Figure 5. Comparing inferred PC2 gene expression signature by lung cancer histological subtypes.

(A) Leukocyte telomere length (LTL) polygenic risk score (PRS) association with the 10-gene expression signature of PC2 in lung adenocarcinoma (The Cancer Genome Atlas [TCGA]-LUAD, N=343) and squamous cell carcinoma (TCGA-LUSC, N=338) cases from TCGA dataset. Results are expressed as beta estimate per SD increase in genetically predicted LTL. Linear regression model adjusted by sex, age, and PC1-5 (genetic ancestry) covariates, PC2 signature as outcome. Statistically significant associations with -values<0.05. Values per SD of (B) PC2, (C) proliferation score, and (D) telomerase/TERT activity gene expression signatures by lung cancer histological subtypes (TCGA-LUAD and TCGA-LUSC). p-Values derived from Student’s t-tests.

Figure 5—figure supplement 1. Generating inferred PC2 signature based on RNA-sequencing data.

(A) Workflow for the generation of the PC2 signature. Calculate principal components based on RNA-sequencing data in both The Cancer Genome Atlas (TCGA)-lung adenocarcinoma (LUAD) training (N=255, 70%) and validation (N=108, 30%) datasets and use partial least square (PLS)-based method to align principal components (upper). Select the most informative genes correlated with the observed PC2 in the training dataset using least absolute shrinkage and selection operator (LASSO) regression model and validate it in the validation set (middle). Apply the PC2 signature to the TCGA-LUSC (lung squamous cell carcinoma) and TCGA-LUAD cohorts. (B) The ranked absolute coefficients/importance of the 10 genes selected by the LASSO models. Negative coefficients in red and positive ones in blue. (C) Scatter plot for the correlations between PC2 gene expression signature and observed principal components (PC1-5) based on RNA-sequencing data in the validation set. PC1 in light blue, PC2 in red, PC3 in grey, PC4 in blue, and PC5 in salmon colours.