Biology subjects

Minna, J. D.

Publications and source records attributed to Minna, J. D..

5 recordsLinked to original sources

bioRxiv2020

Lineage transcription factors co-regulate subtype-specific genes providing a roadmap for systematic identification of small cell lung cancer vulnerabilities

Lineage-defining transcription factors (LTFs) play key roles in tumor cell growth, making them highly attractive, but currently "undruggable", small cell lung cancer (SCLC) vulnerabilities. Delineating LTF genomic binding sites and associated chromatin features would provide important insights into SCLC dependencies. Here we map super-enhancers (SEs) across multiple patient-derived SCLC preclinical models, and find SE patterns are sufficient to classify the models into the recently defined, LTF-based, SCLC subtypes. 3D-chromatin conformation analysis identified genes associated with SEs that define subtype-specific tumor signatures with genes functioning in diverse processes. Focusing on ASCL1-high SCLC (SCLC-A), we found ASCL1 physically interacts with NKX2-1 and PROX1. These factors bind overlapping genomic regions, and co-regulate a set of genes, including genes encoding cell surface proteins, SCN3A and KCNB2 enriched in SCLC-A. Genetic depletion of NKX2-1 or PROX1 alone, or in combinations with ASCL1, did not inhibit SCLC growth more than that achieved by depleting ASCL1 alone. We demonstrate the SE signature supports the LTF classification of SCLC, identify NKX2-1 and PROX1 as ASCL1 co-factors, and substantiate the central importance of ASCL1 as a key dependency factor in the majority of SCLC. The LTF and SE gene sets provide a molecular roadmap for future ASCL1 therapeutic targeting studies.

cancer biology↗

bioRxiv2020

Relationship Between Neuroendocrine and Immune Gene Expression in Small Cell Lung Cancer

Small cell lung cancer (SCLC) is classified as a high-grade neuroendocrine (NE) tumor, but a subset of SCLC has been termed "variant" due to the loss of NE characteristics. In this study, we computed NE scores for patient-derived SCLC cell lines and xenografts, as well as human tumors. We aligned NE properties with transcription factor-defined molecular subtypes. Then we investigated the different immune phenotypes associated with high and low NE scores. We found repression of immune response genes as a shared feature between classic SCLC and pulmonary neuroendocrine cells of the healthy lung. With loss of NE fate, variant SCLC tumors regain cell-autonomous immune gene expression and exhibit higher tumor-immune interactions. Pan-cancer analysis revealed this NE lineage-specific immune phenotype in other cancers. Additionally, we observed MHC I re-expression in SCLC upon development of chemoresistance. These findings provide a new framework to guide design of treatment regimens in SCLC.

cancer biology↗

bioRxiv2020

SARS-CoV-2 infection induces EMT-like molecular changes, including ZEB1-mediated repression of the viral receptor ACE2, in lung cancer models

COVID-19 is an infectious disease caused by SARS-CoV-2, which enters host cells via the cell surface proteins ACE2 and TMPRSS2. Using a variety of normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2. We find that ACE2 expression is restricted to a select population of highly epithelial cells. Notably, infection with SARS-CoV-2 in cancer cell lines, bronchial organoids, and patient nasal epithelium, induces metabolic and transcriptional changes consistent with epithelial to mesenchymal transition (EMT), including upregulation of ZEB1 and AXL, resulting in an increased EMT score. Additionally, a transcriptional loss of genes associated with tight junction function occurs with SARS-CoV-2 infection. The SARS-CoV-2 receptor, ACE2, is repressed by EMT via TGFbeta, ZEB1 overexpression and onset of EGFR TKI inhibitor resistance. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state, associated with a loss of tight junction components with acute respiratory distress syndrome-protective effects. AXL-inhibition and ZEB1-reduction, as with bemcentinib, offers a potential strategy to reverse this effect. These observations highlight the utility of aerodigestive and, especially, lung cancer model systems in exploring the pathogenesis of SARS-CoV-2 and other respiratory viruses, and offer important insights into the potential mechanisms underlying the morbidity and mortality of COVID-19 in healthy patients and cancer patients alike.

cancer biology↗

bioRxiv2020

Single-cell analysis of human lung epithelia reveals concomitant expression of the SARS-CoV-2 receptor ACE2 with multiple virus receptors and scavengers in alveolar type II cells

The novel coronavirus SARS-CoV-2 was identified as the causative agent of the ongoing pandemic COVID 19. COVID-19-associated deaths are mainly attributed to severe pneumonia and respiratory failure. Recent work demonstrated that SARS-CoV-2 binds to angiotensin converting enzyme 2 (ACE2) in the lung. To better understand ACE2 abundance and expression patterns in the lung we interrogated our in-house single-cell RNA-sequencing dataset containing 70,085 EPCAM+ lung epithelial cells from paired normal and lung adenocarcinoma tissues. Transcriptomic analysis revealed a diverse repertoire of airway lineages that included alveolar type I and II, bronchioalveolar, club/secretory, quiescent and proliferating basal, ciliated and malignant cells as well as rare populations such as ionocytes. While the fraction of lung epithelial cells expressing ACE2 was low (1.7% overall), alveolar type II (AT2, 2.2% ACE2+) cells exhibited highest levels of ACE2 expression among all cell subsets. Further analysis of the AT2 compartment (n = 27,235 cells) revealed a number of genes co-expressed with ACE2 that are important for lung pathobiology including those associated with chronic obstructive pulmonary disease (COPD; HHIP), pneumonia and infection (FGG and C4BPA) as well as malarial/bacterial (CD36) and viral (DMBT1) scavenging which, for the most part, were increased in smoker versus light or non-smoker cells. Notably, DMBT1 was highly expressed in AT2 cells relative to other lung epithelial subsets and its expression positively correlated with ACE2. We describe a population of ACE2-positive AT2 cells that co-express pathogen (including viral) receptors (e.g. DMBT1) with crucial roles in host defense thus comprising plausible phenotypic targets for treatment of COVID-19.

genomics↗

bioRxiv2020

SCLC_CellMiner: Integrated Genomics and Therapeutics Predictors of Small Cell Lung Cancer Cell Lines based on their genomic signatures

Model systems are necessary to understand the biology of SCLC and develop new therapies against this recalcitrant disease. Here we provide the first online resource, CellMiner-SCLC (https://discover.nci.nih.gov/SclcCellMinerCDB) incorporating 118 individual SCLC cell lines and extensive omics and drug sensitivity datasets, including high resolution methylome performed for the purpose of the current study. We demonstrate the reproducibility of the cell lines and genomic data across the CCLE, GDSC, CTRP, NCI and UTSW datasets. We validate the SCLC classification based on four master transcription factors: NEUROD1, ASCL1, POU2F3 and YAP1 (NAPY classification) and show transcription networks connecting each them with their downstream and upstream regulators as well as with the NOTCH and HIPPO pathways and the MYC genes (MYC, MYCL1 and MYCN). We find that each of the 4 subsets express specific surface markers for antibody-targeted therapies. The SCLC-Y cell lines differ from the other subsets by expressing the NOTCH pathway and the antigen-presenting machinery (APM), and responding to mTOR and AKT inhibitors. Our analyses suggest the potential value of NOTCH activators, YAP1 inhibitors and immune checkpoint inhibitors in SCLC-Y tumors that can now be independently validated. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/980623v2_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@10930e7org.highwire.dtl.DTLVardef@699d9corg.highwire.dtl.DTLVardef@1ea773corg.highwire.dtl.DTLVardef@3a1589_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LISCLC-CellMiner provides the most extensive SCLC resource in terms of number of cell lines (118 cell lines), extensive omics data (exome, microarray, RNA-seq, copy number, methylomes and microRNA) and drug sensitivity testing. C_LIO_LIWe find evidence of distinct epigenetic profile of SCLC cell lines (global hypomethylation and histone gene methylation), which is consistent with their plasticity. C_LIO_LITranscriptome analyses demonstrate the coherent transcriptional networks associated with the 4 main genomic subgroups (NEUROD1, ASCL1, POU2F3 & YAP1 = NAPY classification) and their connection with the NOTCH and HIPPO signaling pathways. C_LIO_LISCLC-CellMiner provides a conceptual framework for the selection of therapies for SCLC in a personalized fashion allowing putative biomarkers according molecular classifications and molecular characteristics. C_LIO_LISCLC-Y cell lines differ from the other cancer cell lines; their transcriptome resemble NSCLC cell lines. YAP1 cell lines while being the most resistant to standard of care treatments (etoposide, cisplatin and topotecan) respond to mTOR and AKT inhibitors and present native immune predisposition suggesting sensitivity to immune checkpoint inhibitors. C_LI

cancer biology↗