The prognostic value of MicroRNAs associated with fatty acid metabolism in head and neck squamous cell carcinoma

Wang, Xiaojing; Zhao, Yue; Strohmer, Dorothee Franziska; Yang, Wenjin; Xia, Zhijia; Yu, Cong

doi:10.3389/fgene.2022.983672

Cited by 34 publications

(33 citation statements)

References 28 publications

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“…Reprogramming of metabolic pathways ensures the survival and proliferation of cancer cells in a nutrient-deficient environment ( 20 ). Besides, immune cell metabolic reprogramming alters immune cell function by interfering with critical transcriptional and post-transcriptional activation mechanisms, to keep growing tumors from being attacked by the immune system ( 20 , 21 ). Alterations in carbohydrate metabolism in tumor cells have been reported.…”

Section: Discussionmentioning

confidence: 99%

Transcriptome analysis reveals effects of leukemogenic SHP2 mutations in biosynthesis of amino acids signaling

Zhao

Chang²,

Hu³

et al. 2023

Front. Oncol.

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Gain-of-function mutations of SHP2, especially D61Y and E76K, lead to the development of neoplasms in hematopoietic cells. Previously, we found that SHP2-D61Y and -E76K confer HCD-57 cells cytokine-independent survival and proliferation via activation of MAPK pathway. Metabolic reprogramming is likely to be involved in leukemogenesis led by mutant SHP2. However, detailed pathways or key genes of altered metabolisms are unknown in leukemia cells expressing mutant SHP2. In this study, we performed transcriptome analysis to identify dysregulated metabolic pathways and key genes using HCD-57 transformed by mutant SHP2. A total of 2443 and 2273 significant differentially expressed genes (DEGs) were identified in HCD-57 expressing SHP2-D61Y and -E76K compared with parental cells as the control, respectively. Gene ontology (GO) and Reactome enrichment analysis showed that a large proportion of DEGs were involved in the metabolism process. Kyoto Encyclopedia of Gene and Genome (KEGG) pathway enrichment analysis showed that DEGs were the mostly enriched in glutathione metabolism and biosynthesis of amino acids in metabolic pathways. Gene Set Enrichment Analysis (GSEA) revealed that the expression of mutant SHP2 led to a significant activation of biosynthesis of amino acids pathway in HCD-57 expressing mutant SHP2 compared with the control. Particularly, we found that ASNS, PHGDH, PSAT1, and SHMT2 involved in the biosynthesis of asparagine, serine, and glycine were remarkably up-regulated. Together, these transcriptome profiling data provided new insights into the metabolic mechanisms underlying mutant SHP2-driven leukemogenesis.

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Section: Discussionmentioning

confidence: 99%

Transcriptome analysis reveals effects of leukemogenic SHP2 mutations in biosynthesis of amino acids signaling

Zhao

Chang²,

Hu³

et al. 2023

Front. Oncol.

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“…Then, LASSO-Cox regression analysis was applied to 22 OMRGs linked to patients’ prognoses, with minimal criteria determining the penalty parameter (λ) ( 36 ). The equation for computing the risk score was as follows: Risk score =

.…”

Section: Methodsmentioning

confidence: 99%

Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine

Dong

Yuan²,

Ren³

et al. 2023

Front. Endocrinol.

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BackgroundStomach adenocarcinoma (STAD) is one of the primary contributors to deaths that are due to cancer globally. At the moment, STAD does not have any universally acknowledged biological markers, and its predictive, preventive, and personalized medicine (PPPM) remains sufficient. Oxidative stress can promote cancer by increasing mutagenicity, genomic instability, cell survival, proliferation, and stress resistance pathways. As a direct and indirect result of oncogenic mutations, cancer depends on cellular metabolic reprogramming. However, their roles in STAD remain unclear.Method743 STAD samples from GEO and TCGA platforms were selected. Oxidative stress and metabolism-related genes (OMRGs) were acquired from the GeneCard Database. A pan-cancer analysis of 22 OMRGs was first performed. We categorized STAD samples by OMRG mRNA levels. Additionally, we explored the link between oxidative metabolism scores and prognosis, immune checkpoints, immune cell infiltration, and sensitivity to targeted drugs. A series of bioinformatics technologies were employed to further construct the OMRG-based prognostic model and clinical-associated nomogram.ResultsWe identified 22 OMRGs that could evaluate the prognoses of patients with STAD. Pan-cancer analysis concluded and highlighted the crucial part of OMRGs in the appearance and development of STAD. Subsequently, 743 STAD samples were categorized into three clusters with the enrichment scores being C2 (upregulated) > C3 (normal) > C1 (downregulated). Patients in C2 had the lowest OS rate, while C1 had the opposite. Oxidative metabolic score significantly correlates with immune cells and immune checkpoints. Drug sensitivity results reveal that a more tailored treatment can be designed based on OMRG. The OMRG-based molecular signature and clinical nomogram have good accuracy for predicting the adverse events of patients with STAD. Both transcriptional and translational levels of ANXA5, APOD, and SLC25A15 exhibited significantly higher in STAD samples.ConclusionThe OMRG clusters and risk model accurately predicted prognosis and personalized medicine. Based on this model, high-risk patients might be identified in the early stage so that they can receive specialized care and preventative measures, and choose targeted drug beneficiaries to deliver individualized medical services. Our results showed oxidative metabolism in STAD and led to a new route for improving PPPM for STAD.

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“…To analyze the functional significance of the identified SPGs, we used the file "c2.cp.kegg.v7.4.symbols.gmt" from the MSigDB database and performed GSVA enrichment analysis using the "GSVA" R package (23)(24)(25) . We applied the "limma" R package to adjust for P values (P < 0.05) and determine statistical significance of subgroup differences (26,27). Additionally, we used functional enrichment analysis to investigate the pathways and functional annotations associated with DEGs related to SPGs in HCC.…”

Section: Gsva Analysismentioning

confidence: 99%

Prognostic signatures of sphingolipids: Understanding the immune landscape and predictive role in immunotherapy response and outcomes of hepatocellular carcinoma

Zhang

Zhuge²,

Liu

et al. 2023

Front. Immunol.

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BackgroundHepatocellular carcinoma (HCC) is a complex disease with a poor outlook for patients in advanced stages. Immune cells play an important role in the progression of HCC. The metabolism of sphingolipids functions in both tumor growth and immune infiltration. However, little research has focused on using sphingolipid factors to predict HCC prognosis. This study aimed to identify the key sphingolipids genes (SPGs) in HCC and develop a reliable prognostic model based on these genes.MethodsThe TCGA, GEO, and ICGC datasets were grouped using SPGs obtained from the InnateDB portal. A prognostic gene signature was created by applying LASSO-Cox analysis and evaluating it with Cox regression. The validity of the signature was verified using ICGC and GEO datasets. The tumor microenvironment (TME) was examined using ESTIMATE and CIBERSORT, and potential therapeutic targets were identified through machine learning. Single-cell sequencing was used to examine the distribution of signature genes in cells within the TME. Cell viability and migration were tested to confirm the role of the key SPGs.ResultsWe identified 28 SPGs that have an impact on survival. Using clinicopathological features and 6 genes, we developed a nomogram for HCC. The high- and low-risk groups were found to have distinct immune characteristics and response to drugs. Unlike CD8 T cells, M0 and M2 macrophages were found to be highly infiltrated in the TME of the high-risk subgroup. High levels of SPGs were found to be a good indicator of response to immunotherapy. In cell function experiments, SMPD2 and CSTA were found to enhance survival and migration of Huh7 cells, while silencing these genes increased the sensitivity of Huh7 cells to lapatinib.ConclusionThe study presents a six-gene signature and a nomogram that can aid clinicians in choosing personalized treatments for HCC patients. Furthermore, it uncovers the connection between sphingolipid-related genes and the immune microenvironment, offering a novel approach for immunotherapy. By focusing on crucial sphingolipid genes like SMPD2 and CSTA, the efficacy of anti-tumor therapy can be increased in HCC cells.

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The prognostic value of MicroRNAs associated with fatty acid metabolism in head and neck squamous cell carcinoma

Cited by 34 publications

References 28 publications

Transcriptome analysis reveals effects of leukemogenic SHP2 mutations in biosynthesis of amino acids signaling

Transcriptome analysis reveals effects of leukemogenic SHP2 mutations in biosynthesis of amino acids signaling

Identification and characterization of a novel molecular classification incorporating oxidative stress and metabolism-related genes for stomach adenocarcinoma in the framework of predictive, preventive, and personalized medicine

Prognostic signatures of sphingolipids: Understanding the immune landscape and predictive role in immunotherapy response and outcomes of hepatocellular carcinoma

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