A four-hypoxia-genes-based prognostic signature for oral squamous cell carcinoma

Identification and Validation of a Prognostic Signature Derived from the Cancer Stem Cells for Oral Squamous Cell Carcinoma

The progression and metastasis of oral squamous cell carcinoma (OSCC) are highly influenced by cancer stem cells (CSCs) due to their unique self-renewal and plasticity. In this study, data were obtained from a single-cell RNA-sequencing dataset (GSE172577) in the GEO database, and LASSO-Cox regression analysis was performed on 1344 CSCs-related genes to establish a six-gene prognostic signature (6-GPS) consisting of ADM, POLR1D, PTGR1, RPL35A, PGK1, and P4HA1. High-risk scores were significantly associated with unfavorable survival outcomes, and these features were thoroughly validated in the ICGC. The results of nomograms, calibration plots, and ROC curves confirmed the good prognostic accuracy of 6-GPS for OSCC. Additionally, the knockdown of ADM or POLR1D genes may significantly inhibit the proliferation, migration, and invasion of OSCC cells through the JAK/HIF-1 pathway. Furthermore, cell-cycle arrest occurred in the G1 phase by suppressing Cyclin D1. In summary, 6-GPS may play a crucial role in the occurrence and development of OSCC and has the potential to be developed further as a diagnostic, therapeutic, and prognostic tool for OSCC.

Phosphoglycerate-kinase-1 Is a Potential Prognostic Biomarker in HNSCC and Correlates With Immune Cell Infiltration

BACKGROUND/AIM

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer worldwide, with a high recurrence rate and a low cure rate. Phosphoglycerate kinase 1 (PGK1), an essential enzyme in the aerobic glycolysis pathway, is a prognostic marker for a variety of cancers. However, it remains unclear whether a PGK1-based immune signature can be used as a prognostic biomarker in HNSCC patients.

MATERIALS AND METHODS

We explored the potential oncogenic mechanisms of PGK1 by multiple bioinformatics analyses combined with multiple databases, including the correlation between PGK1 and prognosis, and the infiltration of immune cells in HNSCC. Functional enrichment analyses were further performed to investigate the potential role of PGK1 in HNSCC.

RESULTS

The expression of PGK1 was significantly higher in HNSCC tissues compared to normal tissues. High expression of PGK1 was associated with poor prognosis in HNSCC, and multivariate cox regression analysis showed that PGK1 could be an independent prognostic factor in HNSCC. Pathway analysis revealed that PGK1 may regulate the pathogenesis of HNSCC through the immune signaling pathway. Moreover, PGK1 expression significantly correlated with the infiltration level of 16 types of immune cells.

CONCLUSION

The current study reports that PGK1 expression was increased in HNSCC and that high PGK1 expression was closely associated with poor prognosis and immune cell infiltration, which could serve as a promising independent prognostic biomarker and potential immunotherapeutic target for HNSCC.

Regulation of phosphoglycerate kinase 1 and its critical role in cancer

Cells that undergo normal differentiation mainly rely on mitochondrial oxidative phosphorylation to provide energy, but most tumour cells rely on aerobic glycolysis. This phenomenon is called the "Warburg effect". Phosphoglycerate kinase 1 (PGK1) is a key enzyme in aerobic glycolysis. PGK1 is involved in glucose metabolism as well as a variety of biological activities, including angiogenesis, EMT, mediated autophagy initiation, mitochondrial metabolism, DNA replication and repair, and other processes related to tumorigenesis and development. Recently, an increasing number of studies have proven that PGK1 plays an important role in cancer. In this manuscript, we discussed the effects of the structure, function, molecular mechanisms underlying PGK1 regulation on the initiation and progression of cancer. Additionally, PGK1 is associated with chemotherapy resistance and prognosis in tumour patients. This review presents an overview of the different roles played by PGK1 during tumorigenesis, which will help in the design of experimental studies involving PGK1 and enhance the potential for the use of PGK1 as a therapeutic target in cancer. Video Abstract.

Glioblastoma glycolytic signature predicts unfavorable prognosis, immunological heterogeneity, and ENO1 promotes microglia M2 polarization and cancer cell malignancy

Glioblastomas are the most malignant brain tumors, whose progress was promoted by aberrate aerobic glycolysis. The immune environment was highly engaged in glioblastoma formation, while its interaction with aerobic glycolysis remained unclear. Herein, we build a 7-gene Glycolytic Score (GS) by Elastic Net in the training set and two independent validating sets. The GS predicted malignant features and poor survival with good performances. Immune functional analyses and Cibersort calculation identified depressed T cells, B cells, natural killer cells immunity, and high immunosuppressive cell infiltration in the high-GS group. Also, high expressions of the immune-escape genes were discovered. Subsequently, the single-cell analyses validated the glycolysis-related immunosuppression. The functional results manifested the high-GS neoplastic cells' association with T cells, NK cells, and macrophage function regulation. The intercellular cross-talk showed strong associations between high-GS neoplastic cells and M2 macrophages/microglia in several immunological pathways. We finally confirmed that ENO1, the key gene of the GS, promoted M2 microglia polarization and glioblastoma cell malignant behaviors via immunofluorescence, clone formation, CCK8, and transwell rescue experiments. These results indicated the interactions between cancerous glycolysis and immunosuppression and glycolysis' role in promoting glioblastoma progression. Conclusively, we built a robust model and discovered strong interaction between GS and immune, shedding light on prognosis management improvement and therapeutic strategies development for glioblastoma patients.

Development and validation of a novel hypoxia-related signature for prognostic and immunogenic evaluation in head and neck squamous cell carcinoma

Hypoxia plays a critical role in head and neck squamous cell carcinoma (HNSCC) prognosis. However, till now, robust and reliable hypoxia-related prognostic signatures have not been established for an accurate prognostic evaluation in HNSCC patients. This article focused on establishing a risk score model to evaluate the prognosis and guide treatment for HNSCC patients. RNA-seq data and clinical information of 502 HNSCC patients and 44 normal samples were downloaded from The Cancer Genome Atlas (TCGA) database. 433 samples from three Gene Expression Omnibus (GEO) datasets were incorporated as an external validation cohort. In the training cohort, prognostic-related genes were screened and LASSO regression analyses were performed for signature establishment. A scoring system based on SRPX, PGK1, STG1, HS3ST1, CDKN1B, and HK1 showed an excellent prediction capacity for an overall prognosis for HNSCC patients. Patients were divided into high- and low-risk groups, and the survival status of the two groups exhibited a statistically significant difference. Subsequently, gene set enrichment analysis (GSEA) was carried out to explore the underlying mechanisms for the prognosis differences between the high- and low-risk groups. The tumor immune microenvironment was evaluated by CIBERSORT, ESTIMATE, TIDE, and xCell algorithm, etc. Then, we explored the relationships between this prognostic model and the levels of immune checkpoint-related genes. Cox regression analysis and nomogram plot indicated the scoring system was an independent predictor for HNSCC. Moreover, a comparison of predictive capability has been made between the present signature and existing prognostic signatures for HNSCC patients. Finally, we detected the expression levels of proteins encoded by six-HRGs via immunohistochemical analysis in tissue microarray. Collectively, a novel integrated signature considering both HRGs and clinicopathological parameters will serve as a prospective candidate for the prognostic evaluation of HNSCC patients.

Association between cancer stem cell gene expression signatures and prognosis in head and neck squamous cell carcinoma

Background

Various cancer stem cell (CSC) biomarkers and the genes encoding them in head and neck squamous cell carcinoma (HNSCC) have been identified and evaluated. However, the validity of these factors in the prognosis of HNSCC has been questioned and remains unclear. In this study, we examined the clinical significance of CSC biomarker genes in HNSCC, using five publicly available HNSCC cohorts.

Methods

To predict the prognosis of patients with HNSCC, we developed and validated the expression signatures of CSC biomarker genes whose mRNA expression levels correlated with at least one of the four CSC genes (CD44, MET, ALDH1A1, and BMI1).

Results

Patients in The Cancer Genome Atlas (TCGA) HNSCC cohort were classified into CSC gene expression-associated high-risk (CSC-HR; n = 285) and CSC gene expression-associated low-risk (CSC-LR; n = 281) subgroups. The 5-year overall survival and recurrence-free survival rates were significantly lower in the CSC-HR subgroup than in the CSC-LR subgroup (p = 0.04 and 0.02, respectively). The clinical significance of the CSC gene expression signature was validated using four independent cohorts. Analysis using Cox proportional hazards models showed that the CSC gene expression signature was an independent prognostic factor of non-oropharyngeal HNSCC which mostly indicates HPV (–) status. Furthermore, the CSC gene expression signature was associated with the prognosis of HNSCC patients who received radiotherapy.

Conclusion

The CSC gene expression signature is associated with the prognosis of HNSCC and may help in personalized treatments for patients with HNSCC, especially in cases with HPV (–) status who were classified in more detail.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10184-4.

Bioinformatics analysis of the role of aldolase A in tumor prognosis and immunity

Aldolase A (ALDOA) is an enzyme that plays an important role in glycolysis and gluconeogenesis, which is closely related to tumor metabolism. In this study, the overall roles of ALDOA in pan-cancer have been investigated from several aspects using databases and online analysis tools. Using the ONCOMINE database, the expression of ALDOA in various cancers was analyzed. The prognostic role of ALDOA was explored by PrognoScan, GEPIA, and Kaplan–Meier Plotter. The immune-related role of ALDOA and its downstream substrates was decided by TIMER, cBioPortal and String. Our data indicate that ALDOA expression level in lung adenocarcinoma, liver hepatocellular carcinoma, head and neck squamous cell carcinoma is higher than that in normal tissues. Increased expression of ALDOA often indicates a poor prognosis for patients. The correlation between ALDOA and immune infiltration among different tumors is very different. We also investigate the relationship between ALDOA and its upstream/downstream proteins. Our results showed that ALDOA could be used as a biomarker for the tumor prognosis, and could be correlated with the infiltrating levels of macrophages, CD4+ T cells and CD8+ T cells.

A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study

Oral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of the interplay between the immune system and tumor microenvironment has become increasingly evident. This study explored immune-related alterations at the multi-omics level to extract accurate prognostic markers linked to the immune response and presents a more accurate landscape of the immune genomic map during OSCC. The Cancer Genome Atlas (TCGA) OSCC cohort (n = 329) was used to detect the immune infiltration pattern of OSCC and categorize patients into two immunity groups using single-sample gene set enrichment analysis (ssGSEA) and hierarchical clustering analysis. Multiple strategies, including lasso regression (LASSO), Cox proportional hazards regression, and principal component analysis (PCA) were used to screen clinically significant signatures and identify an incorporated prognosis model with robust discriminative power on the survival status of both the training and testing set. We identified two OSCC subtypes based on immunological characteristics: Immunity-high and immunity low, and verified that the categorization was accurate and repeatable. Immunity_ high cluster with a higher immunological and stromal score. 1047 differential genes (DEGs) integrate with immune genes to obtain 319 immue-related DEGs. A robust model with five signatures for OSCC patient prognosis was established. The GEO cohort (n = 97) were used to validate the risk model’s predictive value. The low-risk group had a better overall survival (OS) than the high-risk group. Significant prognostic potential for OSCC patients was found using ROC analysis and immune checkpoint gene expression was lower in the low-risk group. We also investigated at the therapeutic sensitivity of a number of frequently used chemotherapeutic drugs in patients with various risk factors. The underlying biological behavior of the OSCC cell line was preliminarily validated. This study characterizes a reliable marker of OSCC disease progression and provides a new potential target for immunotherapy against this disease.

The Effect of Hypoxia and Hypoxia-Associated Pathways in the Regulation of Antitumor Response: Friends or Foes?

Hypoxia is an environmental stressor that is instigated by low oxygen availability. It fuels the progression of solid tumors by driving tumor plasticity, heterogeneity, stemness and genomic instability. Hypoxia metabolically reprograms the tumor microenvironment (TME), adding insult to injury to the acidic, nutrient deprived and poorly vascularized conditions that act to dampen immune cell function. Through its impact on key cancer hallmarks and by creating a physical barrier conducive to tumor survival, hypoxia modulates tumor cell escape from the mounted immune response. The tumor cell-immune cell crosstalk in the context of a hypoxic TME tips the balance towards a cold and immunosuppressed microenvironment that is resistant to immune checkpoint inhibitors (ICI). Nonetheless, evidence is emerging that could make hypoxia an asset for improving response to ICI. Tackling the tumor immune contexture has taken on an in silico, digitalized approach with an increasing number of studies applying bioinformatics to deconvolute the cellular and non-cellular elements of the TME. Such approaches have additionally been combined with signature-based proxies of hypoxia to further dissect the turbulent hypoxia-immune relationship. In this review we will be highlighting the mechanisms by which hypoxia impacts immune cell functions and how that could translate to predicting response to immunotherapy in an era of machine learning and computational biology.

A novel defined hypoxia-related gene signature to predict the prognosis of oral squamous cell carcinoma

Background

Oral squamous cell carcinoma (OSCC), as the most common oral cancer globally, is very harmful to people's health. Hypoxia is closely related to many cancers. In this study, we have conducted a comprehensive exploration of the impact of hypoxia on OSCC.

Methods

First, we calculated the enrichment score (ES) of hypoxia-related genes in the sample based on the enrichment analysis of the single sample Gene Set Enrichment Analysis (ssGSEA) and expressed it as a potential hypoxia index (HPI). We first identified the relationship between HPI and survival time in OSCC tumor samples. Then we assessed the correlation between hypoxia and the degree of infiltration of various immune cells in OSCC tissues, and screened out gene mutations that may be related to HPI in OSCC. Finally, we constructed a prognostic model of hypoxia-related genes.

Results

In the immune cell infiltration of OSCC, we found that hypoxia was significantly related to the infiltration of eosinophils, macrophages, neutrophils, T helper cells and Th1 cells. In addition, NSD1 mutations may become a signal to suggest that patients with OSCC have higher HPI. Finally, we constructed a prognostic model of 6 sets of hypoxia-related genes (PGK1, JMJD6, S100A4, SLC2A3, DDIT4 and HK1) in OSCC.

Conclusions

Hypoxia is closely related to immune cell infiltration, gene mutation, and prognosis in OSCC patients.