Transcriptomic Correlates of Immunologic Activation in Head and Neck and Cervical Cancer

Immune Subtypes and Characteristics of Endometrial Cancer Based on Immunogenes

Purpose

The aim of this study was to explore the immune subtypes of endometrial cancer (EC) and its characteristics by immunogenes from the perspective of multidimensional genomics (multi-omics).

Patients and Methods

Immune subtypes were carried out using an unsupervised non-negative matrix factorization clustering (NMF) method and their characteristics were analysed. Key genes were identified using random forest analysis. A predictive model for immune subtypes and their clinical prognosis were constructed. The relationship between immune subtypes and molecular subtypes was investigated.

Results

Two immune subtypes C1 and C2 were available. C2 patients were younger, less graded, had significantly higher immune cell infiltration, immune checkpoint expression, tumor neoantigens, tumor mutation load than C1 (P<005). S100A9, CD3D, CD3E, HLA-DRB1 and IL2RB were the key genes with significant survival outcomes. S100A9 expression was lower in C2 than C1, and IL2RB, HLA-DRB1, CD3E and CD3D expression was higher than C1 (P<0.05). The predictive accuracy of five key genes for immune subtypes was good, with a Receiver operating characteristic of 0.941. The incidence of TP53abn type in C2 was significantly lower than that of C1, and the incidence of POLE type was significantly higher than that of C1 (P<0.0001).

Conclusion

EC can be divided into two immune subtypes based on immunogenes. Low expression of S100A9 and high expression of IL2RB, HLA-DRB1, CD3E, and CD3D suggest sensitivity to immunotherapy and a good prognosis.

Assessing the implications of sentinel lymph node removal in cervical cancer: an immunogenetic perspective - a SENTICOL ancillary study

BACKGROUND

Cervical cancer's lymphatic spread primarily begins from the sentinel lymph nodes (SLNs), underlining their pivotal role in disease metastasis. However, these nodes' immune gene expression profiles and immunoregulation mechanisms have yet to be explored.

METHODS

Our study aimed to elucidate the immune cell populations and their roles in the immune gene expression profile of negative SLNs compared with positive SLNs and non-SLNs using Nanostring RNA seq analysis. We performed a principal component analysis on the log2 normalized expression of 685 endogenous genes in the nCounter PanCancer Immune Profiling Panel, followed by an assessment of the differential expression of genes and immune cell type abundance.

RESULTS

We found significant variations in gene expression among the groups, with negative SLNs displaying overexpression of genes related to tumor-infiltrating immune cells, specifically innate cell populations. They also demonstrated the upregulation of genes involved in antigen presentation and T-cell priming. In contrast, positive SLNs were enriched in regulatory networks, suggesting their potential role in immune evasion. A comparison of negative SLNs and non-SLNs revealed increased innate and adaptive immune cell types, underscoring the ongoing T cell response to tumor antigens.

CONCLUSION

Our findings underscore a specific immunogenetic phenotype profile in negative SLNs, emphasizing their crucial role in the initial anticancer response, immunosurveillance, and the propagation of immune tolerance from the primary cervical tumor. These results highlight the potential of SLNs as a novel target for immunotherapy strategies and underscore the importance of new imaging methods for accurately identifying SLN status without removal. Future investigations are needed to understand further the immunological interplay within SLNs and their influence on cervical cancer progression.

A cuproptosis and copper metabolism–related gene prognostic index for head and neck squamous cell carcinoma

Background

The purpose of this study was to identify the prognostic value of cuproptosis and copper metabolism–related genes, to clarify their molecular and immunological characteristics, and to elucidate their benefits in head and neck squamous cell carcinoma (HNSCC).

Methods

The details of human cuproptosis and copper metabolism–related genes were searched and filtered from the msigdb database and the latest literature. To identify prognostic genes associated with cuproptosis and copper metabolism, we used least absolute shrinkage and selection operator regression, and this coefficient was used to set up a prognostic risk score model. HNSCC samples were divided into two groups according to the median risk. Afterwards, the function and immune characteristics of these genes in HNSCC were analyzed.

Results

The 14-gene signature was constructed to classify HNSCC patients into low-risk and high-risk groups according to the risk level. In the The Cancer Genome Atlas (TCGA) cohort, the overall survival (OS) rate of the high-risk group was lower than that of the low-risk group (P &lt; 0.0001). The area under the curve of the time-dependent Receiver Operator Characteristic (ROC) curve assessed the good performance of the genetic signature in predicting OS and showed similar performance in the external validation cohort. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment assays and Protein-Protein Interaction (PPI) protein networks have been used to explore signaling pathways and potential mechanisms that were markedly active in patients with HNSCC. Furthermore, the 14 cuproptosis and copper metabolism-related genes were significantly correlated with the immune microenvironment, suggesting that these genes may be linked with the immune regulation and development of HNSCC.

Conclusions

Our results emphasize the significance of cuproptosis and copper metabolism as a predictive biomarker for HNSCC, and its expression levels seem to be correlated with immune- related features; thus, they may be a possible biomarker for HNSCC prognosis.

CD3D Is an Independent Prognostic Factor and Correlates With Immune Infiltration in Gastric Cancer

The protein encoded by CD3D is part of the T-cell receptor/CD3 complex (TCR/CD3 complex) and is involved in T-cell development and signal transduction. Previous studies have shown that CD3D is associated with prognosis and treatment response in breast, colorectal, and liver cancer. However, the expression and clinical significance of CD3D in gastric cancer are not clear. In this study, we collected 488 gastric cancer tissues and 430 paired adjacent tissues to perform tissue microarrays (TMAs). Then, immunohistochemical staining of CD3D, CD3, CD4, CD8 and PD-L1 was conducted to investigate the expression of CD3D in gastric cancer and the correlation between the expression of CD3D and tumor infiltrating lymphocytes (TILs) and PD-L1. The results showed that CD3D was highly expressed in gastric cancer tissues compared with paracancerous tissues (P<0.000). Univariate and multivariate analyses showed that CD3D was an independent good prognostic factor for gastric cancer (P=0.004, HR=0.677, 95%CI: 0.510-0.898 for univariate analyses; P=0.046, HR=0.687, 95%CI: 0.474-0.994 for multivariate analyses). In addition, CD3D was negatively correlated with the tumor location, Borrmann type and distant metastasis (P=0.012 for tumor location; P=0.007 for Borrmann type; P=0.027 for distant metastasis). In addition, the expression of CD3D was highly positively correlated with the expression of CD3, CD4, CD8, and PD-L1, and the combination of CD3D with CD3, CD4, CD8 and PD-L1 predicted the best prognosis (P=0.043). In summary, CD3D may play an important regulatory role in the tumor immune microenvironment of gastric cancer and may serve as a potential indicator of prognosis and immunotherapy response.

Comprehensive analysis of immune cell infiltration and significant genes in head and neck squamous cell carcinoma

OBJECTIVE

Immunotherapy directed at the tumor microenvironment is effective in the treatment of head and neck squamous cell carcinoma (HNSCC). In contrast, there has been a paucity of research on the relationship between the HNSCC microenvironment and prognostic outcome. Meanwhile, tumor immune cell infiltration (ICI) has emerged as a critical step in immunotherapy.

METHODS

Two algorithms, CIBERSORT and ESTIMATE, were performed to evaluate the ICI view of 885 HNSCC patients using three databases: the Cancer Genome Atlas (TCGA), Arrayexpress, and Gene Expression Omnibus (GEO).

RESULTS

Different ICI subtypes were identified. Following that, 57 different expression genes (DEGs) were discovered. The ICI scores of all patients were calculated using the Principal Component Analysis (PCA) algorithm. Additionally, an immune-related prognostic signature was developed and validated using 17 of 57 DEGs. Patients with a low-ICI or low-risk score had a higher infiltration immune-activated related cells and higher expression of most immune checkpoint-related molecules, indicating a better prognosis. Furthermore, using the pRRophetic algorithm, the sensitivities of many chemotherapeutic drugs were significantly different between two ICI subtypes or two risk groups. Moreover, a nomogram incorporating the ICI score, risk score, and clinical characteristics was developed and was capable of accurately predicting outcomes.

CONCLUSION

The ICI score and 17-gene signature could improve HNSCC survival prediction, promote individual treatment strategies, and provide promising novel immunotherapy biomarkers.