CD8+ T effector and immune checkpoint signatures predict prognosis and responsiveness to immunotherapy in bladder cancer

Chen, Xingyu; Xu, Runshi; He, Dong; Zhang, Yao; Chen, Haotian; Zhu, Yuxing; Cheng, Ying; Li, Rui; Zhu, Rongrong; Gong, Lian; Xiao, Mengqing; Wang, Zhanwang; Deng, Liping; Cao, Ke

doi:10.1038/s41388-021-02019-6

Cited by 64 publications

(45 citation statements)

References 33 publications

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“…The expression of the FGFR3 gene signature ( FGFR3 , TP63 , WNT7B ) in Cluster 1 was significantly higher than in the other two groups, while the CD8 Teff signature ( CD8A , GZMA , GZMB , PRF1 , CXCL9 , CXCL10 , TBX21 ),antigen-processing machinery ( TAP1 , TAP2 , B2M , HLA-A , HLA-B , HLA-C ), and the immune checkpoint signature ( CD274 , PDCD1LG2 , CTLA4 , PDCD1 , LAG3 , HAVCR2 , and TIGIT ) are less expressed in Cluster 1 than the other two modification patterns, and are highly expressed in the Cluster 3 subgroup. The CD8 Teff and the immune checkpoint signatures are often used to predict the efficacy of immunosuppression in patients with immune checkpoint suppression; a higher expression level is linked to better clinical outcomes ( 5 , 52 ). Additionally, our results indicated that the expression of MKI67 and cell cycle genes; DNA replication-dependent histones; DNA-repair genes are significantly higher in Cluster 3; TGFβ receptor and ligand; F-TBRS genes; EMT markers; angiogenesis signature show significantly increased gene expression in Cluster 2.…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, an analysis performed using the ESTIMATE algorithm showed that the stromal and immune scores in Cluster 2 were lower than the other two subtypes, which corroborates our previous results. The expression of immune checkpoint and CD8 + T cell markers were lower in Cluster 2 than in the other two groups, and studies have shown that the expression of these markers is highly sensitive to immune checkpoint inhibitors ( 52 ). Thus, different m 6 A modification patterns are significantly related to immune activation, and a comprehensive evaluation of the m 6 A modification patterns will enable the understanding of the characteristics of TME cell infiltration.…”

Section: Discussionmentioning

confidence: 99%

“…There were significant differences among the than the other two modification patterns, and are highly expressed in the Cluster 3 subgroup. The CD8 Teff and the immune checkpoint signatures are often used to predict the efficacy of immunosuppression in patients with immune checkpoint suppression; a higher expression level is linked to better clinical outcomes (5,52). Additionally, our results indicated that the expression of MKI67 and cell cycle genes; DNA replication-dependent histones; DNA-repair genes are significantly higher in Cluster 3; TGFb receptor and ligand; F-TBRS genes; EMT markers; angiogenesis signature show significantly increased gene expression in Cluster 2.…”

Section: Effect Of M 6 a Methylation Modification On Anti-pd-l1 Immun...mentioning

confidence: 99%

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Identification and Validation of N6-Methyladenosine-Related Biomarkers for Bladder Cancer: Implications for Immunotherapy

et al. 2022

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N6-methyladenosine (m6A) has emerged as one of the most important modifications of RNA. Based on the expression of 23 different modes of m6A regulatory factors, we identified three different m6A modification patterns in bladder cancer. The effects of the three different modes of m6A modification on clinicopathological characteristics, immune cell infiltration levels and expression levels of immune checkpoint genes were comprehensively analyzed. In addition, the effects of different modes of m6A modification on the therapeutic efficacy of anti-PD-L1 immunotherapy (atezolizumab) are also discussed. Our results confirm that m6A methylation plays an important role in immune cell recruitment in the tumor microenvironment of bladder cancer, which influences the efficacy of anti-PD-L1 therapy for bladder cancer. We further confirmed the important role of FTO protein in the biological function of bladder cancer cells by performing in vitro experiments. FTO functions as an oncogene in bladder cancer cells, and upon FTO knockdown, the level of m6A enzyme activity in bladder cancer cells was significantly increased, apoptosis was increased, and cell proliferation and cell invasion were reduced. In addition, our study also confirmed that K216H and K216E are probably important targets for regulating FTO. We provide new insights into the regulatory pathways of the immune microenvironment and the methylation function of m6A in bladder cancer, which will help in designing novel diagnostic methods, prognostic tools, and therapeutic targets.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Effect Of M 6 a Methylation Modification On Anti-pd-l1 Immun...mentioning

confidence: 99%

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Identification and Validation of N6-Methyladenosine-Related Biomarkers for Bladder Cancer: Implications for Immunotherapy

et al. 2022

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“…On the other hand, they have been proven to be able to regulate the functions of immune cells, such as cytotoxic T cells, neutrophils and NK cells, to exert their antitumor effects ( Haabeth et al, 2016 ; Kaplanski, 2018 ; Ju et al, 2021 ). In bladder cancer, pyroptosis has been proven to affect the remodeling of tumor microenvironment (TME) and activation of pyroptosis attributes to infiltration of immune cells and to enhance the efficiency of immunotherapy ( Chen et al, 2021a ). These studies on pyroptosis in cancer cells provide novel insights for cancer cell death, especially in anti-apoptosis tumors, and tumor-immune response.…”

Section: Discussionmentioning

confidence: 99%

Generation and Analysis of Pyroptosis-Based and Immune-Based Signatures for Kidney Renal Clear Cell Carcinoma Patients, and Cell Experiment

et al. 2022

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Background: Pyroptosis is a programmed cell death caused by inflammasomes, which is closely related to immune responses and tumor progression. The present study aimed to construct dual prognostic indices based on pyroptosis-associated and immune-associated genes and to investigate the impact of the biological signatures of these genes on Kidney Renal Clear Cell Carcinoma (KIRC).Materials and Methods: All the KIRC samples from the Cancer Genome Atlas (TCGA) were randomly and equally divided into the training and testing datasets. Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis were used to screen crucial pyroptosis-associated genes (PAGs), and a pyroptosis-associated genes prognostic index (PAGsPI) was constructed. Immune-associated genes (IAGs) related to PAGs were identified, and then screened through Cox and LASSO regression analyses, and an immune-associated genes prognostic index (IAGsPI) was developed. These two prognostic indices were verified by using the testing and the Gene Expression Omnibus (GEO) datasets and an independent cohort. The patients’ response to immunotherapy was analyzed. A nomogram was constructed and calibrated. qRT-PCR was used to detect the expression of PAGs and IAGs in the tumor tissues and normal tissues. Functional experiment was carried out.Results: 86 PAGs and 1,774 differentially expressed genes (DEGs) were obtained. After intersecting PAGs with DEGs, 22 differentially expressed PAGs (DEPAGs) were included in Cox and LASSO regression analyses, identifying 5 crucial PAGs. The PAGsPI was generated. Patients in the high-PAGsPI group had a poor prognosis. 82 differentially expressed IAGs (DEIAGs) were highly correlated with DEPAGs. 7 key IAGs were screened out, and an IAGsPI was generated. Patients in the high-IAGsPI group had a poor prognosis. PAGsPI and IAGsPI were verified to be robust and reliable. The results revealed patients in low-PAGsPI group and high-IAGsPI group may be more sensitive to immunotherapy. The calibrated nomogram was proved to be reliable. An independent cohort study also proved that PAGsPI and IAGsPI performed well in prognosis prediction. We found that the expression of AIM2 may affect proliferation of KIRC cells.Conclusion: PAGsPI and IAGsPI could be regarded as potential biomarkers for predicting the prognosis of patients with KIRC.

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“…Then, to verify that the co-expression network presented a scale-free topology, parameter β (defined as the soft threshold of adjacency matrix) was used to penalize weak correlations and emphasize the strong correlations between AGs ( 15 ). After determining the appropriate β to be 6 based on ScaleFree plot, the adjacency matrix was transformed into a topological overlap matrix, and the new matrix followed the principle of scale-free topology ( 16 ). Finally, the co-expression gene modules (minModuleSize of 15) were identified to explore the functional modules associated with BC progression using the Dynamic Tree Cut algorithm.…”

Section: Methodsmentioning

confidence: 99%

Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer

Zhao

Tan

et al. 2021

Front. Oncol.

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Breast cancer (BC) is the most commonly diagnosed malignancy accompanied by high invasion and metastasis features. Importantly, emerging studies have supported that aging is a key clue that participates in the immune state and development of BC. Nevertheless, there are no studies concerning the aging-related genes (AGs) in constructing the prognosis signature of BC. Here, to address this issue, we initially performed a systematic investigation of the associations between AGs and BC prognosis and accordingly constructed a prognosis risk model with 10 AGs including PLAU, JUND, IL2RG, PCMT1, PTK2, HSPA8, NFKBIA, GCLC, PIK3CA, and DGAT1 by using the least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis. Meanwhile, our analysis further confirmed that the nomogram possessed a robust performance signature for predicting prognosis compared to clinical characteristics of BC patients, including age, clinical stage, and TNM staging. Moreover, the risk score was confirmed as an independent prognostic index of BC patients and was potentially correlated with immune scores, estimate score, immune cell infiltration level, tumor microenvironment, immunotherapy effect, and drug sensitivity. Furthermore, in the external clinical sample validation, AGs were expressed differentially in patients from different risk groups, and tumor-associated macrophage markers were elevated in high-risk BC tissues with more co-localization of AGs. In addition, the proliferation, transwell, and wound healing assays also confirmed the promoting effect of DGAT1 in BC cell proliferation and migration. Therefore, this well-established risk model could be used for predicting prognosis and immunotherapy in BC, thus providing a powerful instrument for combating BC.

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CD8+ T effector and immune checkpoint signatures predict prognosis and responsiveness to immunotherapy in bladder cancer

Cited by 64 publications

References 33 publications

Identification and Validation of N6-Methyladenosine-Related Biomarkers for Bladder Cancer: Implications for Immunotherapy

Identification and Validation of N6-Methyladenosine-Related Biomarkers for Bladder Cancer: Implications for Immunotherapy

Generation and Analysis of Pyroptosis-Based and Immune-Based Signatures for Kidney Renal Clear Cell Carcinoma Patients, and Cell Experiment

Identification of an Aging-Related Gene Signature in Predicting Prognosis and Indicating Tumor Immune Microenvironment in Breast Cancer

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