Gene expression
Can single-cell plus bulk RNA-seq predict LUAD survival?
Open access · cc by · source: Europe PMC
From 8,170 lung cells and TCGA LUAD bulk data, a six-gene score (CP, GOLM1, CYP4B1, DAPK2, NFIX, FHL2) stratified survival (1-/3-/5-year AUC 0.67/0.67/0.64) and tracked TP53, TMB, and PD-L1.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Independence from clinical variables is the test that distinguishes a signature from a restatement of stage.
Signatures can add information beyond standard clinical variables. A risk score built by integrating single-cell and bulk RNA sequencing separated overall survival independently of usual clinicopathology, with high-risk tumours showing more TP53 mutation, higher tumour mutational burden, PD-L1 upregulation and cell-cycle programmes.
Evidence for the claim as stated.
Study at a glance
- Design
- Computational / modelling — Integrated 10x scRNA-seq (GSE149655) with TCGA bulk RNA-seq; LASSO/Cox risk model validated in GSE31210 and GSE13213.
- N
- N=8170 · 8,170 QC’d cells from 4 scRNA-seq samples (2 LUAD, 2 normal); bulk model built in TCGA and validated in two GEO LUAD cohorts.
- Population
- Human LUAD and normal lung single-cell samples plus TCGA/GEO lung adenocarcinoma transcriptomes.
- Outcome
- Six-gene overall-survival risk score, NMF subtypes, TMB/PD-L1 and immune features.
Structured fields used in claim comparison tables when every cited study has a complete layer.
Inspect source passages
Can single-cell plus bulk RNA-seq predict LUAD survival?
These passages occur verbatim in the stored paper text. They support the points listed below; they do not verify every statement in the explanation.
8,170 cells after QC.
A total of 8,170 cells were identified after QC
329 DEGs entered model construction after WGCNA overlap.
Overall, 329 DEGs were selected for prognostic model construction through differential analysis and WGCNA.
Key findings
High-risk patients had worse OS. Risk was independent of usual clinicopathology. High-risk tumors had more TP53 mutation, higher TMB, PD-L1 upregulation, and cell-cycle/DNA-replication programs. NMF found two bulk subtypes with different immune classes.
Methodology
Integrated GSE149655 10x scRNA-seq (UMAP, 13 clusters, 9 cell types), found DEGs, WGCNA (329 genes), NMF subtypes in TCGA, then univariate Cox → LASSO → multivariate Cox to build a median-split risk score, validated in GSE31210 and GSE13213.
Limitations
Retrospective public data, modest AUCs (~0.64–0.67), and scRNA n=4 samples; the score is not a prospective clinical test and does not prove the six genes cause LUAD.
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