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Updated: Dec 1, 2025
Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
Published on: April 12, 2024
Molecular subtypes based on immune-related genes predict the prognosis for hepatocellular carcinoma patients
Bo Hu1, Xiao-Bo Yang1, Xin-Ting Sang1
1Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Insights
This study identified five immune-related subgroups in hepatocellular carcinoma (HCC) and developed a gene signature for prognosis prediction. These findings aid in understanding HCC heterogeneity and developing personalized treatments.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Hepatocellular carcinoma (HCC) is a highly lethal malignancy.
- Understanding HCC heterogeneity is crucial for effective treatment strategies.
Purpose of the Study:
- To identify distinct immune-related clusters within HCC.
- To develop a robust gene signature for predicting overall survival (OS) in HCC patients.
Main Methods:
- Utilized consensus clustering on 375 HCC cases from The Cancer Genome Atlas (TCGA) dataset, analyzing immune-related genes (IRGs) and overall survival (OS).
- Employed ESTIMATE and CIBERSORT algorithms for immune status assessment.
- Validated an 11-gene OS prediction model using the International Cancer Genome Consortium (ICGC) database and confirmed protein expression via immunohistochemistry (IHC).
Main Results:
- Identified five distinct HCC subgroups based on 93 survival-related IRGs, differing in prognosis, immune status, and immune checkpoint expression.
- Developed and validated an 11-gene signature for OS prediction in HCC.
- Observed differential protein expression of specific genes (e.g., LCN2, S100A10, S100A1, CCL26) in HCC tissues compared to normal tissues, alongside varying immunocyte infiltration levels.
Conclusions:
- Immune-related gene (IRG) based classifications effectively explain HCC heterogeneity.
- These classifications offer potential for developing more personalized and efficient treatment approaches for HCC.
Background:
Hepatocellular carcinoma (HCC) is a malignancy exhibiting the highest lethality. The present study aimed to identify different immune-related clusters in HCC and a robust tumor gene signature to facilitate the prognosis prediction for HCC patients.
Methods:
For the 375 HCC cases collected from the dataset of Cancer Genome Atlas (TCGA), their overall survival (OS) and immune-related genes (IRGs) expression patterns were collected. Thereafter, consensus clustering was employed for grouping and functional enrichment, whereas the ESTIMATE algorithm and the CIBERSORT algorithm were used in subsequent assessment. Immunohistochemistry (IHC) was conducted to verify the protein expression of model genes in HCC and adjacent tissues.
Results:
According to consensus clustering with 93-survival related IRGs, a total of five subgroups were found. These five clusters had different prognoses, immune statuses, and expression of immune checkpoints. Afterwards, 11 genes were enrolled for constructing the OS-related prediction model for TCGA HCC cases, which was then validated using the database of International Cancer Genome Consortium (ICGC). The protein expression of LCN2, S100A10, FABP6, PLXNA1, KITLG and OXTR were enhanced in HCC tissues relative to that in normal hepatic tissues, while the protein expression of S100A1, CCL26, CMTM4, IL1RN and RARG were reduced in HCC compared with normal tissues. In addition, different immunocyte infiltration levels between low- and high- groups were further examined.
Conclusions:
According to our results, the IRGs-based classifications assist in explaining the HCC heterogeneity, which may help to develop the more efficient individualized treatments.
