In a new study, researchers aimed to investigate the prognostic significance of senescence-related TME genes in head and neck squamous cell carcinoma (HNSCC) and their potential implications for immunotherapy response.
Head and neck squamous cell carcinoma (HNSCC) is a prevalent and heterogeneous form of cancer that affects thousands of individuals worldwide. The prognosis for HNSCC patients can vary greatly, depending on factors such as tumor stage and site. The tumor microenvironment (TME) plays a crucial role in tumorigenesis and disease progression, with cellular senescence being a key component. Senescent cells, characterized by cell-cycle arrest, have been shown to have both tumor-suppressive and tumor-promoting effects. However, the prognostic significance of senescence-related TME genes in HNSCC remains poorly understood.
In a new study, researchers Young Chan Lee, Yonghyun Nam, Minjeong Kim, Su Il Kim, Jung-Woo Lee, Young-Gyu Eun, and Dokyoon Kim from Kyung Hee University, Kyung Hee University Hospital at Gangdong, and the University of Pennsylvania aimed to investigate the prognostic significance of senescence-related TME genes in HNSCC and their potential implications for immunotherapy response. They utilized data from The Cancer Genome Atlas (TCGA) to identify two distinct subtypes of HNSCC based on the expression of senescence-related TME genes. The team then constructed a risk model consisting of senescence-related TME core genes (STCGs) and validated its prognostic capability in independent cohorts. Their research paper was chosen as an Aging cover paper and published in Volume 16, Issue 2, entitled, “Prognostic significance of senescence-related tumor microenvironment genes in head and neck squamous cell carcinoma.”
“To the best of our knowledge, this is the first study to offer a comprehensive evaluation of the senescence related TME status by integrating senescence related TME genes through a gene-gene network and clustering. Furthermore, we have introduced a novel risk model that utilizes a selected gene set to predict prognosis and confirmed the expression of STCGs in immune cells at single-cell levels.”
Identification of Prognostic Senescence-Related TME Genes
To identify prognostic senescence-related TME genes, the researchers screened a total of 7,878 genes in the TCGA-HNSCC dataset. They identified 288 genes that belonged to TME-related genes, tumor-associated senescence (TAS) genes, and immune-related genes. From these genes, they selected 91 prognostic senescence-related TME genes (PSTGs) based on differential expression analysis and Cox regression analysis.
Senescence-Related TME Subtypes and Characterization
Using consensus clustering analysis, the researchers classified the HNSCC samples into two distinct subtypes based on the expression of PSTGs: subtype 1 and subtype 2. The two subtypes exhibited significant differences in clinical and molecular characteristics. Subtype 2 had a higher prevalence of HPV-positive and oropharyngeal cancer cases, while subtype 1 was characterized by a higher proportion of advanced tumor stage and overall stage.
Further analysis revealed distinct differences between the subtypes in terms of genetic alterations, methylation patterns, enriched pathways, and immune infiltration. Subtype 1 had a higher mutation rate in the TP53 gene and exhibited hypomethylation in several CpG sites compared to subtype 2. Additionally, subtype 2 showed higher immune scores, stromal scores, and ESTIMATE scores, indicating a more favorable immune microenvironment.
The two subtypes also displayed differences in survival outcomes. Kaplan-Meier survival analysis showed that subtype 2 had a more favorable overall survival compared to subtype 1. This difference was enhanced in the HPV-positive cohort, suggesting that the senescence-related TME subtypes may have implications for prognosis in specific patient subgroups.
Risk Scoring Based on Senescence-Related TME Status
Using the 91 PSTGs, the researchers constructed a risk scoring model based on the LASSO Cox regression algorithm. They identified 21 STCGs that were associated with either increased risk or protection. The risk scores based on the expression levels of these genes were calculated for each patient, and the patients were classified into high- and low-risk groups.
The prognostic performance of the risk scoring model was tested in independent cohorts, including the TCGA-HNSCC test set, the GSE41613 cohort, and the KHUMC cohort. The high-risk group showed significantly lower overall survival compared to the low-risk group in the TCGA-HNSCC test set and the GSE41613 cohort. Although not statistically significant, the low-risk group demonstrated a trend towards higher overall survival in the KHUMC cohort.
Immunotherapy Response Prediction and Single-Cell Analysis
The team also investigated the immunotherapy response prediction based on the risk model and the expression of STCGs. They found that the low-risk group had higher immunophenoscores and a significantly higher proportion of responders to immunotherapy compared to the high-risk group.
To further evaluate the senescence-related TME characteristics at the single-cell level, the researchers analyzed single-cell transcriptome data from HNSCC tissue. They found that STCGs were enriched in fibroblast, mono/macrophage, and T cell populations, suggesting that these cell types contribute to the senescent features of HNSCC.
In conclusion, the study sheds light on the prognostic significance of senescence-related TME genes in HNSCC. Their findings highlight the heterogeneity of HNSCC and the importance of the senescence-related TME in prognosis and immunotherapy response. The risk scoring model based on STCGs provides a potential prognostic biomarker for HNSCC patients, and the single-cell analysis further elucidates the association between STCGs and specific cell populations within the TME. These findings contribute to a deeper understanding of the complex interplay between senescence and the TME in HNSCC and have implications for precision medicine and personalized treatment approaches. Further research and validation are needed to fully understand the clinical implications of senescence-related TME genes in HNSCC. However, this study provides valuable insights into the role of cellular senescence in tumor progression and the potential for targeting senescence-related pathways in the development of novel therapeutic strategies for HNSCC patients.
“In conclusion, this study comprehensively investigated the prognostic and immunological features of senescence related TME genes in HNSC. By leveraging these senescence related TME genes, we successfully developed a risk model to predict HNSC prognosis and immunotherapy response, which was robustly validated using external transcriptome datasets. These findings provided evidence for the role of senescence in the TME and highlighted the potential of senescence-related biomarkers as promising therapeutic targets.”
Click here to read the full research paper published in Aging.
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