Profile of sphingolipid-related genes and its association with prognosis highlights sphingolipid metabolism in oral cancer

Spinster homolog 2 reduces malignancies of glioblastoma via PTEN/PI3K/AKT pathway

The molecular mechanisms of glioblastoma (GBM) are unclear, and the prognosis is poor. Spinster homolog 2 (SPNS2) is reportedly involved in pathological processes such as immune response, vascular development, and cancer. However, the biological function and molecular role of SPNS2 in GBM are unclear. SPNS2 is aberrantly low expressed in glioma. Survival curves, risk scores, prognostic nomograms, and univariate and multifactorial Cox regression analyses showed that SPNS2 is an independent prognostic indicator significantly associated with glioma progression and prognosis. Cell function assays and in vivo xenograft transplantation were performed that downregulation of SPNS2 promoted GBM cell growth, migration, invasion, epithelial-mesenchymal transition (EMT), anti-apoptosis, drug resistance, and stemness, while overexpression of SPNS2 had the opposite effect. Meanwhile, the functional enrichment and signaling pathways of SPNS2 in the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and RNA sequencing were analyzed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene set enrichment analysis (GSEA). The above results were related to the inhibition of the PTEN/PI3K/AKT pathway by SPNS2. In addition, we predicted that SPNS2 is closely associated with immune infiltration in the tumor microenvironment by four immune algorithms, ESTIMATE, TIMER, CIBERSORT, and QUANTISEQ. In particular, SPNS2 was negatively correlated with the infiltration of most immune cells, immunomodulators, and chemokines. Finally, single-cell sequencing analysis also revealed that SPNS2 was remarkably correlated with macrophages, and downregulation of SPNS2 promotes the expression of M2-like macrophages. This study provides new evidence that SPNS2 inhibits malignant progression, stemness, and immune infiltration of GBM cells through PTEN/PI3K/AKT pathway. SPNS2 may become a new diagnostic indicator and potential immunotherapeutic target for glioma.

Spermidine Suppresses Oral Carcinogenesis through Autophagy Induction, DNA Damage Repair, and Oxidative Stress Reduction

Autophagy has been proposed to play a dual role in cancer-as a tumor suppressor in early stages and oncogenic in late stages of tumorigenesis. This study investigated the role of autophagy in oral carcinogenesis using the model of oral squamous cell carcinoma (OSCC) induced by carcinogen 4-nitroquinoline 1-oxide (4NQO), mimicking molecular and histopathologic aspects of human OSCC. The induction of autophagy by spermidine (SPD) treatment reduced the severity of lesions and the incidence of OSCC in mice exposed to 4NQO. On the other hand, autophagy inhibition by chloroquine treatment had no protection. The comet assay indicated that SPD reduced 4NQO-induced DNA damage, likely related to the activation of DNA repair and the decrease of reactive oxygen species. As sphingolipid alterations have been reported in OSCC, sphingolipids in the tongue and plasma of animals were analyzed and plasma C16 ceramide levels were shown to increase proportionally to lesion severity, indicating its potential as a biomarker. Mice exposed to 4NQO plus SPD had lower levels of C16 ceramide than the 4NQO group, which indicated SPD's ability to prevent the 4NQO-induced carcinogenesis. Together, these data indicate that activation of autophagy has a tumor suppressor role during the early stages of oral carcinogenesis. Because of its ability to induce autophagy accompanied by reduced oxidative stress and DNA damage, SPD may have a protective action against chemically induced oral cancer.

Overexpression of fatty acid desaturase 3 predicts poor prognosis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies worldwide, because its discovery time is in the late stage of the disease, so it is important to develop HNSCC biomarkers to achieve the purpose of early detection and treatment. Fatty acid desaturase 3 (FADS3), the third member of the FADS family, is involved in sphingolipid biosynthesis. Here, we for the first time investigated FADS3 expression in HNSCC, as well as its potential biological function, prognostic value and its impact on the immune system. In this study, we used bioinformatics for gene expression analysis, clinicopathological analysis, enrichment analysis, and immune infiltration analysis of The Cancer Genome Atlas (TCGA) datasets. Statistical analysis was done using R. Tumor IMmune Estimation Resource (TIMER) and CIBERSORT were used to analyze the effect of FADS3 on immune responses in HNSCC. Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier (KM) survival analysis, and the Human Protein Atlas (HPA) data were used to validate the results from bioinformatics analysis. Our findings indicate that FADS3 influences HNSCC prognosis. High expression of FADS3 is related to higher lymphatic metastasis, histologic grade, and lymphovascular invasion. Gene set enrichment analysis (GSEA) revealed that FADS3 is related to inhibition of amino acid metabolism. CIBERSORT analysis showed high FADS3 expression correlates with reduced levels of B cells. FADS3 is a marker of HNSCC, and high expression of FADS3 is associated with poor prognosis of HNSCC.

Machine learning to construct sphingolipid metabolism genes signature to characterize the immune landscape and prognosis of patients with uveal melanoma

Background

Uveal melanoma (UVM) is the most common primary intraocular malignancy in adults and is highly metastatic, resulting in a poor patient prognosis. Sphingolipid metabolism plays an important role in tumor development, diagnosis, and prognosis. This study aimed to establish a reliable signature based on sphingolipid metabolism genes (SMGs), thus providing a new perspective for assessing immunotherapy response and prognosis in patients with UVM.

Methods

In this study, SMGs were used to classify UVM from the TCGA-UVM and GEO cohorts. Genes significantly associated with prognosis in UVM patients were screened using univariate cox regression analysis. The most significantly characterized genes were obtained by machine learning, and 4-SMGs prognosis signature was constructed by stepwise multifactorial cox. External validation was performed in the GSE84976 cohort. The level of immune infiltration of 4-SMGs in high- and low-risk patients was analyzed by platforms such as CIBERSORT. The prediction of 4-SMGs on immunotherapy and immune checkpoint blockade (ICB) response in UVM patients was assessed by ImmuCellAI and TIP portals.

Results

4-SMGs were considered to be strongly associated with the prognosis of UVM and were good predictors of UVM prognosis. Multivariate analysis found that the model was an independent predictor of UVM, with patients in the low-risk group having higher overall survival than those in the high-risk group. The nomogram constructed from clinical characteristics and risk scores had good prognostic power. The high-risk group showed better results when receiving immunotherapy.

Conclusions

4-SMGs signature and nomogram showed excellent predictive performance and provided a new perspective for assessing pre-immune efficacy, which will facilitate future precision immuno-oncology studies.

Dihydroceramide desaturase 1 (DES1) promotes anchorage-independent survival downstream of HER2-driven glucose uptake and metabolism

Oncogenic reprogramming of cellular metabolism is a hallmark of many cancers, but our mechanistic understanding of how such dysregulation is linked to tumor behavior remains poor. In this study, we have identified dihydroceramide desaturase (DES1)-which catalyzes the last step in de novo sphingolipid synthesis-as necessary for the acquisition of anchorage-independent survival (AIS), a key cancer enabling biology, and establish DES1 as a downstream effector of HER2-driven glucose uptake and metabolism. We further show that DES1 is sufficient to drive AIS and in vitro tumorigenicity and that increased DES1 levels-found in a third of HER2+ breast cancers-are associated with worse survival outcomes. Taken together, our findings reveal a novel pro-tumor role for DES1 as a transducer of HER2-driven glucose metabolic signals and provide evidence that targeting DES1 is an effective approach for overcoming AIS. Results further suggest that DES1 may have utility as a biomarker of aggressive and metastasis-prone HER2+ breast cancer.

Feature screening for survival trait with application to TCGA high-dimensional genomic data

Background

In high-dimensional survival genomic data, identifying cancer-related genes is a challenging and important subject in the field of bioinformatics. In recent years, many feature screening approaches for survival outcomes with high-dimensional survival genomic data have been developed; however, few studies have systematically compared these methods. The primary purpose of this article is to conduct a series of simulation studies for systematic comparison; the second purpose of this article is to use these feature screening methods to further establish a more accurate prediction model for patient survival based on the survival genomic datasets of The Cancer Genome Atlas (TCGA).

Results

Simulation studies prove that network-adjusted feature screening measurement performs well and outperforms existing popular univariate independent feature screening methods. In the application of real data, we show that the proposed network-adjusted feature screening approach leads to more accurate survival prediction than alternative methods that do not account for gene-gene dependency information. We also use TCGA clinical survival genetic data to identify biomarkers associated with clinical survival outcomes in patients with various cancers including esophageal, pancreatic, head and neck squamous cell, lung, and breast invasive carcinomas.

Conclusions

These applications reveal advantages of the new proposed network-adjusted feature selection method over alternative methods that do not consider gene-gene dependency information. We also identify cancer-related genes that are almost detected in the literature. As a result, the network-based screening method is reliable and credible.