A case study: Assessing the efficacy of the revised dosage regimen via prediction model for recurrent event rate using biomarker data.

In recently conducted phase III trials in a rare disease area, patients received monthly treatment at a high dose of the drug, which targets to lower a specific biomarker level, closely associated with the efficacy endpoint, to around 10% across patients. Although this high dose demonstrated strong efficacy, treatments were withheld due to the reports of serious adverse events. Dosing in these studies were later resumed at a reduced dosage which targets to lower the biomarker level to 15%-35% across patients.

Transcriptional activation of Jun and Fos members of the AP-1 complex is a conserved signature of immune aging that contributes to inflammaging.

Diverse mouse strains have different health and life spans, mimicking the diversity among humans. To capture conserved aging signatures, we studied long-lived C57BL/6J and short-lived NZO/HILtJ mouse strains by profiling transcriptomes and epigenomes of immune cells from peripheral blood and the spleen from young and old mice. Transcriptional activation of the AP-1 transcription factor complex, particularly Fos, Junb, and Jun genes, was the most significant and conserved aging signature across tissues and strains.

BiFET: sequencing Bias-free transcription factor Footprint Enrichment Test.

Transcription factor (TF) footprinting uncovers putative protein-DNA binding via combined analyses of chromatin accessibility patterns and their underlying TF sequence motifs. TF footprints are frequently used to identify TFs that regulate activities of cell/condition-specific genomic regions (target loci) in comparison to control regions (background loci) using standard enrichment tests. However, there is a strong association between the chromatin accessibility level and the GC content of a locus and the number and types of TF footprints that can be detected at this site.

A pan-cancer analysis of driver gene mutations, DNA methylation and gene expressions reveals that chromatin remodeling is a major mechanism inducing global changes in cancer epigenomes.

Background: Recent large-scale cancer sequencing studies have discovered many novel cancer driver genes (CDGs) in human cancers. Some studies also suggest that CDG mutations contribute to cancer-associated epigenomic and transcriptomic alterations across many cancer types. Here we aim to improve our understanding of the connections between CDG mutations and altered cancer cell epigenomes and transcriptomes on pan-cancer level and how these connections contribute to the known association between epigenome and transcriptome.

Type 2 Diabetes-Associated Genetic Variants Regulate Chromatin Accessibility in Human Islets.

Type 2 diabetes (T2D) is a complex disorder in which both genetic and environmental risk factors contribute to islet dysfunction and failure. Genome-wide association studies (GWAS) have linked single nucleotide polymorphisms (SNPs), most of which are noncoding, in >200 loci to islet dysfunction and T2D. Identification of the putative causal variants and their target genes and whether they lead to gain or loss of function remains challenging.

The MiAge Calculator: a DNA methylation-based mitotic age calculator of human tissue types.

Cell division is important in human aging and cancer. The estimation of the number of cell divisions (mitotic age) of a given tissue type in individuals is of great interest as it allows not only the study of biological aging (using a new molecular aging target) but also the stratification of prospective cancer risk. Here, we introduce the MiAge Calculator, a mitotic age calculator based on a novel statistical framework, the MiAge model.

Alpha TC1 and Beta-TC-6 genomic profiling uncovers both shared and distinct transcriptional regulatory features with their primary islet counterparts.

Alpha TC1 (αTC1) and Beta-TC-6 (βTC6) mouse islet cell lines are cellular models of islet (dys)function and type 2 diabetes (T2D). However, genomic characteristics of these cells, and their similarities to primary islet alpha and beta cells, are undefined. Here, we report the epigenomic (ATAC-seq) and transcriptomic (RNA-seq) landscapes of αTC1 and βTC6 cells.

Association Between a Single General Anesthesia Exposure Before Age 36 Months and Neurocognitive Outcomes in Later Childhood.

Importance: Exposure of young animals to commonly used anesthetics causes neurotoxicity including impaired neurocognitive function and abnormal behavior. The potential neurocognitive and behavioral effects of anesthesia exposure in young children are thus important to understand.

Objective: To examine if a single anesthesia exposure in otherwise healthy young children was associated with impaired neurocognitive development and abnormal behavior in later childhood.

Randomized Trial of Oral Cyclophosphamide and Veliparib in High-Grade Serous Ovarian, Primary Peritoneal, or Fallopian Tube Cancers, or BRCA-Mutant Ovarian Cancer.

Purpose: Veliparib, a PARP inhibitor, demonstrated clinical activity in combination with oral cyclophosphamide in patients with BRCA-mutant solid tumors in a phase I trial. To define the relative contribution of PARP inhibition to the observed clinical activity, we conducted a randomized phase II trial to determine the response rate of veliparib in combination with cyclophosphamide compared with cyclophosphamide alone in patients with pretreated BRCA-mutant ovarian cancer or in patients with pretreated primary peritoneal, fallopian tube, or high-grade serous ovarian cancers (HGSOC).

Experimental Design: Adult patients were randomized to receive cyclophosphamide alone (50 mg orally once daily) or with veliparib (60 mg orally once daily) in 21-day cycles.

Using passenger mutations to estimate the timing of driver mutations and identify mutator alterations.

Background: Recent developments in high-throughput genomic technologies make it possible to have a comprehensive view of genomic alterations in tumors on a whole genome scale. Only a small number of somatic alterations detected in tumor genomes are driver alterations which drive tumorigenesis. Most of the somatic alterations are passengers that are neutral to tumor cell selection.

Estimating the order of mutations during tumorigenesis from tumor genome sequencing data.

Motivation: Tumors are thought to develop and evolve through a sequence of genetic and epigenetic somatic alterations to progenitor cells. Early stages of human tumorigenesis are hidden from view. Here, we develop a method for inferring some aspects of the order of mutational events during tumorigenesis based on genome sequencing data for a set of tumors.

Identifying cancer driver genes in tumor genome sequencing studies.

Motivation: Major tumor sequencing projects have been conducted in the past few years to identify genes that contain 'driver' somatic mutations in tumor samples. These genes have been defined as those for which the non-silent mutation rate is significantly greater than a background mutation rate estimated from silent mutations. Several methods have been used for estimating the background mutation rate.

Learning transcriptional networks from the integration of ChIP-chip and expression data in a non-parametric model.

Results: We have developed LeTICE (Learning Transcriptional networks from the Integration of ChIP-chip and Expression data), an algorithm for learning a transcriptional network from ChIP-chip and expression data. The network is specified by a binary matrix of transcription factor (TF)-gene interactions partitioning genes into modules and a background of genes that are not involved in the transcriptional regulation. We define a likelihood of a network, and then search for the network optimizing the likelihood.