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Burks, E. J.

Publications and source records attributed to Burks, E. J..

8 recordsLinked to original sources

Clinical feasibility of spatial transcriptomics using discarded tissue from diagnostic breast biopsies

Spatial transcriptomics holds potential to transform cancer diagnostics, yet significant barriers still limit its clinical translation. First, access to primary patient tissue is often restricted by logistical challenges and patient hesitancy. Second, it remains uncertain whether high-quality spatial transcriptomics data can be generated from clinical biopsy sections as these are collected primarily for diagnostic purposes that do not prioritize RNA-quality. We investigated whether discarded tissue slices, generated during standard pathology procedures, could be repurposed for spatial transcriptomics and alleviate concerns about both tissue availability and quality. Here, we established a pipeline to collect and perform spatial in situ transcriptomics on discarded biopsy material from a breast cancer patient, and digitized matched pathology images, including hematoxylin and eosin and traditional histochemistry stains from adjacent sections. Our results show that spatial transcriptomics data from discarded tissue are concordant with the original pathology report, while also providing additional insights such as accurate cell type annotation, detailed spatial architecture, and quantification of biological processes relevant to breast cancer progression. Altogether, our approach using discarded pathology tissue sections provides a practical and scalable solution that would maximize the scientific value of existing clinical specimens and enable high-resolution tumor microenvironment mapping.

genomics↗

Archetype analysis of lung adenocarcinoma premalignancy links heterogeneity in premalignant lesions to diverging features of invasive disease

ABSTRACTLung adenocarcinoma (LUAD), the most common form of lung cancer, is a heterogeneous disease with highly variable histopathologic features and clinical outcomes. LUAD premalignant lesions (PMLs) are localized proliferative lesions of atypical pneumocytes that proliferate along the alveolar walls. In this study, we characterized the molecular heterogeneity across PMLs, regardless of histologic designation, and identified four unique groups or "archetypes" of PMLs using bulk RNA and exome sequencing data from laser captured microdissected PMLs, normal, and tumor tissue from LUAD resection cases. The archetypes were defined based on expression of recurrent gene co-expression modules discovered using the LUAD PMLs we profiled and three publicly available datasets. One PML archetype, termed "proliferation", was associated with increased expression of genes involved in cell proliferation, a pro-tumor immune environment, and enrichment for EGFR driver mutations. Another archetype, termed "normal-like", was associated with similar features to normal tissue, an anti-tumor immune response, and lacked enrichment for driver mutations compared to other archetypes. We projected the PML archetypes into independent gene expression datasets profiling LUAD and found that tumors closest to the proliferation archetype were enriched for multiple features of aggressive LUAD, including high tumor grade and lymph node invasion, and had significantly lower disease-free survival. Proliferation archetype PMLs may represent a subset of lesions with more aggressive features that could improve patient stratification and suggest novel targets for lung cancer interception.

cancer biology↗

Epithelial miR-149-5p up-regulation is associated with immune evasion in progressive bronchial premalignant lesions

The molecular drivers bronchial premalignant lesion progression to invasive lung squamous cell carcinoma are not well defined. Prior work profiling longitudinally collected bronchial premalignant lesion biopsies by RNA sequencing defined a proliferative subtype, enriched with bronchial dysplasia. We found that a gene co-expression module associated with interferon gamma signaling and antigen processing/presentation was down-regulated in progressive/persistent versus regressive lesions within the proliferative subtype, suggesting a functional impact of these genes on immune evasion. RNA from these same premalignant lesions was profiled by microRNA (miRNA) sequencing and a miRNA-gene network analysis identified hsa-miR-149-5p as a potential regulator of this antigen presentation gene co-expression module associated with lesion progression. hsa-miR-149-5p was found to be predominantly expressed in the epithelium and up-regulated in progressive/persistent versus regressive proliferative lesions while targets of this miRNA, the transcriptional coactivator of MHC-I gene expression, NLRC5, and the genes it regulates were down-regulated. MicroRNA in situ hybridization of hsa-miR-149-5p in tissue from adjacent fixed biopsies showed that hsa-miR-149-5p was increased in areas of bronchial dysplasia in progressive/persistent versus regressive lesions. Imaging mass cytometry showed that NLRC5 protein expression was decreased in progressive/persistent versus regressive lesions within areas of hyperplasia, metaplasia, and dysplasia. Additionally, basal cells with high versus low levels of NLRC5 were found to be in close spatial proximity to CD8 T cells, suggesting that these cells exhibit increased functional MHC-I gene expression in lesions with low hsa-miR-149-5p expression. Collectively, our data suggests a functional role for hsa-miR-149-5p in bronchial premalignant lesions and may serve as a therapeutic target for PML immunomodulation. STATEMENT OF SIGNIFICANCEIntegrative analysis across bronchial premalignant lesions has identified and localized a potential regulator of immune evasion in progressive/persistent lesions that could be a novel therapeutic target.

cancer biology↗

Tryptophan metabolism reprogramming contributes to the prothrombotic milieu in mice and humans infected with SARS-CoV-2

SARS-CoV-2 infection disturbs the coagulation balance in the blood, triggering thrombosis and contributing to organ failure. The role of prothrombotic metabolites in COVID-19-associated coagulopathy remains elusive. Leveraging K18-hACE2 mice infected with SARS-CoV-2, we observed higher levels of the tryptophan metabolite, kynurenine, compared to controls. SARS-CoV-2 infected mice showed a significant upregulation of enzymes controlling Kynurenine biogenesis, such as indoleamine 2,3-dioxygenase (IDO-1) and tryptophan 2,3-dioxygenase levels in kidneys and liver, respectively, as well as changes in the enzymes involved in kynurenine catabolism, including kynurenine monooxygenase and kynurinase. Consistent with the agonistic role of these metabolites in Aryl Hydrocarbon Receptor (AHR) signaling, AHR activation and its downstream mediator, tissue factor (TF), a highly potent procoagulant factor, was observed in endothelial cells (ECs) of lungs and kidneys of infected mice. These findings were validated in humans, where compared to controls, sera of COVID-19 patients showed increased levels of Kynurenine, kynurenic acid, anthranilic acid, and quinolinic acid. Activation of the AHR-TF axis was noted in the kidneys and lungs of COVID-19 patients, and COVID-19 sera showed higher IDO-1 activity than controls. Levels of Kyn in COVID-19 patients correlated strongly with the TF-inducing activity of COVID-19 sera on ECs. A specific IDO-1 inhibitor or AHR inhibitor separately or in combination suppressed COVID-19 sera-induced TF activity in ECs. Together, we identified IDO-1 as upregulated by SARS-CoV-2 infection, resulting in augmented Kyn and its prothrombotic catabolites, thereby suggesting the Kyn-AHR-TF axis as possibly a new diagnostic and/or therapeutic target. Key pointsO_LISARS-CoV-2-infection upregulates kynurenine biogenesis in the liver and diminishes kynurenine catabolism in the lungs and kidneys. C_LIO_LIAn increase in kynurenine stimulates the AHR-TF axis in the microvasculature in COVID-19 patients, which is inhibited by pharmacological manipulation. C_LI

systems biology↗

Identification of a gene expression signature of vascular invasion and recurrence in stage I lung adenocarcinoma via bulk and spatial transcriptomics

Microscopic vascular invasion (VI) is predictive of recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but is difficult to assess in resection specimens and cannot be accurately predicted prior to surgery. Thus, new biomarkers are needed to identify this aggressive subset of stage I LUAD tumors. To assess molecular and microenvironment features associated with angioinvasive LUAD we profiled 162 resected stage I tumors with and without VI by RNA-seq and explored spatial patterns of gene expression in a subset of 15 samples by high-resolution spatial transcriptomics (stRNA-seq). Despite the small size of invaded blood vessels, we identified a gene expression signature of VI from the bulk RNA-seq discovery cohort (n=103) and found that it was associated with VI foci, desmoplastic stroma, and high-grade patterns in our stRNA-seq data. We observed a stronger association with high-grade patterns from VI+ compared with VI- tumors. Using the discovery cohort, we developed a transcriptomic predictor of VI, that in an independent validation cohort (n=60) was associated with VI (AUROC=0.86; p=5.42x10-6) and predictive of recurrence-free survival (HR=1.98; p=0.024), even in VI- LUAD (HR=2.76; p=0.003). To determine our VI predictors robustness to intra-tumor heterogeneity we used RNA-seq data from multi-region sampling of stage I LUAD cases in TRACERx, where the predictor scores showed high correlation (R=0.87, p<2.2x10-16) between two randomly sampled regions of the same tumor. Our study suggests that VI-associated gene expression changes are detectable beyond the site of intravasation and can be used to predict the presence of VI. This may enable the prediction of angioinvasive LUAD from biopsy specimens, allowing for more tailored medical and surgical management of stage I LUAD.

cancer biology↗

Graph attention-based fusion of pathology images and gene expression for prediction of cancer survival

Multimodal machine learning models are being developed to analyze pathology images and other modalities, such as gene expression, to gain clinical and biological in-sights. However, most frameworks for multimodal data fusion do not fully account for the interactions between different modalities. Here, we present an attention-based fusion architecture that integrates a graph representation of pathology images with gene expression data and concomitantly learns from the fused information to predict patient-specific survival. In our approach, pathology images are represented as undirected graphs, and their embeddings are combined with embeddings of gene expression signatures using an attention mechanism to stratify tumors by patient survival. We show that our framework improves the survival prediction of human non-small cell lung cancers, out-performing existing state-of-the-art approaches that lever-age multimodal data. Our framework can facilitate spatial molecular profiling to identify tumor heterogeneity using pathology images and gene expression data, complementing results obtained from more expensive spatial transcriptomic and proteomic technologies.

bioinformatics↗

Graph perceiver network for lung tumor and premalignant lesion stratification from histopathology

Bronchial premalignant lesions (PMLs) precede the development of invasive lung squamous carcinoma (LUSC), posing a significant challenge in distinguishing those likely to advance to LUSC from those that might regress without intervention. In this context, we present a novel computational approach, the Graph Perceiver Network (GRAPE-Net), leveraging hematoxylin and eosin (H&E) stained whole slide images (WSIs) to stratify endobronchial biopsies of PMLs across a spectrum from normal to tumor lung tissues. GRAPE-Net outperforms existing frameworks in classification accuracy predicting LUSC, lung adenocarcinoma (LUAD), and non-tumor (normal) lung tissue on The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC) datasets containing lung resection tissues while efficiently generating pathologist-aligned, class-specific heatmaps. The network was further tested using endobronchial biopsies from two data cohorts, containing normal to carcinoma in situ histology, and it demonstrated a unique capability to differentiate carcinoma in situ lung squamous PMLs based on their progression status to invasive carcinoma. The network may have utility in stratifying PMLs for chemoprevention trials or more aggressive follow-up.

pathology↗

SARS-CoV-2 Infection of Pluripotent Stem Cell-derived Human Lung Alveolar Type 2 Cells Elicits a Rapid Epithelial-Intrinsic Inflammatory Response

The most severe and fatal infections with SARS-CoV-2 result in the acute respiratory distress syndrome, a clinical phenotype of coronavirus disease 2019 (COVID-19) that is associated with virions targeting the epithelium of the distal lung, particularly the facultative progenitors of this tissue, alveolar epithelial type 2 cells (AT2s). Little is known about the initial responses of human lung alveoli to SARS-CoV-2 infection due in part to inability to access these cells from patients, particularly at early stages of disease. Here we present an in vitro human model that simulates the initial apical infection of the distal lung epithelium with SARS-CoV-2, using AT2s that have been adapted to air-liquid interface culture after their derivation from induced pluripotent stem cells (iAT2s). We find that SARS-CoV-2 induces a rapid global transcriptomic change in infected iAT2s characterized by a shift to an inflammatory phenotype predominated by the secretion of cytokines encoded by NF-kB target genes, delayed epithelial interferon responses, and rapid loss of the mature lung alveolar epithelial program. Over time, infected iAT2s exhibit cellular toxicity that can result in the death of these key alveolar facultative progenitors, as is observed in vivo in COVID-19 lung autopsies. Importantly, drug testing using iAT2s confirmed an antiviral dose-response to remdesivir and demonstrated the efficacy of TMPRSS2 protease inhibition, validating a putative mechanism used for viral entry in human alveolar cells. Our model system reveals the cell-intrinsic responses of a key lung target cell to infection, providing a physiologically relevant platform for further drug development and facilitating a deeper understanding of COVID-19 pathogenesis.

molecular biology↗