Faculty Bibliography

: Low-dose CT (LDCT) is widely accepted as the preferred method for detecting pulmonary nodules. However, the determination of whether a nodule is benign or malignant involves either repeated scans or invasive procedures that sample the lung tissue. Noninvasive methods to assess these nodules are needed to reduce unnecessary invasive tests. In this study, we have developed a pulmonary nodule classifier (PNC) using RNA from whole blood collected in RNA-stabilizing PAXgene tubes that addresses this need. Samples were prospectively collected from high-risk and incidental subjects with a positive lung CT scan. A total of 821 samples from 5 clinical sites were analyzed. Malignant samples were predominantly stage 1 by pathologic diagnosis and 97% of the benign samples were confirmed by 4 years of follow-up. A panel of diagnostic biomarkers was selected from a subset of the samples assayed on Illumina microarrays that achieved a ROC-AUC of 0.847 on independent validation. The microarray data were then used to design a biomarker panel of 559 gene probes to be validated on the clinically tested NanoString nCounter platform. RNA from 583 patients was used to assess and refine the NanoString PNC (nPNC), which was then validated on 158 independent samples (ROC-AUC = 0.825). The nPNC outperformed three clinical algorithms in discriminating malignant from benign pulmonary nodules ranging from 6-20 mm using just 41 diagnostic biomarkers. Overall, this platform provides an accurate, noninvasive method for the diagnosis of pulmonary nodules in patients with non-small cell lung cancer. SIGNIFICANCE: These findings describe a minimally invasive and clinically practical pulmonary nodule classifier that has good diagnostic ability at distinguishing benign from malignant pulmonary nodules.

BACKGROUND:In lung cancer, upregulation of the PI3K pathway is an early event that contributes to cell proliferation, survival, and tissue invasion. Upregulation of this pathway was recently described as associated with enrichment of the lower airways with bacteria identified as oral commensals. We hypothesize that host-microbe interactions in the lower airways of subjects with lung cancer affect known cancer pathways. METHODS:Airway brushes were collected prospectively from subjects with lung nodules at time of diagnostic bronchoscopy, including 39 subjects with final lung cancer diagnoses and 36 subjects with non-cancer diagnosis. Additionally, samples from 10 healthy control subjects were included. 16S rRNA gene amplicon sequencing and paired transcriptome sequencing (RNAseq) were performed on all airway samples. In addition, an in vitro model with airway epithelial cells exposed to bacteria/bacterial products was performed. RESULTS:The composition of the lower airway transcriptome in the cancer patients was significantly different from the controls, which included upregulation of ERK and PI3K signaling pathways. The lower airways of lung cancer patients were enriched for oral taxa (Streptococcus and Veillonella), which was associated with upregulation of the ERK and PI3K signaling pathways. In vitro exposure of airway epithelial cells to Veillonella, Prevotella, and Streptococcus led to upregulation of these same signaling pathways. CONCLUSIONS:The data presented here shows that several transcriptomic signatures previously identified as relevant to lung cancer pathogenesis are associated with enrichment of the lower airway microbiota with oral commensals.

It remains unclear whether PAX6 acts as a crucial transcription factor for lung cancer stem cell (CSC) traits. We demonstrate that PAX6 acts as an oncogene responsible for induction of cancer stemness properties in lung adenocarcinoma (LUAD). Mechanistically, PAX6 promotes GLI transcription, resulting in SOX2 upregulation directly by the binding of GLI to the proximal promoter region of the SOX2 gene. The overexpressed SOX2 enhances the expression of key pluripotent factors (OCT4 and NANOG) and suppresses differentiation lineage factors (HOPX and NKX2-1), driving cancer cells toward a stem-like state. In contrast, in the differentiated non-CSCs, PAX6 is transcriptionally silenced by its promoter methylation. In human lung cancer tissues, the positive linear correlations of PAX6 expression with GLI and SOX2 expression and its negative correlations with HOPX and NKX2-1 expression were observed. Therapeutically, the blockade of the PAX6-GLI-SOX2 signaling axis elicits a long-lasting therapeutic efficacy by limiting CSC expansion following chemotherapy. Furthermore, a methylation panel including the PAX6 gene yielded a sensitivity of 79.1% and specificity of 83.3% for cancer detection using serum DNA from stage IA LUAD. Our findings provide a rationale for targeting the PAX6-GLI-SOX2 signaling axis with chemotherapy as an effective therapeutic strategy and support the clinical utility of PAX6 gene promoter methylation as a biomarker for early lung cancer detection.