Natural History of Colorectal Polyps Undergoing Longitudinal in Vivo CT Colonography Surveillance.

Background The natural history of colorectal polyps is not well characterized due to clinical standards of care and other practical constraints limiting in vivo longitudinal surveillance. Established CT colonography (CTC) clinical screening protocols allow surveillance of small (6-9 mm) polyps. Purpose To assess the natural history of colorectal polyps followed with CTC in a clinical screening program, with histopathologic correlation for resected polyps. Materials and Methods In this retrospective study, CTC was used to longitudinally monitor small colorectal polyps in asymptomatic adult patients from April 1, 2004, to August 31, 2020. All patients underwent at least two CTC examinations. Polyp growth patterns across multiple time points were analyzed, with histopathologic context for resected polyps. Regression analysis was performed to evaluate predictors of advanced histopathology. Results In this study of 475 asymptomatic adult patients (mean age, 56.9 years ± 6.7 [SD]; 263 men), 639 unique polyps (mean initial diameter, 6.3 mm; volume, 50.2 mm3) were followed for a mean of 5.1 years ± 2.9. Of these 639 polyps, 398 (62.3%) underwent resection and histopathologic evaluation, and 41 (6.4%) proved to be histopathologically advanced (adenocarcinoma, high-grade dysplasia, or villous content), including two cancers and 38 tubulovillous adenomas. Advanced polyps showed mean volume growth of +178% per year (752% per year for adenocarcinomas) compared with +33% per year for nonadvanced polyps and -3% per year for unresected, unretrieved, or resolved polyps (P < .001). In addition, 90% of histologically advanced polyps achieved a volume of 100 mm3 and/or volume growth rate of 100% per year, compared with 29% of nonadvanced and 16% of unresected or resolved polyps (P < .001). Polyp volume-to-diameter ratio was also significantly greater for advanced polyps. For polyps observed at three or more time points, most advanced polyps demonstrated an initial slower growth interval, followed by a period of more rapid growth. Conclusion Small colorectal polyps ultimately proving to be histopathologically advanced neoplasms demonstrated substantially faster growth and attained greater overall size compared with nonadvanced polyps. Clinical trial registration no. NCT00204867 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Dachman in this issue.

Novel autoantibodies help diagnose anti-SSA antibody negative Sjögren disease and predict abnormal labial salivary gland pathology.

OBJECTIVES: Sjögren disease (SjD) diagnosis often requires either positive anti-SSA antibodies or a labial salivary gland biopsy with a positive focus score (FS). One-third of patients with SjD lack anti-SSA antibodies (SSA-), requiring a positive FS for diagnosis. Our objective was to identify novel autoantibodies to diagnose 'seronegative' SjD. METHODS: IgG binding to a high-density whole human peptidome array was quantified using sera from SSA- SjD cases and matched non-autoimmune controls. We identified the highest bound peptides using empirical Bayesian statistical filters, which we confirmed in an independent cohort comprising SSA- SjD (n=76), sicca-controls without autoimmunity (n=75) and autoimmune-feature controls (SjD features but not meeting SjD criteria; n=41). In this external validation, we used non-parametric methods for binding abundance and controlled false discovery rate in group comparisons. For predictive modelling, we used logistic regression, model selection methods and cross-validation to identify clinical and peptide variables that predict SSA- SjD and FS positivity. RESULTS: IgG against a peptide from D-aminoacyl-tRNA deacylase (DTD2) bound more in SSA- SjD than sicca-controls (p=0.004) and combined controls (sicca-controls and autoimmune-feature controls combined; p=0.003). IgG against peptides from retroelement silencing factor-1 and DTD2 were bound more in FS-positive than FS-negative participants (p=0.010; p=0.012). A predictive model incorporating clinical variables showed good discrimination between SjD versus control (area under the curve (AUC) 74%) and between FS-positive versus FS-negative (AUC 72%). CONCLUSION: We present novel autoantibodies in SSA- SjD that have good predictive value for SSA- SjD and FS positivity.

Growth rates and histopathological outcomes of small (6-9 mm) colorectal polyps based on CT colonography surveillance and endoscopic removal.

BACKGROUND AND AIMS: The natural history of small polyps is not well established and rests on limited evidence from barium enema studies decades ago. Patients with one or two small polyps (6-9 mm) at screening CT colonography (CTC) are offered CTC surveillance at 3 years but may elect immediate colonoscopy. This practice allows direct observation of the growth of subcentimetre polyps, with histopathological correlation in patients undergoing subsequent polypectomy. DESIGN: Of 11 165 asymptomatic patients screened by CTC over a period of 16.4 years, 1067 had one or two 6-9 mm polyps detected (with no polyps ≥10 mm). Of these, 314 (mean age, 57.4 years; M:F, 141:173; 375 total polyps) elected immediate colonoscopic polypectomy, and 382 (mean age 57.0 years; M:F, 217:165; 481 total polyps) elected CTC surveillance over a mean of 4.7 years. Volumetric polyp growth was analysed, with histopathological correlation for resected polyps. Polyp growth and regression were defined as volume change of ±20% per year, with rapid growth defined as +100% per year (annual volume doubling). Regression analysis was performed to evaluate predictors of advanced histology, defined as the presence of cancer, high-grade dysplasia (HGD) or villous components. RESULTS: Of the 314 patients who underwent immediate polypectomy, 67.8% (213/314) harboured adenomas, 2.2% (7/314) with advanced histology; no polyps contained cancer or HGD. Of 382 patients who underwent CTC surveillance, 24.9% (95/382) had polyps that grew, while 62.0% (237/382) remained stable and 13.1% (50/382) regressed in size. Of the 58.6% (224/382) CTC surveillance patients who ultimately underwent colonoscopic resection, 87.1% (195/224) harboured adenomas, 12.9% (29/224) with advanced histology. Of CTC surveillance patients with growing polyps who underwent resection, 23.2% (19/82) harboured advanced histology vs 7.0% (10/142) with stable or regressing polyps (OR: 4.0; p<0.001), with even greater risk of advanced histology in those with rapid growth (63.6%, 14/22, OR: 25.4; p<0.001). Polyp growth, but not patient age/sex or polyp morphology/location were significant predictors of advanced histology. CONCLUSION: Small 6-9 mm polyps present overall low risk to patients, with polyp growth strongly associated with higher risk lesions. Most patients (75%) with small 6-9 mm polyps will see polyp stability or regression, with advanced histology seen in only 7%. The minority of patients (25%) with small polyps that do grow have a 3-fold increased risk of advanced histology.

Dimension constraints improve hypothesis testing for large-scale, graph-associated, brain-image data.

For large-scale testing with graph-associated data, we present an empirical Bayes mixture technique to score local false-discovery rates (FDRs). Compared to procedures that ignore the graph, the proposed Graph-based Mixture Model (GraphMM) method gains power in settings where non-null cases form connected subgraphs, and it does so by regularizing parameter contrasts between testing units. Simulations show that GraphMM controls the FDR in a variety of settings, though it may lose control with excessive regularization. On magnetic resonance imaging data from a study of brain changes associated with the onset of Alzheimer's disease, GraphMM produces greater yield than conventional large-scale testing procedures.

Bayes optimal informer sets for early-stage drug discovery.

An important experimental design problem in early-stage drug discovery is how to prioritize available compounds for testing when very little is known about the target protein. Informer-based ranking (IBR) methods address the prioritization problem when the compounds have provided bioactivity data on other potentially relevant targets. An IBR method selects an informer set of compounds, and then prioritizes the remaining compounds on the basis of new bioactivity experiments performed with the informer set on the target. We formalize the problem as a two-stage decision problem and introduce the Bayes Optimal Informer SEt (BOISE) method for its solution. BOISE leverages a flexible model of the initial bioactivity data, a relevant loss function, and effective computational schemes to resolve the two-step design problem. We evaluate BOISE and compare it to other IBR strategies in two retrospective studies, one on protein-kinase inhibition and the other on anticancer drug sensitivity. In both empirical settings BOISE exhibits better predictive performance than available methods. It also behaves well with missing data, where methods that use matrix completion show worse predictive performance.

GM-CSF elicits antibodies to tumor-associated proteins when used as a prostate cancer vaccine adjuvant.

Antibody responses to off-target cancer-associated proteins have been detected following immunotherapies for cancer, suggesting these may be the result of antigen spread. We have previously reported that serum antibodies to prostate cancer-associated proteins were detectable using a high-throughput peptide array. We hypothesized that the breadth of antibody responses elicited by a vaccine could serve as a measure of the magnitude of its induced antigen spread. Consequently, sera from patients with prostate cancer, treated prior to or after vaccination in one of four separate clinical trials, were evaluated for antibody responses to an array of 177,604 peptides derived from over 1600 prostate cancer-associated gene products. Antibody responses to the same group of 5680 peptides previously reported were identified following vaccinations in which patients were administered GM-CSF as an adjuvant, but not with vaccine in the absence of GM-CSF. Hence, antibody responses to off-target proteins following vaccination may not necessarily serve as evidence of antigen spread and must be interpreted with particular caution following vaccine strategies that use GM-CSF, as GM-CSF appears to have direct effects on the production of antibodies. The evaluation of T cell responses to non-target antigens is likely a preferred approach for detection of immune-mediated antigen spread.

MixTwice: large-scale hypothesis testing for peptide arrays by variance mixing.

SUMMARY: Peptide microarrays have emerged as a powerful technology in immunoproteomics as they provide a tool to measure the abundance of different antibodies in patient serum samples. The high dimensionality and small sample size of many experiments challenge conventional statistical approaches, including those aiming to control the false discovery rate (FDR). Motivated by limitations in reproducibility and power of current methods, we advance an empirical Bayesian tool that computes local FDR statistics and local false sign rate statistics when provided with data on estimated effects and estimated standard errors from all the measured peptides. As the name suggests, the MixTwice tool involves the estimation of two mixing distributions, one on underlying effects and one on underlying variance parameters. Constrained optimization techniques provide for model fitting of mixing distributions under weak shape constraints (unimodality of the effect distribution). Numerical experiments show that MixTwice can accurately estimate generative parameters and powerfully identify non-null peptides. In a peptide array study of rheumatoid arthritis, MixTwice recovers meaningful peptide markers in one case where the signal is weak, and has strong reproducibility properties in one case where the signal is strong. AVAILABILITYAND IMPLEMENTATION: MixTwice is available as an R software package https://cran.r-project.org/web/packages/MixTwice/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The conserved protective cyclic AMP-phosphodiesterase function PDE4B is expressed in the adenoma and adjacent normal colonic epithelium of mammals and silenced in colorectal cancer.

Conservation over three mammalian genera-the mouse, rat, and human-has been found for a subset of the transcripts whose level differs between the adenoma and normal epithelium of the colon. Pde4b is one of the triply conserved transcripts whose level is enhanced both in the colonic adenoma and in the normal colonic epithelium, especially adjacent to adenomas. It encodes the phosphodiesterase PDE4B, specific for cAMP. Loss of PDE4B function in the ApcMin/+ mouse leads to a significant increase in the number of colonic adenomas. Similarly, Pde4b-deficient ApcMin/+ mice are hypersensitive to treatment by the inflammatory agent DSS, becoming moribund soon after treatment. These observations imply that the PDE4B function protects against ApcMin-induced adenomagenesis and inflammatory lethality. The paradoxical enhancement of the Pde4b transcript in the adenoma versus this inferred protective function of PDE4B can be rationalized by a feedback model in which PDE4B is first activated by early oncogenic stress involving cAMP and then, as reported for frank human colon cancer, inactivated by epigenetic silencing.

Predicting kinase inhibitors using bioactivity matrix derived informer sets.

Prediction of compounds that are active against a desired biological target is a common step in drug discovery efforts. Virtual screening methods seek some active-enriched fraction of a library for experimental testing. Where data are too scarce to train supervised learning models for compound prioritization, initial screening must provide the necessary data. Commonly, such an initial library is selected on the basis of chemical diversity by some pseudo-random process (for example, the first few plates of a larger library) or by selecting an entire smaller library. These approaches may not produce a sufficient number or diversity of actives. An alternative approach is to select an informer set of screening compounds on the basis of chemogenomic information from previous testing of compounds against a large number of targets. We compare different ways of using chemogenomic data to choose a small informer set of compounds based on previously measured bioactivity data. We develop this Informer-Based-Ranking (IBR) approach using the Published Kinase Inhibitor Sets (PKIS) as the chemogenomic data to select the informer sets. We test the informer compounds on a target that is not part of the chemogenomic data, then predict the activity of the remaining compounds based on the experimental informer data and the chemogenomic data. Through new chemical screening experiments, we demonstrate the utility of IBR strategies in a prospective test on three kinase targets not included in the PKIS.

Molecular transitions from papillomavirus infection to cervical precancer and cancer: Role of stromal estrogen receptor signaling.

To study the multistep process of cervical cancer development, we analyzed 128 frozen cervical samples spanning normalcy, increasingly severe cervical intraepithelial neoplasia (CIN1- CIN3), and cervical cancer (CxCa) from multiple perspectives, revealing a cascade of progressive changes. Compared with normal tissue, expression of many DNA replication/repair and cell proliferation genes was increased in CIN1/CIN2 lesions and further sustained in CIN3, consistent with high-risk human papillomavirus (HPV)-induced tumor suppressor inactivation. The CIN3-to-CxCa transition showed metabolic shifts, including decreased expression of mitochondrial electron transport complex components and ribosomal protein genes. Significantly, despite clinical, epidemiological, and animal model results linking estrogen and estrogen receptor alpha (ERα) to CxCa, ERα expression declined >15-fold from normalcy to cancer, showing the strongest inverse correlation of any gene with the increasing expression of p16, a marker for HPV-linked cancers. This drop in ERα in CIN and tumor cells was confirmed at the protein level. However, ERα expression in stromal cells continued throughout CxCa development. Our further studies localized stromal ERα to FSP1+, CD34+, SMA- precursor fibrocytes adjacent to normal and precancerous CIN epithelium, and FSP1-, CD34-, SMA+ activated fibroblasts in CxCas. Moreover, rank correlations with ERα mRNA identified IL-8, CXCL12, CXCL14, their receptors, and other angiogenesis and immune cell infiltration and inflammatory factors as candidates for ERα-induced stroma-tumor signaling pathways. The results indicate that estrogen signaling in cervical cancer has dramatic differences from ERα+ breast cancers, and imply that estrogen signaling increasingly proceeds indirectly through ERα in tumor-associated stromal fibroblasts.

Single-molecule analysis reveals widespread structural variation in multiple myeloma.

Multiple myeloma (MM), a malignancy of plasma cells, is characterized by widespread genomic heterogeneity and, consequently, differences in disease progression and drug response. Although recent large-scale sequencing studies have greatly improved our understanding of MM genomes, our knowledge about genomic structural variation in MM is attenuated due to the limitations of commonly used sequencing approaches. In this study, we present the application of optical mapping, a single-molecule, whole-genome analysis system, to discover new structural variants in a primary MM genome. Through our analysis, we have identified and characterized widespread structural variation in this tumor genome. Additionally, we describe our efforts toward comprehensive characterization of genome structure and variation by integrating our findings from optical mapping with those from DNA sequencing-based genomic analysis. Finally, by studying this MM genome at two time points during tumor progression, we have demonstrated an increase in mutational burden with tumor progression at all length scales of variation.

Subclonal diversity arises early even in small colorectal tumours and contributes to differential growth fates.

OBJECTIVE AND DESIGN: The goal of the study was to determine whether the mutational profile of early colorectal polyps correlated with growth behaviour. The growth of small polyps (6-9 mm) that were first identified during routine screening of patients was monitored over time by interval imaging with CT colonography. Mutations in these lesions with known growth rates were identified by targeted next-generation sequencing. The timing of mutational events was estimated using computer modelling and statistical inference considering several parameters including allele frequency and fitness. RESULTS: The mutational landscape of small polyps is varied both within individual polyps and among the group as a whole but no single alteration was correlated with growth behaviour. Polyps carried 0-3 pathogenic mutations with the most frequent being in APC, KRAS/NRAS, BRAF, FBXW7 and TP53. In polyps with two or more pathogenic mutations, allele frequencies were often variable, indicating the presence of multiple populations within a single tumour. Based on computer modelling, detectable mutations occurred at a mean polyp size of 30±35 crypts, well before the tumour is of a clinically detectable size. CONCLUSIONS: These data indicate that small colon polyps can have multiple pathogenic mutations in crucial driver genes that arise early in the existence of a tumour. Understanding the molecular pathway of tumourigenesis and clonal evolution in polyps that are at risk for progressing to invasive cancers will allow us to begin to better predict which polyps are more likely to progress into adenocarcinomas and which patients are at greater risk of developing advanced disease.

Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening.

In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces target performance variability. Here we compare traditional consensus scoring methods with a novel, unsupervised gradient boosting approach. We also observed increased score variation among active ligands and developed a statistical mixture model consensus score based on combining score means and variances. To evaluate performance, we used the common performance metrics ROCAUC and EF1 on 21 benchmark targets from DUD-E. Traditional consensus methods, such as taking the mean of quantile normalized docking scores, outperformed individual docking methods and are more robust to target variation. The mixture model and gradient boosting provided further improvements over the traditional consensus methods. These methods are readily applicable to new targets in academic research and overcome the potentially poor performance of using a single docking method on a new target.

Phase I study to evaluate toxicity and feasibility of intratumoral injection of α-gal glycolipids in patients with advanced melanoma.

Effective uptake of tumor cell-derived antigens by antigen-presenting cells is achieved pre-clinically by in situ labeling of tumor with α-gal glycolipids that bind the naturally occurring anti-Gal antibody. We evaluated toxicity and feasibility of intratumoral injections of α-gal glycolipids as an autologous tumor antigen-targeted immunotherapy in melanoma patients (pts). Pts with unresectable metastatic melanoma, at least one cutaneous, subcutaneous, or palpable lymph node metastasis, and serum anti-Gal titer ≥1:50 were eligible for two intratumoral α-gal glycolipid injections given 4 weeks apart (cohort I: 0.1 mg/injection; cohort II: 1.0 mg/injection; cohort III: 10 mg/injection). Monitoring included blood for clinical, autoimmune, and immunological analyses and core tumor biopsies. Treatment outcome was determined 8 weeks after the first α-gal glycolipid injection. Nine pts received two intratumoral injections of α-gal glycolipids (3 pts/cohort). Injection-site toxicity was mild, and no systemic toxicity or autoimmunity could be attributed to the therapy. Two pts had stable disease by RECIST lasting 8 and 7 months. Tumor nodule biopsies revealed minimal to no change in inflammatory infiltrate between pre- and post-treatment biopsies except for 1 pt (cohort III) with a post-treatment inflammatory infiltrate. Two and four weeks post-injection, treated nodules in 5 of 9 pts exhibited tumor cell necrosis without neutrophilic or lymphocytic inflammatory response. Non-treated tumor nodules in 2 of 4 evaluable pts also showed necrosis. Repeated intratumoral injections of α-gal glycolipids are well tolerated, and tumor necrosis was seen in some tumor nodule biopsies after tumor injection with α-gal glycolipids.

Transformation of epithelial cells through recruitment leads to polyclonal intestinal tumors.

Intestinal tumors from mice and humans can have a polyclonal origin. Statistical analyses indicate that the best explanation for this source of intratumoral heterogeneity is the presence of interactions among multiple progenitors. We sought to better understand the nature of these interactions. An initial progenitor could recruit others by facilitating the transformation of one or more neighboring cells. Alternatively, two progenitors that are independently initiated could simply cooperate to form a single tumor. These possibilities were tested by analyzing tumors from aggregation chimeras that were generated by fusing together embryos with unequal predispositions to tumor development. Strikingly, numerous polyclonal tumors were observed even when one genetic component was highly, if not completely, resistant to spontaneous tumorigenesis in the intestine. Moreover, the observed number of polyclonal tumors could be explained by the facilitated transformation of a single neighbor within 144 µm of an initial progenitor. These findings strongly support recruitment instead of cooperation. Thus, it is conceivable that these interactions are necessary for tumors to thrive, so blocking them might be a highly effective method for preventing the formation of tumors in the intestine and other tissues.

A conditional predictive p-value to compare a multinomial with an overdispersed multinomial in the analysis of T-cell populations.

Immunological experiments that record primary molecular sequences of T-cell receptors produce moderate to high-dimensional categorical data, some of which may be subject to extra-multinomial variation caused by technical constraints of cell-based assays. Motivated by such experiments in melanoma research, we develop a statistical procedure for testing the equality of two discrete populations, where one population delivers multinomial data and the other is subject to a specific form of overdispersion. The procedure computes a conditional-predictive p-value by splitting the data set into two, obtaining a predictive distribution for one piece given the other, and using the observed predictive ordinate to generate a p-value. The procedure has a simple interpretation, requires fewer modeling assumptions than would be required of a fully Bayesian analysis, and has reasonable operating characteristics as evidenced empirically and by asymptotic analysis.

Monoallelic silencing and haploinsufficiency in early murine intestinal neoplasms.

Studies of tumors from human familial adenomatous polyposis, sporadic colon cancer, and mouse and rat models of intestinal cancer indicate that the majority of early adenomas develop through loss of normal function of the Adenomatous polyposis coli (APC) gene. In murine models of familial adenomatous polyposis, specifically the multiple intestinal neoplasia mouse (Min) and the polyposis in the rat colon (Pirc) rat, most adenomas have lost their WT copy of the Apc gene through loss of heterozygosity by homologous somatic recombination. We report that large colonic adenomas in the Pirc rat have no detectable copy number losses or gains in genomic material and that most tumors lose heterozygosity only on the short arm of chromosome 18. Examination of early mouse and rat tumors indicates that a substantial subset of tumors shows maintenance of heterozygosity of Apc in genomic DNA, apparently violating Knudson's two-hit hypothesis. Sequencing of the Apc gene in a sampling of rat tumors failed to find secondary mutations in the majority of tumors that maintained heterozygosity of Apc in genomic DNA. Using quantitative allele-specific assays of Apc cDNA, we discovered two neoplastic pathways. One class of tumors maintains heterozygosity of Apc(Min/+) or Apc(Pirc/+) RNA expression and may involve haploinsufficiency for Apc function. Another class of tumors exhibits highly biased monoallelic expression of the mutant Apc allele, providing evidence for a stochastic or random process of monoallelic epigenetic silencing of the tumor suppressor gene Apc.

Limited agreement of independent RNAi screens for virus-required host genes owes more to false-negative than false-positive factors.

Systematic, genome-wide RNA interference (RNAi) analysis is a powerful approach to identify gene functions that support or modulate selected biological processes. An emerging challenge shared with some other genome-wide approaches is that independent RNAi studies often show limited agreement in their lists of implicated genes. To better understand this, we analyzed four genome-wide RNAi studies that identified host genes involved in influenza virus replication. These studies collectively identified and validated the roles of 614 cell genes, but pair-wise overlap among the four gene lists was only 3% to 15% (average 6.7%). However, a number of functional categories were overrepresented in multiple studies. The pair-wise overlap of these enriched-category lists was high, ∼19%, implying more agreement among studies than apparent at the gene level. Probing this further, we found that the gene lists implicated by independent studies were highly connected in interacting networks by independent functional measures such as protein-protein interactions, at rates significantly higher than predicted by chance. We also developed a general, model-based approach to gauge the effects of false-positive and false-negative factors and to estimate, from a limited number of studies, the total number of genes involved in a process. For influenza virus replication, this novel statistical approach estimates the total number of cell genes involved to be ∼2,800. This and multiple other aspects of our experimental and computational results imply that, when following good quality control practices, the low overlap between studies is primarily due to false negatives rather than false-positive gene identifications. These results and methods have implications for and applications to multiple forms of genome-wide analysis.

Drosophila RNAi screen identifies host genes important for influenza virus replication.

All viruses rely on host cell proteins and their associated mechanisms to complete the viral life cycle. Identifying the host molecules that participate in each step of virus replication could provide valuable new targets for antiviral therapy, but this goal may take several decades to achieve with conventional forward genetic screening methods and mammalian cell cultures. Here we describe a novel genome-wide RNA interference (RNAi) screen in Drosophila that can be used to identify host genes important for influenza virus replication. After modifying influenza virus to allow infection of Drosophila cells and detection of influenza virus gene expression, we tested an RNAi library against 13,071 genes (90% of the Drosophila genome), identifying over 100 for which suppression in Drosophila cells significantly inhibited or stimulated reporter gene (Renilla luciferase) expression from an influenza-virus-derived vector. The relevance of these findings to influenza virus infection of mammalian cells is illustrated for a subset of the Drosophila genes identified; that is, for three implicated Drosophila genes, the corresponding human homologues ATP6V0D1, COX6A1 and NXF1 are shown to have key functions in the replication of H5N1 and H1N1 influenza A viruses, but not vesicular stomatitis virus or vaccinia virus, in human HEK 293 cells. Thus, we have demonstrated the feasibility of using genome-wide RNAi screens in Drosophila to identify previously unrecognized host proteins that are required for influenza virus replication. This could accelerate the development of new classes of antiviral drugs for chemoprophylaxis and treatment, which are urgently needed given the obstacles to rapid development of an effective vaccine against pandemic influenza and the probable emergence of strains resistant to available drugs.

Development of a next-generation sequencing protocol for the canine T cell receptor beta chain repertoire.

Profiling the T cell receptor (TCR) repertoire using next-generation sequencing has become common in both human and translational research. Companion dogs with spontaneous tumors, including canine melanoma, share several features, e.g., natural occurrence, shared environmental exposures, natural outbred population, and immunocompetence. T cells play an important role in the adaptive immune system by recognizing specific antigens via a surface TCR. As such, understanding the canine T cell response to vaccines, cancer, immunotherapies, and infectious diseases is critically important for both dog and human health. Off-the-shelf commercial reagents, kits and services are readily available for human, non-human primate, and mouse in this context. However, these resources are limited for the canine. In this study, we present a cost-effective protocol for analysis of canine TCR beta chain genes. Workflow can be accomplished in 1-2 days starting with total RNA and resulting in libraries ready for sequencing on Illumina platforms.