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BackgroundThe tumor microenvironment (TME) is composed of highly heterogeneous extracellular structures and cell types such as endothelial cells, immune cells, and fibroblasts that dynamically influence and communicate with each other. The constant interaction between a tumor and its microenvironment plays a critical role in cancer development and progression and can significantly affect a tumor’s response to therapy and capacity for multi-drug resistance. High resolution analyses of gene and protein expression with spatial context can provide deeper insights into the interactions between tumor cells and surrounding cells within the TME, where a better understanding of the underlying biology can improve treatment efficacy and patient outcomes. Here, we demonstrated the ability to perform streamlined multi-omic tumor analyses by utilizing the 10X Genomics Visium Spatial Gene Expression Solution for FFPE with multiplex protein enablement. This technique simultaneously assesses gene and protein expression to elucidate the immunological profile and microenvironment of different breast cancer samples in conjunction with standard pathological methods.MethodsSerial (5 µm) sections of FFPE human breast cancer samples were placed on Visium Gene Expression (GEX) slides. The Visium GEX slides incorporate ~5,000 molecularly barcoded, spatially encoded capture spots onto which tissue sections are placed, stained, and imaged. Following incubation with a human whole transcriptome, probe-based RNA panel and an immuno-oncology oligo-tagged antibody panel, developed with Abcam conjugated antibodies, the tissues are permeabilized and the representative probes are captured. Paired GEX and protein libraries are generated for each section and then sequenced on an Illumina NovaSeq at a depth of ~50,000 reads per spot. Resulting reads from both libraries are aligned and overlaid with H&E-stained tissue images, enabling analysis of both mRNA and protein expression. Additional analyses and data visualizations were performed on the Loupe Browser v4.1 desktop software.ConclusionsSpatial transcriptomics technology complements pathological examination by combining histological assessment with the throughput and deep biological insight of highly-multiplexed protein detection and RNA-seq. Taken together, our work demonstrated that Visium Spatial technology provides a spatially-resolved, multi-analyte view of the tumor microenvironment, where a greater understanding of cellular behavior in and around tumors can help drive discovery of new biomarkers and therapeutic targets.

Background Hundreds of variants associated with atopic dermatitis (AD) and psoriasis, 2 common inflammatory skin disorders, have previously been discovered through genome-wide association studies (GWASs). The majority of these variants are in noncoding regions, and their target genes remain largely unclear. Objective We sought to understand the effects of these noncoding variants on the development of AD and psoriasis by linking them to the genes that they regulate. Methods We constructed genomic 3-dimensional maps of human keratinocytes during differentiation by using targeted chromosome conformation capture (Capture Hi-C) targeting more than 20,000 promoters and 214 GWAS variants and combined these data with transcriptome and epigenomic data sets. We validated our results with reporter assays, clustered regularly interspaced short palindromic repeats activation, and examination of patient gene expression from previous studies. Results We identified 118 target genes of 82 AD and psoriasis GWAS variants. Differential expression of 58 of the 118 target genes (49%) occurred in either AD or psoriatic lesions, many of which were not previously linked to any skin disease. We highlighted the genes AFG1L, CLINT1, ADO, LINC00302, and RP1-140J1.1 and provided further evidence for their potential roles in AD and psoriasis. Conclusions Our work focused on skin barrier pathology through investigation of the interaction profile of GWAS variants during keratinocyte differentiation. We have provided a catalogue of candidate genes that could modulate the risk of AD and psoriasis. Given that only 35% of the target genes are the gene nearest to the known GWAS variants, we expect that our work will contribute to the discovery of novel pathways involved in AD and psoriasis.

The tumor microenvironment (TME) is composed of highly heterogeneous structures and cell types that dynamically influence and communicate with each other. The constant interaction between a tumor and its microenvironment plays a critical role in how the cancer develops, progresses, and responds to therapies. Traditionally, Hematoxylin and Eosin (H&E) staining has been used to annotate and characterize tissues and associated pathologies. Recent single analyte approaches spatially interrogate targeted or transcriptome-wide expression of RNA in tissue sections, while others capture phenotypes using a limited number of protein markers. However, for a more comprehensive understanding of the unique characteristics of cell types, cell states, and cell-cell interactions within the TME, multiple layers of information are needed and must be studied together. Here we demonstrate a novel, streamlined multiomic spatial assay that integrates histological staining and imaging with simultaneous transcriptome-wide gene expression and highly multiplexed protein expression profiling from the same formalin-fixed paraffin embedded (FFPE) tissue section. In short, tissue sections from archived FFPE samples were placed on slides containing arrayed capture oligos with unique positional barcodes. The H&E or immunofluorescence stained tissues were then imaged, followed by incubation with transcriptome-wide probes and a high-plex DNA-barcoded antibody panel containing intra- and extracellular markers. Transcriptome probes and antibody-barcodes were then spatially captured on the slide and converted into sequencing-ready libraries. Our data analysis and interactive visualization software enable interrogation of all data layers (H&E/immunofluorescence, RNA, protein) from the same tissue section. We apply this method to simultaneously measure gene and protein expression within the TME of human breast cancer and melanoma FFPE samples using whole transcriptome probes and an immune-oncology antibody panel. The data enables comparison and correlation of multiple analytes and their patterns within the same sample section. In addition, this simultaneous detection enables marker-guided regional selection and differential gene expression analysis on the defined regions. Taken together, our data demonstrates that a spatially resolved, multiomic approach provides a more comprehensive understanding of cellular behavior in and around tumors, yielding new insights into disease progression, predictive biomarkers, drug response and resistance, and therapeutic development. Citation Format: Cedric Uytingco, Jennifer Chew, Naishitha Anaparthy, Jun D. Chiang, Christina Galonska, Karthik Ganapathy, Ryo Hatori, Alexander Hermes, Layla Katiraee, Anna-Maria Katsori, William Nitsch, Patrick Roelli, Joe Shuga, Rapolas Spalinskas, Mesruh Turkekul, Benton Veire, Dan Walker, Neil Weisenfeld, Stephen R. Williams, Zachary Bent, Marlon Stoeckius. Multiomic characterization of the tumor microenvironment in FFPE tissue by simultaneous protein and gene expression profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3814.

Macrophages are highly plastic immune cells with temporally distinct transcriptome changes upon lipopolysaccride (LPS) activation. However, to what extent transcriptome reprogramming is mediated via spatial chromatin looping is not well studied. We generated high resolution chromatin interaction maps for LPS-stimulated THP-1 macrophages (0 and 2 h) using capture Hi-C. Success of LPS stimulation was validated with transcriptome sequencing. Circa 2900 genes changed their interaction profile upon LPS stimulation and those gaining interactions were enriched for LPS response relevant processes, suggesting a substantial role for distal regulation. Immune and cardiovascular risk variants were enriched within the interacting regions, thereby providing insights into macrophage biology.

Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10−3 for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p Funding agencies: Swedish Cancer Society, the Swedish Research Council, Linköping University, ALF grants Region Östergötland, the Funds of Radiumhemmet, Marcus Borgströms stiftelse, Stiftelsen Assar Gabrielssons Fond

Supplemental Digital Content is available in the text., Background: Genetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease. Methods: In this study, we generated high-resolution genomic interaction maps (≈750 bases) in aortic endothelial, smooth muscle cells and THP-1 (human leukemia monocytic cell line) macrophages stimulated with lipopolysaccharide using Hi-C coupled with sequence capture targeting 25 429 features, including variants associated with coronary artery disease. We also sequenced their transcriptomes and mapped putative enhancers using chromatin immunoprecipitation with an antibody against H3K27Ac. Results: The regions interacting with promoters showed strong enrichment for enhancer elements and validated several previously known interactions and enhancers. We detected interactions for 727 risk variants obtained by genome-wide association studies and identified novel, as well as established genes and functions associated with cardiovascular diseases. We were able to assign potential target genes for additional 398 genome-wide association studies variants using haplotype information, thereby identifying additional relevant genes and functions. Importantly, we discovered that a subset of risk variants interact with multiple promoters and their expression levels were strongly correlated. Conclusions: In summary, we present a catalog of candidate genes regulated by coronary artery disease–related variants and think that it will be an invaluable resource to further the investigation of cardiovascular pathologies and disease.

Genetic variant landscape of cardiovascular disease (CVD) is dominated by non-coding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct gene both to gain insights into perturbed functions and better assess the risk of disease. In this study, we generated high-resolution genomic interaction maps (~750 bases) in aortic endothelial, smooth muscle and THP-1 macrophages using Hi-C coupled with sequence capture targeting 25,429 features including variants associated with CVD. We detected interactions for 761 CVD risk variants obtained by genome-wide association studies (GWAS) and identified novel as well as established functions associated with CVD. We were able to fine-map 331 GWAS variants using interaction networks, thereby identifying additional genes and functions. We also discovered a subset of risk variants interacting with multiple promoters and the expression levels of such genes were correlated. The presented resource enables functional studies of cardiovascular disease providing novel approaches for its diagnosis and treatment.

BAF complexes are composed of different subunits with varying functional and developmental roles, although many subunits have not been examined in depth. Here we show that the Baf45 subunit Dpf2 maintains pluripotency and ESC differentiation potential. Dpf2 co-occupies enhancers with Oct4, Sox2, p300, and the BAF subunit Brg1, and deleting Dpf2 perturbs ESC self-renewal, induces repression of Tbx3, and impairs mesendodermal differentiation without dramatically altering Brg1 localization. Mesendodermal differentiation can be rescued by restoring Tbx3 expression, whose distal enhancer is positively regulated by Dpf2-dependent H3K27ac maintenance and recruitment of pluripotency TFs and Brg1. In contrast, the PRC2 subunit Eed binds an intragenic Tbx3 enhancer to oppose Dpf2-dependent Tbx3 expression and mesendodermal differentiation. The PRC2 subunit Ezh2 likewise opposes Dpf2-dependent differentiation through a distinct mechanism involving Nanog repression. Together, these findings delineate distinct mechanistic roles for specific BAF and PRC2 subunits during ESC differentiation.

Loss-of-function studies are critically important in gene functional analysis of model organisms and cells. However, conditional gene inactivation in diploid cells is difficult to achieve, as it involves laborious vector construction, multifold electroporation, and complicated genotyping. Here, a strategy is presented for generating biallelic conditional gene and DNA regulatory region knockouts in mouse embryonic stem cells by codelivery of CRISPR-Cas9 and short-homology-arm targeting vectors sequentially or simultaneously. Collectively, a simple and rapid method was presented to knock out any DNA element conditionally. This approach will facilitate the functional studies of essential genes and regulatory regions during development.

Identification of genetically modified (GM) plants remains a difficult task, especially when few information on the GM content in a sample is available. The CaMV P-35S is a commonly applied genetic element in GM plants and represents as such a suitable starting point for the tracing of GM plants. Here, the application of a CaMV P-35S LT-RADE genome walking method on five different GM crops is documented: MON810 maize, LLRICE62 rice, T45 rapeseed, A2704-12 soybean and LLCOTTON25 cotton. Two sets of oligonucleotide primers are presented as a potential forward and reverse genome walking strategy with genomic DNA as template. The method’s applicability for assessing the recombinant nature of P-35S positive signals is discussed in detail. This study demonstrates the general use of LT-RADE in molecular characterization of GMOs retrieving several previously unknown transgenic insert nucleotide sequences. Current limitations and future developments are discussed.

Information on the insertion site and characterization of the transgene(s) in genetically modified organisms (GMO) is very important for safety assessment and identification of a GMO. The generation of such information in general and in particular in emergencies or rapid alert situations involving GMO greatly benefit from the availability of simple, efficient, and rapid approaches. Here, we report on the improvement of a restriction independent method named “Rapid Amplification of genomic DNA Ends” (RADE). The method was developed using maize event MON810 genomic DNA as a model system, testing a standard Taq polymerase or a blend of polymerases (standard Taq and proofreading Tgo polymerases (LT-RADE)). Both methods produce an initial single strand DNA, followed by nested PCR steps and yield easy-to-isolate DNA fragments for further manipulation. We showed that the application of the Taq/Tgo polymerase blend significantly increased the size of the obtained PCR products. Using LT-RADE, we could successfully isolate the flanking regions of the transgenic insert of the GM maize event MON810 and confirmed the existing data on the adjacent regions of the insert. In addition, application of our approach allowed to efficiently isolate and identify, for the first time, the DNA sequences surrounding the insert of GM rice event LLRICE62.