TIMER2.0 for analysis of tumor-infiltrating immune cells

By Taiwen Li, Jingxin Fu, Zexian Zeng, David Cohen, Jing Li, Qianming Chen, Bo Li, Xiaole Shirley Liu. Nucleic Acids Res., 2020

4,296 citations recorded by the source corpus.

Abstract Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor–immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.

Subfields: Immunology, Oncology, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/8ac9aeb3e1e1841db443e011751582ad1d3625e2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Immunology

1. W. Zou
2. Ilona Kryczek
3. Shuang Wei
4. Lieping Chen
5. D. Pardoll

In Oncology

1. W. Zou
2. Lieping Chen

In Pulmonary and Respiratory Medicine

1. Brent R. Stockwell

Citations in the corpus

• IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures (2020, methodology): “TIMER is a published web tool integrating six algorithms for inferring immune cell composition from bulk tumor transcriptome profiles (23).”
• CD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4 (2022, background): “0 analysis, we found that ACSL4 expression levels were lower in multiple types of tumor tissues than normal tissues (Li et al., 2020) (Figure S6A).”
• GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA (2021, background): “0 (13) as the platform for TCGA deconvolution analysis, there are still strong but unmet needs from users on the tumor-normal comparison and other practical functionalities such as the differential analysis in the cell type level.”