Inadequate oxygen (hypoxia) triggers a multifaceted cellular response that has important roles in normal physiology and in many human diseases. A transcription factor, hypoxia-inducible factor (HIF), plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1α protein. Despite the ubiquity and importance of hypoxia responses, little is known about the variation in the global transcriptional response to hypoxia among different cell types or how this variation might relate to tissue- and cell-specific diseases. We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells, breast epithelial cells, smooth muscle cells, and endothelial cells with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This heightened response was associated with a uniquely high level of HIF-1α RNA in renal cells, and it could be diminished by reducing HIF-1α expression via RNA interference. A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. The transcriptional response to hypoxia varies among human cells. Some of this variation is traceable to variation in expression of the HIF1A gene. A gene-expression signature of the cellular response to hypoxia is associated with a significantly poorer prognosis in breast and ovarian cancer.
Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic (n = 60) and transcriptomic (n = 69) analysis of 75 LCNECs and identify two molecular subgroups: “type I LCNECs” with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and “type II LCNECs” enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh, and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.
Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death in the world. Immunological analysis of the tumor microenvironment (immunoscore) shows great promise for improved prognosis and prediction of response to immunotherapy. However, the exact immune cell composition in NSCLC remains unclear. Here, we used flow cytometry to characterize the immune infiltrate in NSCLC tumors, non-cancerous lung tissue, regional lymph node, and blood. The cellular identity of >95% of all CD45+ immune cells was determined. Thirteen distinct immune cell types were identified in NSCLC tumors. T cells dominated the lung cancer landscape (on average 47% of all CD45+ immune cells). CD4+ T cells were the most abundant T cell population (26%), closely followed by CD8+ T cells (22%). Double negative CD4−CD8− T cells represented a small fraction (1.4%). CD19+ B cells were the second most common immune cell type in NSCLC tumors (16%), and four different B cell sub-populations were identified. Macrophages and natural killer (NK) cells composed 4.7 and 4.5% of the immune cell infiltrate, respectively. Three types of dendritic cells (DCs) were identified (plasmacytoid DCs, CD1c+ DCs, and CD141+ DCs) which together represented 2.1% of all immune cells. Among granulocytes, neutrophils were frequent (8.6%) with a high patient-to-patient variability, while mast cells (1.4%), basophils (0.4%), and eosinophils (0.3%) were less common. Across the cohort of patients, only B cells showed a significantly higher representation in NSCLC tumors compared to the distal lung. In contrast, the percentages of macrophages and NK cells were lower in tumors than in non-cancerous lung tissue. Furthermore, the fraction of macrophages with high HLA-DR expression levels was higher in NSCLC tumors relative to distal lung tissue. To make the method readily accessible, antibody panels and flow cytometry gating strategy used to identify the various immune cells are described in detail. This work should represent a useful resource for the immunomonitoring of patients with NSCLC.