Cellular granules lacking boundary membranes harbor RNAs and their associated proteins and play diverse roles controlling the timing and location of protein synthesis. Formation of such granules was emulated by treatment of mouse brain extracts and human cell lysates with a biotinylated isoxazole (b-isox) chemical. Deep sequencing of the associated RNAs revealed an enrichment for mRNAs known to be recruited to neuronal granules used for dendritic transport and localized translation at synapses. Precipitated mRNAs contain extended 3' UTR sequences and an enrichment in binding sites for known granule-associated proteins. Hydrogels composed of the low complexity (LC) sequence domain of FUS recruited and retained the same mRNAs as were selectively precipitated by the b-isox chemical. Phosphorylation of the LC domain of FUS prevented hydrogel retention, offering a conceptual means of dynamic, signal-dependent control of RNA granule assembly.

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

The gene regulatory network (GRN) reveals the regulatory relationships among genes and can provide a systematic understanding of molecular mechanisms underlying biological processes. The importance of computer simulations in understanding cellular processes is now widely accepted; a variety of algorithms have been developed to study these biological networks. The goal of this study is to provide a comprehensive evaluation and a practical guide to aid in choosing statistical methods for constructing large scale GRNs. Using both simulation studies and a real application in E. coli data, we compare different methods in terms of sensitivity and specificity in identifying the true connections and the hub genes, the ease of use, and computational speed. Our results show that these algorithms performed reasonably well, and each method has its own advantages: (1) GeneNet, WGCNA (Weighted Correlation Network Analysis), and ARACNE (Algorithm for the Reconstruction of Accurate Cellular Networks) performed well in constructing the global network structure; (2) GeneNet and SPACE (Sparse PArtial Correlation Estimation) performed well in identifying a few connections with high specificity.

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

We constructed a lung cancer-specific database housing expression data and clinical data from over 6700 patients in 56 studies. Expression data from 23 genome-wide platforms were carefully processed and quality controlled, whereas clinical data were standardized and rigorously curated. Empowered by this lung cancer database, we created an open access web resource—the Lung Cancer Explorer (LCE), which enables researchers and clinicians to explore these data and perform analyses. Users can perform meta-analyses on LCE to gain a quick overview of the results on tumor vs non-malignant tissue (normal) differential gene expression and expression-survival association. Individual dataset-based survival analysis, comparative analysis, and correlation analysis are also provided with flexible options to allow for customized analyses from the user.

We determined the relationship between human papillomavirus (HPV) infection and the HPV types detected in 44 patients with squamous cell carcinoma, 10 laryngeal leukoplakia patients, and 12 patients evaluated for benign laryngeal conditions (controls). The sources of HPV DNA were from brushings from the upper respiratory tract and lesion (benign or malignant), oral rinses, and biopsies of patient lesions. Polymerase chain reaction (PCR) and DNA sequencing were used to identify and type HPV. We detected HPV in 25.0% (11/44) of patients with laryngeal cancer, in 30.0% (3/10) of patients with laryngeal leukoplakia, and in 16.7% (2/12) of noncancer controls. Patients with cancer were not more likely to be identified with oncogenic HPV types ( 18.2%) than either the leukoplakia group (20%) or the control group (16.7%). An increased risk of disease was associated with current tobacco use and former alcohol drinking in cancer patients versus controls and in leukoplakia patients versus controls (all p < .05). After we controlled for tobacco and alcohol effects on the risk of disease, exposure to oncogenic HPV types was associated with an increased risk of laryngeal cancer (odds ratio = 3.0) and of laryngeal leukoplakia (odds ratio = 6.0) compared to controls, although the results were not statistically significant. This study suggests that although HPV infection and HPV oncogenic types are not found at a higher frequency in laryngeal cancer or laryngeal leukoplakia as compared to controls, infection is associated with an increased risk of disease after controlling for the effects of alcohol and tobacco use.

The method of chemotherapy (i.e., intravascular, intrathecal, oral) might dictate the choice of NSAID/NSAID derivative used to treat/prevent a given type of cancer. Also, the p75 NTR tumor suppressor appears to be a common molecular mechanism that mediates the growth inhibiting effectiveness of these drugs.

Prostate stromal and epithelial cell communication is important in prostate functioning and cancer development. Primary human stromal cells from normal prostate stromal cells (PRSC) maintain a smooth muscle phenotype, whereas those from prostate cancer (6S) display reactive and fibroblastic characteristics. Dihydrotestosterone (DHT) stimulates insulin-like growth factor-I (IGF-I) production by 6S but not PSRC cells. Effects of reactive versus normal stroma on normal human prostate epithelial (NPE or PREC) cells are poorly understood. We co-cultured NPE plus 6S or PRSC cells to compare influences of different stromal cells on normal epithelium. Because NPE and PREC cells lose androgen receptor (AR) expression in culture, DHT effects must be modulated by associated stromal cells. When treated with camptothecin (CM), NPE cells, alone and in stromal co-cultures, displayed a dose-dependent increase in DNA fragmentation. NPE/6S co-cultures exhibited reduced CM-induced cell death with exposure to DHT, whereas NPE/PRSC co-cultures exhibited CM-induced cell death regardless of DHT treatment. DHT blocked CM-induced, IGF-I-mediated, NPE death in co-cultured NPE/6S cells without, but not with, added anti-IGF-I and anti-IGF-R antibodies. Lycopene consumption is inversely related to human prostate cancer risk and inhibits IGF-I and androgen signaling in rat prostate cancer. In this study, lycopene, in dietary concentrations, reversed DHT effects of 6S cells on NPE cell death, decreased 6S cell IGF-I production by reducing AR and beta-catenin nuclear localization and inhibited IGF-I-stimulated NPE and PREC growth, perhaps by attenuating IGF-I's effects on serine phosphorylation of Akt and GSK3beta and tyrosine phosphorylation of GSK3. This study expands the understanding of the preventive mechanisms of lycopene in prostate cancer.