Metabolic Molecule PLA2G2D Is a Potential Prognostic Biomarker Correlating With Immune Cell Infiltration and the Expression of Immune Checkpoint Genes in Cervical Squamous Cell Carcinoma

Cervical squamous cell carcinoma (CSCC) is the major pathological type of cervical cancer (CC), the second most prevalent reproductive system malignant tumor threatening the health of women worldwide. The prognosis of CSCC patients is largely affected by the tumor immune microenvironment (TIME); however, the biomarker landscape related to the immune microenvironment of CSCC and patient prognosis is less characterized. Here, we analyzed RNA-seq data of CSCC patients from The Cancer Genome Atlas (TCGA) database by dividing it into high- and low-immune infiltration groups with the MCP-counter and ESTIMATE R packages. After combining weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis, we found that PLA2G2D, a metabolism-associated gene, is the top gene positively associated with immune infiltration and patient survival. This finding was validated using data from The Cancer Genome Characterization Initiative (CGCI) database and further confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, multiplex immunohistochemistry (mIHC) was performed to confirm the differential infiltration of immune cells between PLA2G2D-high and PLA2G2D-low tumors at the protein level. Our results demonstrated that PLA2G2D expression was significantly correlated with the infiltration of immune cells, especially T cells and macrophages. More importantly, PLA2G2D-high tumors also exhibited higher infiltration of CD8+ T cells inside the tumor region than PLA2G2D-low tumors. In addition, PLA2G2D expression was found to be positively correlated with the expression of multiple immune checkpoint genes (ICPs). Moreover, based on other immunotherapy cohort data, PLA2G2D high expression is correlated with increased cytotoxicity and favorable response to immune checkpoint blockade (ICB) therapy. Hence, PLA2G2D could be a novel potential biomarker for immune cell infiltration, patient survival, and the response to ICB therapy in CSCC and may represent a promising target for the treatment of CSCC patients.

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Exploration of a Robust and Prognostic Immune Related Gene Signature for Cervical Squamous Cell Carcinoma

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.625470 ◽

2021 ◽

Vol 8 ◽

Author(s):

Zhihua Zuo ◽

Junjun Xiong ◽

Chuyi Zeng ◽

Yao Jiang ◽

Kang Xiong ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

T Cells ◽

Immune Cells ◽

Immune Cell ◽

Risk Group ◽

External Validation ◽

Cervical Squamous Cell Carcinoma ◽

Immune Cell Infiltration ◽

Prognostic Signature ◽

Kaplan Meier

Background: Cervical squamous cell carcinoma (CESC) is one of the most frequent malignancies in women worldwide. The level of immune cell infiltration and immune-related genes (IRGs) can significantly affect the prognosis and immunotherapy of CESC patients. Thus, this study aimed to identify an immune-related prognostic signature for CESC.Methods: TCGA-CESC cohorts, obtained from TCGA database, were divided into the training group and testing group; while GSE44001 dataset from GEO database was viewed as external validation group. ESTIMATE algorithm was applied to evaluate the infiltration levels of immune cells of CESC patients. IRGs were screened out through weighted gene co-expression network analysis (WGCNA). A multi-gene prognostic signature based on IRGs was constructed using LASSO penalized Cox proportional hazards regression, which was validated through Kaplan–Meier, Cox, and receiver operating characteristic curve (ROC) analyses. The abundance of immune cells was calculated using ssGSEA algorithm in the ImmuCellAI database, and the response to immunotherapy was evaluated using immunophenoscore (IPS) analysis and the TIDE algorithm.Results: In TCGA-CESC cohorts, higher levels of immune cell infiltration were closely associated with better prognoses. Moreover, a prognostic signature was constructed using three IRGs. Based on this given signature, Kaplan–Meier analysis suggested the significant differences in overall survival (OS) and the ROC analysis demonstrated its robust predictive potential for CESC prognosis, further confirmed by internal and external validation. Additionally, multivariate Cox analysis revealed that the three IRGs signature served as an independent prognostic factor for CESC. In the three-IRGs signature low-risk group, the infiltrating immune cells (B cells, CD4/8 + T cells, cytotoxic T cells, macrophages and so on) were much more abundant than that in high-risk group. Ultimately, IPS and TIDE analyses showed that low-risk CESC patients appeared to present with a better response to immunotherapy and a better prognosis than high-risk patients.Conclusion: The present prognostic signature based on three IRGs (CD3E, CD3D, LCK) was not only reliable for survival prediction but efficient to predict the clinical response to immunotherapy for CESC patients, which might assist in guiding more precise individual treatment in the future.

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Identification of Two Novel Alternative Splicing-related Genes in the Cervical Cancer Immune Microenvironment

10.21203/rs.3.rs-1030113/v1 ◽

2021 ◽

Author(s):

Dan Sun ◽

Zhifu Zhi ◽

Aiqian Zhang ◽

Bingsi Gao ◽

Lingxiao Zou ◽

...

Keyword(s):

Cervical Cancer ◽

T Cells ◽

Alternative Splicing ◽

Mast Cells ◽

Risk Score ◽

Immune Cells ◽

Immune Checkpoint ◽

Immune Microenvironment ◽

Hub Genes ◽

Checkpoint Genes

Abstract Background: Cervical cancer (CC) is one of the most common malignant tumors of the female reproductive system. The tumor immunotherapy showed the remarkable effect. Associated alternative splicing (AS)-event signatures provide potential therapeutic targets and improved strategies for new drug development in CC management.Methods: Clinical information and messenger RNA (mRNA) expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Hub genes were extracted from the 7 AS-related genes for correlation analysis with clinical parameters and tumor-immune microenvironment. The relationship between the risk score and the 6 most important checkpoint genes was investigated. Finally, we estimated the Stroma and Immune cells using the Expression data (ESTIMATE) algorithm.Results: It was revealed that T cells CD8, T cells regulatory (Tregs), T cells CD4 memory activated, neutrophils, mast cells resting, mast cells activated, and macrophages M0 had a significant difference between the low- and high risk-score groups. The genes SHF and FOXRED2 were extracted as hub genes. High expression of SHF (P < 0.002) and low expression of FOXRED2 (P < 0.001) were associated with poor prognosis..Immune checkpoint genes IDO1, PDCD1, and HAVCR2, were negatively correlated with risk-score.Conclusions: We used bioinformatics to assess the heterogeneity of tumor-infiltrating immune cells in CESC and discovered out 2 hub genes, SHF and FOXRED2, from the AS prognostic model. The immune checkpoint genes IDO1, PDCD1, and HAVCR2, showed negative correlations with risk-score. The outcomes were significant for studying tumor progression's immune-related mechanisms and exploring novel prognostic predictors and precise therapy methods.

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48 Immune environment correlates with NSCLC and CRC patient survival

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-sitc2021.048 ◽

2021 ◽

Vol 9 (Suppl 3) ◽

pp. A55-A55

Author(s):

Dannah Miller ◽

Huong Nguyen ◽

Kate Hieber ◽

Charles Caldwell ◽

Roberto Gianani

Keyword(s):

T Cells ◽

Image Analysis ◽

Immune Cells ◽

Survival Data ◽

Immune Cell ◽

Patient Survival ◽

Machine Learning Algorithms ◽

Primary Tumors ◽

Cell Lung Carcinoma ◽

Analysis Platform

BackgroundImmune cells within the tumor microenvironment (TME) play a vital role in regulating tumor progression. Therefore, immunotherapies that stimulate anti-tumor responses are of great interest for the treatment of various cancers. PD-L1 expression on immune cells is positively correlated with increased patient survival. Our hypothesis is that non-small cell lung carcinoma (NSCLC) and colorectal cancer (CRC) patients with high immune infiltration and greater amounts of anti-tumor immune cells within the tumor compartment have an increased time of survival compared to cancers with immune excluded or immune desert environments.MethodsOne NSCLC and one CRC tumor microarray (TMA) containing primary tumors, metastases, and normal tissue were stained via multiplex immunofluorescence (mIF) for 6 different immune markers: CD3, CD8, CD56, CD68, CD163, and PD-L1. This multiplex panel was designed to evaluate the immune cell population as well as tumor and immune cell PD-L1 status to aid in research for immunotherapies, specifically anti-PD-L1 therapies. The stained TMAs were analyzed utilizing Flagship Biosciences’ proprietary image analysis platform. Machine learning algorithms stratified cells as belonging to the tumoral or stromal space based on their cellular features. Core level expression data was pulled and represented on a whole-cohort basis. All staining and image analysis outputs were reviewed by a board-certified, MD pathologist. Kaplan-meier curves were generated based on survival data in relation to the levels of immune cells present within the tumor cores as well as the percentage of immune cells infiltrating into the tumor.ResultsThere is a clear correlation between patient survival and the presence or absence of various types of immune cells, including helper T cells, cytotoxic T cells, M1 macrophages, M2, macrophages, NK cells, as well as PDL1 expression on tumor and immune cells. Specifically, the increased presence of anti-tumor immune cells as well as increased expression of PD-L1 on immune cells within the tumor compartment correlates with an increase in patient survival.ConclusionsData generated through Flagship Biosciences’ image analysis platform showed a strong relationship between immune cell presence and localization and NSCLC and CRC patient survival. Altering the immune cells within the tumor to an anti-tumor immune environment could increase patient survival times. Combining immune checkpoint inhibitors with current FDA approved therapies for NSCLC and CRC are of interest to further extend patient survival. Further, utilizing Flagship Biosciences’ image analysis software to understand cancer immune microenvironments should be further utilized to aid in diagnosis and treatment decisions.

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Spatial Profiles of Intratumoral PD-1+ Helper T Cells Predict Prognosis in Head and Neck Squamous Cell Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.769534 ◽

2021 ◽

Vol 12 ◽

Author(s):

Kanako Yoshimura ◽

Takahiro Tsujikawa ◽

Junichi Mitsuda ◽

Hiroshi Ogi ◽

Sumiyo Saburi ◽

...

Keyword(s):

Squamous Cell Carcinoma ◽

T Cells ◽

Tumor Cell ◽

Cell Carcinoma ◽

Squamous Cell ◽

Immune Cells ◽

High Density ◽

Helper T Cells ◽

Tissue Segmentation ◽

Immune Microenvironment

BackgroundFunctional interactions between immune cells and neoplastic cells in the tumor immune microenvironment have been actively pursued for both biomarker discovery for patient stratification, as well as therapeutic anti-cancer targets to improve clinical outcomes. Although accumulating evidence indicates that intratumoral infiltration of immune cells has prognostic significance, limited information is available on the spatial infiltration patterns of immune cells within intratumoral regions. This study aimed to understand the intratumoral heterogeneity and spatial distribution of immune cell infiltrates associated with cell phenotypes and prognosis in head and neck squamous cell carcinoma (HNSCC).MethodsA total of 88 specimens of oropharyngeal squamous cell carcinoma, categorized into discovery (n = 38) and validation cohorts (n = 51), were analyzed for immune contexture by multiplexed immunohistochemistry (IHC) and image cytometry-based quantification. Tissue segmentation was performed according to a mathematical morphological approach using neoplastic cell IHC images to dissect intratumoral regions into tumor cell nests versus intratumoral stroma.ResultsTissue segmentation revealed heterogeneity in intratumoral T cells, varying from tumor cell nest-polarized to intratumoral stroma-polarized distributions. Leukocyte composition analysis revealed higher ratios of TH1/TH2 in tumor cell nests with higher percentages of helper T cells, B cells, and CD66b+ granulocytes within intratumoral stroma. A discovery and validation approach revealed a high density of programmed death receptor-1 (PD-1)+ helper T cells in tumor cell nests as a negative prognostic factor for short overall survival. CD163+ tumor-associated macrophages (TAM) provided the strongest correlation with PD-1+ helper T cells, and cases with a high density of PD-1+ helper T cells and CD163+ TAM had a significantly shorter overall survival than other cases.ConclusionThis study reveals the significance of analyzing intratumoral cell nests and reports that an immune microenvironment with a high density of PD-1+ helper T cells in tumoral cell nests is a poor prognostic factor for HNSCC.

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Identification of the Prognosis Value and Potential Mechanism of Immune Checkpoints in Renal Clear Cell Carcinoma Microenvironment

Frontiers in Oncology ◽

10.3389/fonc.2021.720125 ◽

2021 ◽

Vol 11 ◽

Author(s):

Guodong Liao ◽

Ping Wang ◽

Yuyong Wang

Keyword(s):

Immune Checkpoint ◽

Prognostic Value ◽

Immune Cell ◽

Clear Cell ◽

Clear Cell Carcinoma ◽

Renal Clear Cell Carcinoma ◽

Immune Checkpoints ◽

Immune Cell Infiltration ◽

Free Survival ◽

Checkpoint Genes

BackgroundKidney Renal Clear Cell Carcinoma (KIRC) is one of the most prevalent types of cancer worldwide. KIRC has a poor prognosis and, to date, immunotherapy based on immune checkpoints is the most promising treatment. However, the role of immune checkpoints in KIRC remains ambiguous.MethodsBioinformatics analyses and qRT-PCR were performed to explore and further confirm the prognostic value of immune checkpoint genes and their correlation with immune infiltration in KIRC samples.ResultsThe expression of the immune checkpoint genes CD274, PDCD1LG2, HAVCR2, CTLA4, TIGFT, LAG3, and PDCD1 was upregulated in KIRC tissues. These genes were involved in the activation of the apoptosis pathway in KIRC. Low expression of CD274 and HAVCR2 and high expression of CTLA4 were associated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of KIRC patients. The univariate and multivariate analyses revealed that CTLA4, HAVCR2, age, pTNM stage, and tumor grade were independent factors affecting the prognosis of KIRC patients. A predictive nomogram demonstrated that the calibration plots for the 3‐year and 5‐year OS probabilities showed good agreement compared to the actual OS of KIRC patients. The expression of CTLA4 and HAVCR2 were positively associated with immune cell infiltration, immune biomarkers, chemokines, and chemokine receptors. Moreover, miR-20b-5p was identified as a potential miRNA target of CTLA4 in KIRC.ConclusionOur study clarified the prognostic value of several immune checkpoint regulators in KIRC, revealing a CTLA4/miR-20b-5p axis in the control of immune cell infiltration in the tumor microenvironment.

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Landscape of Immune Microenvironment Under Immune Cell Infiltration Pattern in Breast Cancer

Frontiers in Immunology ◽

10.3389/fimmu.2021.711433 ◽

2021 ◽

Vol 12 ◽

Author(s):

Qianhui Xu ◽

Shaohuai Chen ◽

Yuanbo Hu ◽

Wen Huang

Keyword(s):

Breast Cancer ◽

Immune Cells ◽

Immune Cell ◽

Principal Component ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Signal Pathways ◽

Immune Cell Infiltration ◽

Consensus Clustering ◽

Immune Microenvironment

BackgroundIncreasing evdence supports the suggestion that the immune cell infiltration (ICI) patterns play a pivotal role in tumor progression in breast cancer (BRCA). Nonetheless, there has been no comprehensive analysis of the ICI patterns effects on the clinical outcomes and immunotherapy.MethodsMultiomic data for BRCA samples were downloaded from TCGA. ESTIMATE algorithm, ssGSEA method, and CIBERSORT analysis were used to uncover the landscape of the tumor immune microenvironment (TIME). BRCA subtypes based on the ICI pattern were identified by consensus clustering and principal-component analysis was performed to obtain the ICI scores to quantify the ICI patterns in individual tumors. Their prognostic value was validated by the Kaplan-Meier survival curves. Gene set enrichment analysis (GSEA) was applied for functional annotation. Immunophenoscore (IPS) was employed to explore the immunotherapeutic role of the ICI scores. Finally, the mutation data was analyzed by using the “maftools” R package.ResultsThree different immune infiltration patterns with a distinct prognosis and biological signature were recognized among 1,198 BRCA samples. The characteristics of TIME under these three patterns were highly consistent with three known immune profiles: immune- excluded, immune-desert, and immune-inflamed phenotypes, respectively. The identification of the ICI patterns within individual tumors based on the ICI score, developed under the ICI-related signature genes, contributed into dissecting biological processes, clinical outcome, immune cells infiltration, immunotherapeutic effect, and genetic variation. High ICI score subtype, characterized with a suppression of immunity, suggested an immune-exhausted phenotype. Abundant effective immune cells were discovered in the low ICI score patients, which corresponded to an immune-activated phenotype and might present an immunotherapeutic advantage. Immunophenoscore was implemented as a surrogate of immunotherapeutic outcome, low-ICI scores samples obtained a significantly higher immunophenoscore. Enrichment of the JAK/STAT and VEGF signal pathways were activated in the ICI low-score subgroup. Finally, the synergistic effect between the ICI score and the tumor mutation burden (TMB) was confirmed.ConclusionThis work comprehensively elucidated that the ICI patterns served as an indispensable player in complexity and diversity of TIME. Quantitative identification of the ICI patterns in individual tumor will contribute into mapping the landscape of TIME further optimizing precision immunotherapy.

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Ferroptosis Regulators and Tumor Microenvironment Immune Cell Infiltration Characterization in Adrenocortical Carcinoma

10.21203/rs.3.rs-1242199/v1 ◽

2022 ◽

Author(s):

Chengquan Shen ◽

Jing Liu ◽

Ye Liang ◽

Zhijuan Liang ◽

Liping Wang ◽

...

Keyword(s):

Tumor Microenvironment ◽

Signaling Pathway ◽

Immune Checkpoint ◽

Adrenocortical Carcinoma ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Genes Expression ◽

Receptor Signaling Pathway ◽

Checkpoint Genes

Abstract Background Adrenocortical carcinoma (ACC) is a rare disease with a poor prognosis and lacking effective systemic treatment options. Recent studies showed that ferroptosis play a prominent role in the initiation and development of cancer. Nonetheless, the potential roles of ferroptosis regulators in the prognosis and tumor microenvironment immunomodulator factors expression remain not fully study. Methods TCGA and GEO ACC datasets were used to investigate the relationship between ferroptosis regulators with prognosis and clinical features. Consensus clustering analysis was performed to divided ACC patients into different ferroptosis subgroups. A ferroptosis scoring system was established for individual ACC using principal component analysis algorithms. The correlation between ferroptosis score and tumor microenvironment immune cell infiltration was analyzed. Results Twenty ferroptosis regulators were differentially expressed in ACC and 17 ferroptosis regulators were closely related to the prognosis of ACC. Three ferroptosis subgroups (Cluster A, B, and C) were determined based on the expression of ferroptosis regulators. Cluster C is preferentially associated with favorable OS, PFS, upregulated antigen-presenting genes expression, and higher immune cell infiltration. GSEA also indicated that Cluster C was prominently related to immune fully activation including chemokine signaling pathway, natural killer cell-mediated cytotoxicity, T cell receptor signaling pathway, and Toll-like receptor signaling pathway. A ferroptosis scoring system was constructed and it could serve as an independent prognostic factor for ACC. The ferroptosis scores were significantly correlated with TMB, immune-checkpoint genes expression, and tumor microenvironment immune cell infiltration in ACC. Further analyses indicated that the ferroptosis score integrated with TMB, immune-checkpoint genes expression, and CD4+ T cell infiltration, could predict the prognosis of ACC. Furthermore, a nomogram was constructed to monitor the prognosis of individual ACC patient. RNA isolation and reverse transcription‑quantitative PCR (RT-qPCR) demonstrated significant differences in the expression levels of ACSL4, FANCD2 and SLC7A1 between ACC and normal tissues. Conclusion Our study demonstrated ferroptosis regulators were significantly associated with the prognosis, clinical characteristics, immune-checkpoint genes expression, and tumor microenvironment immune cell infiltration in ACC. This current study provided comprehensive evidence for further research on ferroptosis regulators in ACC and provides new enlightenment for epigenetic regulation of antitumor immune response.

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Identification of an Exosome-Related Signature Associated with Prognosis and Immune Infiltration in Breast Cancer

10.21203/rs.3.rs-1199471/v1 ◽

2022 ◽

Author(s):

Qiaonan Guo ◽

Pengjun Qiu ◽

Kelun Pan ◽

Jianpeng Chen ◽

Jianqing Lin

Keyword(s):

Breast Cancer ◽

T Cells ◽

High Risk ◽

Immune Cell ◽

Risk Group ◽

Risk Groups ◽

Low Risk ◽

Immune Cell Infiltration ◽

Immune Microenvironment ◽

Expression Levels

Abstract Background: Exosomes are nanosized vesicles, play a vital role in breast cancer (BC) occurrence, development, invasion, metastasis, and drug resistance. Nevertheless, studies about exosome-related genes in breast cancer are limited. Besides, the interaction between the exosomes and tumor immune microenvironment (TIME) in BC are still unclear. Hence, we procced to study the potential prognostic value of exosome-related genes and their relationship to immune microenvironment in BC. Methods: 121 exosome-related genes were provided by ExoBCD database and 7 final genes were selected from the intersection of 33 differential expression genes (DEGs) and 19 prognostic genes in BC. Based on the expression levels of the 7 genes, downloaded from The Cancer Genome Atlas (TCGA) database, as well as the regression coefficients, the exosome-related signature was constructed. As a result, the patients in TCGA and GEO database were separated into low- and high- risk groups, respectively. Subsequently, R clusterProfiler package was applied to identify the distinct enrichment pathways between high-risk group and low-risk group. The ESTIMATE method was used to calculate ESTIMATE Score and CIBERSORT was applied to evaluate the immune cell infiltration. Eventually, the different expression levels of immune checkpoint related genes were analyzed between the two risk groups. Results: Results of BC prognosis vary from different risk groups. The low-risk groups were identified with higher survival rate both in TCGA and GEO cohort. The DEGs between high- and low- risk groups were found to enrich in immunity, biological processes, and inflammation pathways. The BC patients with higher ESTIMATE scores were revealed to have better overall survival (OS). Subsequently, CD8+ T cells, naive B cells, CD4+ resting memory T cells, monocytes, and neutrophils were upregulated, while M0 macrophages and M2 macrophages were downregulated in the low-risk group. At last, 4 genes reported as the targets of immune checkpoint inhibitors were further analyzed. The low-risk groups in TCGA and GEO cohorts were indicated with higher expression levels of LAG-3, CD274, TIGIT and CTLA-4. Conclusion: According to this study, exosomes are closely associated with the prognosis and immune cell infiltration of BC patients. These findings may make contributions to improve immunotherapy and bring a new sight for BC treatment strategies.

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Five Genes as Diagnostic Markers of Ischemic Stroke and Their Correlation with Immune Infiltration

10.21203/rs.3.rs-936536/v1 ◽

2021 ◽

Author(s):

Meng Wang ◽

Ruijie Zhang ◽

Qiongfeng Guan ◽

Yindan Yao ◽

Liyuan Han

Keyword(s):

T Cells ◽

Dendritic Cells ◽

Ischemic Stroke ◽

Immune Cells ◽

Immune Cell ◽

Diagnostic Markers ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Γδt Cells ◽

Negatively Associated

Abstract Background: This study aimed to identify potential diagnostic markers of ischemic stroke (IS) and discuss the function of immune cell infiltration during the pathological process. Methods: We used IS datasets from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified, and functional correlation analysis was performed. We then screened and verified the diagnostic markers of IS. We evaluated the infiltration of immune cells in infarcts using CIBERSORT and analyzed the correlation between diagnostic markers and infiltrating immune cells. Results: A total of 366 DEGs were screened in this study. Genes encoding CTSG, F13A1, PABPC1, ECHDC2, BIRC2 and infiltrating monocytes, M0 macrophages, activated dendritic cells, and neutrophils (area under the curve [AUC] = 0.945) were identified as diagnostic markers of IS. Immune cell infiltration analysis suggested that memory B cells, regulatory T cells, M0 macrophages, CD8 + T cells, γδT cells, activated natural killer cells, monocytes, activated mast cells, and neutrophils were involved in the IS process. Analysis of correlations between expressed genes and infiltrating immune cells found that CTSG was positively associated with M0 macrophages, F13A1 was positively associated with monocytes, PABPC1 was positively associated with activated dendritic cells, eosinophils were negatively associated with neutrophils, ECHDC2 was negatively associated with monocytes, and BIRC2 was positively associated with eosinophils. Conclusion: five genes and four types of immune cells were identified as diagnostic markers of IS, and immune cell infiltration may play an important role in the progression of IS.

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

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.731380 ◽

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.

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