Adam B. Olshen

Background: Diabetic peripheral neuropathy (DPN) and chemotherapy-induced peripheral neuropathy (CIPN) are major clinical challenges with limited therapeutic options. While these conditions arise from different causes, they may share common molecular mechanisms that could be targeted for intervention. Methods: We performed consensus weighted gene co-expression network analysis (WGCNA) on two publicly available datasets: GSE185011 (DPN vs healthy controls in peripheral blood mononuclear cells) and GSE173610 (paclitaxel-treated vs control iPSC-derived sensory neurons). After filtering all but the most variable genes, consensus analysis was used to identify conserved co-expression modules across both conditions. Results: Consensus analysis identified a 193-gene module (ME3/brown) significantly associated with both DPN (correlation = 0.817, p = 0.0040) and CIPN (correlation = 0.971, p = 0.0060). Functional enrichment analysis of this module revealed pathways related to Glycolysis, FoxO signaling, Apoptosis, and Autophagy. Conclusions: Our analysis reveals a convergent molecular signature underlying both DPN and CIPN, centered on metabolic reprogramming, transcriptional stress, and programmed cell death. These findings provide a systems-level framework for developing therapies targeting shared pathological mechanisms.

Tanning bed users have a significantly increased risk of melanoma, but it remains unclear how indoor tanning drives melanomagenesis. To better understand the etiology of melanoma associated with tanning bed use, we described the patterns of melanoma in patients with quantifiable tanning bed usage and performed exome sequencing of melanocytes from normal skin of a subset of these patients. Tanning bed users were more likely to have melanoma on body sites with low cumulative levels of sun damage and to have multiple melanomas. The melanocytes in skin from tanning bed users had higher mutation burdens and higher proportions of cells with pathogenic mutations—these differences were most prominent over body sites that experience comparatively less exposure to natural sunlight. We conclude that tanning bed radiation induces melanoma by increasing the mutation burden of melanocytes and by mutagenizing a broader field of melanocytes than are typically exposed to natural sunlight.

Background: Diabetic peripheral neuropathy (DPN) and chemotherapy-induced peripheral neuropathy (CIPN) are major clinical challenges with limited therapeutic options. While these conditions arise from different causes, they may share common molecular mechanisms that could be targeted for intervention. Methods: We performed consensus weighted gene co-expression network analysis (WGCNA) on two publicly available datasets: GSE185011 (DPN vs. healthy controls in peripheral blood mononuclear cells) and GSE173610 (paclitaxel-treated vs. control iPSC-derived sensory neurons). After filtering all but the most variable genes, consensus analysis was used to identify conserved co-expression modules across both conditions. Results: Consensus analysis identified a 193-gene module (ME3/brown) significantly associated with both DPN (correlation=0.817, p=0.0040) and CIPN (correlation=0.971, p=0.0060). Functional enrichment analysis of this module revealed pathways related to Glycolysis, FoxO signaling, Apoptosis, and Autophagy. Conclusions: Our analysis reveals a convergent molecular signature underlying both DPN and CIPN, centered on metabolic reprogramming, transcriptional stress, and programmed cell death. These findings provide a systems-level framework for developing therapies targeting shared pathological mechanisms.

Introduction: Lipopolysaccharide (LPS), a major component of gram-negative bacterial cell walls, elicits strong innate immune activation and is a widely used model for studying inflammatory responses. While the transcriptional response to LPS stimulation has been characterized, the role of alternative splicing (AS) in modulating this response remains largely unexplored. Methods: Using deep RNA sequencing of Peripheral Blood Mononuclear Cells from three healthy female donors, we evaluated transcriptome-wide differential gene expression and alternative splicing in response to LPS stimulation. Results: Our global differential gene expression and pathway impact analyses identified 490 differentially expressed genes and 46 significantly perturbed KEGG pathways, recapitulating known LPS-induced inflammatory responses and identifying two novel signaling pathways, (e.g., SNARE interactions in vesicular transport and the mRNA surveillance pathways). Differential alternative splicing analysis revealed critical impacts on immune-related pathways, including Toll-like receptor signaling, PI3K/AKT signaling, and pro-inflammatory macrophage polarization. Notably, we identified alternative splicing events in genes such as MyD88 and TLR4 , which play key roles in terminating inflammatory signaling, as well as splicing of long non-coding RNAs (e.g., MALAT1 , PVT1 ) with potential regulatory functions in immune responses. Discussion: This study is the first transcriptome-wide characterization of alternative splicing in response to LPS stimulation in PBMCs. Our findings suggest that alternative splicing is a fundamental regulatory mechanism in the inflammatory response and provides potential targets for therapeutic intervention in immune-related conditions.

BioStudies – one package for all the data supporting a study

Introduction Fatigue is the most common and debilitating symptom experienced by cancer patients undergoing chemotherapy (CTX). Prediction of symptom severity can assist clinicians to identify high-risk patients and provide education to decrease symptom severity. The purpose of this study was to predict the severity of morning fatigue in the week following the administration of CTX. Methods Outpatients (n = 1217) completed questionnaires 1 week prior to and 1 week following administration of CTX. Morning fatigue was measured using the Lee Fatigue Scale (LFS). Separate prediction models for morning fatigue severity were created using 157 demographic, clinical, symptom, and psychosocial adjustment characteristics and either morning fatigue scores or individual fatigue item scores. Prediction models were created using two regression and five machine learning approaches. Results Elastic net models provided the best fit across all models. For the EN model using individual LFS item scores, two of the 13 individual LFS items (i.e., “worn out,” “exhausted”) were the strongest predictors. Conclusions This study is the first to use machine learning techniques to accurately predict the severity of morning fatigue from prior to through the week following the administration of CTX using total and individual item scores from the Lee Fatigue Scale (LFS). Our findings suggest that the language used to assess clinical fatigue in oncology patients is important and that two simple questions may be used to predict morning fatigue severity.

Background: A psychological symptom cluster is the most common cluster identified in oncology patients. Although inflammatory mechanisms are hypothesized to underlie this cluster, epigenetic contributions are unknown. Objectives: This study’s purpose was to evaluate associations between the occurrence of a psychological symptom cluster and levels of DNA methylation for inflammatory genes in a heterogeneous sample of patients with cancer receiving chemotherapy. Methods: Prior to their second or third cycle of chemotherapy, 1,071 patients reported the occurrence of 38 symptoms using the Memorial Symptom Assessment Scale. A psychological cluster was identified using exploratory factor analysis. Differential methylation analyses were performed in two independent samples using Illumina Infinium 450K and EPIC microarrays. Expression-associated CpG (eCpG) loci in the promoter region of 114 inflammatory genes on the 450K and 112 genes on the EPIC microarray were evaluated for associations with the psychological cluster. Robust rank aggregation was used to identify differentially methylated genes across both samples. Significance was assessed using a false discovery rate of 0.05 under the Benjamini–Hochberg procedure. Results: Cluster of differentiation 40 (CD40) was differentially methylated across both samples. All six promoter eCpGs for CD40 that were identified across both samples were hypomethylated in the psychological cluster group. Conclusions: This study is the first to suggest associations between a psychological symptom cluster and differential DNA methylation of a gene involved in tissue inflammation and cell-mediated immunity. Our findings suggest that increased CD40 expression through hypomethylation of promoter eCpG loci is involved in the occurrence of a psychological symptom cluster in patients receiving chemotherapy. These findings suggest a direction for mechanistic studies.

Background: Gene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime. Results: We demonstrate the analyses using the tool are reproducible, up to 18x faster using the GPU, and scale linearly with increasing methylation loci. Conclusions: Torch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg.

Background: Methods for inferring the three-dimensional (3D) configuration of chromatin from conformation capture assays that provide strictly pairwise interactions, notably Hi-C, utilize the attendant contact matrix as input. More recent assays, in particular split-pool recognition of interactions by tag extension (SPRITE), capture multi-way interactions instead of solely pairwise contacts. These assays yield contacts that straddle appreciably greater genomic distances than Hi-C, in addition to instances of exceptionally high-order chromatin interaction. Such attributes are anticipated to be consequential with respect to 3D genome reconstruction, a task yet to be undertaken with multi-way contact data. However, performing such 3D reconstruction using distance-based reconstruction techniques requires framing multi-way contacts as (pairwise) distances. Comparing approaches for so doing, and assessing the resultant impact of long-range and multi-way contacts, are the objectives of this study. Results: We obtained 3D reconstructions via multi-dimensional scaling under a variety of weighting schemes for mapping SPRITE multi-way contacts to pairwise distances. Resultant configurations were compared following Procrustes alignment and relationships were assessed between associated Procrustes root mean square errors and key features such as the extent of multi-way and/or long-range contacts. We found that these features had surprisingly limited influence on 3D reconstruction, a finding we attribute to their influence being diminished by the preponderance of pairwise contacts. Conclusion: Distance-based 3D genome reconstruction using SPRITE multi-way contact data is not appreciably affected by the weighting scheme used to convert multi-way interactions to pairwise distances.