersNational Medical Research CouncilMedical Research Council
KeywordsHepatocellular carcinomaEnhancerSignature (topology)Cancer researchComputational biologyBiologyGeneticsGeneGene expressionMathematics

Abstract

fetched live from OpenAlex

Background & Aims: Lifestyle and environmental-related exposures are important risk factors for hepatocellular carcinoma (HCC), suggesting that epigenetic dysregulation significantly underpins HCC. We profiled 30 surgically resected tumours and the matched adjacent normal tissues to understand the aberrant epigenetic events associated with HCC. Methods: We identified tumour differential enhancers and the associated genes by analysing H3K27 acetylation (H3K27ac) chromatin immunoprecipitation sequencing (ChIP-seq) and Hi-C/HiChIP data from the resected tumour samples of 30 patients with early-stage HCC. This epigenome dataset was analysed with previously reported genome and transcriptome data of the overlapping group of patients from the same cohort. We performed patient-specific differential expression testing using multiregion sequencing data to identify genes that undergo both enhancer and gene expression changes. Based on the genes selected, we identified two patient groups and performed a recurrence-free survival analysis. Results: , but much of the enhancer and gene expression changes were patient-specific. A subset of the upregulated genes was activated in a subgroup of patients' tumours. Recurrence-free survival analysis revealed that the patients with a more robust upregulation of those genes showed a worse prognosis. Conclusions: We report the genomic enhancer signature associated with differential prognosis in HCC. Findings that cohere with oncofoetal reprogramming in HCC were underpinned by genome-wide enhancer rewiring. Our results present the epigenetic changes in HCC that offer the rational selection of epigenetic-driven gene targets for therapeutic intervention or disease prognostication in HCC. Impact and Implications: Lifestyle and environmental-related exposures are the important risk factors of hepatocellular carcinoma (HCC), suggesting that tumour-associated epigenetic dysregulations may significantly underpin HCC. We profiled tumour tissues and their matched normal from 30 patients with early-stage HCC to study the dysregulated epigenetic changes associated with HCC. By also analysing the patients' RNA-seq and clinical data, we found the signature genes - with epigenetic and transcriptomic dysregulation - associated with worse prognosis. Our findings suggest that systemic approaches are needed to consider the surrounding cellular environmental and epigenetic changes in HCC tumours.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.229
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it