Deciphering the cancer microenvironment from bulk data with EcoTyper

Andrea Rolong; Bob Chen; Ken S Lau

doi:10.1016/j.cell.2021.09.028

Deciphering the cancer microenvironment from bulk data with EcoTyper

Cell. 2021 Oct 14;184(21):5306-5308. doi: 10.1016/j.cell.2021.09.028.

Authors

Andrea Rolong¹, Bob Chen², Ken S Lau³

Affiliations

¹ Epithelial Biology Center, Vanderbilt University Medical Center, Nashville TN, USA; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville TN, USA.
² Epithelial Biology Center, Vanderbilt University Medical Center, Nashville TN, USA; Program in Chemical and Physical Biology, Vanderbilt University School of Medicine, Nashville TN, USA.
³ Epithelial Biology Center, Vanderbilt University Medical Center, Nashville TN, USA; Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville TN, USA; Program in Chemical and Physical Biology, Vanderbilt University School of Medicine, Nashville TN, USA. Electronic address: ken.s.lau@vanderbilt.edu.

Abstract

In this issue of Cell, Luca, Steen et al. develop the EcoTyper software to deconvolve tumor-microenvironment interactions from high volume bulk transcriptomics data. They demonstrate its effectiveness in improving predictions for tumor progression and patient prognosis for a variety of tumor types from multiple data sources.

Publication types

Research Support, N.I.H., Extramural
Comment

MeSH terms

Humans
Neoplasms* / genetics
Software
Transcriptome
Tumor Microenvironment*

Abstract

Publication types

MeSH terms

Grants and funding