Targeting T cell metabolism in the tumor microenvironment: an anti-cancer therapeutic strategy

Yin, Zhongping Qin Jie; Bai, Ling; Li, Wei; Zeng, Tanlun; Tian, Huimin; Cui, Jiuwei

doi:10.1186/s13046-019-1409-3

Cited by 104 publications

(89 citation statements)

References 76 publications

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“…76 In tumor cells, Warburg metabolic reprogramming tends to result in substrate inflexibility and dependence on a sustained influx of glucose carbons through glycolysis, 16,77,78 factors that are now being exploited to develop therapeutic strategies to limit tumor progression. 79 Tumor cells have multiple mechanisms to compensate for this in- 20 Thus, metabolic shifts toward aerobic glycolysis are critical mediators of malignant transformation and also appear to influence disease prognosis and local T cell immunity.…”

Section: Highly Glycolytic Tumor Cells Rely Upon Warburg Metabolismmentioning

confidence: 99%

Obesity and CD8 T cell metabolism: Implications for anti‐tumor immunity and cancer immunotherapy outcomes

Turbitt

Rosean

Weber

et al. 2020

Immunological Reviews

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Obesity is an established risk factor for many cancers and has recently been found to alter the efficacy of T cell–based immunotherapies. Currently, however, the effects of obesity on immunometabolism remain unclear. Understanding these associations is critical, given the fact that T cell metabolism is tightly linked to effector function. Thus, any obesity‐associated changes in T cell bioenergetics are likely to drive functional changes at the cellular level, alter the metabolome and cytokine/chemokine milieu, and impact cancer immunotherapy outcomes. Here, we provide a brief overview of T cell metabolism in the presence and absence of solid tumor growth and summarize current literature regarding obesity‐associated changes in T cell function and bioenergetics. We also discuss recent findings related to the impact of host obesity on cancer immunotherapy outcomes and present potential mechanisms by which T cell metabolism may influence therapeutic efficacy. Finally, we describe promising pharmaceutical therapies that are being investigated for their ability to improve CD8 T cell metabolism and enhance cancer immunotherapy outcomes in patients, regardless of their obesity status.

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Section: Highly Glycolytic Tumor Cells Rely Upon Warburg Metabolismmentioning

confidence: 99%

Obesity and CD8 T cell metabolism: Implications for anti‐tumor immunity and cancer immunotherapy outcomes

Turbitt

Rosean

Weber

et al. 2020

Immunological Reviews

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“…Immune context in the TME is the medium in which immunotherapies struggle to triumph. Controversies still exist regarding the influence of altered metabolism on the development and functions of infiltrated immune cells [88,161]. Several metabolic targets in the TME and ligands have been identified; however, optimal delivery strategies still need further development [10,162].…”

Section: Discussionmentioning

confidence: 99%

Harnessing nanomedicine to overcome the immunosuppressive tumor microenvironment

Sun

Hyun

et al. 2020

Acta Pharmacol Sin

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Cancer immunotherapy has received extensive attention due to its ability to activate the innate or adaptive immune systems of patients to combat tumors. Despite a few clinical successes, further endeavors are still needed to tackle unresolved issues, including limited response rates, development of resistance, and immune-related toxicities. Accumulating evidence has pinpointed the tumor microenvironment (TME) as one of the major obstacles in cancer immunotherapy due to its detrimental impacts on tumor-infiltrating immune cells. Nanomedicine has been battling with the TME in the past several decades, and the experience obtained could be exploited to improve current paradigms of immunotherapy. Here, we discuss the metabolic features of the TME and its influence on different types of immune cells. The recent progress in nanoenabled cancer immunotherapy has been summarized with a highlight on the modulation of immune cells, tumor stroma, cytokines and enzymes to reverse the immunosuppressive TME.

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“…Memory T cells rely on FAO, while activated Tregs primarily depend on glycolysis and fatty acid synthesis. Nutrient availability in the tumor microenvironment favors different subtypes of T cells (33). ACAA1 was recently also implicated in regulating infiltration of T cell subtypes in the tumor stroma.…”

Section: Discussionmentioning

confidence: 99%

ACAA1 Is a Predictive Factor of Survival and Is Correlated With T Cell Infiltration in Non-Small Cell Lung Cancer

Feng

Shen

2020

Front. Oncol.

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Non-small cell lung cancer (NSCLC) is the predominant subtype of lung cancers. KRAS mutation is the second most prevalent mutation in NSCLC. KRAS mutant cancer cells suppress the anti-tumor T cell response. However, the underlying mechanism is still unknown. Here, we analyzed the differential expression of acetyl-CoA acyltransferase 1 (ACAA1) in various types of cancers using the TIMER database and validated the results in the NSCLC cell line H1944. We silenced oncogenic KRAS by siRNA targeting KRAS G13D , and employed an MAPK signaling pathway inhibitor to clarify the possible regulatory pathway. Moreover, we analyzed the correlation of ACAA1 expression level with B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells. Correlations between expression of ACAA1 and several biomarkers of mutation burden were also tested. Finally, we evaluated the prognostic value of ACAA1 in a wide range of cancers using the Kaplan-Meier Plotter Database. We found lower expression of ACAA1 in tumor tissue than in adjacent normal tissue in various cancers. This result was confirmed using a GEO dataset. Knock-down of mutant KRAS resulted in increased ACAA1 mRNA level in H1944 cells. ACAA1 mRNA level was significantly upregulated in H1944 after treatment with MAPK pathway inhibitor sorafenib, indicating that oncogenic KRAS may downregulate ACAA1 through MAPK signaling. ACAA1 was negatively correlated with biomarkers of tumor mutation burden, including BRCA1, ATM, ATR, CDK1, PMS2, MSH2, and MDH6. Conversely, ACAA1 expression was positively correlated with infiltrating CD4 + cells and with Th1, Th2, Treg cells in the lung tumor microenvironment. Finally, we showed that ACAA1 is a predictive factor for survival in several cancer types. In summary, decreased ACAA1 expression is correlated with poor prognosis and decreases immune infiltration of CD4 + T cells in LUAD and LUSC. ACAA1 also predicts T cell exhaustion in LUSC. The mechanism underlying KRAS/ACAA1 axis-mediated regulation of immune cell infiltration requires further investigation.

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Targeting T cell metabolism in the tumor microenvironment: an anti-cancer therapeutic strategy

Cited by 104 publications

References 76 publications

Obesity and CD8 T cell metabolism: Implications for anti‐tumor immunity and cancer immunotherapy outcomes

Obesity and CD8 T cell metabolism: Implications for anti‐tumor immunity and cancer immunotherapy outcomes

Harnessing nanomedicine to overcome the immunosuppressive tumor microenvironment

ACAA1 Is a Predictive Factor of Survival and Is Correlated With T Cell Infiltration in Non-Small Cell Lung Cancer

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