Many ways to land upright: novel righting strategies allow spotted lanternfly nymphs to land on diverse substrates.

Unlike large animals, insects and other very small animals are so unsusceptible to impact-related injuries that they can use falling for dispersal and predator evasion. Reorienting to land upright can mitigate lost access to resources and predation risk. Such behaviours are critical for the spotted lanternfly (SLF) (), an invasive, destructive insect pest spreading rapidly in the USA.

Correction: Novel Insight into Mutational Landscape of Head and Neck Squamous Cell Carcinoma.

[This corrects the article DOI: 10.1371/journal.pone.

Enter the Matrix: Factorization Uncovers Knowledge from Omics.

Omics data contain signals from the molecular, physical, and kinetic inter- and intracellular interactions that control biological systems. Matrix factorization (MF) techniques can reveal low-dimensional structure from high-dimensional data that reflect these interactions. These techniques can uncover new biological knowledge from diverse high-throughput omics data in applications ranging from pathway discovery to timecourse analysis.

Splice Expression Variation Analysis (SEVA) for inter-tumor heterogeneity of gene isoform usage in cancer.

Motivation: Current bioinformatics methods to detect changes in gene isoform usage in distinct phenotypes compare the relative expected isoform usage in phenotypes. These statistics model differences in isoform usage in normal tissues, which have stable regulation of gene splicing. Pathological conditions, such as cancer, can have broken regulation of splicing that increases the heterogeneity of the expression of splice variants.

Evaluating optimal therapy robustness by virtual expansion of a sample population, with a case study in cancer immunotherapy.

Cancer is a highly heterogeneous disease, exhibiting spatial and temporal variations that pose challenges for designing robust therapies. Here, we propose the VEPART (Virtual Expansion of Populations for Analyzing Robustness of Therapies) technique as a platform that integrates experimental data, mathematical modeling, and statistical analyses for identifying robust optimal treatment protocols. VEPART begins with time course experimental data for a sample population, and a mathematical model fit to aggregate data from that sample population.

PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF.

Summary: Non-negative Matrix Factorization (NMF) algorithms associate gene expression with biological processes (e.g. time-course dynamics or disease subtypes).

Integrative computational analysis of transcriptional and epigenetic alterations implicates DTX1 as a putative tumor suppressor gene in HNSCC.

Over a half million new cases of Head and Neck Squamous Cell Carcinoma (HNSCC) are diagnosed annually worldwide, however, 5 year overall survival is only 50% for HNSCC patients. Recently, high throughput technologies have accelerated the genome-wide characterization of HNSCC. However, comprehensive pipelines with statistical algorithms that account for HNSCC biology and perform independent confirmatory and functional validation of candidates are needed to identify the most biologically relevant genes.

CoGAPS matrix factorization algorithm identifies transcriptional changes in AP-2alpha target genes in feedback from therapeutic inhibition of the EGFR network.

Patients with oncogene driven tumors are treated with targeted therapeutics including EGFR inhibitors. Genomic data from The Cancer Genome Atlas (TCGA) demonstrates molecular alterations to EGFR, MAPK, and PI3K pathways in previously untreated tumors. Therefore, this study uses bioinformatics algorithms to delineate interactions resulting from EGFR inhibitor use in cancer cells with these genetic alterations.

Toward Signaling-Driven Biomarkers Immune to Normal Tissue Contamination.

The goal of this study was to discover a minimally invasive pathway-specific biomarker that is immune to normal cell mRNA contamination for diagnosing head and neck squamous cell carcinoma (HNSCC). Using Elsevier's MedScan natural language processing component of the Pathway Studio software and the TRANSFAC database, we produced a curated set of genes regulated by the signaling networks driving the development of HNSCC. The network and its gene targets provided prior probabilities for gene expression, which guided our CoGAPS matrix factorization algorithm to isolate patterns related to HNSCC signaling activity from a microarray-based study.

Outlier Analysis Defines Zinc Finger Gene Family DNA Methylation in Tumors and Saliva of Head and Neck Cancer Patients.

Head and Neck Squamous Cell Carcinoma (HNSCC) is the fifth most common cancer, annually affecting over half a million people worldwide. Presently, there are no accepted biomarkers for clinical detection and surveillance of HNSCC. In this work, a comprehensive genome-wide analysis of epigenetic alterations in primary HNSCC tumors was employed in conjunction with cancer-specific outlier statistics to define novel biomarker genes which are differentially methylated in HNSCC.

NF-κB and stat3 transcription factor signatures differentiate HPV-positive and HPV-negative head and neck squamous cell carcinoma.

Using high-throughput analyses and the TRANSFAC database, we characterized TF signatures of head and neck squamous cell carcinoma (HNSCC) subgroups by inferential analysis of target gene expression, correcting for the effects of DNA methylation and copy number. Using this discovery pipeline, we determined that human papillomavirus-related (HPV+) and HPV- HNSCC differed significantly based on the activity levels of key TFs including AP1, STATs, NF-κB and p53. Immunohistochemical analysis confirmed that HPV- HNSCC is characterized by co-activated STAT3 and NF-κB pathways and functional studies demonstrate that this phenotype can be effectively targeted with combined anti-NF-κB and anti-STAT therapies.

Correcting transcription factor gene sets for copy number and promoter methylation variations.

Gene set analysis provides a method to generate statistical inferences across sets of linked genes, primarily using high-throughput expression data. Common gene sets include biological pathways, operons, and targets of transcriptional regulators. In higher eukaryotes, especially when dealing with diseases with strong genetic and epigenetic components such as cancer, copy number loss and gene silencing through promoter methylation can eliminate the possibility that a gene is transcribed.

Two clinical phenotypes in polycythemia vera.

Background: Polycythemia vera is the ultimate phenotypic consequence of the V617F mutation in Janus kinase 2 (encoded by JAK2), but the extent to which this mutation influences the behavior of the involved CD34+ hematopoietic stem cells is unknown.

Methods: We analyzed gene expression in CD34+ peripheral-blood cells from 19 patients with polycythemia vera, using oligonucleotide microarray technology after correcting for potential confounding by sex, since the phenotypic features of the disease differ between men and women.

Results: Men with polycythemia vera had twice as many up-regulated or down-regulated genes as women with polycythemia vera, in a comparison of gene expression in the patients and in healthy persons of the same sex, but there were 102 genes with differential regulation that was concordant in men and women.

Outlier Analysis and Top Scoring Pair for Integrated Data Analysis and Biomarker Discovery.

Pathway deregulation has been identified as a key driver of carcinogenesis, with proteins in signaling pathways serving as primary targets for drug development. Deregulation can be driven by a number of molecular events, including gene mutation, epigenetic changes in gene promoters, overexpression, and gene amplifications or deletions. We demonstrate a novel approach that identifies pathways of interest by integrating outlier analysis within and across molecular data types with gene set analysis.

Expression microarray analysis reveals alternative splicing of LAMA3 and DST genes in head and neck squamous cell carcinoma.

Purpose: Prior studies have demonstrated tumor-specific alternative splicing events in various solid tumor types. The role of alternative splicing in the development and progression of head and neck squamous cell carcinoma (HNSCC) is unclear. Our study queried exon-level expression to implicate splice variants in HNSCC tumors.

Novel insight into mutational landscape of head and neck squamous cell carcinoma.

Development of head and neck squamous cell carcinoma (HNSCC) is characterized by accumulation of mutations in several oncogenes and tumor suppressor genes. We have formerly described the mutation pattern of HNSCC and described NOTCH signaling pathway alterations. Given the complexity of the HNSCC, here we extend the previous study to understand the overall HNSCC mutation context and to discover additional genetic alterations.

Activation of the NOTCH pathway in head and neck cancer.

NOTCH1 mutations have been reported to occur in 10% to 15% of head and neck squamous cell carcinomas (HNSCC). To determine the significance of these mutations, we embarked upon a comprehensive study of NOTCH signaling in a cohort of 44 HNSCC tumors and 25 normal mucosal samples through a set of expression, copy number, methylation, and mutation analyses. Copy number increases were identified in NOTCH pathway genes, including the NOTCH ligand JAG1.

The present state and future direction of integrated gene function analysis.

The determination of the function of the protein products of genes has been a major focus of molecular biology since the founding of the discipline. The development of knock-in, knock-down, and transgenic methodologies has greatly speeded laboratory discoveries, while the development of high-throughput measurement technologies for many molecular species has led to the emergence of computational methods capable of predicting functional relationships between genes. In the future, we should see the emergence of quantitative models based on integrated data and laboratory methods that elucidate context-specific functions and identify how gene function depends on changing partners and contexts.

Preferential activation of the hedgehog pathway by epigenetic modulations in HPV negative HNSCC identified with meta-pathway analysis.

Head and neck squamous cell carcinoma (HNSCC) is largely divided into two groups based on their etiology, human papillomavirus (HPV)-positive and -negative. Global DNA methylation changes are known to drive oncogene and tumor suppressor expression in primary HNSCC of both types. However, significant heterogeneity in DNA methylation within the groups results in different transcriptional profiles and clinical outcomes.

Pathways of Toxicity.

Despite wide-spread consensus on the need to transform toxicology and risk assessment in order to keep pace with technological and computational changes that have revolutionized the life sciences, there remains much work to be done to achieve the vision of toxicology based on a mechanistic foundation. To this end, a workshop was organized to explore one key aspect of this transformation - the development of Pathways of Toxicity as a key tool for hazard identification based on systems biology. Several issues were discussed in depth in the workshop: The first was the challenge of formally defining the concept of a Pathway of Toxicity (PoT), as distinct from, but complementary to, other toxicological pathway concepts such as mode of action (MoA).

Identifying context-specific transcription factor targets from prior knowledge and gene expression data.

Numerous methodologies, assays, and databases presently provide candidate targets of transcription factors (TFs). However, TFs rarely regulate their targets universally. The context of activation of a TF can change the transcriptional response of targets.

Implications of systemic dysfunction for the etiology of malignancy.

The current approach to treatment in oncology is to replace the generally cytotoxic chemotherapies with pharmaceutical treatment which inactivates specific molecular targets associated with cancer development and progression. The goal is to limit cellular damage to pathways perceived to be directly responsible for the malignancy. Its underlying assumptions are twofold: (1) that individual pathways are the cause of malignancy; and (2) that the treatment objective should be destruction-either of the tumor or the dysfunctional pathway.

ZNF-mediated resistance to imatinib mesylate in gastrointestinal stromal tumor.

Although imatinib mesylate (IM) has transformed the treatment of gastrointestinal stromal tumors (GIST), many patients experience primary/secondary drug resistance. In a previous study, we identified a gene signature, consisting mainly of Kruppel-associated box (KRAB) domain containing zinc finger (ZNF) transcriptional repressors that predict short-term response to IM. To determine if these genes have functional significance, a siRNA library targeting these genes was constructed and applied to GIST cells in vitro.

MAGEB2 is activated by promoter demethylation in head and neck squamous cell carcinoma.

Purpose: Although promoter hypermethylation has been an accepted means of tumor suppressor gene inactivation, activation of otherwise normally repressed proto-oncogenes by promoter demethylation has been infrequently documented.

Experimental Design: In this study we performed an integrative, whole-genome analysis for discovery of epigenetically activated proto-oncogenes in head and neck cancer tumors. We used the 47K GeneChip U133 Plus 2.

Updating annotations with the distributed annotation system and the automated sequence annotation pipeline.

Summary: The integration between BioDAS ProServer and Automated Sequence Annotation Pipeline (ASAP) provides an interface for querying diverse annotation sources, chaining and linking results, and standardizing the output using the Distributed Annotation System (DAS) protocol. This interface allows pipeline plans in ASAP to be integrated into any system using HTTP and also allows the information returned by ASAP to be included in the DAS registry for use in any DAS-aware system. Three example implementations have been developed: the first accesses TRANSFAC information to automatically create gene sets for the Coordinated Gene Activity in Pattern Sets (CoGAPS) algorithm; the second integrates annotations from multiple array platforms and provides unified annotations in an R environment; and the third wraps the UniProt database for integration with the SPICE DAS client.