Transposable element (TE)-derived sequences comprise more than half of the human genome, and their presence has been documented to alter gene expression in a number of different ways, including the generation of alternatively spliced transcript isoforms. Alternative splicing has been associated with tumorigenesis for a number of different cancers. The objective of this study was to broadly characterize the role of human TEs in generating alternatively spliced transcript isoforms in cancer. To do so, we screened for the presence of TE-derived sequences co-located with alternative splice sites that are differentially used in normal versus cancer tissues. We analysed a comprehensive set of alternative splice variants characterized for 614 matched normal-tumour tissue pairs across 13 cancer types, resulting in the discovery of 4820 TE-generated alternative splice events distributed among 723 cancer-associated genes. Short interspersed nuclear elements (Alu) and long interspersed nuclear elements (L1) were found to contribute the majority of TE-generated alternative splice sites in cancer genes. A number of cancer-associated genes, including MYH11 , WHSC1 and CANT1 , were shown to have overexpressed TE-derived isoforms across a range of cancer types. TE-derived isoforms were also linked to cancer-specific fusion transcripts, suggesting a novel mechanism for the generation of transcriptome diversity via trans -splicing mediated by dispersed TE repeats. This article is part of a discussion meeting issue ‘Crossroads between transposons and gene regulation'.

While overall cancer mortality has steadily decreased in recent decades, cancer health disparities among racial and ethnic population groups persist. Here we studied the relationship between cancer survival disparities (CSD), genetic ancestry (GA), and tumor molecular signatures across 33 cancers in a cohort of 9,818 patients. GA correlated with race and ethnicity but showed observable differences in effects on CSD, with significant associations identified in four cancer types: breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), and skin cutaneous carcinoma (SKCM). Differential gene expression and methylation between ancestry groups associated cancer-related genes with CSD, of which seven protein-coding genes (PAQR6, LIME1, SAP25, MXD3, CCER2, RFLNA, and CTSW) significantly interacted with GA and exacerbated observed survival disparities.These findings indicated that regulatory changes mediated by epigenetic mechanisms have a greater contribution to CSD than population-specific mutations. Overall, we uncovered various molecular mechanisms through which GA might impact CSD, revealing potential population-specific therapeutic targets for groups disproportionately burdened by cancer.

An integrated, parallel‐plate microfluidic device is engineered to interrogate and fractionate cells based on their adhesivity to a substrate surface functionalized with adhesive ligand in a tightly controlled flow environment to elucidate associated cell‐intrinsic pathways. Wall shear stress levels and endothelial presentation of E‐selectin are modeled after the inflamed vasculature microenvironment in order to simulate in vitro conditions under which in vivo hematogenous metastasis occurs. Based on elution time from the flow channel, the collection of separate fractions of cells—noninteracting and interacting—at high yields and viabilities enables multiple postperfusion analyses, including flow cytometry, in vivo metastasis modeling, and transcriptomic analysis. This platform enables the interrogation of flow‐regulated cell molecular profiles, such as (co)expression levels of natively expressed selectin ligands sLex, CD44, and carcinoembryonic antigen, and cancer stem cell marker CD24. This additionally reveals E‐selectin adhesivity exhibited by metastatic human colon carcinoma cells to be a transient phenotype. Facile and rapid, this methodology for unbiased, label free sorting of large populations of cells based on their adhesion in flow represents a method of studying flow‐regulated adhesion in vitro for the identification of molecular drug targets for development as antimetastatic cancer therapeutics.

Genome-wide association studies have uncovered thousands of genetic variants that are associated with a wide variety of human traits. Knowledge of how trait-associated variants are distributed within and between populations can provide insight into the genetic basis of group-specific phenotypic differences, particularly for health-related traits. We analyzed the genetic divergence levels for (i) individual trait-associated variants and (ii) collections of variants that function together to encode polygenic traits, between two neighboring populations in Colombia that have distinct demographic profiles: Antioquia (Mestizo) and Chocó (Afro-Colombian). Genetic ancestry analysis showed 62% European, 32% Native American, and 6% African ancestry for Antioquia compared to 76% African, 10% European, and 14% Native American ancestry for Chocó, consistent with demography and previous results. Ancestry differences can confound cross-population comparison of polygenic risk scores (PRS); however, we did not find any systematic bias in PRS distributions for the two populations studied here, and population-specific differences in PRS were, for the most part, small and symmetrically distributed around zero. Both genetic differentiation at individual trait-associated SNPs and population-specific PRS differences between Antioquia and Chocó largely reflected anthropometric phenotypic differences that can be readily observed between the populations along with reported disease prevalence differences. Cases where population-specific differences in genetic risk did not align with observed trait (disease) prevalence point to the importance of environmental contributions to phenotypic variance, for both infectious and complex, common disease. The results reported here are distributed via a web-based platform for searching trait-associated variants and PRS divergence levels at http://map.chocogen.com.