Multi-cohort analysis identifies a blood-based immune transcriptomic signature for early lung cancer detection.

Early diagnosis of lung cancer is critical for timely intervention and reducing mortality. The immune system and cancer are intricately linked, which provides a unique opportunity to monitor changes in the immune system as a biomarker of cancer development. We collected bulk blood transcriptome from 432 lung cancer cases, 8154 healthy controls, and 14,187 samples with other diseases from 241 datasets for discovery. We also obtained a prospectively enrolled cohort of 371 subjects (172 with lung cancer) and 454 subjects from the Framingham Heart Study (42 with lung cancer) for validation. Furthermore, we integrated single-cell RNA sequencing profiles of 1,022,063 cells from 260 blood, lymph node, or lung tissue samples from lung cancer patients and other samples across 15 datasets. We performed a multi-cohort blood transcriptome meta-analysis and identified 6 genes consistently differentially expressed between lung cancer and other samples. Using the 6-gene signature, we defined a lung cancer score that was primarily derived from myeloid cells and was consistently higher in tumor-associated macrophages and fibroblasts than their normal counterparts. In the prospectively enrolled cohort, the diagnostic classifier using the lung cancer score had an AUROC of 0.822 (95% CI: 0.78-0.864) for distinguishing patients with lung cancer from control or benign samples. The classifiers could also potentially reduce the need for additional testing in 37% of patients with benign lung conditions at 90% sensitivity. Importantly, the lung cancer score was also significantly associated with an elevated risk of future lung cancer diagnosis in the Framingham cohort study. Together, we identified a robust blood-based immune gene signature for early detection of lung cancer, which has potential for further clinical development to aid early cancer detection and diagnosis.