Biology subjects

Skinner, H.

Publications and source records attributed to Skinner, H..

4 recordsLinked to original sources

bioRxiv2026

Integrative multi-omic analysis identifies tumor-intrinsic p38 as a driver of immune exclusion in human epithelial cancers

Patients with tumors not responding to immune-checkpoint inhibition (ICI) often harbor a non-T cell-inflamed tumor microenvironment, characterized by the absence of IFN-{gamma}-associated CD8+ T cells and dendritic cell activation. While the role of p38 mitogen-activated protein kinases (MAPKs) in regulating dendritic and myeloid cells is established, the tumor-intrinsic immunomodulatory function of p38 remains underexplored. Here, we identify tumor cell-intrinsic p38 signaling as a target candidate associated with immune exclusion and reduced immunotherapy response. In human papillomavirus-negative head and neck squamous carcinoma (HNSCC), molecular analysis of 395 tumor tissues revealed a p38-centered network enriched in non-T cell-inflamed tumors. Multi-cancer single-cell RNA sequencing analysis of over 200,000 cells further identifies p38 activation as a potential immune-exclusion program across multiple epithelial tumor types, including HNSCC and lung squamous cell carcinoma (LUSC), supported by tissue validation in [~]250 human biospecimens using multispectral imaging and digital spatial profiling. Functional studies demonstrate that p38 knockdown or pharmacologic inhibition in HNSCC and LUSC cell lines increases T cell migration, with CXCL16 identified as a chemokine mediator in vitro; neutralization of CXCL16 attenuated this effect. Together, these findings identify tumor-intrinsic p38 activation as a driver of immune exclusion in epithelial cancers and support its potential as a therapeutic target to overcome immunotherapy resistance.

Cancer Biology↗

bioRxiv2024

Reliable RNA-seq analysis from FFPE specimens as a means to accelerate cancer-related health disparities research

Whole transcriptome sequencing (WTS/ RNA-Seq) is a ubiquitous tool for investigating cancer biology. RNA isolated from frozen sources limits possible studies for analysis of associations with phenotypes or clinical variables requiring long-term follow-up. Although good correlations are reported in RNA-Seq data from paired frozen and formalin fixed paraffin embedded (FFPE) samples, uncertainties regarding RNA quality, methods of extraction, and data reliability are hurdles to utilization of archival samples. We compared three different platforms for performing RNA-seq using archival FFPE oropharyngeal squamous carcinoma (OPSCC) specimens stored up to 20 years, as part of an investigation of transcriptional profiles related to health disparities. We developed guidelines to purify DNA and RNA from FFPE tissue and perform downstream RNA-seq and DNA SNP arrays. RNA was extracted from 150 specimens, with an average yield of 401.8 ng/cm2 of tissue. Most samples yielded sufficient RNA reads >13,000 protein coding genes which could be used to differentiate HPV-associated from HPV-independent OPSCCs. Co-isolated DNA was used to identify patient ancestry. Utilizing the methods described in this study provides a robust, reliable, and standardized means of DNA & RNA extraction from FFPE as well as a means by which to assure the quality of the data generated.

cancer biology↗

bioRxiv2024

Purified diets containing high levels of soluble fiber and grain-based diets promote similar gastrointestinal morphometry yet distinct microbial communities

Grain-based diets (GBDs) are widely used in rodent studies but their utility is limited due to batch-to-batch variability resulting from inconsistent ingredients. Purified diets (PDs) are composed of only known and refined ingredients and offer a solution to the constraints of GBDs. However, unlike GBDs, PDs commonly used as control diets typically contain little to no soluble fiber. We therefore sought to identify a combination of fibers in PDs that best recapitulates the gastrointestinal morphometry and intestinal microbial composition of mice fed GBDs. Adult male mice (n=30) were randomly assigned to one of six diets--two GBDs and four PDs with varying insoluble and soluble fiber composition--for 28 days. 16S rRNA gene sequencing was used to compare microbial profiles across different gastrointestinal (GI) niches and diets. Gut microbiotas and cecal weights were distinct between mice fed the two GBDs, indicating that GBDs are unreliable controls in diet-based studies. Unexpectedly, intestinal microbial richness decreased as the amount of soluble fiber in the PDs increased and the addition of multiple soluble fibers did not rescue this effect. Mice fed PDs with high soluble fiber content ([≥] 75% of dietary fiber was soluble fiber) best recapitulated GI morphometry of mice fed GBDs, but intestinal microbial communities were distinct between PD- and GBD-fed mice. Although supplementing PDs with soluble fiber improved GI morphometry, further research to determine the optimal mixture of soluble and insoluble fibers is required to more closely mirror the intestinal microbial diversity observed in mice fed GBDs. ImportanceDietary fibers are essential for maintaining gut health. Insoluble fibers aid in fecal bulking and water retention while soluble fiber is a fermentative substrate for intestinal microbial communities. GBDs are commonly used in preclinical research but the variability in ingredients across batches impedes reproducibility. PDs, which are composed of highly refined ingredients, pose a potential solution but the most widely used low-fat control PDs contain no soluble fiber. This study intended to identify a PD with a combination of fibers that promotes murine gut health and microbial diversity. A PD with optimal fiber composition would aid in the standardization and reproducibility of studies investigating intestinal physiology and the gut microbiota.

microbiology↗

bioRxiv2017

Imaging-Genomics Study Of Head-Neck Squamous Cell Carcinoma: Associations Between Radiomic Phenotypes And Genomic Mechanisms Via Integration Of TCGA And TCIA

PurposeRecent data suggest that imaging radiomics features for a tumor could predict important genomic biomarkers. Understanding the relationship between radiomic and genomic features is important for basic cancer research and future patient care. For Head and Neck Squamous Cell Carcinoma (HNSCC), we perform a comprehensive study to discover the imaging-genomics associations and explore the potential of predicting tumor genomic alternations using radiomic features.\n\nMethodsOur retrospective study integrates whole-genome multi-omics data from The Cancer Genome Atlas (TCGA) with matched computed tomography imaging data from The Cancer Imaging Archive (TCIA) for the same set of 126 HNSCC patients. Linear regression analysis and gene set enrichment analysis are used to identify statistically significant associations between radiomic imaging features and genomic features. Random forest classifier is used to predict two key HNSCC molecular biomarkers, the status of human papilloma virus (HPV) and disruptive TP53 mutation, based on radiomic features.\n\nResultsWide-spread and statistically significant associations are discovered between genomic features (including miRNA expressions, protein expressions, somatic mutations, and transcriptional activities, copy number variations, and promoter region DNA methylation changes of pathways) and radiomic features characterizing the size, shape, and texture of tumor. Prediction of HPV and TP53 mutation status using radiomic features achieves an area under the receiver operating characteristics curve (AUC) of 0.71 and 0.641, respectively.\n\nConclusionOur analysis suggests that radiomic features are associated with genomic characteristics in HNSCC and provides justification for continued development of radiomics as biomarkers for relevant genomic alterations in HNSCC.

cancer biology↗