The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

Integrative analysis of 111 reference human epigenomes

Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

This Perspective explores and explains the fundamental dogma of nanoparticle delivery to tumours and answers two central questions: ‘how many nanoparticles accumulate in a tumour?’ and ‘how does this number affect the clinical translation of nanomedicines?’

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Analysis of nanoparticle delivery to tumours

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique-cross-trait LD Score regression-for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

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An atlas of genetic correlations across human diseases and traits.

AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

Simple Summary Gallbladder disease (GBD) has been linked to small bowel cancer, but earlier reports have been based on a few cancer cases and no previous studies have adjusted for potential confounders. We report a 1.4-fold increased risk of small bowel adenocarcinoma, 1.8-fold increased risk of adenomas, and a 2.1-fold increased risk of carcinoids in patients with GBD compared to matched comparators. Absolute risks were low, however (<1 per 1000 patients followed for 10 years) for all three outcomes. We lacked detailed data on body mass index, cigarette smoking, and GBD biomarkers. Further results from an observational study, like ours, cannot establish a causal relationship or rule out the presence of residual confounding. The increased risk of carcinoid, seen 11–16 years after GBD diagnosis, may represent an etiologically plausible causal link to carcinoid development and warrants further study. The reported low absolute risks argue against targeted surveillance for small bowel cancer after GBD diagnosis. In conclusion, this study reports a moderately increased relative risk of small bowel cancers and adenomas in patients with GBD; absolute risks were however low. Abstract Background and aims: Small bowel cancer is a rare but rising malignancy. The etiology is poorly understood and there is a need for large-scale studies. Gallbladder disease (GBD), inducing localized inflammation, has been suggested to increase small bowel cancer risk. Methods: We retrieved nationwide data from Sweden’s 28 pathology departments on all adults (age 20–79) with pathology-confirmed GBD diagnosed in 1965–2017. In total 156,390 GBD patients were matched with up to 5 matched comparators from the general population and follow-up started one year after GBD diagnosis. We used stratified Cox regression to calculate hazard ratios (HRs) for small bowel adenocarcinoma, adenomas, and carcinoids. Results: During a median follow-up of 12 years, we identified 92 small bowel adenocarcinomas, 132 adenomas, and 81 carcinoid tumors in the GBD cohort. Corresponding incidence rates were 4.8, 6.9, and 4.2 per 100,000 person-years (PY), compared to 3.2, 3.2, and 1.8 in matched comparators. The adjusted HR was 1.42 (95% CI = 1.08–1.87) for small bowel adenocarcinoma, 1.79 (95% CI = 1.41–2.27) for adenoma, and 2.07 (95% CI = 1.52–2.81) for carcinoid. The excess cancer risk was most pronounced during the first year of follow-up for adenocarcinomas and during the first six years for adenomas while for carcinoids the HR peaked 10–15 years after start of follow-up. Conclusions: In this nationwide cohort study, GBD was associated with an increased risk of small bowel cancer. The excess risk of small bowel adenocarcinoma was mainly seen during the first years of follow-up while small bowel carcinoid risk peaked 11–16 years after GBD diagnosis.

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Gall Bladder Disease and the Risk of Small Bowel Cancer—Results from a Nationwide Swedish Cohort Study

Neural networks play very significant role when it comes to analysis of proteins and nucleic acid sequences. Many of the pattern recognition software are based on neural networks for prediction of biological patterns. Modern sequencing advancement fuels up the collection of data related to DNA, RNA, and protein sequences. The complexity and enormous size of this data require best computational algorithms for analysis and interpretation. This information will assist in developing useful insight for biomolecular structural predictions and prediction of interactions between such molecules. A neural system investigation framework is a succession of computations that attempts to see concealed associations in a lot of data through a technique that imitates the way where the human mind works. In this sense, neural frameworks suggest systems of neurons, artificial in nature. Vectors and matrices based linear algebra and topology designs supported various types of neural architectures. Neural frameworks can conform to advancing info; so the framework makes the best result without hoping to refresh the yield rules. The possibility of neural frameworks, which has its basic establishments in man-made consciousness, is rapidly getting ubiquity in the progression of in silico designing systems. Here, we talk about and sum up the uses of Neural Networks in computational biology, with a specific spotlight on applications in protein and Nucleic acid bioinformatics. We concluded with giving basic insights of neural networks in multiple domains of life sciences like gene prediction, protein structure prediction, epitope prediction, expression, co-expression, protein–protein interaction, and many other domains.

Neural Network Analysis

Tu1632 – Association Between Bowel Movements and Diverticulitis in Women

Background: Hyperactive PI3K signaling is associated with a more aggressive subtype of estrogen receptor (ER) positive breast cancer (BC) and with endocrine resistance. Loss or downregulation of PI3K9s inhibitor PTEN is more common in basal and luminal B vs. luminal A BC. However, the role of PTEN in modulating response to various endocrine therapies is unclear. Here we investigated the effects of PTEN knockdown (KD) on endocrine sensitivity and the potential of multiple kinase inhibitors to restore and improve responses. Methods: Nude mice bearing ER+ BC xenograft tumors of MCF7 cells stably expressing a doxycycline (Dox)-inducible PTEN-shRNA were randomized to four endocrine treatment groups [continued estrogen (E2) supplementation, or E2-deprivation (ED) alone or in combination with tamoxifen (Tam) or fulvestrant (Ful)]; all -/+ Dox. The effects of single or combined kinase inhibitors on these endocrine treatments -/+ Dox were studied in vitro using inhibitors (i) to mTOR (AZD2014, 0.2 μM), AKT (AZD5363, 1 μM), or MEK (Selumetinib/ARRY-142886, 1 μM). Cell growth, apoptosis, and ER and progesterone receptor (PR) signaling were analyzed using cell cytometry, qRT/PCR, and Western blotting. Synergism tests were used to examine the growth effects of the most promising combinatorial therapy with multiple kinase inhibitors in different endocrine settings. Results: In wild-type (WT) PTEN xenograft tumors, endocrine therapies were very effective, inducing frequent tumor regression. In PTEN KD tumors endocrine therapies were less effective — PTEN KD delayed tumor regression in all endocrine regimens and accelerated tumor progression in the Tam treated group. Furthermore, at day 250, only 1/8 and 0/7 tumors had developed resistance in the ED and the Ful (−Dox) groups, respectively, while with PTEN KD (+Dox), 7/15 and 5/15 tumors developed resistance to ED and to Ful. In vitro PTEN KD also induced resistance to all endocrine therapies. mRNA and/or protein levels of ER and PR were suppressed by PTEN KD and restored by mTORi and AKTi. In cells with WT PTEN, mTORi was highly effective with or without endocrine therapy. However, AKTi and MEKi were more effective in combination with endocrine therapy. All three inhibitors were less effective upon PTEN KD. The mTORi plus AKTi combination resulted in a potent synergistic inhibition in PTEN KD cells in the presence of E2 or with ED. In contrast, in the presence of Tam, AKTi plus MEKi, independent of PTEN status, was the most effective combination at the doses chosen. Finally, these inhibitors and combinations were more effective in the presence of Ful than ED or Tam in WT PTEN cells. AKTi combined with Ful was still highly effective even in PTEN KD cells, but mTORi and MEKi were less effective. Conclusions: Our results suggest that PTEN loss renders endocrine therapy less effective in in vitro and in vivo experimental models. Single AKT/MEK kinase inhibitors are more potent in the presence of endocrine therapy. In PTEN KD cells, the activity of all three kinase inhibitors is largely diminished, except for AKTi in the presence of fulvestrant. Kinase inhibitor combinations are generally more effective, but the optimal combinations vary by PTEN status and type of endocrine therapy. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr PD01-01.

Abstract PD01-01: Overcoming endocrine therapy resistance related to PTEN loss by strategic combinations with mTOR, AKT, or MEK inhibitors

Gold nanoshells with NIR plasmon resonance can be modified to simultaneously enhance conjugated NIR
fluorescence dyes and T2 contrast of embedded iron-oxide nanoparticles, and molecularly targeted to breast and other
cancers. We calibrated the theranostic performance of magneto-fluorescent nanoshells, and contrasted the performance
of molecularly targeted and untargeted nanoshells for breast cancer therapy, employing MCF-7L and their HER2 overexpressing
derivative MCF-7/HER2-18 breast cancer cells as in vitro model systems. Silica core gold nanoshells with
plasmon resonance on ~810 nm were doped with NIR dye ICG and ~10 nm iron-oxide nanoparticles in a ~20 nm epilayer
of silica. A subset of nanoshells was conjugated to antibodies targeting HER2. Cell viability with varying laser
power levels in presence and absence of bare and HER2-targeted nanoshells was assessed by calcein and propidium
iodide staining. For MCF-7L cells, increasing power resulted in increased cell death (F=5.63, p=0.0018), and bare
nanoshells caused more cell death than HER2-targeted nanoshells or laser treatment alone (F=30.13, p<0.001). For
MCF-7/HER2-18 cells, death was greater with HER2-targeted nanoshells and was independent of laser power. This
study demonstrates the capability of magneto-fluorescent nanocomplexes for imaging and therapy of breast cancer cells,
and the advantages of targeting receptors unique to cancer cells.

Amit Joshi

Papers

Gall Bladder Disease and the Risk of Small Bowel Cancer—Results from a Nationwide Swedish Cohort Study

Neural Network Analysis

Tu1632 – Association Between Bowel Movements and Diverticulitis in Women

Abstract PD01-01: Overcoming endocrine therapy resistance related to PTEN loss by strategic combinations with mTOR, AKT, or MEK inhibitors

Calibrating the imaging and therapy performance of magneto-fluorescent gold nanoshells for breast cancer