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Summary Background Data on patients with COVID-19 who have cancer are lacking. Here we characterise the outcomes of a cohort of patients with cancer and COVID-19 and identify potential prognostic factors for mortality and severe illness. Methods In this cohort study, we collected de-identified data on patients with active or previous malignancy, aged 18 years and older, with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from the USA, Canada, and Spain from the COVID-19 and Cancer Consortium (CCC19) database for whom baseline data were added between March 17 and April 16, 2020. We collected data on baseline clinical conditions, medications, cancer diagnosis and treatment, and COVID-19 disease course. The primary endpoint was all-cause mortality within 30 days of diagnosis of COVID-19. We assessed the association between the outcome and potential prognostic variables using logistic regression analyses, partially adjusted for age, sex, smoking status, and obesity. This study is registered with ClinicalTrials.gov, NCT04354701, and is ongoing. Findings Of 1035 records entered into the CCC19 database during the study period, 928 patients met inclusion criteria for our analysis. Median age was 66 years (IQR 57–76), 279 (30%) were aged 75 years or older, and 468 (50%) patients were male. The most prevalent malignancies were breast (191 [21%]) and prostate (152 [16%]). 366 (39%) patients were on active anticancer treatment, and 396 (43%) had active (measurable) cancer. At analysis (May 7, 2020), 121 (13%) patients had died. In logistic regression analysis, independent factors associated with increased 30-day mortality, after partial adjustment, were: increased age (per 10 years; partially adjusted odds ratio 1·84, 95% CI 1·53–2·21), male sex (1·63, 1·07–2·48), smoking status (former smoker vs never smoked: 1·60, 1·03–2·47), number of comorbidities (two vs none: 4·50, 1·33–15·28), Eastern Cooperative Oncology Group performance status of 2 or higher (status of 2 vs 0 or 1: 3·89, 2·11–7·18), active cancer (progressing vs remission: 5·20, 2·77–9·77), and receipt of azithromycin plus hydroxychloroquine (vs treatment with neither: 2·93, 1·79–4·79; confounding by indication cannot be excluded). Compared with residence in the US-Northeast, residence in Canada (0·24, 0·07–0·84) or the US-Midwest (0·50, 0·28–0·90) were associated with decreased 30-day all-cause mortality. Race and ethnicity, obesity status, cancer type, type of anticancer therapy, and recent surgery were not associated with mortality. Interpretation Among patients with cancer and COVID-19, 30-day all-cause mortality was high and associated with general risk factors and risk factors unique to patients with cancer. Longer follow-up is needed to better understand the effect of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments. Funding American Cancer Society, National Institutes of Health, and Hope Foundation for Cancer Research.

Toll-like receptors 7 and 8 (TLR7 and TLR8) are endosomal pattern recognition receptors that detect a variety of single-stranded RNA species. While TLR7/8 agonists have robust therapeutic potential, clinical utility of these agents is limited by sickness responses associated with treatment induction. To understand the kinetics and mechanism of these responses, we characterized the acute and chronic effects of TLR7 stimulation. Single-cell RNA-sequencing studies, RNAscope, and radiolabeled in situ hybridization demonstrate that central nervous system gene expression of TLR7 is exclusive to microglia. In vitro studies demonstrate that microglia are highly sensitive to TLR7 stimulation, and respond in a dose-dependent manner to the imidazoquinoline R848. In vivo, both intraperitoneal (IP) and intracerebroventricular (ICV) R848 induce acute sickness responses including hypophagia, weight loss, and decreased voluntary locomotor activity, associated with increased CNS pro-inflammatory gene expression and changes to glial morphology. However, chronic daily IP R848 resulted in rapid tachyphylaxis of behavioral and molecular manifestations of illness. In microglial in vitro assays, pro-inflammatory transcriptional responses rapidly diminished in the context of repeated R848. In addition to TLR7 desensitization, we found that microglia become partially refractory to lipopolysaccharide (LPS) following R848 pretreatment, associated with induction of negative regulators A20 and Irak3. Similarly, mice pre-treated with R848 demonstrate reduced sickness responses, hypothalamic inflammation, and hepatic inflammation in response to LPS. These data combined demonstrate that TLR7 stimulation induces acute behavioral and molecular evidence of sickness responses. Following prolonged dosing, R848 induces a refractory state to both TLR7 and TLR4 activation, consistent with induced immune tolerance.

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.

Our study details the stepwise evolution of gilteritinib resistance in FLT3-mutated acute myeloid leukemia (AML). Early resistance is mediated by the bone marrow microenvironment, which protects residual leukemia cells. Removing these supportive extrinsic ligands drives evolution of late, intrinsic resistance. Whole exome sequencing, CRISPR/Cas, metabolomics, proteomics, and pharmacologic approaches were used to mechanistically define both early and late resistance. Early resistant cells undergo metabolic reprogramming, grow more slowly, and are dependent upon Aurora kinase B (AURKB). Late resistant cells are characterized byexpansion of pre-existing NRAS mutant subclones and continued metabolic reprogramming. Our model closely mirrors the timing and mutations of AML patients treated with gilteritinib.Pharmacological inhibition of AURKB resensitized both early resistant cell cultures and primary leukemia cells from gilteritinib-treated AML patients. These findings support a combinatorial strategy to target early resistant AML cells with AURKB inhibitors and gilteritinib before the expansion of pre-existing resistance mutations occurs.

When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments.

This review summarizes the proceedings of a symposium presented at the "Alcoholism and Stress: A Framework for Future Treatment Strategies" conference held in Volterra, Italy on May 9-12, 2017. Psychiatric diseases, including alcohol-use disorders (AUDs), are influenced through complex interactions of genes, neurobiological pathways, and environmental influences. A better understanding of the common neurobiological mechanisms underlying an AUD necessitates an integrative approach, involving a systematic assessment of diverse species and phenotype measures. As part of the World Congress on Stress and Alcoholism, this symposium provided a detailed account of current strategies to identify mechanisms underlying the development and progression of AUDs. Dr. Sean Farris discussed the integration and organization of transcriptome and postmortem human brain data to identify brain regional- and cell type-specific differences related to excessive alcohol consumption that are conserved across species. Dr. Brien Riley presented the results of a genome-wide association study of DSM-IV alcohol dependence; although replication of genetic associations with alcohol phenotypes in humans remains challenging, model organism studies show that COL6A3, KLF12, and RYR3 affect behavioral responses to ethanol, and provide substantial evidence for their role in human alcohol-related traits. Dr. Rob Williams expanded upon the systematic characterization of extensive genetic-genomic resources for quantifying and clarifying phenotypes across species that are relevant to precision medicine in human disease. The symposium concluded with Dr. Robert Hitzemann's description of transcriptome studies in a mouse model selectively bred for high alcohol ("binge-like") consumption and a non-human primate model of long-term alcohol consumption. Together, the different components of this session provided an overview of systems-based approaches that are pioneering the experimental prioritization and validation of novel genes and gene networks linked with a range of behavioral phenotypes associated with stress and AUDs.

Objective Understanding the role of endophenotypes is essential for process models of psychopathology. This study examined which candidate cognitive endophenotypes statistically mediate common variant genetic risk for attention-deficit/hyperactivity disorder (ADHD). Method A case-control design using community-recruited volunteer children 7 to 11 years of age (n = 656, n = 435 ADHD), of whom 514 were of homogenous European ancestry for the primary models (n = 337 ADHD, 177 non-ADHD). Children were assessed with a multi-informant, best-estimate diagnostic procedure and laboratory measures of working memory, response inhibition, executive functioning, arousal/attention, temporal information processing, and processing speed. Latent variables were created for the candidate cognitive measures and for parent- and teacher-rated ADHD dimensions. Polygenic risk scores (PGS) were computed using a discovery sample of 20,183 individuals with ADHD and 35,191 controls from the Psychiatric Genetics Consortium. Cognitive measures that survived multiple testing correction for association with the PGS were evaluated for mediation with ADHD using structural equation models. Results Results were essentially identical in the homogeneous European ancestry subgroup (n = 514) and in the full sample (N = 656). For the European population, the PGS was associated with ADHD diagnosis (Nagelkerke R2 = 0.045; β = 0.233, SE = 0.053, p = .000011) and multi-indicator dimensional ADHD latent variables by parent report (β = 0.185, SE = 0.043) and teacher report (β = 0.165, SE = 0.042). The PGS effect was statistically mediated by working memory (indirect effect, β = 0.101, SE = 0.029, 95% CI = 0.05, 0.16, p = .00049, 43% of genetic effect accounted for) and arousal/alertness (indirect effect β = 0.115, 95% CI = 0.04, 0.20, SE = 0.041, p = .005, 49% of genetic effect accounted for). Conclusion This is the first clear demonstration from molecular genetic data that working memory and arousal regulation are promising cognitive endophenotypes for ADHD with regard to mediating genetic risk from common genetic variants.

A hallmark of the development of cancer is its ability to avoid detection and elimination by the immune system. There are many identified mechanisms of this immune evasion that can be measured both phenotypically and functionally. Functional studies directly show the ability of the tumor microenvironment to suppress immune responses, typically measured as lymphocyte proliferation, cytokine production or killing ability. While a direct measurement of function is ideal, these assays require ex vivo activation which may not accurately mimic in vivo conditions. Phenotypic assays can directly measure the distribution and activation of immune cell types rapidly after isolation, preserving the conditions present in the patient. While conventional flow cytometry is a rapid and well established assay, it currently allows for measurement of only 12-14 parameters. Mass spectrometry-based flow cytometry, or CyTOF, offers the ability to measure 3-fold more parameters than conventional optical-based modalities providing an advantage in depth of analysis that can be crucial for precious human samples. The goal of this report is to describe the system our group has developed to measure both the phenotype and function of immune cells in the bone marrow of patients with acute myeloid leukemia. We hope to explain our system in the context of previous studies aimed at measuring immune status in tumors and to inform the reader as to some experimental approaches our group has found useful in developing the basic data required to rationally pursue immune-based therapies for patients with cancer.

Secreted proteins in the bone marrow microenvironment play critical roles in acute myeloid leukemia (AML). Through an ex vivo functional screen of 94 cytokines, we identified that the pro-inflammatory cytokine interleukin-1 (IL-1) elicited profound expansion of myeloid progenitors in ∼67% of AML patients while suppressing the growth of normal progenitors. Levels of IL-1β and IL-1 receptors were increased in AML patients, and silencing of the IL-1 receptor led to significant suppression of clonogenicity and in vivo disease progression. IL-1 promoted AML cell growth by enhancing p38MAPK phosphorylation and promoting secretion of various other growth factors and inflammatory cytokines. Treatment with p38MAPK inhibitors reversed these effects and recovered normal CD34+ cells from IL-1-mediated growth suppression. These results highlight the importance of ex vivo functional screening to identify common and actionable extrinsic pathways in genetically heterogeneous malignancies and provide impetus for clinical development of IL-1/IL1R1/p38MAPK pathway-targeted therapies in AML.

Leucine-rich repeat kinase 2 (LRRK2) mutations are the most common genetic cause of late-onset autosomal dominant Parkinson’s disease. The pathogenic G2019S mutation enhances LRRK2 kinase activity and induces neurodegeneration in C. elegans, Drosophila and rodent models through unclear mechanisms. Gene expression profiling has the potential to provide detailed insight into the biological pathways modulated by LRRK2 kinase activity in vivo. Prior studies have surveyed the effects of LRRK2 G2019S on genome-wide mRNA expression in complex brain tissues with high cellular heterogeneity, limiting their power to detect more restricted gene expression changes occurring in a cell type-specific manner. Here, we used translating ribosome affinity purification (TRAP) coupled to RNA-seq to profile dopamine neuron–specific gene expression changes caused by LRRK2 G2019S in the Drosophila CNS. A modest number of genes were differentially expressed in the presence of mutant LRRK2 that represent a broad range of molecular functions including DNA repair (RfC3), mRNA metabolism and translation (Ddx1 and lin-28), calcium homeostasis (MCU), and other categories (Ugt37c1, disp, l(1)G0196, CG6602, CG1126 and CG11068). Further analysis on a subset of these genes revealed that LRRK2 G2019S did not alter their expression across the whole brain, consistent with dopamine neuron–specific effects uncovered by the TRAP approach that may offer insight into the neurodegenerative process. To our knowledge, this is the first study to profile the effects of LRRK2 G2019S on DA neuron gene expression in vivo. Beyond providing a set of differentially expressed gene candidates relevant to LRRK2, we demonstrate the effective use of TRAP to perform high-resolution assessment of dopamine neuron gene expression for the study of PD.

Genetic heterogeneity remains an ongoing challenge in treating acute myeloid leukemia (AML). Identifying microenvironment-driven pathways that are active across AML genetic subtypes should allow the development of broadly effective therapies. We have shown that AML microenvironment is rich in proinflammatory cytokine interleukin-1β (IL-1β) and promotes AML progression. The transcriptome analysis revealed that ASF1B (anti-silencing function1B), a histone chaperone, is one of the most differentially expressed genes in AML progenitors as compared to normal cells upon IL-1β stimulation. The functional roles of ASF1B in hematopoiesis and leukemia remain elusive. We identified that IL-1β upregulates ASF1B in various genetic subtypes of AML at both mRNA and protein levels. Upon shRNA-mediated ASF1B depletion, AML cells exhibited reduced cell viability, inhibited growth, cell cycle arrest, and impaired colony formation ability. In vivo xenograft model showed 80% reduction in leukemic burden and spleen size following ASF1B silencing. Using a MLL-ENL murine bone marrow transplantation model, we found that ASF1B overexpression alone shortened survival (p = 0.02) of MLL-ENL leukemic mice to the same extent as IL-1β-treated recipients versus vehicle-treated group (p = 0.03), suggesting that high ASF1B levels mimic IL-1β-mediated growth effects in AML. In a complementary study, both heterozygous and complete deletion of ASF1B extended survival of mice (p In summary, we demonstrate that elevated ASF1B expression promotes disease progression in AML. We also provide in vitro and in vivo evidence that ASF1B plays a critical role in potentiating IL-1β-dependent AML growth. Therefore, ASF1B can serve as a novel route of therapeutic strategy to suppress microenvironmental-driven growth in various AML genetic subtypes.

Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines, as well as the early identification of individuals with the highest risk that may require supportive treatment. Here, we completed a large screen of mice from the Collaborative Cross (CC) that we infected with influenza, SARS-coronavirus, and West Nile virus. CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality following infection and strains exhibiting no mortality to these infections. We then used comprehensive pre-infection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection. These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design.

The Collaborative Cross (CC) is a panel of reproducible recombinant inbred mouse strains with high levels of standing genetic variation, thereby affording unprecedented opportunity to perform experiments in a small animal model containing controlled genetic diversity while allowing for genetic replicates. Here, we advance the utility of this unique mouse resource for immunology research, as it allows for both examination and genetic dissection of mechanisms behind adaptive immune states in mice with distinct and defined genetic makeups. This approach is founded on quantitative trait locus mapping: identifying genetically variant genome regions associated with phenotypic variance in traits-of-interest. Furthermore, the CC can be utilized for mouse model development; distinct strains have unique immunophenotypes and immune properties, making them suitable for research on particular diseases and infections. Here, we describe variation in cellular immune phenotypes across F1 crosses of CC strains, and reveal novel quantitative trait loci responsible for several immune phenotypes.

Gene set analysis (GSA) is a promising tool for uncovering the polygenic effects associated with complex diseases. However, the available techniques reflect a wide variety of hypotheses about how genetic effects interact to contribute to disease susceptibility. The lack of consensus about the best way to perform GSA has led to confusion in the field and has made it difficult to compare results across methods. A clear understanding of the various choices made during GSA – such as how gene sets are defined, how single-nucleotide polymorphisms (SNPs) are assigned to genes, and how individual SNP-level effects are aggregated to produce gene- or pathway-level effects – will improve the interpretability and comparability of results across methods and studies. In this review we provide an overview of the various data sources used to construct gene sets and the statistical methods used to test for gene set association, as well as provide guidelines for ensuring the comparability of results.

While molecular genetic abnormalities can tell us much about the pathogenesis of acute myeloid leukemia (AML), these molecular genetics do not always explain drug resistance or sensitivity, leaving room for other mechanisms of tumor pathogenesis outside of genetic events. The Beat AML 1.0 project was a multicenter project to sequence and functionally query AML samples against over 120 drugs. The results have helped form disease models on how mutations affect disease phenotype and drug sensitivity and have assisted in identifying gene signature profiles that may facilitate selecting the most effective treatment options. However, there are factors outside of genetic abnormalities that affect disease pathogenesis. For example, tumor-associated macrophages in the tumor microenvironment play a role in pathogenesis and represent therapeutic targets.

Selective breeding offers several important advantages over using inbred strain panels in detecting genetically correlated traits to the selection phenotype. The purpose of the current study was to selectively breed for prepulse inhibition (PPI) of the acoustic startle response (ASR), to pharmacologically and behaviorally characterize the selected lines and to use the lines for quantitative trait loci (QTL) mapping. Starting with heterogeneous stock mice formed by crossing the C57BL/6J, DBA/2J, BALB/cJ and LP/J inbred strains and using a short-term selective breeding strategy, animals were selected for High and Low PPI. The selection phenotype was the 80 dB prepulse tone (15 dB above the background noise). After five generations of selection, the High and Low lines differed significantly (78.1 +/- 3.1 vs. 45.2 +/- 3.9 [percent inhibition], p0.00001). The effects of haloperidol and MK-801 on PPI were not different between the High and Low lines. However, at the highest dose tested (10 mg/kg), the High line was more sensitive than the Low line to the disruptive PPI effects of methamphetamine. The lines did not differ in terms of basal activity or methamphetamine-induced changes in locomotor activity. The High and Low lines were genotyped using a panel of 768 SNPs. Significant QTLs (LOD10) were detected on chromosomes 11 and 16 that appeared similar to those detected previously [Hitzemann, R., Bell, J., Rasmussen, E., McCaughran, J. Mapping the genes for the acoustic startle response (ASR) and prepulse inhibition of the ASR in the BXD recombinant inbred series: effect of high-frequency hearing loss and cochlear pathology. In: Willott JF, editor. Handbook of mouse auditory research: From behavior to molecular biology. New York: CRC Press; 2001, p. 441-455.; Petryshen, T. L, Kirby, A., Hammer, R.P. Jr, Purcell, S., O'Leary, S.B., Singer, J.B., et al. Two quantitative trait loci for prepulse inhibition of startle identified on mouse chromosome 16 using chromosome substitution strains. Genetics 2005; 171: 1895-1904.]. Overall, the current study illustrates that the heritability of PPI is sufficient for shortterm selective breeding and that the lines which are developed can be used to characterize the factors associated with the regulation of PPI.

The ability to maintain cognitive function during aging is a complex process subject to genetic and environmental influences. Alzheimer's disease (AD) is the most common disorder causing cognitive decline among the elderly. Among those with AD, there is broad variation in the relationship between AD neuropathology and clinical manifestations of dementia. Differences in expression of genes involved in neural processing pathways may contribute to individual differences in maintenance of cognitive function. We performed whole genome expression profiling of RNA obtained from frontal cortex of clinically non-demented and AD subjects to identify genes associated with brain aging and cognitive decline. Genetic mapping information and biological function annotation were incorporated to highlight genes of particular interest. The candidate genes identified in this study were compared with those from two other studies in different tissues to identify common underlying transcriptional profiles. In addition to confirming sweeping transcriptomal differences documented in previous studies of cognitive decline, we present new evidence for up-regulation of actin-related processes and down-regulation of translation, RNA processing and localization, and vesicle-mediated transport in individuals with cognitive decline.

The homeobox transcription factor Pdx-1 is necessary for pancreas organogenesis and beta cell function, however, most Pdx-1-regulated genes are unknown. To further the understanding of Pdx-1 in beta cell biology, we have characterized its genomic targets in NIT-1 cells, a mouse insulinoma cell line. To identify novel targets, we developed a microarray that includes traditional promoters as well as non-coding conserved elements, micro-RNAs, and elements identified through an unbiased approach termed serial analysis of chromatin occupancy. In total, 583 new Pdx-1 target genes were identified, many of which contribute to energy sensing and insulin release in pancreatic beta cells. By analyzing 31 of the protein-coding Pdx-1 target genes, we show that 29 are expressed in beta cells and, of these, 68% are down- or up-regulated in cells expressing a dominant negative mutant of Pdx-1. We additionally show that many Pdx-1 targets also interact with NeuroD1/BETA2, including the micro-RNA miR-375, a known regulator of insulin secretion.

Wnt signaling induces the nuclear accumulation of beta-catenin and transcription of specific target genes via the DNA-binding proteins TCF/Lef. Although all known beta-catenin target genes encode proteins, genome-wide RNA profiling studies indicate that many transcripts do not have this capability. Transcription factor-binding sites associated with these noncoding transcripts can be identified using unbiased techniques such as serial analysis of chromatin occupancy (SACO). We used this method to identify a beta-catenin-regulated antisense RNA expressed in HCT116 colorectal carcinoma cells, a cellular model of activated beta-catenin signaling. Genomic signature tags designating putative beta-catenin-binding sites mapped to the 3'-untranslated region (3'-UTR) of the E2F4 gene. We showed that both beta-catenin and TCF4 bind to the E2F4 3'-UTR site in vivo, inducing expression of an E2F4 antisense transcript. LiCl, which mimics Wnt signaling, also induced expression of the E2F4 antisense transcript and decreased E2F4 protein levels. This effect was blocked by a cDNA expressing the E2F4 3'-UTR sense strand. The antisense-mediated decrease in E2F4 protein was reflected by reduced E2F4 association with specific target genes, including CCNA2, CDC2, PCNA, and Rad54. We propose that Wnt/beta-catenin signaling may contribute to colorectal carcinogenesis by reducing the level of the E2F4 cell cycle repressor via an antisense mechanism.

Alzheimer's disease (AD) is a late-onset and progressive neurodegenerative disorder characterized clinically by memory loss, impairment of other cognitive functions, and changes in behavior and personality. The overall aim of this review is to summarize recent advances in studies of AD progression and the use of animal models in gene expression studies of AD progression. Genetic causes of AD are known only for early-onset AD patients. For a majority of late-onset AD patients, causal factors are still unknown. Currently, there are no early detectable biomarkers for late-onset AD, and there is a lack of understanding of AD pathophysiology, particularly at the early stages of disease progression, before pathology develops. Human histopathological and biochemical studies provide valuable information regarding the last stages of AD pathogenesis. However, to understand early cellular changes in AD progression before symptoms develop, animal models are still our only alternative. Several research groups have created genetically engineered animal models, particularly models of the mouse, rat, fly, and worm, which have allowed us to better, understand the initiating events of AD progression. Recently, state-of-the-art methods have helped elucidate gene expression changes in affected and unaffected tissues from postmortem AD brains and from animal models developed for AD studies. These methods allow the investigation of mRNA-based transcriptosomal profiles of brain specimens from AD humans and transgenic animals. The major finding from these studies is that AD progression and pathogenesis involve multiple cellular pathways, which suggests that AD is a complex and heterogeneous disease.

The CREB transcription factor regulates differentiation, survival, and synaptic plasticity. The complement of CREB targets responsible for these responses has not been identified, however. We developed a novel approach to identify CREB targets, termed serial analysis of chromatin occupancy (SACO), by combining chromatin immunoprecipitation (ChIP) with a modification of SAGE. Using a SACO library derived from rat PC12 cells, we identified ∼41,000 genomic signature tags (GSTs) that mapped to unique genomic loci. CREB binding was confirmed for all loci supported by multiple GSTs. Of the 6302 loci identified by multiple GSTs, 40% were within 2 kb of the transcriptional start of an annotated gene, 49% were within 1 kb of a CpG island, and 72% were within 1 kb of a putative cAMP-response element (CRE). A large fraction of the SACO loci delineated bidirectional promoters and novel antisense transcripts. This study represents the most comprehensive definition of transcription factor binding sites in a metazoan species.

The recent letter by Cortes and Pavlidis [1] brings attention to two important points regarding the interpretation of results from gene set analyses (GSA). In particular, the authors provided a clear example of the problems that can occur when correlation between genes is not taken into account [e.g., when the same single nucleotide polymorphism (SNP) is mapped to multiple genes] [2]. As we discussed in our recent review [3], the choice of strategy used to map SNPs to genes can have important consequences for the results obtained from a GSA, and we appreciate Cortes and Pavlidis’ clarification of the issue.

A rigorous, in-depth meta-analysis of public transcriptomics data from 5 hand-curated studies for human cells exposed to 2, 5, or 10 Gy of ionizing radiation from the Gene Expression Omnibus (GEO) online repository was performed. These data sets were categorized into two groups based on the type of cell line (normal or cancer), and each group was analyzed separately, comparing irradiated and non-irradiated samples. Gene expression and pathway analysis was performed on each data set. In addition, a drug target analysis was performed to identify drugs that significantly target the genes and pathways that were found to be differentially expressed. The meta-analysis of these data sets found pathways that were significantly enriched for individual data sets. In addition, the following pathways were found to be significantly enriched across all cancer group data sets: Cell Cycle Mitotic, DNA Replication, Mitotic M-M/G1 phases, AKT phosphorylates targets in the cytosol, M Phase, and Mitotic Prometaphase. Finally, the following putative candidate drug targets for these pathways were identified: POLA1, POLA2, PLK1, CENPE, AURKB, CDKN1B, and RB1.