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Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer
Published on: May 21, 2019
Reference-guided computational framework identifies microenvironment metabolic subtypes and targets using pan-cancer
Ke Tang1,2,3, Ya Han1,2,3, Dongqing Sun1,2,3
1Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Orthopedics, School of Life Science and Technology, Tongji Hospital, Tongji University, Shanghai, 200092, China.
Background:
Metabolic reprogramming is a hallmark of cancer; however, the mechanisms driving metabolic heterogeneity across diverse cell types in the tumor microenvironment remain poorly understood. Most existing methods predict metabolic states at the pathway level but rarely map reaction-level alterations to their upstream regulators, thereby constraining both interpretability and translational relevance.
Methods:
We developed MetroSCREEN, a reference-guided computational framework that infers reaction-level metabolic flux propensity and nominates upstream regulators from bulk and single-cell transcriptomes. MetroSCREEN uses a fast enrichment-based procedure to quantify reaction-level metabolic activity. To characterize metabolic regulons, it integrates intrinsic gene-regulatory signals with extrinsic cell-cell interaction cues, then applies a robust multi-evidence ranking scheme to combine these information sources, and finally employs a constraint-based causal discovery module to infer regulatory directionality.
Results:
MetroSCREEN accurately predicts reaction-level metabolic activities and their upstream regulators, as demonstrated using paired transcriptomic-metabolomic datasets from the cancer cell lines. We further validated predicted regulators with in-house single-cell CRISPR screens in PC9 cells targeting metabolic regulators. Applying MetroSCREEN to a pan-cancer single-cell atlas of more than 700,000 fibroblasts and myeloid cells across 36 cancer types, we identified ZNF281 and STAT1 as key regulators of collagen metabolism, which is elevated in extracellular-matrix-associated fibroblasts and macrophages at tumor margins. By contrast, APOE and KLF7 regulate sphingolipid metabolism and antigen presentation in macrophages. Leveraging extensive tumor profiles, MetroSCREEN also delineates metabolic subtypes and regulators associated with patient survival and response to immunotherapy.
Conclusions:
MetroSCREEN is a robust and scalable approach for characterizing metabolic heterogeneity and pinpointing metabolic regulators at single-cell resolution, unveiling novel antitumor targets for future metabolic interventions. The source codes of MetroSCREEN is available at the Github site https://github.com/wanglabtongji/MetroSCREEN .
Insights
We developed MetroSCREEN, a computational tool to map cancer cell metabolism and identify key regulators. This approach reveals novel targets for cancer therapies by analyzing metabolic heterogeneity at single-cell resolution.
Area of Science:
- Computational biology
- Cancer research
- Metabolomics
Background:
- Metabolic reprogramming is a key cancer hallmark, but its heterogeneity in the tumor microenvironment is poorly understood.
- Existing methods lack reaction-level insights and upstream regulator identification, limiting clinical translation.
Purpose of the Study:
- To develop a computational framework, MetroSCREEN, for inferring reaction-level metabolic flux and identifying upstream regulators from transcriptomic data.
- To characterize metabolic heterogeneity and discover novel therapeutic targets in cancer.
Main Methods:
- MetroSCREEN employs an enrichment-based procedure for reaction-level metabolic activity quantification.
- It integrates gene-regulatory signals and cell-cell interactions to define metabolic regulons.
- A causal discovery module infers regulatory directionality for robust regulator nomination.
Main Results:
- MetroSCREEN accurately predicts reaction-level metabolic activities and regulators using transcriptomic-metabolomic data and single-cell CRISPR screens.
- Analysis of a pan-cancer atlas revealed ZNF281/STAT1 regulate collagen metabolism and APOE/KLF7 regulate sphingolipid metabolism and antigen presentation.
- Identified metabolic subtypes and regulators linked to patient survival and immunotherapy response.
Conclusions:
- MetroSCREEN offers a robust, scalable method for dissecting metabolic heterogeneity at single-cell resolution.
- It pinpoints metabolic regulators, uncovering potential antitumor targets for metabolic interventions.
