scholarly journals Identification of an Autophagy-Related Risk Signature Correlates With Immunophenotype and Predicts Immune Checkpoint Blockade Efficacy of Neuroblastoma

2021 ◽  
Vol 9 ◽  
Author(s):  
Wenjuan Kang ◽  
Jiajian Hu ◽  
Qiang Zhao ◽  
Fengju Song
Keyword(s):  
T Cells ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Immune Checkpoint Blockade ◽  
Low Risk ◽  
Checkpoint Blockade ◽  
Gene Set Enrichment Analysis ◽  
Immune Microenvironment ◽  
Tumor Tissues

Neuroblastoma is one of the malignant solid tumors with the highest mortality in childhood. Targeted immunotherapy still cannot achieve satisfactory results due to heterogeneity and tolerance. Exploring markers related to prognosis and evaluating the immune microenvironment remain the major obstacles. Herein, we constructed an autophagy-related gene (ATG) risk model by multivariate Cox regression and least absolute shrinkage and selection operator regression, and identified four prognostic ATGs (BIRC5, GRID2, HK2, and RNASEL) in the training cohort, then verified the signature in the internal and external validation cohorts. BIRC5 and HK2 showed higher expression in MYCN amplified cell lines and tumor tissues consistently, whereas GRID2 and RNASEL showed the opposite trends. The correlation between the signature and clinicopathological parameters was further analyzed and showing consistency. A prognostic nomogram using risk score, International Neuroblastoma Staging System stage, age, and MYCN status was built subsequently, and the area under curves, net reclassification improvement, and integrated discrimination improvement showed more satisfactory prognostic predicting performance. The ATG prognostic signature itself can significantly divide patients with neuroblastoma into high- and low-risk groups; differentially expressed genes between the two groups were enriched in autophagy-related behaviors and immune cell reactions in gene set enrichment analysis (false discovery rate q -value < 0.05). Furthermore, we evaluated the relationship of the signature risk score with immune cell infiltration and the cancer-immunity cycle. The low-risk group was characterized by more abundant expression of chemokines and higher immune checkpoints (PDL1, PD1, CTLA-4, and IDO1). The risk score was significantly correlated with the proportions of CD8+ T cells, CD4+ memory resting T cells, follicular helper T cells, memory B cells, plasma cells, and M2 macrophages in tumor tissues. In conclusion, we developed and validated an autophagy-related signature that can accurately predict the prognosis, which might be meaningful to understand the immune microenvironment and guide immune checkpoint blockade.

scholarly journals O4 Mechanisms of lung cancer hyper-progression promoted by PD-1 immune checkpoint blockade

2020 ◽  
Vol 8 (Suppl 2) ◽  
pp. A5.1-A5
Author(s):  
A Martinez-Usatorre ◽  
E Kadioglu ◽  
C Cianciaruso ◽  
B Torchia ◽  
J Faget ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Regulatory T Cells ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Immune Checkpoint Blockade ◽  
Genetically Engineered ◽  
Checkpoint Blockade ◽  
Therapeutic Benefits ◽  
Angiopoietin 2

BackgroundImmune checkpoint blockade (ICB) with antibodies against PD-1 or PD-L1 may provide therapeutic benefits in patients with non-small cell lung cancer (NSCLC). However, most tumours are resistant and cases of disease hyper-progression have also been reported.Materials and MethodsGenetically engineered mouse models of KrasG12Dp53null NSCLC were treated with cisplatin along with antibodies against angiopoietin-2/VEGFA, PD-1 and CSF1R. Tumour growth was monitored by micro-computed tomography and the tumour vasculature and immune cell infiltrates were assessed by immunofluorescence staining and flow cytometry.ResultsCombined angiopoietin-2/VEGFA blockade by a bispecific antibody (A2V) modulated the vasculature and abated immunosuppressive macrophages while increasing CD8+effector T cells in the tumours, achieving disease stabilization comparable or superior to cisplatin-based chemotherapy. However, these immunological responses were unexpectedly limited by the addition of a PD-1 antibody, which paradoxically enhanced progression of a fraction of the tumours through a mechanism involving regulatory T cells and macrophages. Elimination of tumour-associated macrophages with a CSF1R-blocking antibody induced NSCLC regression in combination with PD-1 blockade and cisplatin.ConclusionsThe immune cell composition of the tumour determines the outcome of PD-1 blockade. In NSCLC, high infiltration of regulatory T cells and immunosuppressive macrophages may account for tumour hyper-progression upon ICB.Disclosure InformationA. Martinez-Usatorre: None. E. Kadioglu: None. C. Cianciaruso: None. B. Torchia: None. J. Faget: None. E. Meylan: None. M. Schmittnaegel: None. I. Keklikoglou: None. M. De Palma: None.

scholarly journals Identification of Robust Immune‐Associated lncRNAs Signature for Immune Checkpoint Blockade and Prognosis in Breast Cancer

2020 ◽  
Author(s):  
Qianhui Xu ◽  
Yuxin Wang ◽  
Wen Huang
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Immune Checkpoint ◽  
Risk Model ◽  
Cox Regression ◽  
Checkpoint Inhibitors ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas

Abstract Background: There have numerous evidences to support that long non-coding RNAs (lncRNAs) may be crucial parts in cancer immunity. We aimed to establish a novel and robust immune-associated lncRNAs signature to improve prognostic precision in patients with breast cancer(BRCA).Methods: BRCA cases were obtained from the The Cancer Genome Atlas (TCGA) database. Immune‐related lncRNAs presenting significant association with prognosis were screened through stepwise univariate Cox regression and LASSO algorithm, and multivariate Cox regression. Kaplan-Meier analysis, ROC analyses, and proportional hazards model further conducted. The prediction reliability was further estimated in the internal validation set and combination set. Gene set enrichment analysis (GSEA) was applied for functional annotation. The correlation between immune checkpoint inhibitors and this signature was employed. Results: 13 immune-related lncRNAs were systematically identified to establish immune-related lncRNAs predictive prognosis signature. The risk model we built showed significant correlation with BRCA patients’ prognosis. The value of ROC for this lncRNAs model was up to 0.821. This immune‐related lncRNAs signature can serve as an independent prognostic biomolecular factor. Our lncRNAs signature involved in chondrocyte development, endoderm development and so forth. This lncRNAs risk model was associated with tumor immune infiltration (i.e., B cells, Dendritic, Neutrophils, CD8 T cells and CD4 T cells, etc.,) and immune checkpoint blockade (ICB) therapy key molecules (i.e., PDCD1).Conclusion: The immune‐related lncRNA signature we established possesses latent prognostic value for patients with BRCA and may have the capability to predict the clinical outcome of ICB treatment, which could provide guidance for immunological decision in patients with BRCA.

scholarly journals Identification of Robust Immune‐Associated lncRNAs Signature for Immune Checkpoint Blockade and Prognosis in Pancreatic Ductal Adenocarcinoma

2020 ◽  
Author(s):  
Qianhui Xu ◽  
Yuxin Wang ◽  
Wen Huang
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Cox Regression ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Ductal Adenocarcinoma ◽  
Cox Regression Analysis

Abstract Background: An increasing body of evidence has suggested that long non-coding RNAs (lncRNAs) can serve as essential regulators in cancer immunity. We aimed to establish a robust immune-associated lncRNA signature for pancreatic ductal adenocarcinoma (PDAC) outcome prediction to enhance prognostic accuracy.Methods: Pancreatic cancer samples were obtained from the The Cancer Genome Atlas (TCGA) project. Immune‐related lncRNAs displaying significant association with overall survival (OS) were screened through univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. The prediction reliability was further estimated in the internal validation set and combination set. Gene set enrichment analysis (GSEA) of the lncRNA model risk score was performed for functional annotation. The correlation between immune checkpoint inhibitors and this signature was examined. Results: 5 immune-related lncRNAs were confirmed to establish five‐immune-related lncRNAs prognostic signature. The constructed risk model showed significant correlation with PDAC OS. The area under the curve (AUC) for this lncRNA model was up to 0.747. This immune‐related lncRNA signature was correlated with disease progression and worse survival and was an independent prognostic biomarker. Our signature mediated chondrocyte development, laminin binding and so forth. This risk score model was associated with immune cell infiltration (i.e., CD4 T cells, etc.,) and immune checkpoint blockade (ICB) immunotherapy‐related molecules (i.e., PDCD1 and CTLA4).Conclusion: The immune‐related lncRNA signature we established possesses latent prognostic value for patients with PDAC and may have the potential to measure the response to ICB immunotherapy, which could guide for immunological treatment in PDAC.

scholarly journals Immune checkpoint blockade impairs immunosuppressive mechanisms of regulatory T cells in B-cell lymphoma

2021 ◽  
Vol 14 (9) ◽  
pp. 101170
Author(s):  
Vera Bauer ◽  
Fatima Ahmetlić ◽  
Nadine Hömberg ◽  
Albert Geishauser ◽  
Martin Röcken ◽  
...  
Keyword(s):  
T Cells ◽  
Regulatory T Cells ◽  
B Cell ◽  
Immune Checkpoint ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade

scholarly journals Identification of a two-gene prognostic model associated with cytolytic activity for colon cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaoye Jiang ◽  
Zhongxiang Jiang ◽  
Lichun Xiang ◽  
Xuenuo Chen ◽  
Jiao Wu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Risk Score ◽  
Immune Checkpoint ◽  
Prognostic Model ◽  
Quantitative Polymerase Chain Reaction ◽  
Cytolytic Activity ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Aberrant Expression ◽  
Immune Activity

Abstract Background Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT. Methods A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors. Results In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy. Conclusions Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy.

scholarly journals IMMU-19. TARGETING GLIOBLASTOMA IMMUNOSUPPRESSION AND TREATMENT RESISTANCE WITH IBRUTINIB IN COMBINATION WITH STEREOTACTIC RADIATION AND IMMUNE CHECKPOINT BLOCKADE

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii108-ii108
Author(s):  
Jayeeta Ghose ◽  
Baisakhi Raychaudhuri ◽  
Kevin Liu ◽  
William Jiang ◽  
Pooja Gulati ◽  
...  
Keyword(s):  
T Cells ◽  
Combination Therapy ◽  
Median Survival ◽  
Immune Checkpoint ◽  
Survival Benefit ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Control Group ◽  
Triple Combination ◽  
Triple Combination Therapy

Abstract BACKGROUND Glioblastoma (GBM) is associated with systemic and intratumoral immunosuppression. Part of this immunosuppression is mediated by myeloid derived suppressor cells (MDSCs). Preclinical evidence shows that ibrutinib, a tyrosine kinase inhibitor FDA approved for use in chronic lymphocytic leukemia and known to be CNS penetrant, can decrease MDSC generation and function. Also, focal radiation therapy (RT) synergizes with anti-PD-1 therapy in mouse GBM models. Thus, we aimed to test the combination of these approaches on immune activation and survival in a preclinical immune-intact GBM mouse model. METHODS C57BL/6 mice intracranially implanted with the murine glioma cell line GL261-Luc2 were divided into 8 groups consisting of treatments with ibrutinib, RT (10 Gy SRS), or anti-PD-1 individually or in each combination (along with a no treatment control group). Immune cell subset changes (flow-cytometry) and animal survival (Kaplan-Meier) were assessed (n=10 mice per group). RESULTS Median survival of the following groups including control (28 days), ibrutinib (27 days), RT (30 days) or anti-PD-1 (32 days) showed no significant differences. However, a significant improvement in median survival was seen in mice given combinations of ibrutinib+RT (35 days), ibrutinib+anti-PD-1 (38 days), and triple therapy with ibrutinib+RT+anti-PD-1 (48 days, p < 0.05) compared to controls or single treatment groups. The reproducible survival benefit of triple combination therapy was abrogated in the setting of CD4+ and CD8+ T cell depletion. Contralateral intracranial tumor re-challenge in long-term surviving mice suggested generation of tumor-specific immune memory responses. The immune profile of the tumor microenvironment (TME) showed increased cytotoxic CD8+ T cells and decreased MDSCs and regulatory T cells in the triple combination therapy mice compared to controls. CONCLUSION The combination of ibrutinib, focal RT, and anti-PD-1 immune checkpoint blockade led to a significant survival benefit compared to controls in a preclinical model of GBM.

scholarly journals Immune‐related Long Noncoding RNA Signature for Patients with Cervical Cancer

2020 ◽  
Author(s):  
Jianfeng Zheng ◽  
Jinyi Tong ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cell ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Training Set ◽  
Score Model

Abstract Background: Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune‐related lncRNAs(IRLs) of CC has never been reported. This study aimed to establish an IRL signature for patients with CC.Methods: The RNA-seq dataset was obtained from the TCGA, GEO, and GTEx database. The immune scores（IS）based on single-sample gene set enrichment analysis (ssGSEA) were calculated to identify the IRLs, which were then analyzed using univariate Cox regression analysis to identify significant prognostic IRLs. A risk score model was established to divide patients into low-risk and high-risk groups based on the median risk score of these IRLs. This was then validated by splitting TCGA dataset(n=304) into a training-set(n=152) and a valid-set(n=152). The fraction of 22 immune cell subpopulations was evaluated in each sample to identify the differences between low-risk and high-risk groups. Additionally, a ceRNA network associated with the IRLs was constructed.Results: A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson’s correlation analysis between immune score and lncRNA expression (P < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (P < 0.05) were identified which demonstrated an ability to stratify patients into low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low‐risk group showed longer overall survival (OS) than those in the high‐risk group in the training-set, valid-set, and total-set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four IRLs signature in predicting the one-, two-, and three-year survival rates were larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Conclusions: Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four-IRLs in the development of CC were ascertained preliminarily.

scholarly journals Non-conventional Inhibitory CD4+Foxp3–PD-1hi T Cells as a Biomarker of Immune Checkpoint Blockade Activity

Cancer Cell ◽  
2018 ◽  
Vol 34 (4) ◽  
pp. 691 ◽  
Author(s):  
Roberta Zappasodi ◽  
Sadna Budhu ◽  
Matthew D. Hellmann ◽  
Michael A. Postow ◽  
Yasin Senbabaoglu ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Checkpoint ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade
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