Evidence map›Paper›PMID 38499648›Full record

ReviewCancer gene therapy2024

Heterogeneity of hepatocellular carcinoma: from mechanisms to clinical implications.

Fatema Safri, Romario Nguyen, Shadi Zerehpooshnesfchi, Jacob George, Liang Qiao

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Cancer gene therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
104citing papers in PubMed, 4 pooled it
–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

104 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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44 more citing papers are in PubMed but not listed here.

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.

Fatema SafriStorr Liver Centre, The Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, 2145, Australia.ORCID 0009-0006-0942-1700
Romario NguyenStorr Liver Centre, The Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, 2145, Australia.
Shadi ZerehpooshnesfchiStorr Liver Centre, The Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, 2145, Australia.ORCID 0009-0005-1472-7563
Jacob GeorgeStorr Liver Centre, The Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, 2145, Australia. Jacob.george@sydney.edu.au.
Liang QiaoStorr Liver Centre, The Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, 2145, Australia. liang.qiao@sydney.edu.au.ORCID 0000-0002-4723-8935

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAnimalsGenetic HeterogeneityHumans

Identifiers

PMID38499648
PMCPMC11327108

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.