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Cancer-Critical Genes II: Tumor Suppressor Genes

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...

Cancer-Critical Genes II: Tumor Suppressor Genes

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...

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Updated: Jul 3, 2026

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

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Published on: February 28, 2021

Integrative transcriptomic and CRISPR dependency analysis identifies hepatoblastoma-specific essential genes and

Christophe Desterke¹, Ana Jarén², Raquel Francés³

¹Université Paris-Saclay, Faculté de Médecine, INSERM-UMRS1310, Villejuif, France.

Cancer Genetics

|July 1, 2026

Summary

This study identifies key genes essential for hepatoblastoma (HB) and develops a predictive signature for tumor identification. It also highlights HDAC11 as a potential therapeutic target for drug repurposing in pediatric cancer.

Keywords:

CRISPR dependency map Deep learning Drug–gene interactions Esssential genes Hepatoblastoma Single-cell RNA sequencing

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Investigation of Genetic Dependencies Using CRISPR-Cas9-based Competition Assays

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Published on: January 7, 2019

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Last Updated: Jul 3, 2026

Functional Assessment of BRCA1 variants using CRISPR-Mediated Base Editors

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Published on: February 28, 2021

Investigation of Genetic Dependencies Using CRISPR-Cas9-based Competition Assays

Investigation of Genetic Dependencies Using CRISPR-Cas9-based Competition Assays

Published on: January 7, 2019

Area of Science:

Oncology
Genomics
Bioinformatics

Background:

Hepatoblastoma (HB) is the most common childhood liver cancer, but its molecular drivers are not fully understood.
Identifying essential genes and biomarkers is crucial for improving diagnosis and treatment.

Purpose of the Study:

To identify genes essential for hepatoblastoma (HB) growth and survival.
To develop a molecular signature for accurate tumor identification and patient stratification.
To uncover potential therapeutic targets and repurposing strategies for HB.

Main Methods:

Integrated transcriptomic profiling with CRISPR-Cas9 dependency data to identify HB-essential genes.
Developed a 16-gene predictive signature using Elastic Net regression, validated in independent cohorts.
Utilized single-cell RNA-seq and deep learning for cell-type-specific expression analysis and tumor classification.
Analyzed drug-gene interactions to identify actionable therapeutic targets.

Main Results:

Identified 73 HB-essential genes not found in adult liver cancers.
The 16-gene signature achieved high accuracy (AUC > 0.99) in distinguishing HB from normal liver.
Deep learning classifier accurately differentiated tumor cells from hepatocytes, highlighting key gene contributors.
HDAC11 was identified as a druggable target with potential for repurposing approved pediatric cancer drugs.

Conclusions:

An integrative approach successfully identified clinically relevant genes and predictive signatures for hepatoblastoma.
Expression-based scores can aid in patient stratification.
Targeting HDAC11 with existing pediatric drugs offers a promising strategy for hepatoblastoma treatment.