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We present a spatial omics approach that merges and expands the capabilities of independently performedin situassays on a single tissue section. Our spatial multimodal analysis combines histology, mass spectrometry imaging, and spatial transcriptomics to facilitate precise measurements of mRNA transcripts and low-molecular weight metabolites across tissue regions. We demonstrate the potential of our method using murine and human brain samples in the context of dopamine and Parkinson’s disease.

The lung contains numerous specialized cell types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a comprehensive topographic atlas of early human lung development. Here we report 83 cell states and several spatially resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated single-cell RNA sequencing and spatially resolved transcriptomics into a web-based, open platform for interactive exploration. We show distinct gene expression programmes, accompanying sequential events of cell differentiation and maturation of the secretory and neuroendocrine cell types in proximal epithelium. We define the origin of airway fibroblasts associated with airway smooth muscle in bronchovascular bundles and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas provides a rich resource for further research and a reference for defining deviations from homeostatic and repair mechanisms leading to pulmonary diseases.

Spatially resolved transcriptomics has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of methods targeting the polyA tails of mRNA relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available spatial resolved transcriptomics assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), a workflow designed to improve mRNA recovery from fresh frozen specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we test the RRST protocol on tissue sections collected from five challenging tissue types, including human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyze 52 tissue sections and demonstrate that RRST is a versatile, powerful, and reproducible protocol for fresh frozen specimens of different qualities and origins. ispartof: Nat Commun vol:14 issue:1 pages:509- ispartof: location:England status: Published online

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer1. Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics2 to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone. ispartof: NATURE BIOTECHNOLOGY vol:40 issue:4 pages:476-+ ispartof: location:United States status: published

Oncogene-induced senescence (OIS) is an inherent and important tumor suppressor mechanism. However, if not removed timely via immune surveillance, senescent cells also have detrimental effects. Although this has mostly been attributed to the senescence-associated secretory phenotype (SASP) of these cells, we recently proposed that "escape" from the senescent state is another unfavorable outcome. The mechanism underlying this phenomenon remains elusive. Here, we exploit genomic and functional data from a prototypical human epithelial cell model carrying an inducible CDC6 oncogene to identify an early-acquired recurrent chromosomal inversion that harbors a locus encoding the circadian transcription factor BHLHE40. This inversion alone suffices for BHLHE40 activation upon CDC6 induction and driving cell cycle re-entry of senescent cells, and malignant transformation. Ectopic overexpression of BHLHE40 prevented induction of CDC6-triggered senescence. We provide strong evidence in support of replication stress-induced genomic instability being a causative factor underlying "escape" from oncogene-induced senescence.

DNA fluorescence in situ hybridization (DNA FISH) is a powerful method to study chromosomal organization in single cells. At present, there is a lack of free resources of DNA FISH probes and probe design tools which can be readily applied. Here, we describe iFISH, an open-source repository currently comprising 380 DNA FISH probes targeting multiple loci on the human autosomes and chromosome X, as well as a genome-wide database of optimally designed oligonucleotides and a freely accessible web interface (http://ifish4u.org) that can be used to design DNA FISH probes. We individually validate 153 probes and take advantage of our probe repository to quantify the extent of intermingling between multiple heterologous chromosome pairs, showing a much higher extent of intermingling in human embryonic stem cells compared to fibroblasts. In conclusion, iFISH is a versatile and expandable resource, which can greatly facilitate the use of DNA FISH in research and diagnostics., DNA FISH allows for the visual analysis of chromosomal organisation in individual cells. Here the authors present iFISH, an open-source repository of ready-to-use DNA FISH probes along with tools for probe design.

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we provide an unsupervised approach to study spatial genome integrity in situ to describe previously unidentified clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120 000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Introduction: Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. In order to obtain spatial information of clonal genetic events, prior studies have used methods such as laser capture microdissection, which results in assessment of small regions or even single cells. These studies have an inherent bias as a limited number of regions per tissue section can be retrieved and examined. Furthermore, because investigators have selected such regions based on morphology, previous studies have limited their analyses to histologically defined tumour areas while excluding regions populated by benign cells. The possibility to perform unsupervised genome and tissue-wide analysis would therefore provide an important contribution to delineate clonal events. We sought study spatial genome integrity in situ to gain molecular insight into clonal relationships. Materials and Methods: We employed spatially resolved transcriptomics (Visium, 10x Genomics) to infer spatial copy number variations in >120 000 spatial regions across multiple organs, including three whole axial prostates and additional tissues from skin, breast and brain tumors. We used this information to deduce clonal relationships between regions harboring 5-20 cells. Results: We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue. We perform an in-depth spatial analysis of cancers that includes an unprecedented interrogation of up to 50,000 tissue domains in a single patient, and 120,000 tissue domains across 10 patients. In a prostate section, we observed that many CNVs occurred in histologically benign luminal epithelial cells, most notably in chromosomes 8 and 10. This clone constituted a region of exclusively benign acinar cells branching off a duct lined by largely copy neutral cells. The changes in these cells were shared with the nearby intermediate risk prostate cancer cells in the same tissue section. We observed similar findings in another patient’s cutaneous squamous cell carcinoma (cSCC), wherein benign squamous epithelial had alterations in chromosomes 1 and 12 that were shared with nearby cSCC. Our results suggest a model for how genomic instability arises in histo-pathologically benign tissue that may represent early events in cancer evolution. Furthermore the spatial information allowed us to identify small clonal units not evident from morphology and hence would be overlooked by pathologists. Conclusions: We present the first large-scale, comprehensive atlas of genomic evolution at high spatial resolution in prostate cancer. Our study adds an important new approach to the armamentarium of cancer molecular pathology. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for focal therapy in prostate cancer. Citation Format: Andrew Erickson, Emelie Berglund, Mengxiao He, Maja Marklund, Reza Mirzazadeh, Niklas Schultz, Linda Kvastad, Alma Andersson, Ludvig Bergenstråhle, Joseph Bergenstråhle, Ludvig Larsson, Alia Shamikh, Elisa Basmaci, Teresita Diaz De Ståhl, Timothy Rajakumar, Kim Thrane, Andrew L. Ji, Paul A. Khavari, Firaz Tarish, Anna Tanoglidi, Jonas Maaskola, Richard Colling, Tuomas Mirtti, Freddie Hamdy, Dan J. Woodcock, Thomas Helleday, Ian G. Mills, Alastair D. Lamb, Joakim Lundenberg. The spatial landscape of clonal somatic mutations in benign and malignant tissue [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 2171.

Introduction: Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. In order to obtain spatial information of clonal genetic events, prior studies have used methods such as laser capture microdissection, which results in assessment of small regions or even single cells. These studies have an inherent bias as a limited number of regions per tissue section can be retrieved and examined. Furthermore, because investigators have selected such regions based on morphology, previous studies have limited their analyses to histologically defined tumor areas while excluding regions populated by benign cells. The possibility to perform unsupervised genome and tissue-wide analysis would therefore provide an important contribution to delineate clonal events. We sought study spatial genome integrity in situ to gain molecular insight into clonal relationships. Materials and Methods: We employed spatially resolved transcriptomics (Visium, 10x Genomics) to infer spatial copy number variations in >120 000 spatial regions across multiple organs, including three whole axial prostates and additional tissues from skin, breast and brain tumors. We additionally performed in silico assessment of spatial copy number inference. We used this information to deduce clonal relationships between regions harboring 5-20 cells. Results: We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumors and in nearby benign tissue. We perform an in-depth spatial analysis of cancers that includes an unprecedented interrogation of up to 50,000 tissue domains in a single patient, and 120,000 tissue domains across 10 patients. In a prostate section, we observed that many CNVs occurred in histologically benign luminal epithelial cells, most notably in chromosomes 8 and 10. This clone constituted a region of exclusively benign acinar cells branching off a duct lined by largely copy neutral cells. The changes in these cells were shared with the nearby intermediate risk prostate cancer cells in the same tissue section. We observed similar findings in another patient’s cutaneous squamous cell carcinoma (cSCC), wherein benign squamous epithelial had alterations in chromosomes 1 and 12 that were shared with nearby cSCC. Our results suggest a model for how genomic instability arises in histo-pathologically benign tissue that may represent early events in cancer evolution. Furthermore the spatial information allowed us to identify small clonal units not evident from morphology and hence would be overlooked by pathologists. Conclusions: We present the first large-scale, comprehensive atlas of genomic evolution at high spatial resolution in prostate cancer. Our study adds an important new approach to the armamentarium of cancer molecular pathology. We highlight the power of an unsupervised approach to capture the molecular and spatial continuums in a tissue context and challenge the rationale for focal therapy in prostate cancer Citation Format: Andrew Erickson, Emelie Berglund, Mengxiao He, Maja Marklund, Reza Mirzazadeh, Niklas Schultz, Ludvig Bergenstråhle, Linda Kvastad, Alma Andersson, Joseph Bergenstråhle, Ludvig Larsson, Alia Shamikh, Elisa Basmaci, Teresita Diaz De Ståhl, Timothy Rajakumar, Kim Thrane, Andrew L. Ji, Paul A. Khavari, Firaz Tarish, Anna Tanoglidi, Jonas Maaskola, Richard Colling, Tuomas Mirtti, Freddie C. Hamdy, Dan J. Woodcock, Thomas Helleday, Ian G. Mills, Alastair D. Lamb, Joakim Lundeberg. The spatial landscape of clonal somatic mutations in benign and malignant tissue [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR016.

Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.

Current multiplexing strategies for massively parallel sequencing of genomic DNA mainly rely on library indexing in the final steps of library preparation. This procedure is costly and time-consuming, because a library must be generated separately for each sample. Furthermore, library preparation is challenging in the case of fixed samples, such as DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissues. Here we describe CUTseq, a method that uses restriction enzymes and in vitro transcription to barcode and amplify genomic DNA prior to library construction. We thoroughly assess the sensitivity and reproducibility of CUTseq in both cell lines and FFPE samples, and demonstrate an application of CUTseq for multi-region DNA copy number profiling within single FFPE tumor sections, to assess intratumor genetic heterogeneity at high spatial resolution. In conclusion, CUTseq is a versatile and cost-effective method for library preparation for reduced representation genome sequencing, which can find numerous applications in research and diagnostics., Genomics DNA library preparation from formalin-fixed paraffin-embedded tissues is challenging. Here the authors describe CUTseq that uses restriction enzymes and in vitro amplification to barcode samples for reduced representation genome sequencing.

Functional validation of candidate genes for adaptation and speciation remains challenging. We here exemplify the utility of a method quantifying individual mRNA transcripts in revealing the molecular basis of divergence in feather pigment synthesis during early-stage speciation in crows. Using a padlock probe assay combined with rolling circle amplification we quantified cell-type specific gene expression in the native, histological context of growing feather follicles. Expression of Tyrosinase related protein 1 (TYRP1), Solute carrier family 45 member 2 (SLC45A2) and Hematopoietic prostaglandin D synthase (HPGDS) was melanocyte-limited and significantly reduced in follicles from hooded crow explaining the substantially lower melanin content in grey vs. black feathers. The central upstream transcription factor Microphthalmia-associated transcription factor (MITF) only showed differential expression specific to melanocytes - a feature not captured by bulk RNA-seq. Overall, this study provides insight into the molecular basis of an evolutionary young transition in pigment synthesis, and demonstrates the power of histologically explicit, statistically substantiated single-cell gene expression quantification for functional genetic inference in natural populations.

DNA double-strand breaks (DSBs) are major DNA lesions that are constantly formed during physiological processes such as DNA replication, transcription, and recombination, or as a result of exogenous agents such as ionizing radiation, radiomimetic drugs, and genome editing nucleases. Unrepaired DSBs threaten genomic stability by leading to the formation of potentially oncogenic rearrangements such as translocations. In past few years, several methods based on next-generation sequencing (NGS) have been developed to study the genome-wide distribution of DSBs or their conversion to translocation events. We developed Breaks Labeling, Enrichment on Streptavidin, and Sequencing (BLESS), which was the first method for direct labeling of DSBs in situ followed by their genome-wide mapping at nucleotide resolution (Crosetto et al., Nat Methods 10:361-365, 2013). Recently, we have further expanded the quantitative nature, applicability, and scalability of BLESS by developing Breaks Labeling In Situ and Sequencing (BLISS) (Yan et al., Nat Commun 8:15058, 2017). Here, we first present an overview of existing methods for genome-wide localization of DSBs, and then focus on the BLESS and BLISS methods, discussing different assay design options depending on the sample type and application.

DNA double-strand breaks (DSBs) are major DNA lesions that are constantly formed during physiological processes such as DNA replication, transcription, and recombination, or as a result of exogenous agents such as ionizing radiation, radiomimetic drugs, and genome editing nucleases. Unrepaired DSBs threaten genomic stability by leading to the formation of potentially oncogenic rearrangements such as translocations. In past few years, several methods based on next-generation sequencing (NGS) have been developed to study the genome-wide distribution of DSBs or their conversion to translocation events. We developed Breaks Labeling, Enrichment on Streptavidin, and Sequencing (BLESS), which was the first method for direct labeling of DSBs in situ followed by their genome-wide mapping at nucleotide resolution (Crosetto et al., Nat Methods 10:361-365, 2013). Recently, we have further expanded the quantitative nature, applicability, and scalability of BLESS by developing Breaks Labeling In Situ and Sequencing (BLISS) (Yan et al., Nat Commun 8:15058, 2017). Here, we first present an overview of existing methods for genome-wide localization of DSBs, and then focus on the BLESS and BLISS methods, discussing different assay design options depending on the sample type and application.

Precisely measuring the location and frequency of DNA double-strand breaks (DSBs) along the genome is instrumental to understanding genomic fragility, but current methods are limited in versatility, sensitivity or practicality. Here we present Breaks Labeling In Situ and Sequencing (BLISS), featuring the following: (1) direct labelling of DSBs in fixed cells or tissue sections on a solid surface; (2) low-input requirement by linear amplification of tagged DSBs by in vitro transcription; (3) quantification of DSBs through unique molecular identifiers; and (4) easy scalability and multiplexing. We apply BLISS to profile endogenous and exogenous DSBs in low-input samples of cancer cells, embryonic stem cells and liver tissue. We demonstrate the sensitivity of BLISS by assessing the genome-wide off-target activity of two CRISPR-associated RNA-guided endonucleases, Cas9 and Cpf1, observing that Cpf1 has higher specificity than Cas9. Our results establish BLISS as a versatile, sensitive and efficient method for genome-wide DSB mapping in many applications., National Institute of General Medical Sciences (U.S.) (Grant T32GM007753), National Institute of Mental Health (U.S.) (Grant 5DP1-MH100706), National Institute of Mental Health (U.S.) (Grant 1R01-MH110049)

We present a method for genome-wide DNA double-strand Breaks (DSBs) Labeling In Situ and Sequencing (BLISS) which, compared to existing methods, introduces several key features: 1) high efficiency and low input requirement by in situ DSB labeling in cells or tissue sections directly on a solid surface; 2) easy scalability by performing in situ reactions in multi-well plates; 3) high sensitivity by linearly amplifying tagged DSBs using in vitro transcription; and 4) accurate DSB quantification and control of PCR biases by using unique molecular identifiers. We demonstrate the ability to use BLISS to quantify natural and drug-induced DSBs in low-input samples of cancer cells, primary mouse embryonic stem cells, and mouse liver tissue sections. Finally, we applied BLISS to compare the specificity of CRISPR-associated RNA-guided endonucleases Cas9 and Cpf1, and found that Cpf1 has higher specificity than Cas9. These results establish BLISS as a versatile, sensitive, and efficient method for genome-wide DSB mapping in many applications.

The most common malware detection approaches which are based on signature matching and are not sufficient for metamorphic malware detection, since virus kits and metamorphic engines can produce variants with no resemblance to one another. Metamorphism provides an efficient way for eluding malware detection software kits. Code obfuscation methods like dead-code insertion are also widely used in metamorphic malware. In order to address the problem of detecting mutated generations, we propose a method based on Opcode Graph Similarity (OGS). OGS tries to detect metamorphic malware using the similarity of opcode graphs. In this method, all nodes and edges have a respective effect on classification, but in the proposed method, edges of graphs are pruned using Linear Discriminant Analysis (LDA). LDA is based on the concept of searching for a linear combination of predictors that best separates two or more classes. Most distinctive edges are identified with LDA and the rest of edges are removed. The metamorphic malware families considered here are NGVCK and metamorphic worms that we denote these worms as MWOR. The results show that our approach is capable of classifying metamorphosed instances with no or minimum false alarms. Also, our proposed method can detect NGVCK and MWOR with high accuracy rate., 5th International Conference on Computer and Knowledge Engineering (lCCKE)