Faculty Bibliography

Human papillomavirus (HPV) causes a number of neoplastic diseases in humans. Here, we show a complex normal HPV community in a cohort of 103 healthy human subjects, by metagenomics analysis of the shotgun sequencing data generated from the NIH Human Microbiome Project. The overall HPV prevalence was 68.9% and was highest in the skin (61.3%), followed by the vagina (41.5%), mouth (30%), and gut (17.3%). Of the 109 HPV types as well as additional unclassified types detected, most were undetectable by the widely used commercial kits targeting the vaginal/cervical HPV types. These HPVs likely represent true HPV infections rather than transitory exposure because of strong organ tropism and persistence of the same HPV types in repeat samples. Coexistence of multiple HPV types was found in 48.1% of the HPV-positive samples. Networking between HPV types, cooccurrence or exclusion, was detected in vaginal and skin samples. Large contigs assembled from short HPV reads were obtained from several samples, confirming their genuine HPV origin. This first large-scale survey of HPV using a shotgun sequencing approach yielded a comprehensive map of HPV infections among different body sites of healthy human subjects. IMPORTANCE: This nonbiased survey indicates that the HPV community in healthy humans is much more complex than previously defined by widely used kits that are target selective for only a few high- and low-risk HPV types for cervical cancer. The importance of nononcogenic viruses in a mixed HPV infection could be for stimulating or inhibiting a coexisting oncogenic virus via viral interference or immune cross-reaction. Knowledge gained from this study will be helpful to guide the designing of epidemiological and clinical studies in the future to determine the impact of nononcogenic HPV types on the outcome of HPV infections.

The incidence of esophageal adenocarcinoma has increased dramatically in the United States and Europe since the 1970s without apparent cause. Although specific host factors can affect risk of disease, such a rapid increase in incidence must be predominantly environmental. In the stomach, infection with Helicobacter pylori has been linked to chronic atrophic gastritis, an inflammatory precursor of gastric adenocarcinoma. However, the role of H. pylori in the development of esophageal adenocarcinoma is not well established. Meanwhile, several studies have established that a complex microbiome in the distal esophagus might play a more direct role. Transformation of the microbiome in precursor states to esophageal adenocarcinoma-reflux esophagitis and Barrett metaplasia-from a predominance of gram-positive bacteria to mostly gram-negative bacteria raises the possibility that dysbiosis is contributing to pathogenesis. However, knowledge of the microbiome in esophageal adenocarcinoma itself is lacking. Microbiome studies open a new avenue to the understanding of the etiology and pathogenesis of reflux disorders.

The microbiome is a new center of attention for studies on the pathogenesis of human disease by focusing on the alterations of all microorganisms living in a particular site or system of human body, referred as microbiota. Evidence suggests that microbiota could contribute to the pathogenesis of a number of chronic diseases, including cancers, both locally and remotely. Multiple mechanisms have been proposed and/or proven for the microbiota's role in tumorigenesis, such as via induction of chronic inflammation, genotoxicity, bacterium-mediated cell proliferation, and activation of procarcinogens. Emerging data suggest that indigenous microbiota in the urinary tract may play an important role in the tumorigenesis of urothelial carcinoma, similar to other tumors. Future studies are needed to adequately define the microbiota composition and correlate its change with urothelial carcinoma.

Transcriptional intermediary factor 1 gamma (Tif1gamma) (Ectodermin/PTC7/RFG7/TRIM33) is a transcriptional cofactor with an important role in the regulation of the TGFbeta pathway. It has been suggested that it competes with Smad2/Smad3 for binding to Smad4, or alternatively that it may target Smad4 for degradation, although its role in carcinogenesis is unclear. In this study, we showed that Tif1gamma interacts with Smad1/Smad4 complex in vivo, using both yeast two-hybrid and coimmunoprecipitation assays. We demonstrated that Tif1gamma inhibits transcriptional activity of the Smad1/Smad4 complex through its PHD domain or bromo-domainin pancreatic cells by luciferase assay. Additionally, there is a dynamic inverse relationship between the levels of Tif1gamma and Smad4 in benign and malignant pancreatic cell lines. Overexpression of Tif1gamma resulted in decreased level of Smad4. Both overexpression and knockdown of Tif1gamma resulted in growth inhibition in both benign and cancerous pancreatic cell lines, attributable to a G2-phase cell cycle arrest, but only knockdown of Tif1gamma reduces tumor cell invasiveness in vitro. Our study demonstrated that imbalanced expression of Tif1gamma results in inhibition of pancreatic ductal epithelial cell growth. In addition, knockdown of Tif1gamma may inhibit tumor invasion. These data suggest that Tif1gamma might serve as a potential therapeutic target for pancreatic cancer.

Large cell neuroendocrine carcinoma of the prostate (LCNEC), de novo in particular, is an extremely rare entity that has only been described in the literature in case reports. Historically, the majority of the cases of LCNEC reported in the literature represent typical prostatic adenocarcinomas that transformed after long standing androgen deprivation therapy (ADT). These cases were admixed with histological areas of usual adenocarcinoma and showed hybrid features of both neuroendocrine and usual adenocarcinoma. Here we present a case of an LCNEC without admixed areas of usual prostatic adenocarcinoma arising de novo in a patient without prior history of hormonal therapy. The tumor also shows morphologic evidence of neuroendocrine differentiation; composed of large sheets and nests of cells with moderate amphophilic cytoplasm with peripheral palisading, and vesicular clumpy chromatin with prominent nucleoli. The carcinoma's prostatic origin is indicated by positive immunohistochemical staining for PSA, PAP, PSMA, racemase, and Nkx3.1. Diffusely positive staining for chromogranin and synaptophysin, as well as the presence of secretory granules in the cytoplasm of the tumor cells demonstrated by electron microscopy supports the NE differentiation. NE prostate cancer usually does not express AR and is refractory to ADT therapy while AR and ERG are positive in this case. In summary, we report a de novo LCNEC of the prostate with review of literature, in particular, clinical implications.

We tested the hypothesis that an altered community of gut microbes is associated with risk of colorectal cancer (CRC) in a study of 47 CRC case subjects and 94 control subjects. 16S rRNA genes in fecal bacterial DNA were amplified by universal primers, sequenced by 454 FLX technology, and aligned for taxonomic classification to microbial genomes using the QIIME pipeline. Taxonomic differences were confirmed with quantitative polymerase chain reaction and adjusted for false discovery rate. All statistical tests were two-sided. From 794217 16S rRNA gene sequences, we found that CRC case subjects had decreased overall microbial community diversity (P = .02). In taxonomy-based analyses, lower relative abundance of Clostridia (68.6% vs 77.8%) and increased carriage of Fusobacterium (multivariable odds ratio [OR] = 4.11; 95% confidence interval [CI] = 1.62 to 10.47) and Porphyromonas (OR = 5.17; 95% CI = 1.75 to 15.25) were found in case subjects compared with control subjects. Because of the potentially modifiable nature of the gut bacteria, our findings may have implications for CRC prevention.

BACKGROUND: Crohn's disease (CD) results from defects in the mucosal immune response to luminal factors in genetically susceptible individuals. The role of the gut microbiome in CD pathogenesis has been suggested by several studies. Until recently454-pyrosequencing approach was considered the gold standard for microbiome studies. However, newer, more efficient, and cost-effective technologies are now available(1). Compared to other next-generation platforms, Illumina MiSeq has the advantage of higher throughput, better sequencing accuracy, and a shorter running time (24hrs). In this study, we designed a cost-efficient double-barcoding 16S rRNA sequencing using the MiSeq 2x250 pair-end method to evaluate the performance of MiSeq on 16S rRNA sequencing of the fecal microbiome of Ashkenazi Jews (AJ, a genetically homogeneous high-risk population) with and without Crohn's disease. (Figure presented) METHODS: Stool from 27 AJ-CD patients (in remission) and 16 AJ healthy controls was analyzed. We established a protocol for a multiple double-barcoding 16S rRNA sequencing using the MiSeq system (Fig. 1) and performed a taxon-based and phylogenetic analysis. Total DNA was extracted from the fecal samples and PCRamplified with unique 8-bp barcoded primer sets targeting the 347-803 V3-to-V4 hypervariable regions. The 460bp PCR amplicons were pooled in equal molar amounts and sent for library preparation and sequencing. RESULTS: A single MiSeq run generated a total of ;10 million paired reads. Our quality report revealed more than 95% reads with the average sequencing quality score passing Q30 and more than 50% reads with the quality of any individual base calling passing Q30. After merging, filtering by quality of the individual base calling and read length (>400bp), we obtained, on average, ;10 thousand reads per sample. QIIME pipeline(2) was applied for taxonomy assignment (Fig. 2a) and diversity analysis. Repeated measurements of 8 subjects showed high correlations (r² > 0.99). We observed a!

BACKGROUND: Recent advances in next-generation DNA sequencing enable rapid high-throughput quantitation of microbial community composition in human samples, opening up a new field of microbiomics. One of the promises of this field is linking abundances of microbial taxa to phenotypic and physiological states, which can inform development of new diagnostic, personalized medicine, and forensic modalities. Prior research has demonstrated the feasibility of applying machine learning methods to perform body site and subject classification with microbiomic data. However, it is currently unknown which classifiers perform best among the many available alternatives for classification with microbiomic data. RESULTS: In this work, we performed a systematic comparison of 18 major classification methods, 5 feature selection methods, and 2 accuracy metrics using 8 datasets spanning 1,802 human samples and various classification tasks: body site and subject classification and diagnosis. CONCLUSIONS: We found that random forests, support vector machines, kernel ridge regression, and Bayesian logistic regression with Laplace priors are the most effective machine learning techniques for performing accurate classification from these microbiomic data.