TIGER: A Web Portal of Tumor Immunotherapy Gene Expression Resource

chen, zhihang; Luo, Ziwei; Zhang, Di; Li, Huiqin; Liu, Xuefei; Zhu, Kaiyu; Zhang, Hongwan; Wang, Zongping; Zhou, Penghui; Ren, Jian; An, Zhen

doi:10.1101/2022.04.10.487568

Cited by 7 publications

(4 citation statements)

References 68 publications

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“…The TIMER, TIDE, CIBERSORT, CIBERSORT-ABS, QUANTISEQ, XCELL, MCPCOUNTER and EPIC algorithms are used for the estimation of their relationships. In addition, tumor immunotherapy gene expression resource (TIGER) [ 17 ] was used to analyze the effects of PDHB on the immunotherapeutic response.…”

Section: Methodsmentioning

confidence: 99%

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy

Zhang¹,

Yan²,

Liang³

et al. 2023

Heliyon

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Section: Methodsmentioning

confidence: 99%

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy

Zhang¹,

Yan²,

Liang³

et al. 2023

Heliyon

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“…All patients receiving three different ICIs were grouped into responders and non-responders basing on the calculated response in the ROC plotter website. A web portal of tumor immunotherapy gene expression resource named TIGER (http://tiger.canceromics.org/) [40] also provided information on the prognosis of patients and drug responses to ICIs in various tumors from different data sources.…”

Section: Effect Of Crabp2 Level On Prognosis and Response Of Icis In ...mentioning

confidence: 99%

CRABP2 regulates infiltration of cancer-associated fibroblasts and immune response in melanoma

ZENG,

CHEN,

et al. 2024

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Finding biomarkers for immunotherapy is an urgent issue in cancer treatment. Cellular retinoic acid-binding protein 2 (CRABP2) is a controversial factor in the occurrence and development of human tumors. However, there is limited research on the relationship between CRABP2 and immunotherapy response. This study found that negative correlations of CRABP2 and immune checkpoint markers (PD-1, PD-L1, and CTLA-4) were observed in breast invasive carcinoma (BRCA), skin cutaneous melanoma (SKCM), stomach adenocarcinoma (STAD) and testicular germ cell tumors (TGCT). In particular, in SKCM patients who were treated with PD-1 inhibitors, high levels of CRABP2 predicted poor prognosis. Additionally, CRABP2 expression was elevated in cancer-associated fibroblasts (CAFs) at the single-cell level. The expression of CRABP2 was positively correlated with markers of CAFs, such as MFAP5, PDPN, ITGA11, PDGFRα/β and THY1 in SKCM. To validate the tumor-promoting effect of CRABP2 in vivo , SKCM xenograft mice models with CRABP2 overexpression have been constructed. These models showed an increase in tumor weight and volume. Enrichment analysis indicated that CRABP2 may be involved in immune-related pathways of SKCM, such as extracellular matrix (ECM) receptor interaction and epithelial-mesenchymal transition (EMT). The study suggests that CRABP2 may regulate immunotherapy in SKCM patients by influencing infiltration of CAFs. In conclusion, this study provides new insights into the role of CRABP2 in immunotherapy response. The findings suggest that CRABP2 may be a promising biomarker for PD-1 inhibitors in SKCM patients. Further research is needed to confirm these findings and to explore the clinical implications of CRABP2 in immunotherapy.

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“…The TIGER online databases (33) was used to analyze sc-RNA sequencing sets of LUAD patients from GEO database. Two single-cell RNA-sequencing sets for LUAD, namely GSE131907 and GSE123904, were selected for specific analysis.…”

Section: Single-cell Rna-sequencing Analysismentioning

confidence: 99%

Comprehensively analysis of the FGD family with potential effects on prognosis and immune infiltration in lung adenocarcinoma

Zhang

Guan

et al. 2023

Preprint

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Background：The FGD family consists of six genes, namely FGD1/2/3/4/5/6. Their roles in lung adenocarcinoma have been unidentified. This research focused on determining the diagnostic efficacy, prognostic value, and immune-related functions of them in lung adenocarcinoma(LUAD). Methods：From the TCGA database, mRNA data for the FGD gene family and clinical data for the patients were obtained. Immunohistochemistry was performed to validate representative FGD gene’s expression. A relationship between the FGD genes and immune system molecules was examined using the TIMER and GEPIA databases, the ssGSEA and the MCPcounter methods. Clinical prognosis in LUAD were analyzed by searching for TCGA, KMplotter and GEPIA databases. The TIDE algorithm, TCIA, KMplotter, ROCplotter and ICBatlas databases were used to analyze the value of FGD2 in predicting the efficacy of immunotherapy. TIGER database was used to analyze single-cell RNA-sequencing data. The immune-related prognostic model was constructed using 3 machine learning algorithms: K-means clustering, LASSO regression, and WGCNA analysis. Results: All the six FGD genes’ protein and mRNA were aberrant expressed in the tissues of LUAD in contrast to healthy ones, and our external experiment confirmed FGD2’s expression pattern. Low expression of FGD2, 3, 5 resulted in a shorter OS time and were determined as independent prognostic factors via multivariate analyses. FGD2, 3, 5 were markedly linked to immune infiltration while FGD1, 4, 6 were not. Sc-RNA sequencing analysis indicating that FGD2, 3, 5 were mainly expressed in immunocytes. NSCLC patients with higher FGD2 may more responsive to ICB therapy. The functions of FGD2, 3, 5 and FGD1, 4, 6 in LUAD are heterogeneous, and patients can be separated in to two groups based on these six FGDs’ expression. A prognostic model constructed by immune-related DEGs between these two groups had good predictive value in one training set and 4 testing sets. Conclusions: FGD2, FGD3 and FGD5 can be used as diagnostic, prognostic, and immune-implicated biomarkesr for patients with LUAD and FGD2 may help to predict the ICB therapy efficacy. The immune-related prognostic model had satisfactory predictive value.

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TIGER: A Web Portal of Tumor Immunotherapy Gene Expression Resource

Cited by 7 publications

References 68 publications

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy

CRABP2 regulates infiltration of cancer-associated fibroblasts and immune response in melanoma

Comprehensively analysis of the FGD family with potential effects on prognosis and immune infiltration in lung adenocarcinoma

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