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This research aims to explore the shared molecular features between lung cancer and tuberculosis granulomas through transcriptomic analysis.

April 5, 2026Cancer Research0 citations

Heterogeneous Graph Neural Network Meta-Analysis of Lung Cancer and Tuberculosis Responses

Abstract 4193: Heterogeneous graph neural network meta-analysis of lung cancer and tuberculosis transcriptomic datasets reveals convergent host response networks

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Authors

ATAndrew Maxwell Triska SSSelvakumar Subbian NGNatarajan Ganesan

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Overview

Meta-analysis reveals shared gene expression pathways in lung cancer and tuberculosis granulomas, suggesting potential therapeutic targets.

Key Points

This research aims to explore the shared molecular features between lung cancer and tuberculosis granulomas through transcriptomic analysis.
Performed meta-analysis on 450 RNA-seq samples from patients with lung cancer, TB, and healthy controls.
Processed FASTQ files to create count matrices and employed DESeq2 for differential gene expression assessment.
Constructed co-expression networks using WGCNA with batch correction.
Developed a Heterogeneous Graph Transformer for modeling gene interactions comprehensively.
Identified distinct gene expression clusters indicating convergent pathways between lung cancer and TB granulomas.
Overlapping immune and oncogenic signaling pathways were enriched, including NF-κB and PI3K-Akt.
Highlighted chromatin remodeling and epigenetic plasticity as shared themes.
Proposed chronic inflammation and immune mimicry as key mechanisms potentially serving as biomarkers.

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Cite This Study

Triska et al. (2026) studied this question.

synapsesocial.com/papers/69d1fd73a79560c99a0a381c https://doi.org/10.1158/1538-7445.am2026-4193

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April 5, 2026Cancer Research0 citations

Heterogeneous Graph Neural Network Meta-Analysis of Lung Cancer and Tuberculosis Responses

Abstract 4193: Heterogeneous graph neural network meta-analysis of lung cancer and tuberculosis transcriptomic datasets reveals convergent host response networks

View Full Paper

Authors

ATAndrew Maxwell Triska SSSelvakumar Subbian NGNatarajan Ganesan

Discussion

Member takes

Overview

Meta-analysis reveals shared gene expression pathways in lung cancer and tuberculosis granulomas, suggesting potential therapeutic targets.

Key Points

This research aims to explore the shared molecular features between lung cancer and tuberculosis granulomas through transcriptomic analysis.
Performed meta-analysis on 450 RNA-seq samples from patients with lung cancer, TB, and healthy controls.
Processed FASTQ files to create count matrices and employed DESeq2 for differential gene expression assessment.
Constructed co-expression networks using WGCNA with batch correction.
Developed a Heterogeneous Graph Transformer for modeling gene interactions comprehensively.
Identified distinct gene expression clusters indicating convergent pathways between lung cancer and TB granulomas.
Overlapping immune and oncogenic signaling pathways were enriched, including NF-κB and PI3K-Akt.
Highlighted chromatin remodeling and epigenetic plasticity as shared themes.
Proposed chronic inflammation and immune mimicry as key mechanisms potentially serving as biomarkers.

Ask AI

Helpful

Bookmark

View Full Paper

Cite This Study

Triska et al. (2026) studied this question.

synapsesocial.com/papers/69d1fd73a79560c99a0a381c https://doi.org/10.1158/1538-7445.am2026-4193

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View Full Paper