Repetitive head impacts induce neuronal loss and neuroinflammation in young athletes

Repetitive head impacts (RHI) sustained from contact sports are the largest risk factor for chronic traumatic encephalopathy (CTE). Currently, CTE can only be diagnosed after death and the multicellular cascade of events that trigger initial hyperphosphorylated tau (p-tau) deposition remain unclear. Further, the symptoms endorsed by young individuals with early disease are not fully explained by the extent of p-tau deposition, severely hampering development of therapeutic interventions. Here, we show that RHI exposure associates with a multicellular response in young individuals (<51 years old) prior to the onset of CTE p-tau pathology that correlates with number of years of RHI exposure. Leveraging single nucleus RNA sequencing of tissue from 8 control, 9 RHI-exposed, and 11 low stage CTE individuals, we identify SPP1+ inflammatory microglia, angiogenic and inflamed endothelial cell profiles, reactive astrocytes, and altered synaptic gene expression in excitatory and inhibitory neurons in all individuals with exposure to RHI. Surprisingly, we also observe a significant loss of cortical sulcus layer 2/3 neurons in contact sport athletes compared to controls independent of p-tau pathology. These results provide robust evidence that multiple years of RHI exposure is sufficient to induce lasting cellular alterations that may underlie p-tau deposition and help explain the early clinical symptoms observed in young former contact sport athletes. Furthermore, these data identify specific cellular responses to repetitive head impacts that may direct future identification of diagnostic and therapeutic strategies for CTE.

Myc Dysregulation in Activated Macrophages Initiates Iron-Mediated Lipid Peroxidation that Fuels Type I Interferon and Compromises TB Resistance

A quarter of human population is infected with Mycobacterium tuberculosis, but less than 10% of those infected develop clinical, mostly pulmonary, TB. To dissect mechanisms of susceptibility in immunocompetent individuals, we developed a genetically defined sst1-susceptible mouse model that uniquely reproduces a defining feature of human TB: development of necrotic lung lesions after infection with virulent Mtb. In this study, we explored the connectivity of the sst1-regulated pathways during prolonged macrophage activation with TNF. We determined that the aberrant response of the sst1-susceptible macrophages to TNF was primarily driven by conflicting Myc and antioxidant response pathways that resulted in a coordinated failure to properly sequester intracellular iron and activate ferroptosis inhibitor enzymes. Consequently, iron-mediated lipid peroxidation fueled IFNβ superinduction and sustained the Type I Interferon (IFN-I) pathway hyperactivity that locked the sst1-susceptible macrophages in a state of unresolving stress and compromised their resistance to Mtb. The accumulation of the aberrantly activated, stressed, macrophages within granuloma microenvironment led to the local failure of anti-tuberculosis immunity and tissue necrosis. Our findings suggest a novel link between metabolic dysregulation in macrophages and susceptibility to TB, offering insights into potential therapeutic targets aimed at modulating macrophage function and improving TB control.

Endothelial Erg Regulates Expression of Pulmonary Lymphatic Junctional and Inflammation Genes in Mouse Lungs Impacting Lymphatic Transport

The ETS transcription factor ERG is a master regulator of endothelial gene specificity and highly enriched in the capillary, vein, and arterial endothelial cells. ERG expression is critical for endothelial barrier function, permeability, and vascular inflammation. A dysfunctional vascular endothelial ERG has been shown to impair lung capillary homeostasis, contributing to pulmonary fibrosis as previously observed in IPF lungs. Our preliminary observations indicate that lymphatic endothelial cells (LEC) in the human IPF lung also lack ERG. To understand the role of ERG in pulmonary LECs, we developed LEC-specific inducible Erg-CKO and Erg-GFP-CKO conditional knockout (CKO) mice under Prox1 promoter. Whole lung microarray analysis, flow cytometry, and qPCR confirmed an inflammatory and pro-lymphvasculogenic predisposition in Erg-CKO lung. FITC-Dextran tracing analysis showed an increased pulmonary interstitial lymphatic fluid transport from the lung to the axial lymph node. Single-cell transcriptomics confirmed that genes associated with cell junction integrity were downregulated in Erg-CKO pre-collector and collector LECs. Integrating Single-cell transcriptomics and CellChatDB helped identify LEC specific communication pathways contributing to pulmonary inflammation, trans-endothelial migration, inflammation, and Endo-MT in Erg-CKO lung. Our findings suggest that downregulation of lymphatic Erg crucially affects LEC function, LEC permeability, pulmonary LEC communication pathways and lymphatic transcriptomics.

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. In an exploratory analysis of PBMC datasets, we find that some droplets that were originally called 'empty' due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a 'spongelet' which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.

Characterization of highly active mutational signatures in tumors from a large Chinese population

The majority of mutational signatures have been characterized in tumors from Western countries and the degree to which mutational signatures are similar or different in Eastern populations has not been fully explored. We leveraged a large-scale clinical sequencing cohort of tumors from a Chinese population containing 25 tumor types and found that the highly active mutational signatures were similar to those previously characterized1,2. The aristolochic acid signature SBS22 was observed in four soft tissue sarcomas and the POLE-associated signature SBS10 was observed in a gallbladder carcinoma. In lung adenocarcinoma, the polycyclic aromatic hydrocarbon (PAH) signature SBS4 was significantly higher in males compared to females but not associated with smoking status. The UV-associated signature SBS7 was significantly lower in cutaneous melanomas from the Chinese population compared to a similar American cohort. Overall, these results add to our understanding of the mutational processes that contribute to tumors from the Chinese population.

Single-Cell Characterization of Pulmonary Nodules Implicates Suppression of Immunosurveillance across Early Stages of Lung Adenocarcinoma

A greater understanding of molecular, cellular, and immunological changes during the early stages of lung adenocarcinoma development could improve diagnostic and therapeutic approaches in patients with pulmonary nodules at risk for lung cancer. To elucidate the immunopathogenesis of early lung tumorigenesis, we evaluated surgically resected pulmonary nodules representing the spectrum of early lung adenocarcinoma as well as associated normal lung tissues using single-cell RNA sequencing and validated the results by flow cytometry and multiplex immunofluorescence (MIF). Single-cell transcriptomics revealed a significant decrease in gene expression associated with cytolytic activities of tumor-infiltrating natural killer and natural killer T cells. This was accompanied by a reduction in effector T cells and an increase of CD4+ regulatory T cells (Treg) in subsolid nodules. An independent set of resected pulmonary nodules consisting of both adenocarcinomas and associated premalignant lesions corroborated the early increment of Tregs in premalignant lesions compared with the associated normal lung tissues by MIF. Gene expression analysis indicated that cancer-associated alveolar type 2 cells and fibroblasts may contribute to the deregulation of the extracellular matrix, potentially affecting immune infiltration in subsolid nodules through ligand-receptor interactions. These findings suggest that there is a suppression of immune surveillance across the spectrum of early-stage lung adenocarcinoma.

SIGNIFICANCE

Analysis of a spectrum of subsolid pulmonary nodules by single-cell RNA sequencing provides insights into the immune regulation and cell-cell interactions in the tumor microenvironment during early lung tumor development.

Bulk brain tissue cell-type deconvolution with bias correction for single-nuclei RNA sequencing data using DeTREM

BACKGROUND

Quantifying cell-type abundance in bulk tissue RNA-sequencing enables researchers to better understand complex systems. Newer deconvolution methodologies, such as MuSiC, use cell-type signatures derived from single-cell RNA-sequencing (scRNA-seq) data to make these calculations. Single-nuclei RNA-sequencing (snRNA-seq) reference data can be used instead of scRNA-seq data for tissues such as human brain where single-cell data are difficult to obtain, but accuracy suffers due to sequencing differences between the technologies.

RESULTS

We propose a modification to MuSiC entitled 'DeTREM' which compensates for sequencing differences between the cell-type signature and bulk RNA-seq datasets in order to better predict cell-type fractions. We show DeTREM to be more accurate than MuSiC in simulated and real human brain bulk RNA-sequencing datasets with various cell-type abundance estimates. We also compare DeTREM to SCDC and CIBERSORTx, two recent deconvolution methods that use scRNA-seq cell-type signatures. We find that they perform well in simulated data but produce less accurate results than DeTREM when used to deconvolute human brain data.

CONCLUSION

DeTREM improves the deconvolution accuracy of MuSiC and outperforms other deconvolution methods when applied to snRNA-seq data. DeTREM enables accurate cell-type deconvolution in situations where scRNA-seq data are not available. This modification improves characterization cell-type specific effects in brain tissue and identification of cell-type abundance differences under various conditions.

Interactive analysis of single-cell data using flexible workflows with SCTK2

Analysis of single-cell RNA sequencing (scRNA-seq) data can reveal novel insights into the heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analyses. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single-Cell Toolkit 2 (SCTK2), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.

Integrative genetic and genomic networks identify microRNA associated with COPD and ILD

Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) are clinically and molecularly heterogeneous diseases. We utilized clustering and integrative network analyses to elucidate roles for microRNAs (miRNAs) and miRNA isoforms (isomiRs) in COPD and ILD pathogenesis. Short RNA sequencing was performed on 351 lung tissue samples of COPD (n = 145), ILD (n = 144) and controls (n = 64). Five distinct subclusters of samples were identified including 1 COPD-predominant cluster and 2 ILD-predominant clusters which associated with different clinical measurements of disease severity. Utilizing 262 samples with gene expression and SNP microarrays, we built disease-specific genetic and expression networks to predict key miRNA regulators of gene expression. Members of miR-449/34 family, known to promote airway differentiation by repressing the Notch pathway, were among the top connected miRNAs in both COPD and ILD networks. Genes associated with miR-449/34 members in the disease networks were enriched among genes that increase in expression with airway differentiation at an air-liquid interface. A highly expressed isomiR containing a novel seed sequence was identified at the miR-34c-5p locus. 47% of the anticorrelated predicted targets for this isomiR were distinct from the canonical seed sequence for miR-34c-5p. Overexpression of the canonical miR-34c-5p and the miR-34c-5p isomiR with an alternative seed sequence down-regulated NOTCH1 and NOTCH4. However, only overexpression of the isomiR down-regulated genes involved in Ras signaling such as CRKL and GRB2. Overall, these findings elucidate molecular heterogeneity inherent across COPD and ILD patients and further suggest roles for miR-34c in regulating disease-associated gene-expression.

A contamination focused approach for optimizing the single-cell RNA-seq experiment

Droplet-based single-cell RNA-seq (scRNA-seq) data are plagued by ambient contaminations caused by nucleic acid material released by dead and dying cells. This material is mixed into the buffer and is co-encapsulated with cells, leading to a lower signal-to-noise ratio. Although there exist computational methods to remove ambient contaminations post-hoc, the reliability of algorithms in generating high-quality data from low-quality sources remains uncertain. Here, we assess data quality before data filtering by a set of quantitative, contamination-based metrics that assess data quality more effectively than standard metrics. Through a series of controlled experiments, we report improvements that can minimize ambient contamination outside of tissue dissociation, via cell fixation, improved cell loading, microfluidic dilution, and nuclei versus cell preparation; many of these parameters are inaccessible on commercial platforms. We provide end-users with insights on factors that can guide their decision-making regarding optimizations that minimize ambient contamination, and metrics to assess data quality.

Abstract 4651: Comparison of the tumor and lymph node immune microenvironment in early non-small cell lung cancer through multimodal single cell sequencing

Background/Purpose: Previous studies have analyzed the tumor and local immune microenvironments in lung cancers and suggest immune modulation is associated with worse clinical outcome. However, the tumor-immune microenvironment in early stage lung tumors and lymph nodes (LNs) have not been fully described. We aim to compare cell states in the immune microenvironments between lung tumors and LNs through multi-modal profiling of the transcriptome and surface proteins.

Methods: Needle biopsy samples were taken from 10 treatment-naive early stage lung cancer patients undergoing lung cancer resections. Tissues were obtained from normal lung, lung tumor, and multiple mediastinal LNs, and processed for scRNA-seq including labeling with Total-Seq C CITE-seq panel to quantify the levels of 130 cell surface proteins. In total, 76,721 cells (4,462 normal lung; 39,019 tumor; 33,240 LN) were identified with a median of 1,673 genes and 92 protein features detected per cell. Protein expression was decontaminated through the decontX algorithm. Weighted-Nearest Neighbor analysis from the Seurat R package was applied to integrate the CITE-seq and RNA-seq level data for clustering cells into subpopulations.

Results: Six broad cell populations were identified including T/NK, myeloid (CD14+), B (CD19+), mast (TPSAB1+), pDC (IRF8+), and epithelial (EPCAM+) cells. Among 8 CD4+ T lymphocyte subpopulations and 11 CD8+ T lymphocyte subpopulations observed through clustering, a naïve CD4+ and a CD8+ T subpopulation (LEF1+, TCF7+) was observed respectively. These naïve T lymphocyte populations displayed increased proportions in LNs in comparison to tumors. In addition, 5 of the 8 observed CD4+ T lymphocyte populations were enriched in LNs. Immune populations enriched in LNs were largely shared and uniform across different patients. In contrast, a single CD4+ and CD8+ T lymphocyte subpopulation displayed expression of T lymphocyte exhaustion markers (TIGIT+, LAG3+, PD-1+) and were enriched in tumors. 6 of the 11 observed CD8+ T lymphocyte populations were enriched in tumor samples in comparison to LNs. Two alveolar macrophage populations (MARCO+) were enriched in normal lung tissue, in which one showed a heightened stress response.

Conclusion: Single-cell profiling reveals diversity in immune cell populations between LNs, tumor, and adjacent normal tissue in early-stage LUAD. The results suggest the composition of immune cell type is fairly consistent across LNs but more heterogeneous in the tumor and adjacent normal tissue in early-stage patients. In the future, we aim to determine if these immune subpopulations are associated with survival, recurrence, aggressiveness, and predict responses for neoadjuvant treatments, which could improve prognosis and patient quality of life.

Citation Format: Zhanhao Xi, Yusuke Koga, Shannon McDermott, Jennifer Beane, Sarah A. Mazzilli, Kei Suzuki, Joshua D. Campbell. Comparison of the tumor and lymph node immune microenvironment in early non-small cell lung cancer through multimodal single cell sequencing. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4651.

Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data

A large number of genomic and imaging datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While much effort has been devoted to capturing information related to biospecimen information and experimental procedures, the metadata standards that describe data matrices and the analysis workflows that produced them are relatively lacking. Detailed metadata schema related to data analysis are needed to facilitate sharing and interoperability across groups and to promote data provenance for reproducibility. To address this need, we developed the Matrix and Analysis Metadata Standards (MAMS) to serve as a resource for data coordinating centers and tool developers. We first curated several simple and complex "use cases" to characterize the types of feature-observation matrices (FOMs), annotations, and analysis metadata produced in different workflows. Based on these use cases, metadata fields were defined to describe the data contained within each matrix including those related to processing, modality, and subsets. Suggested terms were created for the majority of fields to aid in harmonization of metadata terms across groups. Additional provenance metadata fields were also defined to describe the software and workflows that produced each FOM. Finally, we developed a simple list-like schema that can be used to store MAMS information and implemented in multiple formats. Overall, MAMS can be used as a guide to harmonize analysis-related metadata which will ultimately facilitate integration of datasets across tools and consortia. MAMS specifications, use cases, and examples can be found at https://github.com/single-cell-mams/mams/.

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. Using an exploratory analysis of PBMC datasets, we find that some droplets that were originally called "empty" due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a "spongelet" which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.

Abstract P075: Comparison of the tumor and lymph node immune microenvironment in early non-small cell lung cancer through multimodal single cell sequencing

Background/Purpose: Previous studies have analyzed the tumor and local immune microenvironments in lung cancers and suggest immune modulation is associated with worse clinical outcome. However, the tumor-immune microenvironment in early-stage lung tumors and lymph nodes (LNs) have not been fully described. We aim to compare cell states in the immune microenvironments between lung tumors and LNs through multi-modal profiling of the transcriptome and surface proteins. Methods: Needle biopsy samples were taken from 10 treatment-naive early-stage lung cancer patients undergoing lung cancer resections. Tissues were obtained from normal lung, lung tumor, and multiple mediastinal LNs, and processed with scRNA-seq along with the Total-Seq C panel to quantify the levels of 130 cell surface proteins. In total, 98,337 cells (4,661 normal lung; 52,119 tumor; 42,117 LN) were identified with a median of 1,401 genes and 23 protein features detected per cell. Weighted-Nearest Neighbor analysis from the Seurat R package was applied to integrate the CITE-seq and RNA-seq level data for clustering cells into subpopulations. Results: Six broad cell populations were identified including T/NK, myeloid (CD14+), B (CD19+), mast (TPSAB1+), pDC (IRF8+), and epithelial (EPCAM+) cells. Protein expression measured with CITE-seq revealed additional T cell populations not captured by scRNA-seq. Preliminary results have identified cell populations enriched in LNs, which include naive CD4+ (CD4, FHIT, LEF1, CCR7) and CD8+ T cells (CD8A, TCF7, LEF1, CD27, CCR7). Additionally, we have identified numerous other CD8+ T-cell subpopulations enriched in tumors, including resident memory CD8+ T cells (KLRC1, ITGAE, ITGA1, VIM, JUN). Furthermore, immune populations enriched in LNs were similarly shared across different patients, while those enriched in tumors displayed patient-level specificity. Conclusion: Single-cell profiling reveals diversity in immune cell populations between LNs, tumor, and adjacent normal tissue in early-stage LUAD. The results suggest the composition of immune cell type is consistent across LNs but more heterogeneous in the tumor and adjacent normal tissue. In the future, we aim to determine if these markers for various immune subpopulations are associated with survival, recurrence, aggressiveness, and predict responses for neoadjuvant treatments, which could improve prognosis and patient quality of life.

Citation Format: Zhan Xi, Yusuke Koga, Shannon McDermott, Jennifer E. Beane, Sarah A. Mazzilli, Kei Suzuki, Joshua D. Campbell. Comparison of the tumor and lymph node immune microenvironment in early non-small cell lung cancer through multimodal single cell sequencing. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P075.

Smoking modulates different secretory subpopulations expressing SARS-CoV-2 entry genes in the nasal and bronchial airways

SARS-CoV-2 infection and disease severity are influenced by viral entry (VE) gene expression patterns in the airway epithelium. The similarities and differences of VE gene expression (ACE2, TMPRSS2, and CTSL) across nasal and bronchial compartments have not been fully characterized using matched samples from large cohorts. Gene expression data from 793 nasal and 1673 bronchial brushes obtained from individuals participating in lung cancer screening or diagnostic workup revealed that smoking status (current versus former) was the only clinical factor significantly and reproducibly associated with VE gene expression. The expression of ACE2 and TMPRSS2 was higher in smokers in the bronchus but not in the nose. scRNA-seq of nasal brushings indicated that ACE2 co-expressed genes were highly expressed in club and C15orf48+ secretory cells while TMPRSS2 co-expressed genes were highly expressed in keratinizing epithelial cells. In contrast, these ACE2 and TMPRSS2 modules were highly expressed in goblet cells in scRNA-seq from bronchial brushings. Cell-type deconvolution of the gene expression data confirmed that smoking increased the abundance of several secretory cell populations in the bronchus, but only goblet cells in the nose. The association of ACE2 and TMPRSS2 with smoking in the bronchus is due to their high expression in goblet cells which increase in abundance in current smoker airways. In contrast, in the nose, these genes are not predominantly expressed in cell populations modulated by smoking. In individuals with elevated lung cancer risk, smoking-induced VE gene expression changes in the nose likely have minimal impact on SARS-CoV-2 infection, but in the bronchus, smoking may lead to higher viral loads and more severe disease.

Celda: a Bayesian model to perform co-clustering of genes into modules and cells into subpopulations using single-cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) has emerged as a powerful technique to quantify gene expression in individual cells and to elucidate the molecular and cellular building blocks of complex tissues. We developed a novel Bayesian hierarchical model called Cellular Latent Dirichlet Allocation (Celda) to perform co-clustering of genes into transcriptional modules and cells into subpopulations. Celda can quantify the probabilistic contribution of each gene to each module, each module to each cell population and each cell population to each sample. In a peripheral blood mononuclear cell dataset, Celda identified a subpopulation of proliferating T cells and a plasma cell which were missed by two other common single-cell workflows. Celda also identified transcriptional modules that could be used to characterize unique and shared biological programs across cell types. Finally, Celda outperformed other approaches for clustering genes into modules on simulated data. Celda presents a novel method for characterizing transcriptional programs and cellular heterogeneity in scRNA-seq data.

Inactivation of the Hippo tumor suppressor pathway promotes melanoma

Melanoma is commonly driven by activating mutations in the MAP kinase BRAF; however, oncogenic BRAF alone is insufficient to promote melanomagenesis. Instead, its expression induces a transient proliferative burst that ultimately ceases with the development of benign nevi comprised of growth-arrested melanocytes. The tumor suppressive mechanisms that restrain nevus melanocyte proliferation remain poorly understood. Here we utilize cell and murine models to demonstrate that oncogenic BRAF leads to activation of the Hippo tumor suppressor pathway, both in melanocytes in vitro and nevus melanocytes in vivo. Mechanistically, we show that oncogenic BRAF promotes both ERK-dependent alterations in the actin cytoskeleton and whole-genome doubling events, which independently reduce RhoA activity to promote Hippo activation. We also demonstrate that functional impairment of the Hippo pathway enables oncogenic BRAF-expressing melanocytes to bypass nevus formation and rapidly form melanomas. Our data reveal that the Hippo pathway enforces the stable arrest of nevus melanocytes and represents a critical barrier to melanoma development.

Activating mutations of BRAF alone are inadequate to drive melanoma formation. Here the authors show that activation of Hippo signalling by oncogenic BRAF represents an additional safeguard to limit BRAF-dependent human melanocyte growth and melanoma formation.

Abstract 2201: Epithelial, stromal, and immune changes associated with lung squamous premalignant lesion severity identified by single-cell RNA-seq

Background: Bronchial pre-malignant lesions (PMLs) are the putative precursors for bronchial squamous cell carcinoma. PMLs represent a spectrum of histologies, from low-grade lesions (hyperplasia, metaplasia) to high-grade lesions (dysplasia, carcinoma in situ). The majority of these lesions will regress or remain stable without clinical intervention while a subset of lesions will progress to invasive carcinoma. We performed single-cell RNA sequencing (scRNAseq) of these lesions to elucidate the cross-talk between epithelial, stromal, and immune populations in lesions of increasing histological grade.

Methods: Thirty lesions from seventeen participants were biopsied via bronchoscopy. Cells were sorted by CD45+/- FACS gating and sequenced with the Cel-Seq2 protocol. Celda was used to bi-cluster genes into modules and cells into clusters. Cells were filtered by mitochondrial percentage (%mito &lt; 50%), minimum UMI counts (nUMI &gt; 300), and doublet detection. Cell types were labeled by marker gene expression.

Results: After filtering low quality cells, we analyzed 4,382 cells. We observed expected smoking related shifts in epithelial cell type proportions, including an increase in secretory cells (χ2 = 31.39, p = 2.11 X 10-8) and a decrease in ciliated cells (χ2 = 4.83, p = 0.028) among current smokers. Distinct differences in expression of transcriptional modules were observed between KRT5+ (basal) cells from different histologic grades. Basal cells from high grade lesions expressed smoking detoxification and cell cycle gene programs, while low grade lesion basal cells expressed differentiation gene programs. We also identified a group of cells from CIS lesions involved in an epithelial-to-mesenchymal transition, marked by an increase in SPARC and COL4A1 expression and a decrease in CDH1 expression. Subpopulations of immune cells identified include macrophages, CD4/8+ T, B, dendritic cells, and natural killer cells. Several clusters of CD4+ and CD8+ T cells displayed an exhausted phenotype, marked by the expression of PD-1, CTLA4, LAG3, and TIGIT. Samples with high grade histology (dysplasia, carcinoma in situ) were enriched in CD4+ Tregs and myeloid cells compared to low grade histology samples (hyperplasia, metaplasia), which were enriched in Natural Killer and cytotoxic CD8+ T cells (χ2 = 298.95, p = 0.001).

Discussion: Our results suggest that changes in specific transcriptional programs are associated with the transition of epithelial cells to more invasive states and that changes in immune populations are associated with increasing histological grade. These signatures can suggest novel avenues for chemoprevention and cancer interception.

Citation Format: Conor Shea, Lukas Kalinke, Kitty De Jong, Kate Gowers, Diane Ding, Sherry Zhang, Gang Liu, Jack Cunningham, Ipsita Dey-Guha, Mark Hennon, Sai Yendamuri, Christopher Stevenson, Avrum Spira, Mary E. Reid, Marc E. Lenburg, Sam M. Janes, Jennifer E. Beane, Sarah A. Mazzilli, Joshua D. Campbell. Epithelial, stromal, and immune changes associated with lung squamous premalignant lesion severity identified by single-cell RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2201.

A single-cell lung atlas of complement genes identifies the mesothelium and epithelium as prominent sources of extrahepatic complement proteins

To understand functional duality of the complement system in host defense and lung injury, a more comprehensive view of its localized production in the lung, and the impact of age on complement production are essential. Here, we explored the expression of complement genes through computational analysis of preexisting single cell RNA sequencing data from lung transcriptomes of healthy young (3 months) and old C57BL/6 mice (24 months), and humans. We characterized the distribution of 48 complement genes. Across 28 distinct immune and non-immune cell types in mice, mesothelial cells expressed the greatest number of complement genes (e.g., C1ra, C2, C3), and regulators (e.g., Serping1, Cfh). C5 was abundant in type II alveolar epithelial cells and C1q in interstitial lung macrophages. There were only moderate differences in gene expression between young and old mice. Among 57 human lung cell types, mesothelial cells showed abundant complement expression. A few differences in gene  expression (e.g., FCN1, CFI, C6, C7) were also evident between mice and human lung cells. Our findings present a novel perspective on the expression patterns of complement genes in normal lungs. These findings highlight the potential functions of complement in tissue-specific homeostasis and immunity and may foster a mechanistic understanding of its role in lung health and disease.

Humanized mice reveal a macrophage-enriched gene signature defining human lung tissue protection during SARS-CoV-2 infection

The human immunological mechanisms defining the clinical outcome of SARS-CoV-2 infection remain elusive. This knowledge gap is mostly driven by the lack of appropriate experimental platforms recapitulating human immune responses in a controlled human lung environment. Here, we report a mouse model (i.e., HNFL mice) co-engrafted with human fetal lung xenografts (fLX) and a myeloid-enhanced human immune system to identify cellular and molecular correlates of lung protection during SARS-CoV-2 infection. Unlike mice solely engrafted with human fLX, HNFL mice are protected against infection, severe inflammation, and histopathological phenotypes. Lung tissue protection from infection and severe histopathology associates with macrophage infiltration and differentiation and the upregulation of a macrophage-enriched signature composed of 11 specific genes mainly associated with the type I interferon signaling pathway. Our work highlights the HNFL model as a transformative platform to investigate, in controlled experimental settings, human myeloid immune mechanisms governing lung tissue protection during SARS-CoV-2 infection.

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) can be used to gain insights into cellular heterogeneity within complex tissues. However, various technical artifacts can be present in scRNA-seq data and should be assessed before performing downstream analyses. While several tools have been developed to perform individual quality control (QC) tasks, they are scattered in different packages across several programming environments. Here, to streamline the process of generating and visualizing QC metrics for scRNA-seq data, we built the SCTK-QC pipeline within the singleCellTK R package. The SCTK-QC workflow can import data from several single-cell platforms and preprocessing tools and includes steps for empty droplet detection, generation of standard QC metrics, prediction of doublets, and estimation of ambient RNA. It can run on the command line, within the R console, on the cloud platform or with an interactive graphical user interface. Overall, the SCTK-QC pipeline streamlines and standardizes the process of performing QC for scRNA-seq data.

Quality control (QC) is a crucial step in single-cell RNA-seq data analysis. Here, the authors present the SCTK-QC pipeline which generates and visualizes a comprehensive set of QC metrics to streamline the process of detecting and removing poor quality cells and other artifacts.

The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the Discovery, Prediction, and Exploration of Mutational Signatures

Mutational signatures are patterns of somatic alterations in the genome caused by carcinogenic exposures or aberrant cellular processes. To provide a comprehensive workflow for preprocessing, analysis, and visualization of mutational signatures, we created the Mutational Signature Comprehensive Analysis Toolkit (musicatk) package. musicatk enables users to select different schemas for counting mutation types and to easily combine count tables from different schemas. Multiple distinct methods are available to deconvolute signatures and exposures or to predict exposures in individual samples given a pre-existing set of signatures. Additional exploratory features include the ability to compare signatures to the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, embed tumors in two dimensions with uniform manifold approximation and projection, cluster tumors into subgroups based on exposure frequencies, identify differentially active exposures between tumor subgroups, and plot exposure distributions across user-defined annotations such as tumor type. Overall, musicatk will enable users to gain novel insights into the patterns of mutational signatures observed in cancer cohorts. SIGNIFICANCE: The musicatk package empowers researchers to characterize mutational signatures and tumor heterogeneity with a comprehensive set of preprocessing utilities, discovery and prediction tools, and multiple functions for downstream analysis and visualization.

ExperimentSubset: an R package to manage subsets of Bioconductor Experiment objects

MOTIVATION

R Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for storing one or more matrix-like assays along with associated row and column data. These objects have been used to facilitate the storage and analysis of high-throughput genomic data generated from technologies such as single-cell RNA sequencing. One common computational task in many genomics analysis workflows is to perform subsetting of the data matrix before applying down-stream analytical methods. For example, one may need to subset the columns of the assay matrix to exclude poor-quality samples or subset the rows of the matrix to select the most variable features. Traditionally, a second object is created that contains the desired subset of assay from the original object. However, this approach is inefficient as it requires the creation of an additional object containing a copy of the original assay and leads to challenges with data provenance.

RESULTS

To overcome these challenges, we developed an R package called ExperimentSubset, which is a data container that implements classes for efficient storage and streamlined retrieval of assays that have been subsetted by rows and/or columns. These classes are able to inherently provide data provenance by maintaining the relationship between the subsetted and parent assays. We demonstrate the utility of this package on a single-cell RNA-seq dataset by storing and retrieving subsets at different stages of the analysis while maintaining a lower memory footprint. Overall, the ExperimentSubset is a flexible container for the efficient management of subsets.

AVAILABILITY AND IMPLEMENTATION

ExperimentSubset package is available at Bioconductor: https://bioconductor.org/packages/ExperimentSubset/ and Github: https://github.com/campbio/ExperimentSubset.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Elevated T cell repertoire diversity is associated with progression of lung squamous cell premalignant lesions

Objective

The immune response to invasive carcinoma has been the focus of published work, but little is known about the adaptive immune response to bronchial premalignant lesions (PMLs), precursors of lung squamous cell carcinoma. This study was designed to characterize the T cell receptor (TCR) repertoire in PMLs and its association with clinical, pathological, and molecular features.

Methods

Endobronchial biopsies (n=295) and brushings (n=137) from high-risk subjects (n=50), undergoing lung cancer screening at approximately 1-year intervals via autofluorescence bronchoscopy and CT, were profiled by RNA-seq. We applied the TCR Repertoire Utilities for Solid Tissue/Tumor tool to the RNA-seq data to identify TCR CDR3 sequences across all samples. In the biopsies, we measured the correlation of TCR diversity with previously derived immune-associated PML transcriptional signatures and PML outcome. We also quantified the spatial and temporal distribution of shared and clonally expanded TCRs. Using the biopsies and brushes, the ratio of private (ie, found in one patient only) and public (ie, found in two or more patients) TCRs was quantified, and the CDR3 sequences were compared with those found in curated databases with known antigen specificities.

Results

We detected 39,303 unique TCR sequences across all samples. In PML biopsies, TCR diversity was negatively associated with a transcriptional signature of T cell mediated immune activation (p=4e-4) associated with PML outcome. Additionally, in lesions of the proliferative molecular subtype, TCR diversity was decreased in regressive versus progressive/persistent PMLs (p=0.045). Within each patient, TCRs were more likely to be shared between biopsies sampled at the same timepoint than biopsies sampled at the same anatomic location at different times. Clonally expanded TCRs, within a biopsied lesion, were more likely to be expanded at future time points than non-expanded clones. The majority of TCR sequences were found in a single sample, with only 3396 (8.6%) found in more than one sample and 1057 (2.7%) found in two or more patients (ie, public); however, when compared with a public database of CDR3 sequences, 4543 (11.6%) of TCRs were identified as public. TCRs with known antigen specificities were enriched among public TCRs (p<0.001).

Conclusions

Decreased TCR diversity may reflect nascent immune responses that contribute to PML elimination. Further studies are needed to explore the potential for immunoprevention of PMLs.

Abstract 2212: Cellular and molecular changes associated with lung squamous premalignant lesion severity identified by single-cell RNA-seq

Background: Sampling the bronchial airway during bronchoscopies in screening populations at high risk for lung cancer has increased detection of squamous bronchial pre-malignant lesions (PML). The majority of these lesions will regress or remain stable without any clinical intervention. However, a subset of lesions will progress to invasive malignancy. In this work, we investigate the gene expression changes in epithelial cell states and immune cell proportion shifts associated with premalignant histologic stage using single-cell RNA sequencing to begin to identify molecular features associated with PML regression or progression.

Methods: Cells (n=3,325) were isolated from 11 endobronchial biopsies from 9 patients, where biopsy histology range from normal, dysplasia, carcinoma in situ (CIS) and squamous cell carcinoma. Immune cells (CD45+) and epithelial cells (CD45− EPCAM+) were sorted into separate 96-well plates using fluorescence activated cell sorting (FACS) and sequenced using CEL-Seq2 single cell RNA seq protocol.

Results: After filtering low quality cells, we profiled 2,998 cells (1,052 CD45+ and 1,946 CD45−) with an average of 1,190 genes per cell. Within the epithelial cells, we focused on basal cells as they are the airway progenitor cells. We observed distinct differences in expression of KRT5+ (basal) cells between different histologic grades, where KRT5+ cells present in a hyperplasic lesion expressed multiple secretory cell markers suggesting they were transitioning to a secretory cell phenotype and KRT5+ cells from a CIS lesion from a current smoker expressed higher levels of smoking inducible genes, such as GSTM1 and CYP1A1. Lastly, KRT5+ cells from a lung squamous carcinoma tumor expressed higher levels of many genes related to cell cycle progression. Among the immune populations, low-grade PMLs with non-dysplastic histology were enriched for CD8+ T cells, whereas higher-grade PMLs and an invasive tumor were enriched for myeloid cells.

Conclusions: To date, we have begun to identify histology-associated cellular and molecular profiles in bronchial premalignancy and early-stage carcinoma. Future resampling of these patients and expansion of cases will allow us to discover biomarkers associated with lesion progression and molecular targets for lung cancer interception.

Citation Format: Conor Shea, Lukas Kalinke, Kitty De Jong, Kate Gowers, Diane Ding, Sherry Zhang, Gang Liu, Jack Cunningham, Ipsita Dey-Guha, Mark Hennon, Sai Yendumuri, Christopher Stevenson, Steven Dubinett, Avrum Spira, Marc Lenburg, Samuel Janes, Mary Reid, Jennifer Beane, Sarah Mazzilli, Joshua D. Campbell. Cellular and molecular changes associated with lung squamous premalignant lesion severity identified by single-cell RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2212.

Abstract 171: Cloud-based bulk and single-cell RNAseq pipelines in the Terra platform for the Lung PCA

Introduction: The Lung Precancer Atlas (PCA) is developing bulk and single cell RNA-seq pipelines to process Lung PCA sequencing data collected across our multi-institutional consortium. The pipelines will be publicly available to run using the Terra Cloud platform so that they can be used by other members of the NCI Human Tumor Atlas Network (HTAN) and the broader research community.

Method: We built our single cell and bulk RNA-seq pipelines for integration in the Terra cloud platform. Terra utilizes a Google Cloud/BigQuery backend to store data with built-in security features. The Terra platform provides a uniform resource for pipeline development and data processing for investigators located across multiple institutions.

Result: The RNA-seq pipeline in Terra used by GTeX and HTOP utilizes STAR to align reads to a reference genome, RSEM and RNASeQC-2 to quantify expression and compute quality metrics. We have added additional quality metrics using the FASTQC and RSEQC tools as well as GATK germline variant calling. Somalier is used to perform fast fingerprinting for multiple samples derived from the same patient. The pipeline was also modified to estimate TCR/BCR repertoires using TRUST to facilitate downstream analyses of the immunological status of lung premalignant lesions. We have also enhanced Terra pipelines for droplet and plate-based single cell RNA sequencing data. The single cell RNA-seq preprocessing pipeline for 10X data included steps from CellRanger for demultiplexing, alignment to a reference genome, and count matrix generation. We have added the quality control pipeline from the singleCellTK package, which generates and aggregates quality control metrics from 8 different tools including those for doublet detection and ambient RNA quantification. For plate-based CEL-seq2 data, we have built a pipeline utilizing the SCRUFF package for alignment and singleCellTK for quality control. The count matrices and QC metrics are aggregated into SingleCellExperiment or SummarizedExperiment R objects for downstream analyses.

Conclusion: Our completed Terra pipelines will allow researchers in the Lung PCA to process RNA sequencing data using a consistent set of tools and gene annotation. These pipelines, and the standardization of data processing and quality control that they provide, may be of use to other investigators in the Human Tumor Atlas Network as well as to broader scientific community.

Citation Format: Chris Husted, François Aguet, Conor Shea, Adam Gower, William Mischler, Yusuke Koga, Rui Hong, Steven Dubinett, Avrum Spira, Sarah A. Mazzilli, Ethan Cerami, Ignaty Leshchiner, Marc E. Lenburg, Gad Getz, Jennifer E. Beane, Joshua D. Campbell. Cloud-based bulk and single-cell RNAseq pipelines in the Terra platform for the Lung PCA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 171.

Genetic Ancestry Contributes to Somatic Mutations in Lung Cancers from Admixed Latin American Populations

Inherited lung cancer risk, particularly in nonsmokers, is poorly understood. Genomic and ancestry analysis of 1,153 lung cancers from Latin America revealed striking associations between Native American ancestry and their somatic landscape, including tumor mutational burden, and specific driver mutations in EGFR, KRAS, and STK11. A local Native American ancestry risk score was more strongly correlated with EGFR mutation frequency compared with global ancestry correlation, suggesting that germline genetics (rather than environmental exposure) underlie these disparities. SIGNIFICANCE: The frequency of somatic EGFR and KRAS mutations in lung cancer varies by ethnicity, but we do not understand why. Our study suggests that the variation in EGFR and KRAS mutation frequency is associated with genetic ancestry and suggests further studies to identify germline alleles that underpin this association.See related commentary by Gomez et al., p. 534.This article is highlighted in the In This Issue feature, p. 521.

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

Comparative Genomics Reveals Distinct Immune-oncologic Pathways in African American Men with Prostate Cancer

PURPOSE

The role of immune-oncologic mechanisms of racial disparities in prostate cancer remains understudied. Limited research exists to evaluate the molecular underpinnings of immune differences in African American men (AAM) and European American men (EAM) prostate tumor microenvironment (TME).

EXPERIMENTAL DESIGN

A total of 1,173 radiation-naïve radical prostatectomy samples with whole transcriptome data from the Decipher GRID registry were used. Transcriptomic expressions of 1,260 immune-specific genes were selected to assess immune-oncologic differences between AAM and EAM prostate tumors. Race-specific differential expression of genes was assessed using a rank test, and intergene correlational matrix and gene set enrichment was used for pathway analysis.

RESULTS

AAM prostate tumors have significant enrichment of major immune-oncologic pathways, including proinflammatory cytokines, IFNα, IFNγ, TNFα signaling, ILs, and epithelial-mesenchymal transition. AAM TME has higher total immune content score (ICS^HIGH) compared with 0 (37.8% vs. 21.9%, P = 0.003). AAM tumors also have lower DNA damage repair and are genomically radiosensitive as compared with EAM. IFITM3 (IFN-inducible transmembrane protein 3) was one of the major proinflammatory genes overexpressed in AAM that predicted increased risk of biochemical recurrence selectively for AAM in both discovery [HR_AAM = 2.30; 95% confidence interval (CI), 1.21-4.34; P = 0.01] and validation (HR_AAM = 2.42; 95% CI, 1.52-3.86; P = 0.0001) but not in EAM.

CONCLUSIONS

Prostate tumors of AAM manifest a unique immune repertoire and have significant enrichment of proinflammatory immune pathways that are associated with poorer outcomes. Observed immune-oncologic differences can aid in a genomically adaptive approach to treating prostate cancer in AAM.

Genomic Profiling of Prostate Cancers from Men with African and European Ancestry

PURPOSE

African American (AFR) men have the highest mortality rate from prostate cancer (PCa) compared with men of other racial/ancestral groups. Differences in the spectrum of somatic genome alterations in tumors between AFR men and other populations have not been well-characterized due to a lack of inclusion of significant numbers in genomic studies.

EXPERIMENTAL DESIGN

To identify genomic alterations associated with race, we compared the frequencies of somatic alterations in PCa obtained from four publicly available datasets comprising 250 AFR and 611 European American (EUR) men and a targeted sequencing dataset from a commercial platform of 436 AFR and 3018 EUR men.

RESULTS

Mutations in ZFHX3 as well as focal deletions in ETV3 were more frequent in tumors from AFR men. TP53 mutations were associated with increasing Gleason score. MYC amplifications were more frequent in tumors from AFR men with metastatic PCa, whereas deletions in PTEN and rearrangements in TMPRSS2-ERG were less frequent in tumors from AFR men. KMT2D truncations and CCND1 amplifications were more frequent in primary PCa from AFR men. Genomic features that could impact clinical decision making were not significantly different between the two groups including tumor mutation burden, MSI status, and genomic alterations in select DNA repair genes, CDK12, and in AR.

CONCLUSIONS

Although we identified some novel differences in AFR men compared with other populations, the frequencies of genomic alterations in current therapeutic targets for PCa were similar between AFR and EUR men, suggesting that existing precision medicine approaches could be equally beneficial if applied equitably.

Generation of Genetically Engineered Mouse Lung Organoid Models for Squamous Cell Lung Cancers Allows for the Study of Combinatorial Immunotherapy

PURPOSE

Lung squamous cell carcinoma (LSCC) is a deadly disease for which only a subset of patients responds to immune checkpoint blockade (ICB) therapy. Therefore, preclinical mouse models that recapitulate the complex genetic profile found in patients are urgently needed.

EXPERIMENTAL DESIGN

We used CRISPR genome editing to delete multiple tumor suppressors in lung organoids derived from Cre-dependent SOX2 knock-in mice. We investigated both the therapeutic efficacy and immunologic effects accompanying combination PD-1 blockade and WEE1 inhibition in both mouse models and LSCC patient-derived cell lines.

RESULTS

We show that multiplex gene editing of mouse lung organoids using the CRISPR-Cas9 system allows for efficient and rapid means to generate LSCCs that closely mimic the human disease at the genomic and phenotypic level. Using this genetically defined mouse model and three-dimensional tumoroid culture system, we show that WEE1 inhibition induces DNA damage that primes the endogenous type I IFN and antigen presentation system in primary LSCC tumor cells. These events promote cytotoxic T-cell-mediated clearance of tumor cells and reduce the accumulation of tumor-infiltrating neutrophils. Beneficial immunologic features of WEE1 inhibition are further enhanced by the addition of anti-PD-1 therapy.

CONCLUSIONS

We developed a mouse model system to investigate a novel combinatory approach that illuminates a clinical path hypothesis for combining ICB with DNA damage-inducing therapies in the treatment of LSCC.

Abstract A122: Comparison of mutational profiles in primary prostate cancers between men with African and European ancestry

Background: African American men have more than twice the age-adjusted mortality rate from prostate cancer than European American men. Lower rate of PSA screening, less aggressive treatment, and other socioeconomic factors have been raised as possible reasons for this disparity, but genetic differences between prostate cancers from African and European ancestry have not been fully investigated as most sequencing studies so far have studied the latter group. The goal of this study is to perform a meta-analysis across various publicly available sequencing datasets and identify mutational profiles associated with African American ancestry in prostate cancer.

Methods: Whole exome sequencing data from 499 treatment-naive prostate cancers were analyzed from The Cancer Genome Atlas (TCGA). The ethnicity of each patient was inferred using previously published method (1). Our analysis included whole-exome sequencing data from 404 European and 159 African prostate cancers. African American samples were aggregate of TCGA and recently published African American prostate cancer data (2). We looked at previously shown 97 significantly mutated genes in prostate cancer (3). Using coding mutations, a Fisher's exact test was performed for each gene to compare the frequencies between populations. In a separate analysis, these two exome datasets were combined with two other targeted sequencing datasets from Huang et al. (2) (n = 86) and Abida et al. (4) (n = 424) using only genes common to all platforms.

Results: Among 97 genes, only KDM6A was significantly enriched in African American samples (p = 0.039). NCOR1, ERF, and AR tended to be more mutated in African American samples. TP53, SPEN, and PIK3CA were more mutated in prostate cancer of European ancestry (p &lt; 0.05). PTEN and CTNNB1 tended to be more mutated in European tumors even though they did not meet statistical significance. For the meta-analysis across both exome and targeted sequencing datasets, we observed that ZFHX3 was significantly more frequent in tumors from African American versus other populations (8% versus 2%, FDR = 0.0001). ZFHX3 was also strongly enriched for loss-of-function mutations (p = 1.2e-9), further supporting its role as a tumor suppressor.

Discussion: The contribution of tumor genetics to outcome disparities in African American prostate cancer is under active investigation. Our analysis shows that African American prostate cancers tend to harbor fewer mutations in previously identified prostate cancer genes such as PIK3CA, TP53, PTEN, and CTNNB1 and potentially more mutations in KDM6A and ZFHX3. As prostate cancers have a lower mutation rate, the number of tumors needed to detect low frequency mutations is high. More sequencing of African American prostate cancers may elucidate additional genetic contributions to higher mortality.

Citation Format: Eejung Kim, Yusuke Koga, Jian Carrot-Zhang, Joshua D. Campbell, Franklin Huang. Comparison of mutational profiles in primary prostate cancers between men with African and European ancestry [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr A122.

Cross organelle stress response disruption promotes gentamicin-induced proteotoxicity

Gentamicin is a nephrotoxic antibiotic that causes acute kidney injury (AKI) primarily by targeting the proximal tubule epithelial cell. The development of an effective therapy for gentamicin-induced renal cell injury is limited by incomplete mechanistic insight. To address this challenge, we propose that RNAi signal pathway screening could identify a unifying mechanism of gentamicin-induced cell injury and suggest a therapeutic strategy to ameliorate it. Computational analysis of RNAi signal screens in gentamicin-exposed human proximal tubule cells suggested the cross-organelle stress response (CORE), the unfolded protein response (UPR), and cell chaperones as key targets of gentamicin-induced injury. To test this hypothesis, we assessed the effect of gentamicin on the CORE, UPR, and cell chaperone function, and tested the therapeutic efficacy of enhancing cell chaperone content. Early gentamicin exposure disrupted the CORE, evidenced by a rise in the ATP:ADP ratio, mitochondrial-specific H2O2 accumulation, Drp-1-mediated mitochondrial fragmentation, and endoplasmic reticulum-mitochondrial dissociation. CORE disruption preceded measurable increases in whole-cell oxidative stress, misfolded protein content, transcriptional UPR activation, and its untoward downstream effects: CHOP expression, PARP cleavage, and cell death. Geranylgeranylacetone, a therapeutic that increases cell chaperone content, prevented mitochondrial H2O2 accumulation, preserved the CORE, reduced the burden of misfolded proteins and CHOP expression, and significantly improved survival in gentamicin-exposed cells. We identify CORE disruption as an early and remediable cause of gentamicin proteotoxicity that precedes downstream UPR activation and cell death. Preserving the CORE significantly improves renal cell survival likely by reducing organelle-specific proteotoxicity during gentamicin exposure.

Decontamination of ambient RNA in single-cell RNA-seq with DecontX

Droplet-based microfluidic devices have become widely used to perform single-cell RNA sequencing (scRNA-seq). However, ambient RNA present in the cell suspension can be aberrantly counted along with a cell's native mRNA and result in cross-contamination of transcripts between different cell populations. DecontX is a novel Bayesian method to estimate and remove contamination in individual cells. DecontX accurately predicts contamination levels in a mouse-human mixture dataset and removes aberrant expression of marker genes in PBMC datasets. We also compare the contamination levels between four different scRNA-seq protocols. Overall, DecontX can be incorporated into scRNA-seq workflows to improve downstream analyses.

Characterizing smoking-induced transcriptional heterogeneity in the human bronchial epithelium at single-cell resolution

The human bronchial epithelium is composed of multiple distinct cell types that cooperate to defend against environmental insults. While studies have shown that smoking alters bronchial epithelial function and morphology, its precise effects on specific cell types and overall tissue composition are unclear. We used single-cell RNA sequencing to profile bronchial epithelial cells from six never and six current smokers. Unsupervised analyses led to the characterization of a set of toxin metabolism genes that localized to smoker ciliated cells, tissue remodeling associated with a loss of club cells and extensive goblet cell hyperplasia, and a previously unidentified peri-goblet epithelial subpopulation in smokers who expressed a marker of bronchial premalignant lesions. Our data demonstrate that smoke exposure drives a complex landscape of cellular alterations that may prime the human bronchial epithelium for disease.

Genomic and immune profiling of pre-invasive lung adenocarcinoma

Adenocarcinoma in situ and minimally invasive adenocarcinoma are the pre-invasive forms of lung adenocarcinoma. The genomic and immune profiles of these lesions are poorly understood. Here we report exome and transcriptome sequencing of 98 lung adenocarcinoma precursor lesions and 99 invasive adenocarcinomas. We have identified EGFR, RBM10, BRAF, ERBB2, TP53, KRAS, MAP2K1 and MET as significantly mutated genes in the pre/minimally invasive group. Classes of genome alterations that increase in frequency during the progression to malignancy are revealed. These include mutations in TP53, arm-level copy number alterations, and HLA loss of heterozygosity. Immune infiltration is correlated with copy number alterations of chromosome arm 6p, suggesting a link between arm-level events and the tumor immune environment.

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smoking and/or human papillomavirus (HPV). SCCs harbor 3q, 5p, and other recurrent chromosomal copy-number alterations (CNAs), DNA mutations, and/or aberrant methylation of genes and microRNAs, which are correlated with the expression of multi-gene programs linked to squamous cell stemness, epithelial-to-mesenchymal differentiation, growth, genomic integrity, oxidative damage, death, and inflammation. Low-CNA SCCs tended to be HPV(+) and display hypermethylation with repression of TET1 demethylase and FANCF, previously linked to predisposition to SCC, or harbor mutations affecting CASP8, RAS-MAPK pathways, chromatin modifiers, and immunoregulatory molecules. We uncovered hypomethylation of the alternative promoter that drives expression of the ΔNp63 oncogene and embedded miR944. Co-expression of immune checkpoint, T-regulatory, and Myeloid suppressor cells signatures may explain reduced efficacy of immune therapy. These findings support possibilities for molecular classification and therapeutic approaches.

Abstract 3393: Altered immune response in the transcriptome of patients with lung cancer

Introduction The immune system is critical to surveying and eradicating abnormal cells, but tumor cells develop ways to escape immunosurveillance and induce an immunosuppressive state. We previously developed and validated gene expression (GE) signatures measured in the normal airway-epithelial brushings in patients undergoing bronchoscopy for suspicion of lung cancer (LC). In this study, we seek to understand if the immunosuppressive environment extends to the airway field of injury via profiling of endobronchial biopsies from the central airway containing a broader range of cell types, including immune cells.

Methods Endobronchial biopsies from normal-appearing regions of the central airway were collected from ever smokers undergoing workup of indeterminate pulmonary nodules (7-30 mm in diameter) suspicious for LC at military and VA hospitals within the DECAMP consortium. Initially, total RNA from the biopsies (n=44, discovery-set) were isolated and sequenced. Reads were aligned to hg19 using STAR and gene level counts were quantified with RSEM. Poor quality samples were removed using FASTQC and RSEQC. Differential GE associated with cancer status was identified using edgeR, adjusting for smoking-status, COPD and sample quality. RNA from additional endobronchial biopsies (n=49, validation-set) were isolated and preprocessed similarly. Genes differentially expressed with LC status in the discovery-set were tested in the validation-set using gene set variation analysis (GSVA). Functional enrichment of cancer associated genes was explored using Enrichr. Comparison of cancer signatures identified in previously published LC studies was investigated using GSEA. CIBERSORT, xCell, TIMER software and single-cell RNA sequencing data generated from airway brushings were used to deconvolute the immune cell content of the bulk biopsy samples.

Results We identified a GE signature associated with LC which was significantly and concordantly enriched in the validation set of biopsies and two previously published studies of LC-associated GE in airway brushings. Genes decreased in LC patient biopsies were enriched for genes involved in immune-related pathways, including cytokine interactions, the inflammatory response and neutrophil degranulation. Computational deconvolution and comparison with single-cell RNAseq data predicts a decrease in neutrophils in the airway of LC patients.

Conclusion We identified LC-associated GE alterations in smokers presenting with indeterminate pulmonary nodules. Down-regulated genes in LC subjects are strongly associated with immune system function, specifically neutrophil biology. Subjects with LC appear to have an immunosuppressive environment directed towards myeloid cell populations, and this could have implications for the future development of immunoprevention therapies.

Citation Format: Kahkeshan Hijazi, Julian Lel, Ehab Billatos, Elizabeth Moses, Christopher S. Stevenson, Matthew V. Lorenzi, Gang Liu, Joshua D. Campbell, Yusuke Koga, Jiarui Zhang, Fenghai Duan, Helga Marques, Marc E. Lenburg, Avrum E. Spira, Jennifer Beane. Altered immune response in the transcriptome of patients with lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3393.

Pipeliner: A Nextflow-Based Framework for the Definition of Sequencing Data Processing Pipelines

The advent of high-throughput sequencing technologies has led to the need for flexible and user-friendly data preprocessing platforms. The Pipeliner framework provides an out-of-the-box solution for processing various types of sequencing data. It combines the Nextflow scripting language and Anaconda package manager to generate modular computational workflows. We have used Pipeliner to create several pipelines for sequencing data processing including bulk RNA-sequencing (RNA-seq), single-cell RNA-seq, as well as digital gene expression data. This report highlights the design methodology behind Pipeliner that enables the development of highly flexible and reproducible pipelines that are easy to extend and maintain on multiple computing environments. We also provide a quick start user guide demonstrating how to setup and execute available pipelines with toy datasets.

scruff: an R/Bioconductor package for preprocessing single-cell RNA-sequencing data

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) enables the high-throughput quantification of transcriptional profiles in single cells. In contrast to bulk RNA-seq, additional preprocessing steps such as cell barcode identification or unique molecular identifier (UMI) deconvolution are necessary for preprocessing of data from single cell protocols. R packages that can easily preprocess data and rapidly visualize quality metrics and read alignments for individual cells across multiple samples or runs are still lacking.

RESULTS

Here we present scruff, an R/Bioconductor package that preprocesses data generated from the CEL-Seq or CEL-Seq2 protocols and reports comprehensive data quality metrics and visualizations. scruff rapidly demultiplexes, aligns, and counts the reads mapped to genome features with deduplication of unique molecular identifier (UMI) tags. scruff also provides novel and extensive functions to visualize both pre- and post-alignment data quality metrics for cells from multiple experiments. Detailed read alignments with corresponding UMI information can be visualized at specific genome coordinates to display differences in isoform usage. The package also supports the visualization of quality metrics for sequence alignment files for multiple experiments generated by Cell Ranger from 10X Genomics. scruff is available as a free and open-source R/Bioconductor package.

CONCLUSIONS

scruff streamlines the preprocessing of scRNA-seq data in a few simple R commands. It performs data demultiplexing, alignment, counting, quality report and visualization systematically and comprehensively, ensuring reproducible and reliable analysis of scRNA-seq data.

Molecular subtyping reveals immune alterations associated with progression of bronchial premalignant lesions

Bronchial premalignant lesions (PMLs) are precursors of lung squamous cell carcinoma, but have variable outcome, and we lack tools to identify and treat PMLs at risk for progression to cancer. Here we report the identification of four molecular subtypes of PMLs with distinct differences in epithelial and immune processes based on RNA-Seq profiling of endobronchial biopsies from high-risk smokers. The Proliferative subtype is enriched with bronchial dysplasia and exhibits up-regulation of metabolic and cell cycle pathways. A Proliferative subtype-associated gene signature identifies subjects with Proliferative PMLs from normal-appearing uninvolved large airway brushings with high specificity. In progressive/persistent Proliferative lesions expression of interferon signaling and antigen processing/presentation pathways decrease and immunofluorescence indicates a depletion of innate and adaptive immune cells compared with regressive lesions. Molecular biomarkers measured in PMLs or the uninvolved airway can enhance histopathological grading and suggest immunoprevention strategies for intercepting the progression of PMLs to lung cancer.

Abstract 3248: Genomic characterization of premalignant lung squamous cell carcinoma lesions

Background: Lung squamous cell carcinoma (SqCC) arises in the epithelial layer of the bronchial airway and is often preceded by the development of premalignant lesions. However, not all premalignant lesions progress to lung SqCC and many will regress spontaneously. Understanding the somatic alterations and molecular subtypes associated with progression will allow us to identify biomarkers for early detection and develop therapeutic strategies for disease prevention and interception. Methods: Biopsies were obtained from high-risk smokers undergoing lung cancer screening by auto-fluorescence bronchoscopy and CT at the Roswell Park Cancer Institute. For each subject, multiple sites were sampled repeatedly over time. One biopsy from each region was sent for pathological review while another biopsy was taken for molecular studies. Whole-exome sequencing (WES) was performed at Uniform Services University to 120x coverage and RNA-seq was performed at Boston University School of Medicine. Results: The median number of somatic mutations across all premalignant lesions that underwent DNA-seq (150 biopsies from 20 subjects) was 0.45 per megabase and displayed a modest association with histological grade (p=0.05). The most frequently mutated known lung cancer genes included NOTCH1 (14%), TP53 (6%), FAT1 (3%), PIK3CA (2%), KRAS (&lt;1%), and CDKN2A (&lt;1%). One patient had a moderate dysplastic lesion without any detectable arm-level copy number changes or known cancer mutations. Six months later, this lesion had progressed to severe dysplasia and obtained many genomic alterations commonly observed in squamous cell carcinoma including 3q gain, 3p loss, and mutations in TP53, NOTCH1, and CDKN2A. Using RNA-seq, we identified 4 distinct molecular subtypes using 197 biopsies from 29 subjects. One subtype was enriched for samples with dysplasia histology, high basal cell content, and the “Classical” SqCC tumor gene expression subtype (p&lt;0.001). These associations replicated in an independent set of 111 biopsies from 20 subjects. Genes associated with IFN-gamma signaling and T cell mediated immunity were down-regulated among lesions that persisted or progressed vs. those that regressed within the high-grade subtype. Staining of adjacent biopsies revealed that decreased expression of these immune pathways was associated with decreased numbers of CD4+ and CD8+ T cells within the lesions and surrounding tissue. Conclusions: The somatic alterations observed in known cancer genes may be among the earliest events in lung SqCC development and may be useful as biomarkers for early detection. Molecular classification of these lesions into molecular subtypes may lead to biomarkers of disease progression that could be used to identify at-risk patients for aggressive surveillance or for prevention trials.

Citation Format: Joshua D. Campbell, Xijun Zhang, Catalina Perdomo, Sarah Mazzilli, Yaron Geshalter, Samjot S. Dhillon, Gang Liu, Sherry Zhang, Hanqiao Liu, Jessica Vick, Christopher Moy, Stefano Monti, Evan Johnson, Matthew Meyerson, Matthew Wilkerson, Clifton Dalgard, Suso Platero, Chris Stevenson, Marc Lenburg, Mary Reid, Jennifer Beane, Avrum Spira. Genomic characterization of premalignant lung squamous cell carcinoma lesions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3248.

Somatic Superenhancer Duplications and Hotspot Mutations Lead to Oncogenic Activation of the KLF5 Transcription Factor

The Krüppel-like family of transcription factors plays critical roles in human development and is associated with cancer pathogenesis. Krüppel-like factor 5 gene (KLF5) has been shown to promote cancer cell proliferation and tumorigenesis and to be genomically amplified in cancer cells. We recently reported that the KLF5 gene is also subject to other types of somatic coding and noncoding genomic alterations in diverse cancer types. Here, we show that these alterations activate KLF5 by three distinct mechanisms: (i) Focal amplification of superenhancers activates KLF5 expression in squamous cell carcinomas; (ii) Missense mutations disrupt KLF5-FBXW7 interactions to increase KLF5 protein stability in colorectal cancer; (iii) Cancer type-specific hotspot mutations within a zinc-finger DNA binding domain of KLF5 change its DNA binding specificity and reshape cellular transcription. Utilizing data from CRISPR/Cas9 gene knockout screening, we reveal that cancer cells with KLF5 overexpression are dependent on KLF5 for their proliferation, suggesting KLF5 as a putative therapeutic target.Significance: Our observations, together with previous studies that identified oncogenic properties of KLF5, establish the importance of KLF5 activation in human cancers, delineate the varied genomic mechanisms underlying this occurrence, and nominate KLF5 as a putative target for therapeutic intervention in cancer. Cancer Discov; 8(1); 108-25. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 1.

NetSig: network-based discovery from cancer genomes

Methods that integrate molecular network information and tumor genome data could complement gene-based statistical tests to identify likely new cancer genes; but such approaches are challenging to validate at scale, and their predictive value remains unclear. We developed a robust statistic (NetSig) that integrates protein interaction networks with data from 4,742 tumor exomes. NetSig can accurately classify known driver genes in 60% of tested tumor types and predicts 62 new driver candidates. Using a quantitative experimental framework to determine in vivo tumorigenic potential in mice, we found that NetSig candidates induce tumors at rates that are comparable to those of known oncogenes and are ten-fold higher than those of random genes. By reanalyzing nine tumor-inducing NetSig candidates in 242 patients with oncogene-negative lung adenocarcinomas, we find that two (AKT2 and TFDP2) are significantly amplified. Our study presents a scalable integrated computational and experimental workflow to expand discovery from cancer genomes.

Identification of transforming growth factor-beta-regulated microRNAs and the microRNA-targetomes in primary lung fibroblasts

Background

Lung fibroblasts are involved in extracellular matrix homeostasis, which is mainly regulated by transforming growth factor-beta (TGF-β), and are therefore crucial in lung tissue repair and remodeling. Abnormal repair and remodeling has been observed in lung diseases like COPD. As miRNA levels can be influenced by TGF-β, we hypothesized that TGF-β influences miRNA expression in lung fibroblasts, thereby affecting their function.

Materials and methods

We investigated TGF-β1-induced miRNA expression changes in 9 control primary parenchymal lung fibroblasts using miRNA arrays. TGF-β1-induced miRNA expression changes were validated and replicated in an independent set of lung fibroblasts composted of 10 controls and 15 COPD patients using qRT-PCR. Ago2-immunoprecipitation followed by mRNA expression profiling was used to identify the miRNA-targetomes of unstimulated and TGF-β1-stimulated primary lung fibroblasts (n = 2). The genes affected by TGF-β1-modulated miRNAs were identified by comparing the miRNA targetomes of unstimulated and TGF-β1-stimulated fibroblasts.

Results

Twenty-nine miRNAs were significantly differentially expressed after TGF-β1 stimulation (FDR<0.05). The TGF-β1-induced miR-455-3p and miR-21-3p expression changes were validated and replicated, with in addition, lower miR-455-3p levels in COPD (p<0.05). We identified 964 and 945 genes in the miRNA-targetomes of unstimulated and TGF-β1-stimulated lung fibroblasts, respectively. The TGF-β and Wnt pathways were significantly enriched among the Ago2-IP enriched and predicted targets of miR-455-3p and miR-21-3p. The miR-455-3p target genes HN1, NGF, STRADB, DLD and ANO3 and the miR-21-3p target genes HHEX, CHORDC1 and ZBTB49 were consistently more enriched after TGF-β1 stimulation.

Conclusion

Two miRNAs, miR-455-3p and miR-21-3p, were induced by TGF-β1 in lung fibroblasts. The significant Ago2-IP enrichment of targets of these miRNAs related to the TGF-β and/or Wnt pathways (NGF, DLD, HHEX) in TGF-β1-stimulated fibroblasts suggest a role for these miRNAs in lung diseases by affecting lung fibroblast function.

Alterations in Bronchial Airway miRNA Expression for Lung Cancer Detection

We have previously shown that gene expression alterations in normal-appearing bronchial epithelial cells can serve as a lung cancer detection biomarker in smokers. Given that miRNAs regulate airway gene expression responses to smoking, we evaluated whether miRNA expression is also altered in the bronchial epithelium of smokers with lung cancer. Using epithelial brushings from the mainstem bronchus of patients undergoing bronchoscopy for suspected lung cancer (as part of the AEGIS-1/2 clinical trials), we profiled miRNA expression via small-RNA sequencing from 347 current and former smokers for which gene expression data were also available. Patients were followed for one year postbronchoscopy until a final diagnosis of lung cancer (n = 194) or benign disease (n = 153) was made. Following removal of 6 low-quality samples, we used 138 patients (AEGIS-1) as a discovery set to identify four miRNAs (miR-146a-5p, miR-324-5p, miR-223-3p, and miR-223-5p) that were downregulated in the bronchial airway of lung cancer patients (ANOVA P < 0.002, FDR < 0.2). The expression of these miRNAs is significantly more negatively correlated with the expression of their mRNA targets than with the expression of other nontarget genes (K-S P < 0.05). Furthermore, these mRNA targets are enriched among genes whose expression is elevated in cancer patients (GSEA FDR < 0.001). Finally, we found that the addition of miR-146a-5p to an existing mRNA biomarker for lung cancer significantly improves its performance (AUC) in the 203 samples (AEGIS-1/2) serving an independent test set (DeLong P < 0.05). Our findings suggest that there are miRNAs whose expression is altered in the cytologically normal bronchial epithelium of smokers with lung cancer, and that they may regulate cancer-associated gene expression differences. Cancer Prev Res; 10(11); 651-9. ©2017 AACR.

The cellular and molecular determinants of emphysematous destruction in COPD

The introduction of microCT has made it possible to show that the terminal bronchioles are narrowed and destroyed before the onset of emphysematous destruction in COPD. This report extends those observations to the cellular and molecular level in the centrilobular phenotype of emphysematous destruction in lungs donated by persons with very severe COPD (n = 4) treated by lung transplantation with unused donor lungs (n = 4) serving as controls. These lung specimens provided companion samples to those previously examined by microCT (n = 61) that we examined using quantitative histology (n = 61) and gene expression profiling (n = 48). The histological analysis showed that remodeling and destruction of the bronchiolar and alveolar tissue is associated with macrophage, CD4, CD8, and B cell infiltration with increased formation of tertiary lymphoid organs. Moreover, gene set enrichment analysis showed that genes known to be expressed by natural killer (NK), lymphoid tissue inducer (LTi), and innate lymphoid cell 1 (ILC1) cells, but not ILC2 or ILC3 cells, were enriched in the expression profiles associated with CD4, CD8, and B cell infiltration. Based on these findings, we postulate that the centrilobular phenotype of emphysematous destruction COPD is driven by a Th1 response activated by infiltrating ILC1, NK, and LTi cells.

Comparison of Prevalence and Types of Mutations in Lung Cancers Among Black and White Populations

Importance

Lung cancer is the leading cause of cancer death in the United States in all ethnic and racial groups. The overall death rate from lung cancer is higher in black patients than in white patients.

Objective

To compare the prevalence and types of somatic alterations between lung cancers from black patients and white patients. Differences in mutational frequencies could illuminate differences in prognosis and lead to the reduction of outcome disparities by more precisely targeting patients' treatment.

Design, Setting, and Participants

Tumor specimens were collected from Baptist Cancer Center (Memphis, Tennessee) over the course of 9 years (January 2004-December 2012). Genomic analysis by massively parallel sequencing of 504 cancer genes was performed at Dana-Farber Cancer Institute (Boston, Massachusetts). Overall, 509 lung cancer tumors specimens (319 adenocarcinomas; 142 squamous cell carcinomas) were profiled from 245 black patients and 264 white patients.

Main Outcomes and Measures

The frequencies of genomic alterations were compared between tumors from black and white populations.

Results

Overall, 509 lung cancers were collected and analyzed (273 women [129 black patients; 144 white patients] and 236 men [116 black patients; 120 white patients]). Using 313 adenocarcinomas and 138 squamous cell carcinomas with genetically supported ancestry, overall mutational frequencies and copy number changes were not significantly different between black and white populations in either tumor type after correcting for multiple hypothesis testing. Furthermore, specific activating alterations in members of the receptor tyrosine kinase/Ras/Raf pathway including EGFR and KRAS were not significantly different between populations in lung adenocarcinoma.

Conclusions and Relevance

These results demonstrate that lung cancers from black patients are similar to cancers from white patients with respect to clinically actionable genomic alterations and suggest that clinical trials of targeted therapies could significantly benefit patients in both groups.