Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma

The discovery of the 13 conserved genes is an important step toward understanding HCC heterogeneity and the TME, potentially leading to the identification of more reliable biomarkers and therapeutic targets. We have stratified and validated the liver cancer populations. The findings suggest further research is needed to explore additional factors influencing the TME beyond gene expression, such as tumour microbiome and stromal cell interactions.

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Publication Details

Journal
BMC Cancer
Published
2025-05-10
DOI
https://doi.org/10.1186/s12885-025-14242-5
Citations
2
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
3.04
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article

Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma

Animesh Acharjee, Mae Montserrat Reierson
2 citations
BMC Cancer
Ferroptosis and cancer prognosis
3.04
article

Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma

Animesh Acharjee, Mae Montserrat Reierson
article en
2 citations

Abstract

The discovery of the 13 conserved genes is an important step toward understanding HCC heterogeneity and the TME, potentially leading to the identification of more reliable biomarkers and therapeutic targets. We have stratified and validated the liver cancer populations. The findings suggest further research is needed to explore additional factors influencing the TME beyond gene expression, such as tumour microbiome and stromal cell interactions.

BMC CancerVol. 25(1)
University of Birmingham (GB)
Zero hunger
Openalex Percentile: Top 10%
Ferroptosis and cancer prognosis
3.04
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