| URL: | http://tiger.canceromics.org |
| Full name: | A Web Portal of Tumor Immunotherapy Gene Expression Resource |
| Description: | Here, we present TIGER, a tumor immunotherapy gene expression resource, which contains bulk transcriptome data of 1508 tumor samples with clinical immunotherapy outcomes and 11,057 tumor/normal samples without clinical immunotherapy outcomes, as well as single-cell transcriptome data of 2,116,945 immune cells from 655 samples. TIGER provides many useful modules for analyzing collected and user-provided data. Using the resource in TIGER, we identified a tumor-enriched subset of CD4+ T cells. Patients with melanoma with a higher signature score of this subset have a significantly better response and survival under immunotherapy. |
| Year founded: | 2022 |
| Last update: | 2022-08-29 |
| Version: | 1.0 |
| Accessibility: |
Accessible
|
| Country/Region: | China |
| Data type: | |
| Data object: | |
| Database category: | |
| Major species: | |
| Keywords: |
| University/Institution: | Sun Yat-sen University |
| Address: | State Key Laboratory of Oncology in South China, Cancer Center, Collaborative Innovation Center for Cancer Medicine, School of Life Sciences, Sun Yat-sen University, Guangzhou 510060, China. |
| City: | |
| Province/State: | |
| Country/Region: | China |
| Contact name (PI/Team): | Zhixiang Zuo |
| Contact email (PI/Helpdesk): | zuozhx@sysucc.org.cn |
|
TIGER: A Web Portal of Tumor Immunotherapy Gene Expression Resource. [PMID: 36049666]
Immunotherapy is a promising cancer treatment method; however, only a few patients benefit from it. The development of new immunotherapy strategies and effective biomarkers of response and resistance are urgently needed. Recently, high-throughput bulk and single-cell gene expression profiling technologies have generated valuable resources. However, these resources are not well organized and systematic analysis is difficult. Here, we present TIGER, a tumor immunotherapy gene expression resource, which contains bulk transcriptome data of 1508 tumor samples with clinical immunotherapy outcomes and 11,057 tumor/normal samples without clinical immunotherapy outcomes, as well as single-cell transcriptome data of 2,116,945 immune cells from 655 samples. TIGER provides many useful modules for analyzing collected and user-provided data. Using this resource in TIGER, we identified a tumor-enriched subset of CD4 T cells. Patients with melanoma with a higher signature score of this subset have a significantly better response and survival under immunotherapy. We believe that TIGER will be helpful in understanding anti-tumor immunity mechanisms and discovering effective biomarkers. TIGER is freely accessible at http://tiger.canceromics.org/. |