Identification and Validation of 17-lncRNA Related to Regulatory T Cell Heterogeneity as a Prognostic Signature for Head and Neck Squamous Cell Carcinoma

The Complex Role of Mast Cells in Head and Neck Squamous Cell Carcinoma: A Systematic Review

Background and Objectives: Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous malignancy influenced by various genetic and environmental factors. Mast cells (MCs), typically associated with allergic responses, have recently emerged as key regulators of the HNSCC tumor microenvironment (TME). This systematic review explores the role of MCs in HNSCC pathogenesis and their potential as prognostic markers and therapeutic targets. Materials and Methods: A systematic search was conducted in the PubMed, Scopus and ClinicalTrials.gov databases until 31 December 2023, using "Mast cells" AND "Head and neck squamous cell carcinoma" as search terms. Studies in English which reported on MCs and HNSCC were included. Screening, data extraction and analysis followed PRISMA guidelines. No new experiments were conducted. Results: Out of 201 articles, 52 studies met the inclusion criteria, 43 of which were published between 2020 and 2023. A total of 28821 HNSCC and 9570 non-cancerous tissue samples had been examined. MC density and activation varied among normal tissues and HNSCC. Genetic alterations associated with MCs were identified, with specific gene expressions correlating with prognosis. Prognostic gene signatures associated with MC density were established. Conclusions: MCs have arisen as multifaceted TME modulators, impacting various aspects of HNSCC development and progression. Possible site-specific or HPV-related differences in MC density and activation should be further elucidated. Despite conflicting findings on their prognostic role, MCs represent promising targets for novel therapeutic strategies, necessitating further research and clinical validation for personalized HNSCC treatment.

LncRNAs exhibit subtype-specific expression, survival associations, and cancer-promoting effects in breast cancer

Long non-coding RNAs (lncRNAs) play important roles in cancer progression, influencing processes such as invasion, metastasis, and drug resistance. Their reported cell type-dependent expression patterns suggest the potential for specialized functions in specific contexts. In breast cancer, lncRNA expression has been associated with different subtypes, highlighting their relevance in disease heterogeneity. However, our understanding of lncRNA function within breast cancer subtypes remains limited, warranting further investigation. We conducted a comprehensive analysis using the TANRIC dataset derived from the TCGA-BRCA cohort, profiling the expression, patient survival associations and immune cell type correlations of 12,727 lncRNAs across subtypes. Our findings revealed subtype-specific associations of lncRNAs with patient survival, tumor infiltrating lymphocytes and other immune cells. Targeting of lncRNAs exhibiting subtype-specific survival associations and expression in a panel of breast cancer cells demonstrated a selective reduction in cell proliferation within their associated subtype, supporting subtype-specific functions of certain lncRNAs. Characterization of HER2 + -specific lncRNA LINC01269 and TNBC-specific lncRNA AL078604.2 showed nuclear localization and altered expression of hundreds of genes enriched in cancer-promoting processes, including apoptosis, cell proliferation and immune cell regulation. This work emphasizes the importance of considering the heterogeneity of breast cancer subtypes and the need for subtype-specific analyses to fully uncover the relevance and potential impact of lncRNAs. Collectively, these findings demonstrate the contribution of lncRNAs to the distinct molecular, prognostic, and cellular composition of breast cancer subtypes.

Construction and validation of a prognostic nine-gene signature associated with radiosensitivity in head and neck squamous cell carcinoma

Background

Radiotherapy is an effective treatment for head and neck squamous cell carcinoma (HNSCC), however how to predict the prognosis is not clear.

Methods

Here we collected 262 radiosensitivity-associated genes, screened and constructed a prognostic nine-gene risk model through univariate COX, lasso regression, stepwise regression and multivariate COX analysis for transcriptome and clinical information of HNSCC patients obtained from the cancer genome atlas (TCGA) and gene expression omnibus (GEO) databases.

Results

The reliability and robustness of the risk model were verified by receiver operating characteristic (ROC) curves, risk maps, and Kaplan-Meier (KM) curves analysis. Differences in immune cell infiltration and immune-related pathway enrichment between high-risk and low-risk subgroups were determined by multiple immune infiltration analyses. Meanwhile, the mutation map and the responses to immunotherapy were also differentiated by the prognostic nine-gene signature associated with radiosensitivity. These nine genes expression in HNSCC was verified in the Human Protein Atlas (HPA) database. After that, these nine genes expression was verified to be related to radiation resistance through in-vitro cell experiments.

Conclusions

All results showed that the nine-gene signature associated with radiosensitivity is a potential prognostic indicator for HNSCC patients after radiotherapy and provides potential gene targets for enhancing the efficacy of radiotherapy.

Non-coding RNA in tumor-infiltrating regulatory T cells formation and associated immunotherapy

Cancer immunotherapy has exhibited promising antitumor effects in various tumors. Infiltrated regulatory T cells (Tregs) in the tumor microenvironment (TME) restrict protective immune surveillance, impede effective antitumor immune responses, and contribute to the formation of an immunosuppressive microenvironment. Selective depletion or functional attenuation of tumor-infiltrating Tregs, while eliciting effective T-cell responses, represents a potential approach for anti-tumor immunity. Furthermore, it does not disrupt the Treg-dependent immune homeostasis in healthy organs and does not induce autoimmunity. Yet, the shared cell surface molecules and signaling pathways between Tregs and multiple immune cell types pose challenges in this process. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), regulate both cancer and immune cells and thus can potentially improve antitumor responses. Here, we review recent advances in research of tumor-infiltrating Tregs, with a focus on the functional roles of immune checkpoint and inhibitory Tregs receptors and the regulatory mechanisms of ncRNAs in Treg plasticity and functionality.

Molecular Signature of Long Non-Coding RNA Associated with Areca Nut-Induced Head and Neck Cancer

The areca nut is a high-risk carcinogen for head and neck cancer (HNC) patients in Southeast Asia. The underlying molecular mechanism of areca nut-induced HNC remains unclear, especially regarding the role of long non-coding RNA (lncRNA). This study employed a systemic strategy to identify lncRNA signatures related to areca nut-induced HNC. In total, 84 cancer-related lncRNAs were identified. Using a PCR array method, 28 lncRNAs were identified as being dysregulated in HNC cells treated with areca nut (17 upregulated and 11 downregulated). Using bioinformatics analysis of The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) dataset, 45 lncRNAs were differentially expressed in tumor tissues from HNC patients (39 over- and 6 under-expressions). The integrated evaluation showed 10 lncRNAs dysregulated by the areca nut and altered expression in patients, suggesting that these panel molecules participate in areca nut-induced HNC. Five oncogenic (LUCAT1, MIR31HG, UCA1, HIF1A-AS2, and SUMO1P3) and tumor-suppressive (LINC00312) lncRNAs were independently validated, and three key molecules were further examined. Pathway prediction revealed that LUCAT1, UCA1, and MIR31HG modulate multiple oncogenic mechanisms, including stress response and cellular motility. Clinical assessment showed that these lncRNAs exhibited biomarker potentials in diagnosis (area under the curve = 0.815 for LUCAT1) and a worse prognosis (both p < 0.05, survival analysis). Cellular studies further demonstrated that MIR31HG facilitates areca nut-induced cancer progression, as silencing this molecule attenuated arecoline-induced invasion ability in HNC cells. This study identified lncRNA signatures that play a role in areca nut-induced HNC. These molecules may be further applied in risk assessment, diagnosis, prognosis, and therapeutics for areca nut-associated malignancies.

Identifying Oxidized Lipid Metabolism-Related LncRNAs as Prognostic Biomarkers of Head and Neck Squamous Cell Carcinoma

The relationship between oxidized lipid metabolism and the immunological function of cancer is well known. However, the functions and regulatory mechanisms of lncRNAs associated with oxidized lipid metabolism in head and neck squamous cell carcinoma (HNSCC) remain to be fully elucidated. In this study, we established an oxidized lipid metabolism-related lncRNA prognostic signature to assess the prognosis and immune infiltration of HNSCC patients. The HNSCC transcriptome was obtained from The Cancer Genome Atlas. The choice of the target genes with a relevance score greater than 10 was performed via a correlation analysis by GeneCards. Patients were categorized by risk score and generated with multivariate Cox regression, which was then validated and evaluated using the Kaplan–Meier analysis and time-dependent receiver operating characteristics (ROC). A nomogram was constructed by combining the risk score with the clinical data. We constructed a risk score with 24 oxidized lipid metabolism-related lncRNAs. The areas’ 1-, 2-, and 3-year OS under the ROC curve (AUC) were 0.765, 0.724, and 0.724, respectively. Furthermore, the nomogram clearly distinguished the survival probabilities of patients in high- and low-risk groups, between which substantial variations were revealed by immune infiltration analysis. The results supported the fact that oxidized lipid metabolism-related lncRNAs might predict prognoses and assist with differentiating amid differences in immune infiltration in HNSCC.

Identification and verification of eight cancer-associated fibroblasts related genes as a prognostic signature for head and neck squamous cell carcinoma

Cancer-associated fibroblasts (CAFs) can exert their immunosuppressive effects by secreting various effectors that are involved in the regulation of tumor-infiltrating immune cells as well as other immune components in the tumor immune microenvironment (TIME), thereby promoting tumorigenesis, progression, metastasis, and drug resistance. Although a large number of studies suggest that CAFs play a key regulatory role in the development of head and neck squamous cell carcinoma (HNSCC), there are limited studies on the relevance of CAFs to the prognosis of HNSCC. In this study, we identified a prognostic signature containing eight CAF-related genes for HNSCC by univariate Cox analysis, lasso regression, stepwise regression, and multivariate Cox analysis. Our validation in primary cultures of CAFs from human HNSCC and four human HNSCC cell lines confirmed that these eight genes are indeed characteristic markers of CAFs. Immune cell infiltration differences analysis between high-risk and low-risk groups according to the eight CAF-related genes signature hinted at CAFs regulatory roles in the TIME, further revealing its potential role on prognosis. The signature of the eight CAF-related genes was validated in different independent validation cohorts and all showed that it was a valid marker for prognosis. The significantly higher overall survival (OS) in the low-risk group compared to the high-risk group was confirmed by Kaplan-Meier (K-M) analysis, suggesting that the signature of CAF-related genes can be used as a non-invasive predictive tool for HNSCC prognosis. The low-risk group had significantly higher levels of tumor-killing immune cell infiltration, as confirmed by CIBERSORT analysis, such as CD8⁺ T cells, follicular helper T cells, and Dendritic cells (DCs) in the low-risk group. In contrast, the level of infiltration of pro-tumor cells such as M0 macrophages and activated Mast cells (MCs) was lower. It is crucial to delve into the complex mechanisms between CAFs and immune cells to find potential regulatory targets and may provide new evidence for subsequently targeted immunotherapy. These results suggest that the signature of the eight CAF-related genes is a powerful indicator for the assessment of the TIME of HNSCC. It may provide a new and reliable potential indicator for clinicians to predict the prognosis of HNSCC, which may be used to guide treatment and clinical decision-making in HNSCC patients. Meanwhile, CAF-related genes are expected to become tumor biomarkers and effective targets for HNSCC.

The Two Faces of Immune-Related lncRNAs in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a group of cancers originating from the mucosal epithelium in the oral cavity, larynx, oropharynx, nasopharynx, and hypopharynx. Molecular factors can be key in the diagnosis, prognosis, and treatment of HNSCC patients. Long non-coding RNAs (lncRNAs) are molecular regulators composed of 200 to 100,000 nucleotides that act on the modulation of genes that activate signaling pathways associated with oncogenic processes such as proliferation, migration, invasion, and metastasis in tumor cells. However, up until now, few studies have discussed the participation of lncRNAs in modeling the tumor microenvironment (TME) to generate a protumor or antitumor environment. Nevertheless, some immune-related lncRNAs have clinical relevance, since AL139158.2, AL031985.3, AC104794.2, AC099343.3, AL357519.1, SBDSP1, AS1AC108010.1, and TM4SF19-AS1 have been associated with overall survival (OS). MANCR is also related to poor OS and disease-specific survival. MiR31HG, TM4SF19-AS1, and LINC01123 are associated with poor prognosis. Meanwhile, LINC02195 and TRG-AS1 overexpression is associated with favorable prognosis. Moreover, ANRIL lncRNA induces resistance to cisplatin by inhibiting apoptosis. A superior understanding of the molecular mechanisms of lncRNAs that modify the characteristics of TME could contribute to increasing the efficacy of immunotherapy.

Relationships of Ferroptosis and Pyroptosis-Related Genes with Clinical Prognosis and Tumor Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Ferroptosis and pyroptosis are two new programmed cell death (PCD) modes discovered in recent years. However, the potential value of ferroptosis and pyroptosis-related genes (FPRGs) in prognosis prediction and the tumor immune microenvironment of head and neck squamous cell carcinoma (HNSCC) is still unclear. We obtained 21 significant FPRGs based on the training dataset (TCGA- HNSC) using the univariate Cox and differential expression analysis. The TCGA- HNSC (n = 502) dataset was clustered into two group (clusters A and B) based on the 21 significant FPRGs. 1467 differentially expressed genes (DEGs) between cluster A and B were put into univariate Cox and Least absolute shrinkage and selection operator (LASSO) analysis to build a risk model. The predictive capability of the risk model was successfully confirmed by internal validation, external validation, and clinical sample validation. To improve the clinical applicability, a nomogram model combined risk score and clinical information were constructed. Moreover, the patients with lower risk score were characterized by increased immune response and tumor mutation burden (TMB), while the patients with higher risk score were characterized by increased TP53 mutation rate. In conclusion, our comprehensive analysis of the FPRGs revealed their significant role in prognosis prediction and the tumor immune microenvironment. The risk model containing 9 FPRGs could be a potential prognostic markers and effective immunotherapy targets for HNSCC.

Identification and Validation of a Novel Immune Infiltration-Based Diagnostic Score for Early Detection of Hepatocellular Carcinoma by Machine-Learning Strategies

Objective

To investigate the diagnostic gene biomarkers for hepatocellular carcinoma (HCC) and identify the immune cell infiltration characteristics in this pathology.

Methods

Five gene expression datasets were obtained through Gene Expression Omnibus (GEO) portal. After batch effect removal, differentially expressed genes (DEGs) were conducted between 209 HCC and 146 control tissues and functional correlation analyses were performed. Two machine learning algorithms were used to develop diagnostic signatures. The discriminatory ability of the gene signature was measured by AUC. The expression levels and diagnostic value of the identified biomarkers in HCC were further validated in three independent external cohorts. CIBERSORT algorithm was adopted to explore the immune infiltration of HCC. A correlation analysis was carried out between these diagnostic signatures and immune cells.

Results

A total of 375 DEGs were identified. GPC3, ACSM3, SPINK1, COL15A1, TP53I3, RRAGD, and CLDN10 were identified as the early diagnostic signatures of HCC and were all validated in external cohorts. The corresponding results of AUC presented excellent discriminatory ability of these feature genes. The immune cell infiltration analysis showed that multiple immune cells associated with these biomarkers may be involved in the development of HCC.

Conclusion

This study indicates that GPC3, ACSM3, SPINK1, COL15A1, TP53I3, RRAGD, and CLDN10 are potential biomarkers associated with immune infiltration in HCC. Combining these genes can be used for early detection of HCC and evaluating immune cell infiltration. Further studies are needed to explore their roles underlying the occurrence of HCC.