Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics.

Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations.

Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics.

Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies.

SiftCell: A robust framework to detect and isolate cell-containing droplets from single-cell RNA sequence reads.

Single-cell RNA sequencing (scRNA-seq) massively profiles transcriptomes of individual cells encapsulated in barcoded droplets in parallel. However, in real-world scRNA-seq data, many barcoded droplets do not contain cells, but instead, they capture a fraction of ambient RNAs released from damaged or lysed cells. A typical first step to analyze scRNA-seq data is to filter out cell-free droplets and isolate cell-containing droplets, but distinguishing them is often challenging; incorrect filtering may mislead the downstream analysis substantially.

Single cell and spatial sequencing define processes by which keratinocytes and fibroblasts amplify inflammatory responses in psoriasis.

The immunopathogenesis of psoriasis, a common chronic inflammatory disease of the skin, is incompletely understood. Here we demonstrate, using a combination of single cell and spatial RNA sequencing, IL-36 dependent amplification of IL-17A and TNF inflammatory responses in the absence of neutrophil proteases, which primarily occur within the supraspinous layer of the psoriatic epidermis. We further show that a subset of SFRP2 fibroblasts in psoriasis contribute to amplification of the immune network through transition to a pro-inflammatory state.

TREM2 macrophages induced by human lipids drive inflammation in acne lesions.

Acne affects 1 in 10 people globally, often resulting in disfigurement. The disease involves excess production of lipids, particularly squalene, increased growth of , and a host inflammatory response with foamy macrophages. By combining single-cell and spatial RNA sequencing as well as ultrahigh-resolution Seq-Scope analyses of early acne lesions on back skin, we identified TREM2 macrophages expressing lipid metabolism and proinflammatory gene programs in proximity to hair follicle epithelium expressing squalene epoxidase.

Microscopic examination of spatial transcriptome using Seq-Scope.

Spatial barcoding technologies have the potential to reveal histological details of transcriptomic profiles; however, they are currently limited by their low resolution. Here, we report Seq-Scope, a spatial barcoding technology with a resolution comparable to an optical microscope. Seq-Scope is based on a solid-phase amplification of randomly barcoded single-molecule oligonucleotides using an Illumina sequencing platform.

Holistic characterization of single-hepatocyte transcriptome responses to high-fat diet.

During nutritional overload and obesity, hepatocyte function is grossly altered, and a subset of hepatocytes begins to accumulate fat droplets, leading to nonalcoholic fatty liver disease (NAFLD). Recent single-cell studies revealed how nonparenchymal cells, such as macrophages, hepatic stellate cells, and endothelial cells, heterogeneously respond to NAFLD. However, it remains to be characterized how hepatocytes, the major constituents of the liver, respond to nutritional overload in NAFLD.

Exemestane may be less detrimental than letrozole to bone health in women homozygous for the UGT2B17*2 gene deletion.

Purpose: UGT2B17 gene deletion (UGT2B17*2) has been reported to affect bone health as well as the pharmacokinetics of aromatase inhibitor (AI) drugs such as exemestane. The goal of this study was to assess associations between UGT2B17 gene deletion and bone health prior to and after 24 months of AI treatment in postmenopausal women with hormone receptor positive (HR+) breast cancer.

Methods: Bone health in women with HR+ breast cancer enrolled on the prospective randomized Exemestane and Letrozole Pharmacogenetics (ELPh) trial was determined by measuring bone turnover markers (BTM) and bone mineral density (BMD) pre-treatment and after 3 BTM and 24 BMD months of treatment with either the steroidal AI exemestane or the nonsteroidal AI letrozole.

Comparison of Nine Tools for Screening Drug-Drug Interactions of Oral Oncolytics.

Purpose: Patients with cancer are an especially vulnerable population to potential drug-drug interactions (DDIs). This makes it important to adequately screen them for DDIs. The objective of this study was to compare the abilities of nine DDI screening tools to detect clinically relevant interactions with oral oncolytics.

Attempted replication of SNPs in RANKL and OPG with musculoskeletal adverse events during aromatase inhibitor treatment for breast cancer.

Aromatase inhibitor (AI) therapy is highly efficacious in the treatment of estrogen receptor-positive breast cancer; however, in a subset of patients AI use is discontinued due to drug-induced musculoskeletal adverse events (MS-AE). Several studies have investigated the role of germline single nucleotide polymorphisms (SNPs) on patients' risk of MS-AEs; however, no associations have yet to be validated for translation into clinical practice. This study attempted to replicate SNPs in RANKL ( rs7984870 ) and OPG ( rs2073618 ) on the risk of AI-induced MS-AEs and screen for secondary associations with MS-AE-related treatment discontinuation and serum and urine markers of bone health.