Identification of an immune checkpoint gene signature that accurately predicts prognosis and immunotherapy response in endometrial carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with relatively high malignancy and rapid disease progression. Metabolism-related genes (MRGs) are involved in the pathogenesis of HCC. This study explored potential key MRGs and their effect on T-cell immune function in the tumor immune microenvironment to provide new insight for the treatment of HCC. Of 456 differentially expressed MRGs identified from TCGA database, 21 were screened by MCODE and cytoHubba algorithms. From the key module, GAD1, SPP1, WFS1, GOT2, EHHADH, and APOA1 were selected for validation. The six MRGs were closely correlated with survival outcomes and clinicopathological characteristics in HCC. Receiver operating characteristics analysis and Kaplan-Meier plots showed that these genes had good prognostic value for HCC. Gene set enrichment analysis of the six MRGs indicated that they were associated with HCC development. TIMER and GEPIA databases revealed that WFS1 was significantly positively correlated and EHHADH was negatively correlated with tumor immune cell infiltration and immune checkpoint expression. Finally, quantificational real-time polymerase chain reaction (qRT-PCR) confirmed the expression of WFS1 and EHHADH mRNA in our own patients’ cohort samples and four HCC cell lines. Collectively, the present study identified six potential MRG biomarkers associated with the prognosis and tumor immune infiltration of HCC, thus providing new insight into the pathogenesis and treatment of HCC.

Download Full-text

An Immune Checkpoint-Related Gene Signature for Predicting Survival of Pediatric Acute Myeloid Leukemia

Journal of Oncology ◽

10.1155/2021/5550116 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Feng Jiang ◽

Xin-Yu Wang ◽

Ming-Yan Wang ◽

Yan Mao ◽

Xiao-Lin Miao ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Immune Checkpoint ◽

Myeloid Leukemia ◽

Immune Cell ◽

Cox Regression ◽

Secondary Data ◽

Gene Signature ◽

Pediatric Acute Myeloid Leukemia ◽

Pediatric Aml ◽

Acute Myeloid

Objective. The aim of this research was to create a new genetic signature of immune checkpoint-associated genes as a prognostic method for pediatric acute myeloid leukemia (AML). Methods. Transcriptome profiles and clinical follow-up details were obtained in Therapeutically Applicable Research to Generate Effective Treatments (TARGET), a database of pediatric tumors. Secondary data was collected from the Gene Expression Omnibus (GEO) to test the observations. In univariate Cox regression and multivariate Cox regression studies, the expression of immune checkpoint-related genes was studied. A three-mRNA signature was developed for predicting pediatric AML patient survival. Furthermore, the GEO cohort was used to confirm the reliability. A bioinformatics method was utilized to identify the diagnostic and prognostic value. Results. A three-gene (STAT1, BATF, EML4) signature was developed to identify patients into two danger categories depending on their OS. A multivariate regression study showed that the immune checkpoint-related signature (STAT1, BATF, EML4) was an independent indicator of pediatric AML. By immune cell subtypes analyses, the signature was correlated with multiple subtypes of immune cells. Conclusion. In summary, our three-gene signature can be a useful tool to predict the OS in AML patients.

Download Full-text

The effect of m6A RNA methylation regulators on tumor microenvironment in clear cell renal cell carcinoma

10.21203/rs.3.rs-283399/v1 ◽

2021 ◽

Author(s):

Shuaishuai Huang ◽

Xiaodong Qing ◽

Qiuzi Lin ◽

Qiaoling Wu ◽

Xue Wang ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Tumor Microenvironment ◽

Immune Checkpoint ◽

Renal Cell ◽

Clear Cell ◽

Gene Signature ◽

Consensus Clustering ◽

Cell Renal Cell Carcinoma ◽

Rna Methylation ◽

M6a Rna Methylation

Abstract Background: m6A RNA methylation and tumor microenvironment (TME) have been reported to play important roles in the progression and prognosis of clear cell renal cell carcinoma (ccRCC). However, whether m6A RNA methylation regulators affect TME in ccRCC remains unknown. Thus, the current study is designed to comprehensively evaluate the effect of m6A RNA methylation regulators on TME in ccRCC.Methods: Transcriptome data of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering analysis was conducted based on the expressions of m6A RNA methylation regulators. Survival differences were evaluated by Kaplan-Meier (K-M) analysis between the clusters. DESeq2 package was used to analyze the differentially expressed genes (DEGs) between the clusters. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were analyzed by ClusterProfiler R package. Immune, stromal and ESTIMATE scores were assessed by ESTIMATE algorithm. CIBERSORT algorithm was applied to evaluate immune infiltration. The expressions of human leukocyte antigen (HLA), immune checkpoint molecules, and Th1/IFNγ gene signature associated with TME were also compared between the clusters. TIDE algorithm and subclass mapping were used to analyze the clinical response of different clusters to PD-1 and CTLA-4 blockade. Results: The expressions of fifteen m6A regulators were significantly different between ccRCC and normal kidney tissues. Based on the expressions of those fifteen m6A regulators, two clusters were identified by consensus clustering, in which cluster 1 had better overall survival (OS). A total of 4,429 DEGs were found between the two clusters, and were enriched into immune-related biological processes. Further analysis of the two clusters’ TME showed that cluster 1 had lower immune and ESTIMATE scores, higher expressions of HLA and lower expressions of immune checkpoint molecules. Besides, immune infiltration and the expressions of Th1/IFNγ gene signature also have significant differences between two clusters. Conclusions: Our study revealed that m6A regulators were important participants in the development of ccRCC, with a close relationship with TME.

Download Full-text

Dedifferentiated Endometrial Carcinoma Could be A Target for Immune Checkpoint Inhibitors (Anti PD-1/PD-L1 Antibodies)

International Journal of Molecular Sciences ◽

10.3390/ijms20153744 ◽

2019 ◽

Vol 20 (15) ◽

pp. 3744 ◽

Cited By ~ 3

Author(s):

Ruriko Ono ◽

Kentaro Nakayama ◽

Kohei Nakamura ◽

Hitomi Yamashita ◽

Tomoka Ishibashi ◽

...

Keyword(s):

Endometrial Carcinoma ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitors ◽

Checkpoint Inhibitors ◽

Tumor Infiltrating Lymphocytes ◽

Undifferentiated Carcinoma ◽

Endometrioid Adenocarcinoma ◽

Mmr Deficiency ◽

Well Differentiated ◽

Mmr Proteins

Dedifferentiated endometrial carcinoma (DDEC) is defined as an undifferentiated carcinoma admixed with differentiated endometrioid carcinoma (Grade 1 or 2). It has poor prognosis compared with Grade 3 endometrioid adenocarcinoma and is often associated with the loss of mismatch repair (MMR) proteins, which is seen in microsatellite instability (MSI)-type endometrial cancer. Recent studies have shown that the effectiveness of immune checkpoint inhibitor therapy is related to MMR deficiency; therefore, we analyzed the immunophenotype (MMR deficient and expression of PD-L1) of 17 DDEC cases. In the undifferentiated component, nine cases (53%) were deficient in MMR proteins and nine cases (53%) expressed PD-L1. PD-L1 expression was significantly associated with MMR deficiency (p = 0.026). In addition, the presence of tumor-infiltrating lymphocytes (CD8+) was significantly associated with MMR deficiency (p = 0.026). In contrast, none of the cases showed PD-L1 expression in the well-differentiated component. Our results show that DDEC could be a target for immune checkpoint inhibitors (anti PD-L1/PD-1 antibodies), especially in the undifferentiated component. As a treatment strategy for DDEC, conventional paclitaxel plus carboplatin and cisplatin plus doxorubicin therapies are effective for those with the well-differentiated component. However, by using immune checkpoint inhibitors in combination with other conventional treatments, it may be possible to control the undifferentiated component and improve prognosis.

Download Full-text

Panel-derived TMB and immune-related GEP are associated with the response to immune checkpoint inhibitors (ICIs) in urothelial cancers.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e17047 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e17047-e17047

Author(s):

Kien Thiam Tan ◽

Shu-Jen Chen ◽

Yi-Lin Hsieh ◽

Yu-Li Su ◽

Yi-hua Jan ◽

...

Keyword(s):

Internal Control ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitor ◽

Checkpoint Inhibitor ◽

Checkpoint Inhibitors ◽

Group Analysis ◽

Predictive Biomarkers ◽

Cell Types ◽

Gene Signature ◽

Chang Gung Memorial Hospital

e17047 Background: Tumor mutational burden (TMB) and gene expression profile (GEP) have emerged as potential biomarkers for the prediction of response to the immune checkpoint inhibitor (ICI) treatment. An interferon-g gene signature was shown recently to predict ICI response in a pan-cancer setting. For TMB, not only did TMB-high patients experience better clinical outcome with ICI, but panel-derived TMB was also shown to be comparable to the gold standard, TMB derived from whole exome sequencing. Here, we evaluate possible correlations between panel-derived TMB, as well as immune-related GEP, with ICI response in urothelial cancers. Methods: FFPE tumor tissues from 30 patients with urothelial cancers who had previously received ICI as monotherapies or combination with chemotherapies at Kaohsiung Chang Gung Memorial Hospital were retrospectively tested for targeted next-generation sequencing (ACTOnco) and quantitative PCR-based GEP (ACTTME), for the identification of nonsynonymous variants across 440 cancer-associated genes and expression levels of > 90 immune-related genes, respectively. TMB was calculated by using the sequenced regions of ACTOnco to estimate the number of somatic nonsynonymous mutations per megabase of all protein-coding genes. For ACTTME, Cq values were normalized to internal control before group analysis. RECIST criteria were used to categorize tumor response to the treatment. Results: Patients were defined as responders (CR/PR) and non-responders (SD/PD) according to the RECIST criteria. In the ICI monotherapy cohort, the responders (n = 8) had significantly higher TMB than non-responders (n = 15) (Median 16.2 muts/Mb vs. 6.5 muts/Mb, p= 0.0035). In contrast, for the cohort receiving ICI combination therapy, several genes implicated in hypoxia (HIF1A), suppressive cell types (Treg & MDSC) and immune checkpoint (PD-L2) were significantly elevated ( p< 0.05) in the non-responder group by 2 to 8 folds. Conclusions: Despite the fact that the cohort size is small, this study showed panel-derived TMB, as well as immune-related GEP, can potentially serve as predictive biomarkers to identify urothelial cancer patients for immune checkpoint inhibitor therapy.

Download Full-text

9-Gene Signature Correlated With CD8+ T Cell Infiltration Activated by IFN-γ: A Biomarker of Immune Checkpoint Therapy Response in Melanoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.622563 ◽

2021 ◽

Vol 12 ◽

Author(s):

Kexin Yan ◽

Yuxiu Lu ◽

Zhangyong Yan ◽

Yutao Wang

Keyword(s):

T Cell ◽

Tumor Microenvironment ◽

Immune Checkpoint ◽

Cellular Response ◽

Antigen Processing ◽

Checkpoint Inhibitors ◽

Prognostic Significance ◽

Gene Signature ◽

Melanoma Tumor ◽

Related Factors

PurposeTo identify CD8+ T cell-related factors and the co-expression network in melanoma and illustrate the interactions among CD8+ T cell-related genes in the melanoma tumor microenvironment.MethodWe obtained melanoma and paracancerous tissue mRNA matrices from TCGA-SKCM and GSE65904. The CIBERSORT algorithm was used to assess CD8+ T cell proportions, and the “estimate” package was used to assess melanoma tumor microenvironment purity. Weighted gene co-expression network analysis was used to identify the most related co-expression modules in TCGA-SKCM and GSE65904. Subsequently, a co-expression network was built based on the joint results in the two cohorts. Subsequently, we identified the core genes of the two most relevant modules of CD8+T lymphocytes according to the module correlation, and constructed the signature using ssGSEA. Later, we compared the signature with the existing classical pathways and gene sets, and confirmed the important prognostic significance of the signature in this paper.ResultsNine co-expressed genes were identified as CD8+ T cell-related genes enriched in the cellular response to interferon−gamma process and antigen processing and presentation of peptide antigen. In the low expression level group, inflammation and immune responses were weaker. Single-cell sequencing and immunohistochemistry indicated that these nine genes were highly expressed in CD8+ T cells group.ConclusionWe identified nine-gene signature, and the signature is considered as the biomarker for T lymphocyte response and clinical response to immune checkpoint inhibitors for melanoma

Download Full-text

Signature Based on Immune-Related LncRNA Can Predict Overall Survival of Osteosarcoma Patients

10.21203/rs.3.rs-45370/v1 ◽

2020 ◽

Author(s):

Longqing Li ◽

Lianghao Zhang ◽

Manhas Adbul Khader ◽

Yan Zhang ◽

Xinchang Lu ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Immune Checkpoint ◽

High Throughput Sequencing ◽

Immune Cell ◽

Cox Regression ◽

Risk Group ◽

Low Risk ◽

Checkpoint Gene ◽

Cox Regression Analysis

Abstract Background: Osteosarcoma is a malignant bone tumor common in children and adolescents. Metastatic status remains the most important guideline for classifying patients and making clinical decisions. Despite many efforts, newly diagnosed patients receive the same therapy that patients have received over the last 4 decades. With the development of high-throughput sequencing technology and the rise of immunotherapy, it is necessary to deeply explore the immune molecular mechanism of osteosarcoma.Methods: We obtained RNA-seq data and clinical information of osteosarcoma patients from TCGA database and TARGET database. With the help of co-expression analysis we identified immune-related lncRNA and then by means of univariate Cox regression analysis prognostic-related lncRNA was screened out. And also by using least absolute shrinkage and selection operator regression method a model based on immune-related lncRNA was constructed. The differences in overall survival, immune infiltration, immune checkpoint gene expression, and tumor microenvironmental immunity type between the two groups were evaluated.Results: We constructed a signature consisting of 13 lncRNA. Our results show that signatures can reliably predict the overall survival of patients with osteosarcoma and can bring net clinical benefits. Further more, the signatures can be used for further risk stratification of the metastasis patients. Patients in the low-risk group had higher immune cell infiltration and immune checkpoint gene expression. The results from gene set variation analysis show that patients in low-risk group are closely related to immune-related pathways when compared with patients in high-risk group. Finally, patients in the low-risk group are more likely to be classified as TMIT I and hence more likely to benefit from immunotherapy.Conclusion: Our signature may be a reliable marker for predicting the overall survival of patients with osteosarcoma.

Download Full-text

A Novel Immune Checkpoint-Related Gene Signature to Predict Overall Survival and Immunotherapy Response in Triple-Negative Breast Cancer

10.21203/rs.3.rs-528492/v1 ◽

2021 ◽

Author(s):

Jingyi Liu ◽

Siyuan Tian ◽

Yuwei Ling ◽

Xinyi Zhang ◽

Yan Li ◽

...

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Immune Checkpoint ◽

Triple Negative ◽

Cox Regression ◽

Expression Profiles ◽

Expression Patterns ◽

Molecular Taxonomy ◽

Gene Signature ◽

Cox Regression Analysis

Abstract Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer that lacks effective therapeutic targets. Immunotherapy is considered as a novel treatment strategy for TNBC. However, only some patients could benefit from the treatment. Limited studies have comprehensively explored expression patterns and prognostic value of immune checkpoint genes (ICGs) in TNBC. In this study, we downloaded relevant ICGs expression profiles and clinical TNBC data from the Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to develop a multi-gene signature for predicting the prognostic outcome. PDCD1, PDCD1LG2 and KIR3DL2 were identified as hub genes and incorporated into the model. This gene signature could stratify patients into two prognostic subgroups, and unfavorable clinical outcomes were observed in high-risk patients. The predictive performance was assessed by the receiver operating characteristic curves. Moreover, we also analyzed differences in immune status and therapeutic response between both groups. This novel gene signature may be served as a robust prognostic marker, but also an indicator reflecting immunotherapy response.

Download Full-text

Mapping the functional interactions at the tumor-immune checkpoint interface

10.1101/2021.10.06.462889 ◽

2021 ◽

Author(s):

Behnaz Bozorgui ◽

Elisabeth K Kong ◽

Augustin Luna ◽

Anil Korkut

Keyword(s):

Immune System ◽

Statistical Analysis ◽

Endometrial Carcinoma ◽

Immune Checkpoint ◽

Complex Space ◽

Patient Survival ◽

Analysis Framework ◽

Functional Interactions ◽

Immunotherapy Target

It is challenging to identify the tumor-immune system interactions that modulate immune states and immunotherapy responses due to the prohibitively complex space of possible interactions. Our statistical analysis framework, ImogiMap quantifies tumor-immune interactions based on their synergistic co-associations with immune-associated phenotypes. ImogiMap-based analyses recapitulated known interactions modulating immunotherapy responses and nominated the CD86/CD70 axis as an immunotherapy target that overlaps with IFNG overexpression and patient survival in endometrial carcinoma.

Download Full-text

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma

Cancer Cell International ◽

10.1186/s12935-021-02227-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Genhao Zhang ◽

Lisa Su ◽

Xianping Lv ◽

Qiankun Yang

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitors ◽

Doubling Time ◽

Cox Regression ◽

Checkpoint Inhibitors ◽

Gene Signature ◽

Tumor Doubling Time ◽

Prognosis Prediction ◽

Immune Related Genes

Abstract Background Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear. The current study aimed to discover reliable biomarkers for anticipating the future prognosis of HCC patients based on the relationship between TDTRGs and IRGs. Methods Tumor doubling time-related genes (TDTRGs) were acquired from GSE54236 by using Pearson correlation test and immune-related genes (IRGs) were available from ImmPort. Prognostic TDTRGs and IRGs in TCGA-LIHC dataset were determined to create a prognostic model by the LASSO-Cox regression and stepwise Cox regression analysis. International Cancer Genome Consortium (ICGC) and another cohort of individual clinical samples acted as external validations. Additionally, significant impacts of the signature on HCC immune microenvironment and reaction to immune checkpoint inhibitors were observed. Results Among the 68 overlapping genes identified as TDTRG and IRG, a total of 29 genes had significant prognostic relevance and were further selected by performing a LASSO-Cox regression model based on the minimum value of λ. Subsequently, a prognostic three-gene signature including HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), C-type lectin domain family 1 member B (CLEC1B), and Collectin sub-family member 12 (COLEC12) was finally identified by stepwise Cox proportional modeling. The signature exhibited superior accuracy in forecasting the survival outcomes of HCC patients in TCGA, ICGC and the independent clinical cohorts. Patients in high-risk subgroup had significantly increased levels of immune checkpoint molecules including PD-L1, CD276, CTLA4, CXCR4, IL1A, PD-L2, TGFB1, OX40 and CD137, and are therefore more sensitive to immune checkpoint inhibitors (ICIs) treatment. Finally, we first found that overexpression of CLEC1B inhibited the proliferation and migration ability of HuH7 cells. Conclusions In summary, the prognostic signature based on TDTRGs and IRGs could effectively help clinicians classify HCC patients for prognosis prediction and individualized immunotherapies.

Download Full-text