Abstract
The climate-driven species pump hypothesis has been supported in a number of phylogeographic studies of alpine species. Climate-driven shifts in distribution, coupled with rapid demographic ...change, have led to strong genetic drift and lineage diversification. Although the species pump has been linked to rapid speciation in a number of studies, few studies have demonstrated that ecological divergence accompanies rapid speciation. Here we examine genetic, morphological and physiological variation in members of the ground beetle taxon Nippononebria, to test three competing hypotheses of evolutionary diversification: isolation and incomplete lineage sorting (no speciation), recent speciation without ecological divergence, or recent speciation with ecological divergence into alpine habitats. Genetic data are consistent with recent divergence, with major lineages forming in the last million years. A species tree analysis, in conjunction with morphological divergence in male reproductive traits, support the formation of three recognized Nippononebria taxa. Furthermore, both morphological and physiological traits demonstrate ecological divergence in alpine lineages, with convergent shifts in body shape and thermal tolerance breadth. This provides strong evidence that the climate-driven species pump can generate ecological novelty, though it is argued that spatial scale may be a key determinant of broader patterns of macroevolution in alpine communities.
BackgroundThe tumor microenvironment (TME) is composed of highly heterogeneous cell types that dynamically interact 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. Traditional tissue-based studies of TME can be limited to a small number of target analytes, which can limit biological insights. In this work, we used the Visium CytAssist instrument and Visium CytAssist Spatial Gene and Protein Expression assay from 10x Genomics, which enables whole transcriptome gene expression and multiplexed protein expression profiling from the same formalin fixed & paraffin embedded (FFPE) tissue. Our data provides a more comprehensive understanding of cellular behavior in and around tumors, yielding new insights into disease progression and therapeutic response.MethodsTumor FFPE tissues (breast, prostate, lung, and ovarian cancer) were spatially profiled using the Visium CytAssist instrument and Visium CytAssist Spatial Gene and Protein Expression assay. Tissues were mounted on glass slides, then Hematoxylin & Eosin (H&E) or immunofluorescence (IF) stained. Following decrosslinking, the samples were incubated with RTL and antibody-conjugated probes, then prepared for probe transfer to spatially barcoded Visium slides with 6.5 x 6.5 or 11 x 11 mm capture areas. The captured probes were collected from the slides and used to generate sequencing-ready libraries for transcriptomic and proteomic analysis with spatial context.ResultsUsing the CytAssist workflow, we showcase the ability to spatially resolve oncogenes and immune cells associated with multiple tumor tissues. In the prostate cancer samples, strong correlation was observed between gene and protein expression for immune cell subsets such as activated T, B, and regulatory dendritic cells. CD274 demonstrates the ability to resolve protein expression data even when gene signal is low. Breast and lung cancer samples were screened with fluorescently labeled antibodies in addition to transcriptomic profiling. In particular, PCNA and Vimentin showed the precision and accuracy of probe transfer using the Visium CytAssist Spatial Gene and Protein Expression assay. Expression of these markers map back to distinct morphological features within the samples, allowing identification of differentially expressed genes and proteins associated with those areas.ConclusionsThese data highlight that Visium CytAssist can retrieve transcriptome and protein information from FFPE sections in a spatial context. Implementing Visium CytAssist Spatial Gene and Protein Expression Assay in immuno-oncology studies provides a more comprehensive understanding of clinical tissue samples and provides novel insights into architectural and cellular heterogeneity across multiple cancers.
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.
Abstract
The tumor microenvironment is composed of highly heterogeneous niches, often with varying degrees of immune infiltration. The spatial distribution of immune cells with respect to malignant ...cells can directly impact patient prognosis and overall survival outcomes. The Visium CytAssist Spatial Gene Expression assay uses a whole transcriptome probe-based approach, termed RTL, to detect and quantify mRNA expression with spatial context. Although examination of the tumor microenvironment with an RTL-based spatial assay can provide significant transcriptomic information concerning regions of interest, immune cells frequently have extremely low mRNA expression levels and can be difficult to detect. The use of antibody-conjugated probes specific to immune cell epitopes, which are highly expressed, can enhance data recovered from these tumor samples, enabling spatially accurate detection of immune populations. The Visium CytAssist Spatial Proteogenomic Solution enables identification of immune-specific epitopes via antibody-conjugated probes from the same tissue slide used for transcriptomic analysis. Using the CytAssist workflow, we showcase the ability to comprehensively resolve immune cells associated with multiple immune and tumor tissues, including an array of human breast cancer punches. Spatial expression patterns of immune markers map back to distinct morphological features within the samples, allowing identification of differentially-expressed genes associated with those areas. Overall, these data highlight the value of Visium CytAssist Spatial Proteogenomic Solution in immuno-oncology studies, through the integration of spatially resolved transcriptomic and immune cell marker data.
Abstract
The oscillating glacial–interglacial climate has had well-characterized effects on alpine species, driving rapid distributional and demographic shifts that have led to lineage ...diversification. It is unclear whether adaptive evolution has occurred during these rapid demographic changes, because strong genetic drift can overcome the force of selection. Here, using the alpine ground beetle Nebria vandykei, we test for evidence of adaptive evolution. Initially, we explore the genetic pathways induced during environmental stress responses through RNA sequencing, showing that cold, heat and desiccation stress activate a largely non-overlapping set of molecular pathways. Using additional transcriptome sequencing, we estimate the evolutionary relationship of N. vandykei to related species in the subgenus Catonebria and several outgroups. Phylogenetic analyses suggest that a history of admixture or very rapid diversification underlies the evolution of N. vandykei. Finally, using tests for selection polarized by high- and low-elevation relatives, we demonstrate selection acting on stress response pathways and on pathways known to function in tolerance to cold and hypoxic environments. These results support the role of environmental adaptation in alpine species despite rapid demographic change, while demonstrating that admixture might play a key role in facilitating adaptive diversification of alpine species.
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) and immunohistochemistry staining have 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, analysis of multiple analytes is necessary.
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 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 morphology, 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 areas. 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.
Abstract
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.
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