Subtopic Deep Dive

Ferroptosis in Tumor Microenvironment
Research Guide

What is Ferroptosis in Tumor Microenvironment?

Ferroptosis in the tumor microenvironment (TME) refers to iron-dependent cell death processes influencing stromal cells, extracellular matrix remodeling, and nutrient competition within cancer tissues.

This subtopic examines ferroptosis modulation of TME components like immunosuppression and therapy resistance. Spatial ferroptosis heterogeneity is analyzed using scRNA-seq in tumor contexts (Tang et al., 2020; 3692 citations). Over 20 papers link ferroptosis regulators like GPX4 and SLC7A11 to TME dynamics (Yang et al., 2014; 7013 citations).

15
Curated Papers
3
Key Challenges

Why It Matters

Ferroptosis in TME affects tumor progression by altering stromal cell ferroptosis sensitivity, promoting immunosuppression via lipid peroxidation control (Stockwell et al., 2017; 6942 citations). It drives extracellular matrix remodeling through reactive oxygen species impacting fibroblasts, influencing cancer therapy resistance as seen in sorafenib-induced ferroptosis in solid tumors (Lachaier et al., 2014; 396 citations). Nutrient competition for cystine via SLC7A11 exacerbates TME hypoxia, linking iron metabolism to prognosis in lung cancers (Koppula et al., 2020; 2161 citations).

Key Research Challenges

Spatial Heterogeneity Mapping

Quantifying ferroptosis gradients across TME zones requires integrating scRNA-seq with spatial transcriptomics. Current methods overlook stromal-specific lipid peroxidation markers (Tang et al., 2020). Dixon et al. (2012) foundational work lacks TME context (16751 citations).

Stromal Cell Sensitivity

Determining ferroptosis thresholds in fibroblasts versus tumor cells remains unresolved due to GPX4 variability. NRF2 activation protects stromal cells differently (Dodson et al., 2019; 2172 citations). Yang et al. (2016) highlights lipoxygenase roles but not TME specifics (2166 citations).

Nutrient Competition Modeling

Simulating cystine/glutamate dynamics in hypoxic TME challenges computational models. SLC7A11 overexpression alters ferroptosis dependency (Koppula et al., 2020). Stockwell et al. (2017) reviews metabolism links without quantitative TME simulations.

Essential Papers

1.

Ferroptosis: An Iron-Dependent Form of Nonapoptotic Cell Death

Scott J. Dixon, Kathryn M. Lemberg, Michael R. Lamprecht et al. · 2012 · Cell · 16.8K citations

2.

Regulation of Ferroptotic Cancer Cell Death by GPX4

Wan Seok Yang, Rohitha Sriramaratnam, Matthew Welsch et al. · 2014 · Cell · 7.0K citations

3.

Ferroptosis: A Regulated Cell Death Nexus Linking Metabolism, Redox Biology, and Disease

Brent R. Stockwell, José Pedro Friedmann Angeli, Hülya Bayır et al. · 2017 · Cell · 6.9K citations

4.

Ferroptosis: past, present and future

Jie Li, Feng Cao, He-liang Yin et al. · 2020 · Cell Death and Disease · 3.8K citations

5.

Ferroptosis: molecular mechanisms and health implications

Daolin Tang, Xin Chen, Rui Kang et al. · 2020 · Cell Research · 3.7K citations

Abstract Cell death can be executed through different subroutines. Since the description of ferroptosis as an iron-dependent form of non-apoptotic cell death in 2012, there has been mounting intere...

6.

Ferroptosis: process and function

Yang Xie, Wen‐Chi Hou, Xinxin Song et al. · 2016 · Cell Death and Differentiation · 3.6K citations

7.

NRF2 plays a critical role in mitigating lipid peroxidation and ferroptosis

Matthew Dodson, Raúl Castro-Portuguez, Donna D. Zhang · 2019 · Redox Biology · 2.2K citations

The transcription factor nuclear factor erythroid 2-related factor 2 (NRF2) is a key regulator of the cellular antioxidant response, controlling the expression of genes that counteract oxidative an...

Reading Guide

Foundational Papers

Read Dixon et al. (2012; 16751 citations) first for ferroptosis definition, then Yang et al. (2014; 7013 citations) for GPX4 cancer regulation essential to TME context.

Recent Advances

Study Koppula et al. (2020; 2161 citations) for SLC7A11-TME links and Dodson et al. (2019; 2172 citations) for NRF2 modulation in peroxidation.

Core Methods

Core techniques include GPX4 knockout, lipoxygenase inhibitors (Yang et al., 2016), scRNA-seq clustering, and lipid ROS quantification (Su et al., 2019).

How PapersFlow Helps You Research Ferroptosis in Tumor Microenvironment

Discover & Search

PapersFlow's Research Agent uses searchPapers with 'ferroptosis tumor microenvironment scRNA-seq' to retrieve 50+ papers like Tang et al. (2020), then citationGraph maps GPX4-TME clusters from Dixon et al. (2012), and findSimilarPapers expands to stromal ferroptosis works. exaSearch queries 'SLC7A11 cystine competition cancer TME' for hidden preprints.

Analyze & Verify

Analysis Agent applies readPaperContent on Koppula et al. (2020) to extract SLC7A11-TME interactions, verifies claims with CoVe against Stockwell et al. (2017), and runPythonAnalysis processes scRNA-seq lipid peroxidation data via pandas/NumPy for GPX4 expression stats. GRADE grading scores ferroptosis mechanism evidence as A-level for Dixon et al. (2012).

Synthesize & Write

Synthesis Agent detects gaps in TME stromal ferroptosis modeling, flags contradictions between NRF2 protection (Dodson et al., 2019) and sorafenib induction (Lachaier et al., 2014). Writing Agent uses latexEditText for spatial heterogeneity figures, latexSyncCitations integrates 20+ refs, latexCompile generates review PDFs, and exportMermaid diagrams nutrient competition networks.

Use Cases

"Analyze scRNA-seq data for ferroptosis markers in lung cancer TME"

Research Agent → searchPapers('ferroptosis scRNA lung TME') → Analysis Agent → runPythonAnalysis(pandas on marker expression) → statistical heatmap of GPX4 heterogeneity.

"Draft LaTeX review on ferroptosis-induced TME remodeling"

Synthesis Agent → gap detection(Tang 2020 + Stockwell 2017) → Writing Agent → latexEditText(structure) → latexSyncCitations(25 refs) → latexCompile(PDF with figures).

"Find code for modeling SLC7A11 nutrient competition in TME"

Research Agent → paperExtractUrls(Koppula 2020) → Code Discovery → paperFindGithubRepo → githubRepoInspect → runnable Python sim of cystine dynamics.

Automated Workflows

Deep Research workflow scans 50+ ferroptosis-TME papers via searchPapers → citationGraph → structured report on GPX4/SLC7A11 prognosis links. DeepScan applies 7-step CoVe to verify spatial ferroptosis claims from Tang et al. (2020), with runPythonAnalysis checkpoints. Theorizer generates hypotheses on stromal ferroptosis therapy from Dixon (2012) + Lachaier (2014).

Frequently Asked Questions

What defines ferroptosis in TME?

Iron-dependent lipid peroxidation causing nonapoptotic death in stromal and tumor cells within TME (Dixon et al., 2012). It modulates immunosuppression via GPX4 and SLC7A11.

What methods study ferroptosis-TME interactions?

scRNA-seq for spatial heterogeneity, GPX4 inhibition assays, and lipid peroxidation metrics like 4-HNE staining (Yang et al., 2014; Tang et al., 2020).

What are key papers on this subtopic?

Dixon et al. (2012; 16751 citations) defines ferroptosis; Koppula et al. (2020; 2161 citations) links SLC7A11 to TME nutrient competition; Lachaier et al. (2014) shows sorafenib induction.

What open problems exist?

Modeling dynamic nutrient competition and stromal ferroptosis thresholds; integrating multi-omics for prognosis prediction (Stockwell et al., 2017).

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