ACC2 is under-expressed in lung adenocarcinoma and predicts poor clinical outcomes

Yu, Feiyuan; Xu, Qian; Wei, Qi-Yao; Mo, Hai-Ying; Zhong, Qiu-Hua; Zhao, Xiao‐Yun; Lau, Andy T. Y.; Xu, Yan‐Ming

doi:10.1007/s00432-021-03910-1

Cited by 5 publications

(2 citation statements)

References 43 publications

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“…While using RNA interference (RNAi) to silence the ACC-α gene could inhibit cell proliferation and induce apoptosis of prostate cancer cells ( 34 ). Unlike ACC1, ACC2 plays a role in inhibiting lipid degradation and was found inhibited in various cancers, its expression is also negatively correlated with tumor size and clinical stages of lung adenocarcinoma patients ( 35 , 36 ). Prolyl hydroxylase domain protein 3 (PHD3) could also repress FAO and inhibit leukemia cell proliferation by activating ACC2 ( 37 ).…”

Section: Lipid Metabolism Reprogramming In Tumor Cells and Tumor Stro...mentioning

confidence: 99%

The role of lipid metabolism in tumor immune microenvironment and potential therapeutic strategies

Wang

et al. 2022

Front. Oncol.

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Aberrant lipid metabolism is nonnegligible for tumor cells to adapt to the tumor microenvironment (TME). It plays a significant role in the amount and function of immune cells, including tumor-associated macrophages, T cells, dendritic cells and marrow-derived suppressor cells. It is well-known that the immune response in TME is suppressed and lipid metabolism is closely involved in this process. Immunotherapy, containing anti-PD1/PDL1 therapy and adoptive T cell therapy, is a crucial clinical cancer therapeutic strategy nowadays, but they display a low-sensibility in certain cancers. In this review, we mainly discussed the importance of lipid metabolism in the formation of immunosuppressive TME, and explored the effectiveness and sensitivity of immunotherapy treatment by regulating the lipid metabolism.

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Section: Lipid Metabolism Reprogramming In Tumor Cells and Tumor Stro...mentioning

confidence: 99%

The role of lipid metabolism in tumor immune microenvironment and potential therapeutic strategies

Wang

et al. 2022

Front. Oncol.

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“…Acetyl-coA carboxylase 2 (ACC2) is a key FAM enzyme. Fei-Yuan Yu et al found that ACC2 is low-expressed in tumor cells, and its expression is negatively correlated with tumor progression ( Yu et al, 2022 ). FASN is a homodimeric multienzymatic protein that inhibits and blocks the adipogenic pathway and hinders fatty acid synthesis.…”

Section: Discussionmentioning

confidence: 99%

Applying machine learning algorithms to develop a survival prediction model for lung adenocarcinoma based on genes related to fatty acid metabolism

Cong,

Zhao,

Zhang

et al. 2023

Front. Pharmacol.

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Background: The progression of lung adenocarcinoma (LUAD) may be related to abnormal fatty acid metabolism (FAM). The present study investigated the relationship between FAM-related genes and LUAD prognosis.Methods: LUAD samples from The Cancer Genome Atlas were collected. The scores of FAM-associated pathways from the Kyoto Encyclopedia of Genes and Genomes website were calculated using the single sample gene set enrichment analysis. ConsensusClusterPlus and cumulative distribution function were used to classify molecular subtypes for LUAD. Key genes were obtained using limma package, Cox regression analysis, and six machine learning algorithms (GBM, LASSO, XGBoost, SVM, random forest, and decision trees), and a RiskScore model was established. According to the RiskScore model and clinical features, a nomogram was developed and evaluated for its prediction performance using a calibration curve. Differences in immune abnormalities among patients with different subtypes and RiskScores were analyzed by the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data, CIBERSORT, and single sample gene set enrichment analysis. Patients’ drug sensitivity was predicted by the pRRophetic package in R language.Results: LUAD samples had lower scores of FAM-related pathways. Three molecular subtypes (C1, C2, and C3) were defined. Analysis on differential prognosis showed that the C1 subtype had the most favorable prognosis, followed by the C2 subtype, and the C3 subtype had the worst prognosis. The C3 subtype had lower immune infiltration. A total of 12 key genes (SLC2A1, PKP2, FAM83A, TCN1, MS4A1, CLIC6, UBE2S, RRM2, CDC45, IGF2BP1, ANGPTL4, and CD109) were screened and used to develop a RiskScore model. Survival chance of patients in the high-RiskScore group was significantly lower. The low-RiskScore group showed higher immune score and higher expression of most immune checkpoint genes. Patients with a high RiskScore were more likely to benefit from the six anticancer drugs we screened in this study.Conclusion: We developed a RiskScore model using FAM-related genes to help predict LUAD prognosis and develop new targeted drugs.

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Targeting lipid metabolism via nanomedicine: a prospective strategy for cancer therapy

Huang,

Hou,

et al. 2024

Biomaterials

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ACC2 is under-expressed in lung adenocarcinoma and predicts poor clinical outcomes

Cited by 5 publications

References 43 publications

The role of lipid metabolism in tumor immune microenvironment and potential therapeutic strategies

The role of lipid metabolism in tumor immune microenvironment and potential therapeutic strategies

Applying machine learning algorithms to develop a survival prediction model for lung adenocarcinoma based on genes related to fatty acid metabolism

Targeting lipid metabolism via nanomedicine: a prospective strategy for cancer therapy

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