TIMER2.0 for analysis of tumor-infiltrating immune cells
Taiwen Li,Jingxin Fu,Jingxin Fu,Zexian Zeng,David M. Cohen,Jing Li,Qianming Chen,Bo Li,X. Shirley Liu +8 more
TLDR
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.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.read more
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IOBR: Multi-Omics Immuno-Oncology Biological Research to Decode Tumor Microenvironment and Signatures.
Dongqiang Zeng,Zilan Ye,Rongfang Shen,Guangchuang Yu,Jiani Wu,Yi Xiong,Rui Zhou,Wenjun Qiu,Na Huang,Li Sun,Xuejun Li,Jianping Bin,Yulin Liao,Min Shi,Wangjun Liao +14 more
TL;DR: IOBR as mentioned in this paper is a computational tool for effective Immuno-Oncology Biological Research (IOBR), providing a comprehensive investigation of the estimation of reported or user-built signatures, TME deconvolution, and signature construction based on multi-omics data.
Posted ContentDOI
IOBR: Multi-omics Immuno-Oncology Biological Research to decode tumor microenvironment and signatures
Dongqiang Zeng,Zilan Ye,Guangchuang Yu,Jiani Wu,Yi Xiong,Rui Zhou,Wenjun Qiu,Na Huang,Li Sun,Jianping Bin,Yulin Liao,Min Shi,Wangjun Liao +12 more
TL;DR: A computational tool for effective Immuno-Oncology Biological Research (IOBR), providing comprehensive investigation of estimation of reported or user-built signatures, TME deconvolution and signature construction base on multi-omics data.
Journal ArticleDOI
GEPIA2021: integrating multiple deconvolution-based analysis into GEPIA.
TL;DR: GEPIA2021 as mentioned in this paper is a standalone extension of GEPIA, allowing users to perform multiple interactive analysis based on the deconvolution results, including cell type-level proportion comparison, correlation analysis, differential expression, and survival analysis.
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CD8+ T cells and fatty acids orchestrate tumor ferroptosis and immunity via ACSL4.
Peng Liao,Weimin Wang,Wei Wang,I. Kryczek,Xiong Li,Yingjie Bian,Amanda Sell,Shuang-Yu Wei,Sara Grove,Jeffrey K. Johnson,Paul D. Kennedy,Miguel A. Gijón,Yatrik M. Shah,Weiping Zou +13 more
TL;DR: In this article , T cell-derived interferon (IFN)γ in combination with arachidonic acid (AA) induces immunogenic tumor ferroptosis, serving as a mode of action for CD8+ T cell (CTL)-mediated tumor killing.
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Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.
Jiao Hu,Anze Yu,Anze Yu,Belaydi Othmane,Dongxu Qiu,Huihuang Li,Chao Li,Peihua Liu,Wenbiao Ren,Minfeng Chen,Guanghui Gong,Xi Guo,Huihui Zhang,Jinbo Chen,Xiongbing Zu +14 more
TL;DR: In this paper, the role of anti-Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA was analyzed using RNA sequencing data obtained from The Cancer Genome Atlas.
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TL;DR: The Pan-Cancer initiative compares the first 12 tumor types profiled by TCGA with a major opportunity to develop an integrated picture of commonalities, differences and emergent themes across tumor lineages.