Reshaping the systemic tumor immune environment (STIE) and tumor immune microenvironment (TIME) to enhance immunotherapy efficacy in solid tumors

Xu, Liangliang; Zou, Chang; Zhang, Shanshan; Chu, Timothy Shun Man; Zhang, Yan; Chen, Weiwei; Zhao, Cong; Yang, Li; Xu, Zhiyuan; Dong, Shaowei; Yu, Hao; Li, Bo; Guan, Xin‐Yuan; Hou, Yuzhu; Kong, Feng-Ming Spring

doi:10.1186/s13045-022-01307-2

Cited by 87 publications

(67 citation statements)

References 274 publications

(221 reference statements)

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“…Tumor-associated macrophages (TAMs) in the tumor microenvironment are heterogeneous subsets, including M1 antitumor and M2 tumor-promoting phenotypes. TAMs primarily exert M2-like tumor-promoting effects in the TME and regulate various malignant effects, such as angiogenesis, immunosuppression, and tumor metastasis [ 49 , 50 ]. Prior work has reported that each of the M1 and M2 macrophages are produced by M0 is a quiescent state of macrophages with no particular role until they become polarized [ 51 ].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

Liu

Lai³

et al. 2023

BMC Bioinformatics

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Background Being among the most common malignancies worldwide, hepatocellular carcinoma (HCC) accounting for the third cause of cancer mortality. The regulation of cell death is the most crucial step in tumor progression and has become a crucial target for nearly all therapeutic options. Cuproptosis, a copper-induced cell death, was recently reported in Science. However, its primary function in carcinogenesis is still unclear. Methods Cuproptosis-related lncRNAs significantly associated with overall survival (OS) were screened by stepwise univariate Cox regression. The signature of cuproptosis-related lncRNAs for HCC prognosis was constructed by the LASSO algorithm and multivariate Cox regression. Further Kaplan–Meier analysis, proportional hazards model, and ROC analysis were performed. Functional annotation was performed using gene set enrichment analysis (GSEA). The relationship between prognostic cuproptosis-related lncRNAs and HCC prognosis was further explored by GEPIA(http://gepia.cancer-pku.cn/) online analysis tool. Finally, we used the ESTIMATE and XCELL algorithms to estimate stromal and immune cells in tumor tissue and cast each sample to infer the underlying mechanism of cuproptosis-related lncRNAs in the tumor immune microenvironment (TIME) of HCC patients. Results Four cuproptosis-related lncRNAs were used to construct a prognostic lncRNA signature, which was an independent factor in predicting OS in HCC patients. Kaplan–Meier curves showed significant differences in survival rates between risk subgroups (p = 0.002). At the same time, we found that the expression levels of most immune checkpoint genes increased with increasing risk scores. Tumorigenesis and immunological-related pathways were primarily enhanced in the high-risk group, as determined by GSEA. The results of drug sensitivity analysis showed that compared with patients in the high-risk group, the IC50 values of erlotinib and lapatinib were lower in patients in the low-risk group, while the opposite was true for sunitinib, paclitaxel, gemcitabine, and imatinib. We also found that elevated AL133243.2 expression was significantly associated with worse OS and disease-free survival (DFS), more advanced T stage and higher tumor grade, and reduced immune cell infiltration, suggesting that HCC patients with low AL133243.2 expression in tumor tissues may have a better response to immunotherapy. Conclusion Collectively, the cuproptosis-associated lncRNA signature can serve as an independent predictor to guide individual treatment strategies. Furthermore, AL133243.2 is a promising marker for predicting immunotherapy response in HCC patients. This data may facilitate further exploration of more effective immunotherapy strategies for HCC.

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Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

Liu

Lai³

et al. 2023

BMC Bioinformatics

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“…Despite this increasing use, there is still a lack of biomarkers with predictive value for therapy response ( 1 ). Beyond blocking local immunosuppression, IT success is achieved by systemic antitumor immunity, relying on the functionality and composition of the individual immune system ( 5 ). Therefore, we developed scores based on the individual immune signature of the patient’s peripheral blood and investigated their predictive value for therapy success of IT.…”

Section: Discussionmentioning

confidence: 99%

“…Peripheral immune cells augment, sustain, and reactivate local IT effects by interaction with the tumor microenvironment. For example, circulating CD8 + T cells are assumed to migrate into the tumor microenvironment enhancing local antitumor immunity ( 4 , 5 ).…”

Section: Introductionmentioning

confidence: 99%

“…Due to the crucial role of systemic antitumor immunity for effective tumor control, there is an increasing interest in the immune signature of the peripheral blood as a predictive biomarker for therapeutic success for clinical routine ( 5 ). Previous studies have investigated immune cell lines or laboratory parameters of peripheral blood in specific cancer types without testing across different tumor entities, focusing on changes of biomarkers during IT without predictive value before therapy start.…”

Section: Introductionmentioning

confidence: 99%

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Baseline immune signature score of Tregs × HLA-DR+CD4+ T cells × PD1+CD8+ T cells predicts outcome to immunotherapy in cancer patients

et al. 2022

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BackgroundThe use of immunotherapy (IT) is rapidly increasing across different tumor entities. PD-L1 expression is primarily used for therapy evaluation. The disadvantages of PD-L1 status are spatial and temporal heterogeneity as well as tumor type-dependent variation of predictive value. To optimize patient selection for IT, new prediction markers for therapy success are needed. Based on the systemic efficacy of IT, we dissected the immune signature of peripheral blood as an easily accessible predictive biomarker for therapeutic success.MethodsWe conducted a retrospective clinical study of 62 cancer patients treated with IT. We assessed peripheral immune cell counts before the start of IT via flow cytometry. The predictive value for therapy response of developed immune signature scores was tested by ROC curve analyses and scores were correlated with time to progression (TTP).ResultsHigh score values of “Tregs ÷ (CD4+/CD8+ ratio)” (Score A) and high score values of “Tregs × HLA-DR+CD4+ T cells × PD1+CD8+ T cells” (Score B) significantly correlated with response at first staging (p = 0.001; p < 0.001). At the optimal cutoff point, Score A correctly predicted 79.1% and Score B correctly predicted 89.3% of the staging results (sensitivity: 86.2%, 90.0%; specificity: 64.3%, 87.5%). A high Score A and Score B statistically correlated with prolonged median TTP (6.13 vs. 2.17 months, p = 0.025; 6.43 vs. 1.83 months, p = 0.016). Cox regression analyses for TTP showed a risk reduction of 55.7% (HR = 0.44, p = 0.029) for Score A and an adjusted risk reduction of 73.2% (HR = 0.27, p = 0.016) for Score B.ConclusionThe two identified immune signature scores showed high predictive value for therapy response as well as for prolonged TTP in a pan-cancer patient population. Our scores are easy to determine by using peripheral blood and flow cytometry, apply to different cancer entities, and allow an outcome prediction before the start of IT.

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“…Tumor-associated macrophages (TAMs) in the tumor microenvironment are heterogeneous subsets, including M1 antitumor and M2 tumor-promoting phenotypes. TAMs primarily exert M2-like tumor-promoting effects in the TME and regulate various malignant effects, such as angiogenesis, immunosuppression, and tumor metastasis (33,34). Prior work has reported that each of M1 and M2 macrophages are produced by M0 is a quiescent state of macrophages with no particular role until they become polarized (35).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis of Cuproptosis-Related lncRNAs in Immune Infiltration and Prognosis in Hepatocellular Carcinoma

Liu¹,

Wu²,

Lai³

et al. 2022

Preprint

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Background Being among the most common malignancies worldwide, hepatocellular carcinoma (HCC) accounts now as the fourth primary reason for cancer death. The regulation of cell death is the most crucial step in tumor progression and has become a crucial target for nearly all therapeutic options. Cuproptosis is a lately discovered copper-dependent method of apoptosis regulation. However, its primary function in carcinogenesis is still unclear. Results We developed a signature consisted of four cuproptosis-related lncRNAs (AL133243.2, AL031985.3, AL137127.1, and SNHG18). Compared to the low-risk group, the high-risk group exhibited a poorer outcome. The cuproptosis-related lncRNA signature can estimate HCC patients’ fate independently. Tumorigenesis and immunological-related pathways were primarily enhanced in the high-risk group, as determined by GSEA. Immunotherapy and standard chemotherapy medications such as erlotinib and lapatinib were more suitable for low-risk patients, whereas sunitinib, paclitaxel, gemcitabine, and imatinib were more suitable for high-risk patients. Conclusion The prognostic signature may forecasting HCC patients’ prognosis and establishes the fundamental function of cuproptosis-related lncRNAs in HCC. Cuproptosis-related lncRNAs may perform an important part in the tumor immune microenvironment (TIME), making them a promising treatment for HCC patients.

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Reshaping the systemic tumor immune environment (STIE) and tumor immune microenvironment (TIME) to enhance immunotherapy efficacy in solid tumors

Cited by 87 publications

References 274 publications

Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

Comprehensive analysis of cuproptosis-related lncRNAs in immune infiltration and prognosis in hepatocellular carcinoma

Baseline immune signature score of Tregs × HLA-DR+CD4+ T cells × PD1+CD8+ T cells predicts outcome to immunotherapy in cancer patients

Comprehensive Analysis of Cuproptosis-Related lncRNAs in Immune Infiltration and Prognosis in Hepatocellular Carcinoma

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