Abstract Understanding tumor cell dynamics can improve prognosis and treatment but remains limited for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA sequencing data from 684 NS-LUAD cases and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histologic data further characterized the subtypes. “Steady,” marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver gene alterations, is linked to prolonged survival and low immune evasion. “Proliferative” shows high proliferation markers, TP53 mutations, and gene fusions. “Chaotic,” with high epithelial-to-mesenchymal transition markers, has the worst prognosis, even within stage I tumors. Lacking known molecular or histologic characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the classification and predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving early-stage NS-LUAD prognostication in clinical settings. Significance: The transcriptome of 684 NS-LUAD identifies three subtypes with different cellular dynamics and genomic and morphologic features. A 60-gene signature accurately stratifies subjects for mortality risk, even in stage I, offering a potential clinically applicable tool for treatment decision-making in patients with NS-LUAD. See related commentary by Azizi et al., p. 423
The Association of Modifiable Breast Cancer Risk Factors and Somatic Genomic Alterations in Breast Tumors: The Cancer Genome Atlas Network
Abstract Background: The link between modifiable breast cancer risk factors and tumor genomic alterations remains largely unexplored. We evaluated the association of prediagnostic body mass index (BMI), cigarette smoking, and alcohol consumption with somatic copy number variation (SCNV), total somatic mutation burden (TSMB), seven single base substitution (SBS) signatures (SBS1, SBS2, SBS3, SBS5, SBS13, SBS29, and SBS30), and nine driver mutations (CDH1, GATA3, KMT2C, MAP2K4, MAP3K1, NCOR1, PIK3CA, RUNX1, and TP53) in a subset of The Cancer Genome Atlas (TCGA). Methods: Clinical and genomic data were retrieved from the TCGA database. Risk factor information was collected from four TCGA sites (n = 219 women), including BMI (1 year before diagnosis), cigarette smoking (smokers/nonsmokers), and alcohol consumption (current drinkers/nondrinkers). Multivariable regression analyses were conducted in all tumors and stratified according to estrogen receptor (ER) status. Results: Increasing BMI was associated with increasing SCNV in all women (P = 0.039) and among women with ER− tumors (P = 0.031). Smokers had higher SCNV and TSMB versus nonsmokers (P < 0.05 all women). Alcohol drinkers had higher SCNV versus nondrinkers (P < 0.05 all women and among women with ER+ tumors). SBS3 (defective homologous recombination-based repair) was exclusively found in alcohol drinkers with ER− disease. GATA3 mutation was more likely to occur in women with higher BMI. No association was significant after multiple testing correction. Conclusions: This study provides preliminary evidence that BMI, cigarette smoking, and alcohol consumption can influence breast tumor biology, in particular, DNA alterations. Impact: This study demonstrates a link between modifiable breast cancer risk factors and tumor genomic alterations.
Precancer Atlas to Drive Precision Prevention Trials