Genetic and immunologic features of recurrent stage I lung adenocarcinoma - PubMed (original) (raw)
Genetic and immunologic features of recurrent stage I lung adenocarcinoma
Johannes R Kratz et al. Sci Rep. 2021.
Abstract
Although surgery for early-stage lung cancer offers the best chance of cure, recurrence still occurs between 30 and 50% of the time. Why patients frequently recur after complete resection of early-stage lung cancer remains unclear. Using a large cohort of stage I lung adenocarcinoma patients, distinct genetic, genomic, epigenetic, and immunologic profiles of recurrent tumors were analyzed using a novel recurrence classifier. To characterize the tumor immune microenvironment of recurrent stage I tumors, unique tumor-infiltrating immune population markers were identified using single cell RNA-seq on a separate cohort of patients undergoing stage I lung adenocarcinoma resection and applied to a large study cohort using digital cytometry. Recurrent stage I lung adenocarcinomas demonstrated higher mutation and lower methylation burden than non-recurrent tumors, as well as widespread activation of known cancer and cell cycle pathways. Simultaneously, recurrent tumors displayed downregulation of immune response pathways including antigen presentation and Th1/Th2 activation. Recurrent tumors were depleted in adaptive immune populations, and depletion of adaptive immune populations and low cytolytic activity were prognostic of stage I recurrence. Genomic instability and impaired adaptive immune responses are key features of stage I lung adenocarcinoma immunosurveillance escape and recurrence after surgery.
© 2021. The Author(s).
Conflict of interest statement
JRK reports consulting fees from Razor Genomics, consulting fees from and stock ownership in Oncocyte Corp, and patent rights for a prognostic assay for early-stage lung cancer with royalties paid. MJM, and DMJ report consulting fees from and ownership interest in Razor Genomics, consulting fees from and stock ownership in Oncocyte Corp, and patent rights for a prognostic assay for early-stage lung cancer with royalties paid. JZL, JT, JCL, WVD, AAR, AJC, VC, and MFK declare no potential conflict of interest.
Figures
Figure 1
Recurrence score is prognostic of recurrence in the TCGA lung adenocarcinoma cohort. Recurrence score is directly proportional to probability of recurrence at 5 years within the entire TCGA lung adenocarcinoma cohort (A) and is prognostic of recurrence when stage I patients are divided into cohorts by recurrence score quartile (B).
Figure 2
Genetic alterations in recurrent lung adenocarcinomas. Increasing risk of recurrence is associated with increasing tumor mutation burden (A). An oncoplot of the most frequently mutated genes in the stage I lung adenocarcinoma cohort is shown in (B). Canonical driver mutations are present in stage I tumors but do not occur more frequently in recurrent tumors (C). Copy number alterations occur more frequently in tumors with increasing risk of recurrence (D). Although copy number alterations and mutations are evenly distributed through the genome in recurrence high-risk tumors (E), high-risk (F) versus low-risk (G) tumors show different genome-wide copy number alteration patterns. ***P < 0.0001.
Figure 3
Transcriptomic analysis demonstrates distinct genomic and immunologic features of recurrent lung adenocarcinomas. Heatmap clustering of differentially regulated genes results in clear separation between high- and low-risk tumors across four different gene clusters (A). Differential methylation patterns are also associated with recurrent tumors; decreasing DNA methylation is observed in tumors with increasing risk of recurrence (B) while heatmap clustering of differentially methylated genes results in clear separation between high- and low-risk tumors across two different gene clusters (C). *P < 0.05.
Figure 4
Pathway analysis for differential gene expression heatmap clusters 2 and 3. The top 30 pathways involved in the differential expression of genes in heatmap cluster 2 and 3 are shown in (A) and (B) respectively. Ratio on the x-axis refers to the number of differentially regulated genes in the dataset relative to the total number of pathway genes. The size of each dot represents significance (− log10(_P_-value)); the color of each dot represents the Z-score. A positive Z-score indicates that the observed gene activity positively correlates with predicted pathway member up/down regulation patterns; a negative Z-score indicates anti-correlation.
Figure 5
Recurrent stage I lung adenocarcinomas display immune desert phenotypes. scRNA-seq analysis reveals twenty distinct immune cell populations in stage I lung adenocarcinomas (A). Despite increasing antigenicity (B), tumors with increasing risk of recurrence demonstrate decreasing immune cell infiltration (C).
Figure 6
Recurrent stage I lung adenocarcinomas display adaptive immune cell depleted phenotypes. UMAP analysis reveals distinct tumor immune microenvironments between recurrence high- and low-risk tumors (A). Heatmap analysis demonstrates depletion of adaptive immune cell populations in recurrence high-risk tumors (B). Patients with adaptive-rich immune cell phenotypes have improved 24-month freedom from recurrence compared to tumors with adaptive-depleted phenotypes (C). High cytolytic activity score (CYT) is prognostic of decreased recurrence (D). ***P < 0.0001, **P < 0.001, *P < 0.05.
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