Genomic landscape of patients with non-small cell lung cancer (NSCLC)

NCSLC is the leading cause of cancer deaths in the United States (USA). The 5-year survival rate is 22.9% (7% in those with metastases). Personalized therapies have shown promise but a better understanding of the genomic landscape of the tumor may help further improve survival. Here, we present the genomic landscape and key features of NCSLC patients using a real-world clinico-genomics dataset.

The ConcertAI Genome360TM NCSLC dataset is a deeply curated real-world dataset of 11349 patients from the USA who have undergone a next generation sequencing test. This dataset covers >2000 genes. Here we present the demographic, clinical and genomic characteristics of this cohort. The top 20 genes with pathogenic mutations were identified and co-mutational analysis was performed to identify the most significant genes that were positively and negatively correlated to these genes using chi-squared test with Bonferroni correction. Other clinically relevant biomarkers such as tumor mutation burden (TMB), microsatellite instability (MSI) and Programmed death-ligand 1 (PD-L1) status were also characterised.

The median age at diagnosis was 70 years with an equal gender distribution. Adenocarcinoma (69%) and squamous cell carcinoma (24%) were the two most common histologies. Most patients were diagnosed at stage IV (57%) or III (19%). Brain, bone, and liver were the most prevalent metastatic sites. 22% patients had high expression of PD-L1, 28% had high TMB and only ~1% patients had high MSI. The 20 most frequently mutated genes along with their top 3 most significant (p-value < 3e-5) positively and negatively correlated genes are listed in Table 1.

This analysis provides a deeper understanding of the genomic landscape of NSCLC. The co-mutational analysis provides insights into pathways that are perturbed together providing opportunities to develop treatments to overcome such co-mutations.