Ultra High-plex Spatial Proteogenomic Investigation of Giant Cell Glioblastoma Multiforme Immune Infiltrates Reveals Distinct Protein and RNA Expression Profiles.

A deeper understanding of complex biological processes, including tumor development and immune response, requires ultra high-plex, spatial interrogation of multiple "omes". Here we present the development and implementation of a novel spatial proteogenomic (SPG) assay on the GeoMx Digital Spatial Profiler platform with next-generation sequencing readout that enables ultra high-plex digital quantitation of proteins (>100-plex) and RNA (whole transcriptome, >18,000-plex) from a single formalin-fixed paraffin-embedded (FFPE) sample. This study highlighted the high concordance, R > 0.85 and <15% change in sensitivity between the SPG assay and the single-analyte assays on various cell lines and tissues from human and mouse. Furthermore, we demonstrate that the SPG assay was reproducible across multiple users. When used in conjunction with advanced cellular neighborhood segmentation, distinct immune or tumor RNA and protein targets were spatially resolved within individual cell subpopulations in human colorectal cancer and non-small cell lung cancer. We used the SPG assay to interrogate 23 different glioblastoma multiforme (GBM) samples across four pathologies. The study revealed distinct clustering of both RNA and protein based on pathology and anatomic location. The in-depth investigation of giant cell glioblastoma multiforme (gcGBM) revealed distinct protein and RNA expression profiles compared with that of the more common GBM. More importantly, the use of spatial proteogenomics allowed simultaneous interrogation of critical protein posttranslational modifications alongside whole transcriptomic profiles within the same distinct cellular neighborhoods. Significance: We describe ultra high-plex spatial proteogenomics; profiling whole transcriptome and high-plex proteomics on a single FFPE tissue section with spatial resolution. Investigation of gcGBM versus GBM revealed distinct protein and RNA expression profiles.

High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging.

Resolving the spatial distribution of RNA and protein in tissues at subcellular resolution is a challenge in the field of spatial biology. We describe spatial molecular imaging, a system that measures RNAs and proteins in intact biological samples at subcellular resolution by performing multiple cycles of nucleic acid hybridization of fluorescent molecular barcodes. We demonstrate that spatial molecular imaging has high sensitivity (one or two copies per cell) and very low error rate (0.0092 false calls per cell) and background (~0.04 counts per cell). The imaging system generates three-dimensional, super-resolution localization of analytes at ~2 million cells per sample. Cell segmentation is morphology based using antibodies, compatible with formalin-fixed, paraffin-embedded samples. We measured multiomic data (980 RNAs and 108 proteins) at subcellular resolution in formalin-fixed, paraffin-embedded tissues (nonsmall cell lung and breast cancer) and identified >18 distinct cell types, ten unique tumor microenvironments and 100 pairwise ligand-receptor interactions. Data on >800,000 single cells and ~260 million transcripts can be accessed at http://nanostring.com/CosMx-dataset .

Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling.

Metastatic prostate cancer (mPC) comprises a spectrum of diverse phenotypes. However, the extent of inter- and intra-tumor heterogeneity is not established. Here we use digital spatial profiling (DSP) technology to quantitate transcript and protein abundance in spatially-distinct regions of mPCs. By assessing multiple discrete areas across multiple metastases, we find a high level of intra-patient homogeneity with respect to tumor phenotype. However, there are notable exceptions including tumors comprised of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastases examined are devoid of significant inflammatory infiltrates and lack PD1, PD-L1 and CTLA4, the B7-H3/CD276 immune checkpoint protein is highly expressed, particularly in mPCs with high AR activity. Our results demonstrate the utility of DSP for accurately classifying tumor phenotype, assessing tumor heterogeneity, and identifying aspects of tumor biology involving the immunological composition of metastases.

MEK activation modulates glycolysis and supports suppressive myeloid cells in TNBC.

Triple-negative breast cancers (TNBCs) are heterogeneous and aggressive, with high mortality rates. TNBCs frequently respond to chemotherapy, yet many patients develop chemoresistance. The molecular basis and roles for tumor cell-stromal crosstalk in establishing chemoresistance are complex and largely unclear. Here we report molecular studies of paired TNBC patient-derived xenografts (PDXs) established before and after the development of chemoresistance. Interestingly, the chemoresistant model acquired a distinct KRASQ61R mutation that activates K-Ras. The chemoresistant KRAS-mutant model showed gene expression and proteomic changes indicative of altered tumor cell metabolism. Specifically, KRAS-mutant PDXs exhibited increased redox ratios and decreased activation of AMPK, a protein involved in responding to metabolic homeostasis. Additionally, the chemoresistant model exhibited increased immunosuppression, including expression of CXCL1 and CXCL2, cytokines responsible for recruiting immunosuppressive leukocytes to tumors. Notably, chemoresistant KRAS-mutant tumors harbored increased numbers of granulocytic myeloid-derived suppressor cells (gMDSCs). Interestingly, previously established Ras/MAPK-associated gene expression signatures correlated with myeloid/neutrophil-recruiting CXCL1/2 expression and negatively with T cell-recruiting chemokines (CXCL9/10/11) across patients with TNBC, even in the absence of KRAS mutations. MEK inhibition induced tumor suppression in mice while reversing metabolic and immunosuppressive phenotypes, including chemokine production and gMDSC tumor recruitment in the chemoresistant KRAS-mutant tumors. These results suggest that Ras/MAPK pathway inhibitors may be effective in some breast cancer patients to reverse Ras/MAPK-driven tumor metabolism and immunosuppression, particularly in the setting of chemoresistance.

Multiplex digital spatial profiling of proteins and RNA in fixed tissue.

Digital Spatial Profiling (DSP) is a method for highly multiplex spatial profiling of proteins or RNAs suitable for use on formalin-fixed, paraffin-embedded (FFPE) samples. The approach relies on (1) multiplexed readout of proteins or RNAs using oligonucleotide tags; (2) oligonucleotide tags attached to affinity reagents (antibodies or RNA probes) through a photocleavable (PC) linker; and (3) photocleaving light projected onto the tissue sample to release PC oligonucleotides in any spatial pattern across a region of interest (ROI) covering 1 to ~5,000 cells. DSP is capable of single-cell sensitivity within an ROI using the antibody readout, with RNA detection feasible down to ~600 individual mRNA transcripts. We show spatial profiling of up to 44 proteins and 96 genes (928 RNA probes) in lymphoid, colorectal tumor and autoimmune tissues by using the nCounter system and 1,412 genes (4,998 RNA probes) by using next-generation sequencing (NGS). DSP may be used to profile not only proteins and RNAs in biobanked samples but also immune markers in patient samples, with potential prognostic and predictive potential for clinical decision-making.

Implementation of a Multiplex and Quantitative Proteomics Platform for Assessing Protein Lysates Using DNA-Barcoded Antibodies.

Molecular analysis of tumors forms the basis for personalized cancer medicine and increasingly guides patient selection for targeted therapy. Future opportunities for personalized medicine are highlighted by the measurement of protein expression levels via immunohistochemistry, protein arrays, and other approaches; however, sample type, sample quantity, batch effects, and "time to result" are limiting factors for clinical application. Here, we present a development pipeline for a novel multiplexed DNA-labeled antibody platform which digitally quantifies protein expression from lysate samples. We implemented a rigorous validation process for each antibody and show that the platform is amenable to multiple protocols covering nitrocellulose and plate-based methods. Results are highly reproducible across technical and biological replicates, and there are no observed "batch effects" which are common for most multiplex molecular assays. Tests from basal and perturbed cancer cell lines indicate that this platform is comparable to orthogonal proteomic assays such as Reverse-Phase Protein Array, and applicable to measuring the pharmacodynamic effects of clinically-relevant cancer therapeutics. Furthermore, we demonstrate the potential clinical utility of the platform with protein profiling from breast cancer patient samples to identify molecular subtypes. Together, these findings highlight the potential of this platform for enhancing our understanding of cancer biology in a clinical translation setting.

Development and verification of the PAM50-based Prosigna breast cancer gene signature assay.

BACKGROUND: The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories. METHODS: 514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies. RESULTS: The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online. CONCLUSIONS: The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

Multiplexed measurements of gene signatures in different analytes using the Nanostring nCounter Assay System.

BACKGROUND: We assessed NanoString's nCounter Analysis System for its ability to quantify gene expression of forty-eight genes in a single reaction with 100 ng of total RNA or an equivalent amount of tissue lysate. In the nCounter System, multiplexed gene expression target levels are directly detected, without enzymatic reactions, via two sequence-specific probes. The individual mRNA is captured with one mRNA target sequence-specific capture probe that is used in a post-hybridization affinity purification procedure. The second mRNA target specific-sequence and fluorescent-labeled colored coded probe is then used in the detection with the 3-component complex separated on a surface via an applied electric field followed by imaging. We evaluated reproducibility, accuracy, concordance with quantitative RT-PCR, linearity, dynamic range, and the ability of the system to assay different inputs (matched samples of total RNA from Flash Frozen (FF) and Formalin Fixed Paraffin Embedded Tissues (FFPET), and crude tissue lysates (CTL)). FINDINGS: The nCounter Analysis System provided data equivalent to that produced by Taqman(R)-based assays for genes expressed within the ranges of the calibration curves (above ~0.5 mRNA copies per human cell based on an assumption of 10 pg of total RNA per cell). System response was linear over more than two orders of magnitude with typical CVs of ~6% for concentrations above 1 fM (105 molecules per mL). Profiling the industry-standard MAQC data set yielded correlation coefficients of >0.83 for intensity values and >0.99 for measured ratios. Ninety percent of nCounter ratio measurements were within 1.27-1.33 fold changes of the Taqman(R) data (0.34-0.41 in log2 scale) for FF total RNA samples. CONCLUSION: The nCounter Analysis System generated robust data for multi-gene expression signatures across three different sample preparation conditions.

High throughput digital quantification of mRNA abundance in primary human acute myeloid leukemia samples.

Acute promyelocytic leukemia (APL) is characterized by the t(15;17) chromosomal translocation, which results in fusion of the retinoic acid receptor alpha (RARA) gene to another gene, most commonly promyelocytic leukemia (PML). The resulting fusion protein, PML-RARA, initiates APL, which is a subtype (M3) of acute myeloid leukemia (AML). In this report, we identify a gene expression signature that is specific to M3 samples; it was not found in other AML subtypes and did not simply represent the normal gene expression pattern of primary promyelocytes. To validate this signature for a large number of genes, we tested a recently developed high throughput digital technology (NanoString nCounter). Nearly all of the genes tested demonstrated highly significant concordance with our microarray data (P < 0.05). The validated gene signature reliably identified M3 samples in 2 other AML datasets, and the validated genes were substantially enriched in our mouse model of APL, but not in a cell line that inducibly expressed PML-RARA. These results demonstrate that nCounter is a highly reproducible, customizable system for mRNA quantification using limited amounts of clinical material, which provides a valuable tool for biomarker measurement in low-abundance patient samples.

A perturbation model of the gene regulatory network for oral and aboral ectoderm specification in the sea urchin embryo.

The current gene regulatory network (GRN) for the sea urchin embryo pertains to pregastrular specification functions in the endomesodermal territories. Here we extend gene regulatory network analysis to the adjacent oral and aboral ectoderm territories over the same period. A large fraction of the regulatory genes predicted by the sea urchin genome project and shown in ancillary studies to be expressed in either oral or aboral ectoderm by 24 h are included, though universally expressed and pan-ectodermal regulatory genes are in general not. The loci of expression of these genes have been determined by whole mount in situ hybridization. We have carried out a global perturbation analysis in which expression of each gene was interrupted by introduction of morpholino antisense oligonucleotide, and the effects on all other genes were measured quantitatively, both by QPCR and by a new instrumental technology (NanoString Technologies nCounter Analysis System). At its current stage the network model, built in BioTapestry, includes 22 genes encoding transcription factors, 4 genes encoding known signaling ligands, and 3 genes that are yet unknown but are predicted to perform specific roles. Evidence emerged from the analysis pointing to distinctive subcircuit features observed earlier in other parts of the GRN, including a double negative transcriptional regulatory gate, and dynamic state lockdowns by feedback interactions. While much of the regulatory apparatus is downstream of Nodal signaling, as expected from previous observations, there are also cohorts of independently activated oral and aboral ectoderm regulatory genes, and we predict yet unidentified signaling interactions between oral and aboral territories.

Direct multiplexed measurement of gene expression with color-coded probe pairs.

We describe a technology, the NanoString nCounter gene expression system, which captures and counts individual mRNA transcripts. Advantages over existing platforms include direct measurement of mRNA expression levels without enzymatic reactions or bias, sensitivity coupled with high multiplex capability, and digital readout. Experiments performed on 509 human genes yielded a replicate correlation coefficient of 0.999, a detection limit between 0.1 fM and 0.5 fM, and a linear dynamic range of over 500-fold. Comparison of the NanoString nCounter gene expression system with microarrays and TaqMan PCR demonstrated that the nCounter system is more sensitive than microarrays and similar in sensitivity to real-time PCR. Finally, a comparison of transcript levels for 21 genes across seven samples measured by the nCounter system and SYBR Green real-time PCR demonstrated similar patterns of gene expression at all transcript levels.

Discovery of novel methylation biomarkers in cervical carcinoma by global demethylation and microarray analysis.

A genome-wide screening study for identification of hypermethylated genes in invasive cervical cancer (ICC) was carried out to augment our previously discovered panel of three genes found to be useful for detection of ICC and its precursor neoplasia. Putatively hypermethylated and silenced genes were reactivated in four ICC cell lines by treatment with 5-aza-2'-deoxycytidine and trichostatin A and identified on expression microarrays. Thirty-nine of the 235 genes up-regulated in multiple ICC cell lines were further examined to determine the methylation status of associated CpG islands. The diagnostic use of 23 genes that were aberrantly methylated in multiple ICC cell lines were then analyzed in DNA from exfoliated cells obtained from patients with or without ICC. We show, for the first time, that aberrant methylation of six genes (SPARC, TFPI2, RRAD, SFRP1, MT1G, and NMES1) is present in a high proportion of ICC clinical samples but not in normal samples. Of these genes, SPARC and TFPI2 showed the highest frequency of aberrant methylation in ICC specimens (86.4% for either) and together were hypermethylated in all but one ICC cases examined. We conclude that expression profiling of epigenetically reactivated genes followed by methylation analysis in clinical samples is a powerful tool for comprehensive identification of methylation markers. Several novel genes identified in our study may be clinically useful for detection or stratification of ICC and/or of its precursor lesions and provide a basis for better understanding of mechanisms involved in development of ICC.

A portable surface plasmon resonance sensor system for real-time monitoring of small to large analytes.

Many environmental applications exist for biosensors capable of providing real-time analyses. One pressing current need is monitoring for agents of chemical- and bio-terrorism. These applications require systems that can rapidly detect small organics including nerve agents, toxic proteins, viruses, spores and whole microbes. A second area of application is monitoring for environmental pollutants. Processing of grab samples through chemical laboratories requires significant time delays in the analyses, preventing the rapid mapping and cleanup of chemical spills. The current state of development of miniaturized, integrated surface plasmon resonance (SPR) sensor elements has allowed for the development of inexpensive, portable biosensor systems capable of the simultaneous analysis of multiple analytes. Most of the detection protocols make use of antibodies immobilized on the sensor surface. The Spreeta 2000 SPR biosensor elements manufactured by Texas Instruments provide three channels for each sensor element in the system. A temperature-controlled two-element system that monitors for six analytes is currently in use, and development of an eight element sensor system capable of monitoring up to 24 different analytes will be completed in the near future. Protein toxins can be directly detected and quantified in the low picomolar range. Elimination of false positives and increased sensitivity is provided by secondary antibodies with specificity for different target epitopes, and by sensor element redundancy. Inclusion of more than a single amplification step can push the sensitivity of toxic protein detection to femtomolar levels. The same types of direct detection and amplification protocols are used to monitor for viruses and whole bacteria or spores. Special protocols are required for the detection of small molecules. Either a competition type assay where the presence of analyte inhibits the binding of antibodies to surface-immobilized analyte, or a displacement assay, where antibodies bound to analyte on the sensor surface are displaced by free analyte, can be used. The small molecule detection assays vary in sensitivity from the low micromolar range to the high picomolar.

Role of paraoxonase (PON1) status in pesticide sensitivity: genetic and temporal determinants.

Individual differences in detoxication capacities for specific organophosphorous (OP) compounds are due largely to differences in catalytic efficiency or abundance of the HDL-associated enzyme, paraoxonase (PON1). First, we provide evidence that children less than 2 years of age represent a particularly susceptible population for OP exposure due to low abundance of PON1 and variable onset of plasma PON1 activity. Second, we describe studies examining the neurotoxic effects of chronic, low-level OP pesticide exposure in mice. PON1 knockout (PON1(-/-)) and wild-type mice were exposed chronically (PN4 to PN21) to low levels of chlorpyrifos oxon (CPO). Endpoints included cholinesterase activity, histopathology, gene expression, and behavior. Even at PN4, when PON1 levels were low in wild-type mice, PON1(-/-) mice were more sensitive to inhibition of brain cholinesterase by CPO. At PN22, and persisting as long as 4 months, chronic developmental exposure to 0.18 mg/kg/d or 0.25 mg/kg/d CPO resulted in perinuclear vacuolization of cells in a discrete area of the neocortex and irregular distribution of neurons in the cortical plate, with an increase in the number of affected cells at 0.25mg/kg/d. Third, we describe a transgenic mouse model in which human transgenes encoding either hPON1Q192 or hPON1R192 were expressed at equal levels in place of mouse PON1. The developmental onset of expression followed the mouse time course and was identical for the two transgenes, allowing these mice to be used to assess the importance of the Q192R polymorphism during development. Adult mice expressing hPON1R192 were significantly more resistant than hPON1Q192 mice to CPO toxicity. Our studies indicate that children less than 2 years old, especially those homozygous for PON1Q192, would be predicted to be particularly susceptible to CPO toxicity.

Gene expression profiling of the cellular transcriptional network regulated by alpha/beta interferon and its partial attenuation by the hepatitis C virus nonstructural 5A protein.

Alpha/beta interferons (IFN-alpha/beta) induce potent antiviral and antiproliferative responses and are used to treat a wide range of human diseases, including chronic hepatitis C virus (HCV) infection. However, for reasons that remain poorly understood, many HCV isolates are resistant to IFN therapy. To better understand the nature of the cellular IFN response, we examined the effects of IFN treatment on global gene expression by using several types of human cells, including HeLa cells, liver cell lines, and primary fetal hepatocytes. In response to IFN, 50 of the approximately 4,600 genes examined were consistently induced in each of these cell types and another 60 were induced in a cell type-specific manner. A search for IFN-stimulated response elements (ISREs) in genomic DNA located upstream of IFN-stimulated genes revealed both previously identified and novel putative ISREs. To determine whether HCV can alter IFN-regulated gene expression, we performed microarray analyses on IFN-treated HeLa cells expressing the HCV nonstructural 5A (NS5A) protein and on IFN-treated Huh7 cells containing an HCV subgenomic replicon. NS5A partially blocked the IFN-mediated induction of 14 IFN-stimulated genes, an effect that may play a role in HCV resistance to IFN. This block may occur through repression of ISRE-mediated transcription, since NS5A also inhibited the IFN-mediated induction of a reporter gene driven from an ISRE-containing promoter. In contrast, the HCV replicon had very little effect on IFN-regulated gene expression. These differences highlight the importance of comparing results from multiple model systems when investigating complex phenomena such as the cellular response to IFN and viral mechanisms of IFN resistance.

Identification of novel tumor markers in hepatitis C virus-associated hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common primary cancer associated frequently with hepatitis C virus (HCV). To gain insight into the molecular mechanisms of hepatocarcinogenesis, and to identify potential HCC markers, we performed cDNA microarray analysis on surgical liver samples from 20 HCV-infected patients. RNA from individual tumors was compared with RNA isolated from adjacent nontumor tissue that was cirrhotic in all of the cases. Gene expression changes related to cirrhosis were filtered out using experiments in which pooled RNA from HCV-infected cirrhotic liver without tumors was compared with pooled RNA from normal liver. Expression of approximately 13,600 genes was analyzed using the advanced analysis tools of the Rosetta Resolver System. This analysis revealed a set of 50 potential HCC marker genes, which were up-regulated in the majority of the tumors analyzed, much more widely than common clinical markers such as cell proliferation-related genes. This HCC marker set contained several cancer-related genes, including serine/threonine kinase 15 (STK15), which has been implicated in chromosome segregation abnormalities but which has not been linked previously with liver cancer. In addition, a set of genes encoding secreted or plasma proteins was identified, including plasma glutamate carboxypeptidase (PGCP) and two secreted phospholipases A2 (PLA2G13 and PLA2G7). These genes may provide potential HCC serological markers because of their strong up-regulation in more than half of the tumors analyzed. Thus, high throughput methods coupled with high-order statistical analyses may result in the development of new diagnostic tools for liver malignancies.

Cellular gene expression upon human immunodeficiency virus type 1 infection of CD4(+)-T-cell lines.

The expression levels of approximately 4,600 cellular RNA transcripts were assessed in CD4(+)-T-cell lines at different times after infection with human immunodeficiency virus type 1 strain BRU (HIV-1(BRU)) using DNA microarrays. We found that several classes of genes were inhibited by HIV-1(BRU) infection, consistent with the G(2) arrest of HIV-1-infected cells induced by Vpr. These included genes involved in cell division and transcription, a family of DEAD-box proteins (RNA helicases), and all genes involved in translation and splicing. However, the overall level of cell activation and signaling was increased in infected cells, consistent with strong virus production. These included a subgroup of transcription factors, including EGR1 and JUN, suggesting they play a specific role in the HIV-1 life cycle. Some regulatory changes were cell line specific; however, the majority, including enzymes involved in cholesterol biosynthesis, of changes were regulated in most infected cell lines. Compendium analysis comparing gene expression profiles of our HIV-1 infection experiments to those of cells exposed to heat shock, interferon, or influenza A virus indicated that HIV-1 infection largely induced specific changes rather than simply activating stress response or cytokine response pathways. Thus, microarray analysis confirmed several known HIV-1 host cell interactions and permitted identification of specific cellular pathways not previously implicated in HIV-1 infection. Continuing analyses are expected to suggest strategies for impacting HIV-1 replication in vivo by targeting these pathways.

Cellular transcriptional profiling in influenza A virus-infected lung epithelial cells: the role of the nonstructural NS1 protein in the evasion of the host innate defense and its potential contribution to pandemic influenza.

The NS1 protein of influenza A virus contributes to viral pathogenesis, primarily by enabling the virus to disarm the host cell type IFN defense system. We examined the downstream effects of NS1 protein expression during influenza A virus infection on global cellular mRNA levels by measuring expression of over 13,000 cellular genes in response to infection with wild-type and mutant viruses in human lung epithelial cells. Influenza A/PR/8/34 virus infection resulted in a significant induction of genes involved in the IFN pathway. Deletion of the viral NS1 gene increased the number and magnitude of expression of cellular genes implicated in the IFN, NF-kappaB, and other antiviral pathways. Interestingly, different IFN-induced genes showed different sensitivities to NS1-mediated inhibition of their expression. A recombinant virus with a C-terminal deletion in its NS1 gene induced an intermediate cellular mRNA expression pattern between wild-type and NS1 knockout viruses. Most significantly, a virus containing the 1918 pandemic NS1 gene was more efficient at blocking the expression of IFN-regulated genes than its parental influenza A/WSN/33 virus. Taken together, our results suggest that the cellular response to influenza A virus infection in human lung cells is significantly influenced by the sequence of the NS1 gene, demonstrating the importance of the NS1 protein in regulating the host cell response triggered by virus infection.