A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

T cell-mediated curation and restructuring of tumor tissue coordinates an effective immune response

Antigen-specific T cells traffic to, are influenced by, and create unique cellular microenvironments. Here we characterize these microenvironments over time with multiplexed imaging in a melanoma model of adoptive T cell therapy and human patients with melanoma treated with checkpoint inhibitor therapy. Multicellular neighborhood analysis reveals dynamic immune cell infiltration and inflamed tumor cell neighborhoods associated with CD8+ T cells. T cell-focused analysis indicates T cells are found along a continuum of neighborhoods that reflect the progressive steps coordinating the anti-tumor immune response. More effective anti-tumor immune responses are characterized by inflamed tumor-T cell neighborhoods, flanked by dense immune infiltration neighborhoods. Conversely, ineffective T cell therapies express anti-inflammatory cytokines, resulting in regulatory neighborhoods, spatially disrupting productive T cell-immune and -tumor interactions. Our study provides in situ mechanistic insights into temporal tumor microenvironment changes, cell interactions critical for response, and spatial correlates of immunotherapy outcomes, informing cellular therapy evaluation and engineering.

Robust single-cell matching and multimodal analysis using shared and distinct features

The ability to align individual cellular information from multiple experimental sources is fundamental for a systems-level understanding of biological processes. However, currently available tools are mainly designed for single-cell transcriptomics matching and integration, and generally rely on a large number of shared features across datasets for cell matching. This approach underperforms when applied to single-cell proteomic datasets due to the limited number of parameters simultaneously accessed and lack of shared markers across these experiments. Here, we introduce a cell-matching algorithm, matching with partial overlap (MARIO) that accounts for both shared and distinct features, while consisting of vital filtering steps to avoid suboptimal matching. MARIO accurately matches and integrates data from different single-cell proteomic and multimodal methods, including spatial techniques and has cross-species capabilities. MARIO robustly matched tissue macrophages identified from COVID-19 lung autopsies via codetection by indexing imaging to macrophages recovered from COVID-19 bronchoalveolar lavage fluid by cellular indexing of transcriptomes and epitopes by sequencing, revealing unique immune responses within the lung microenvironment of patients with COVID.

A real-time GPU-accelerated parallelized image processor for large-scale multiplexed fluorescence microscopy data

Highly multiplexed, single-cell imaging has revolutionized our understanding of spatial cellular interactions associated with health and disease. With ever-increasing numbers of antigens, region sizes, and sample sizes, multiplexed fluorescence imaging experiments routinely produce terabytes of data. Fast and accurate processing of these large-scale, high-dimensional imaging data is essential to ensure reliable segmentation and identification of cell types and for characterization of cellular neighborhoods and inference of mechanistic insights. Here, we describe RAPID, a Real-time, GPU-Accelerated Parallelized Image processing software for large-scale multiplexed fluorescence microscopy Data. RAPID deconvolves large-scale, high-dimensional fluorescence imaging data, stitches and registers images with axial and lateral drift correction, and minimizes tissue autofluorescence such as that introduced by erythrocytes. Incorporation of an open source CUDA-driven, GPU-assisted deconvolution produced results similar to fee-based commercial software. RAPID reduces data processing time and artifacts and improves image contrast and signal-to-noise compared to our previous image processing pipeline, thus providing a useful tool for accurate and robust analysis of large-scale, multiplexed, fluorescence imaging data.

Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironments

Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.

Abstract PD6-03: Spatio-molecular dissection of the breast cancer metastatic microenvironment

Metastatic breast cancer (MBC) remains incurable due to inevitable development of therapeutic resistance. Although tumor cell intrinsic mechanisms of resistance in MBC are beginning to be elucidated by bulk sequencing studies, the roles of the tumor microenvironment and intratumor heterogeneity in therapeutic resistance remain underexplored due to both technological barriers and limited availability of samples. To comprehensively capture these characteristics we have adapted a research biopsy protocol to collect tissue for an array of single-cell and spatio-molecular assays whose performance we have optimized for MBC, including single-cell and single-nucleus RNA sequencing, Slide-Seq, Multiplexed Error-Robust FISH (MERFISH), Expansion Sequencing (ExSEQ), Co-detection by Indexing (CODEX) and Multiplexed Ion Beam Imaging (MIBI). To date, we have successfully performed single-cell or single-nucleus RNAseq in 67 MBC biopsies and generated detailed accompanying clinical annotations for each. These samples provide a representation of the clinicopathological diversity of MBC including different breast cancer subtypes (44 HR+/HER2-, 3 HR-/HER2+, 3 HR+/HER2+, 16 TNBC, 1 unknown), common anatomic sites of metastasis (37 liver, 9 axilla, 7 breast, 5 bone, 3 chest wall, 3 neck, 1 brain, 1 lung, 1 skin), metastatic presentations (53 recurrent, 14 de novo) and histologic subtypes in the breast (45 IDC, 7 ILC, 6 mixed, 3 DCIS, 1 mucinous, 5 unknown/NA). Following optimization, both single-cell and single-nucleus RNA seq perform well in these MBC biopsies recovering all expected cell types including the malignant, stromal (e.g. fibroblasts, endothelial cells), myeloid (e.g. monocytes, macrophages) and lymphoid compartments (e.g. T cells, B cells, NK cells) as well as relevant oncogenic programs (e.g. cell cycle programs in all compartments; EMT-like and ER signaling programs in the malignant compartment, immune checkpoint programs in the lymphoid compartment; and fibroblast activation and vascular homeostasis programs in the stromal compartment). In addition to differences between the two techniques, these data demonstrate substantial intratumor heterogeneity in cell type composition. For example in liver biopsies the average number of cells per sample compartment by single nucleus RNA-seq was 6745 malignant (56%, SD 4216), 4637 stromal (41%, SD 3727), 1196 lymphoid (8%, SD 1617) and 874 myeloid (6%, SD 852); in breast biopsies the average number of cells per compartment by single nucleus RNA-seq was 6421 malignant (70%, SD 3497), 1628 stromal (24%, SD 117), 333 lymphoid (4%, SD 170) and 213 myeloid (3%, SD 117). Additionally, we find both inter- and intra-tumor heterogeneity in expression patterns and programs including, for example, expression of ER, PR and HER2 within clinical receptor subtypes (log normalized counts for ER expression in tumor cells by single cell RNA-seq: HR+/HER2- 0.921 (SD 0.714); HR+/HER2+ 0.768 (SD 0.624); HR-/HER2+ 0.018 (SD 0.122); and HR-/HER2- 0.005 (SD 0.066). For a subset of 13 biopsies we are also completing the spatiomolecular characterization methods on serial sections of a single adjacent biopsy. This unique experimental setup was designed to enable efficient comparison and integration of these assays. In spite of differences between experimental techniques and readouts, cell typing can be approached by annotation transfer from matching single cell or single nucleus RNAseq data, enabling exploratory analyses including evaluation of spatial phenotypes and cell type colocalization. Overall, these single cell and spatial data afford a comprehensive atlas including cell types, cell states/programs, cell interactions and spatial organization in MBC lesions. Future analyses will include serial biopsies over time and integration of clinicopathologic data including therapeutic response and resistance.

Citation Format: Daniel L Abravanel, Johanna Klughammer, Timothy Blosser, Yury Goltsev, Sizun Jiang, Yunjao Bai, Evan Murray, Shahar Alon, Yi Cui, Daniel R Goodwin, Anubhav Sinha, Ofir Cohen, Michal Slyper, Orr Ashenberg, Danielle Dionne, Judit Jané-Valbuena, Caroline BM Porter, Asa Segerstolpe, Julia Waldman, Sébastien Vigneau, Karla Helvie, Allison Frangieh, Laura DelloStritto, Miraj Patel, Jingyi We, Kathleen Pfaff, Nicole Cullen, Ana Lako, Madison Turner, Isaac Wakiro, Sara Napolitano, Abhay Kanodia, Rebecca Ortiz, Colin MacKichan, Stephanie Inga, Judy Chen, Aaron R Thorner, Asaf Rotem, Scott Rodig, Fei Chen, Edward S Boyden, Garry P Nolan, Xiaowei Zhuang, Orit Rozenblatt-Rosen, Bruce E Johnson, Aviv Regev, Nikhil Wagle. Spatio-molecular dissection of the breast cancer metastatic microenvironment [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD6-03.

A community-based approach to image analysis of cells, tissues and tumors

Emerging multiplexed imaging platforms provide an unprecedented view of an increasing number of molecular markers at subcellular resolution and the dynamic evolution of tumor cellular composition. As such, they are capable of elucidating cell-to-cell interactions within the tumor microenvironment that impact clinical outcome and therapeutic response. However, the rapid development of these platforms has far outpaced the computational methods for processing and analyzing the data they generate. While being technologically disparate, all imaging assays share many computational requirements for post-collection data processing. As such, our Image Analysis Working Group (IAWG), composed of researchers in the Cancer Systems Biology Consortium (CSBC) and the Physical Sciences - Oncology Network (PS-ON), convened a workshop on "Computational Challenges Shared by Diverse Imaging Platforms" to characterize these common issues and a follow-up hackathon to implement solutions for a selected subset of them. Here, we delineate these areas that reflect major axes of research within the field, including image registration, segmentation of cells and subcellular structures, and identification of cell types from their morphology. We further describe the logistical organization of these events, believing our lessons learned can aid others in uniting the imaging community around self-identified topics of mutual interest, in designing and implementing operational procedures to address those topics and in mitigating issues inherent in image analysis (e.g., sharing exemplar images of large datasets and disseminating baseline solutions to hackathon challenges through open-source code repositories).

Rhesus Macaque CODEX Multiplexed Immunohistochemistry Panel for Studying Immune Responses During Ebola Infection

Non-human primate (NHP) animal models are an integral part of the drug research and development process. For some biothreat pathogens, animal model challenge studies may offer the only possibility to evaluate medical countermeasure efficacy. A thorough understanding of host immune responses in such NHP models is therefore vital. However, applying antibody-based immune characterization techniques to NHP models requires extensive reagent development for species compatibility. In the case of studies involving high consequence pathogens, further optimization for use of inactivated samples may be required. Here, we describe the first optimized CO-Detection by indEXing (CODEX) multiplexed tissue imaging antibody panel for deep profiling of spatially resolved single-cell immune responses in rhesus macaques. This 21-marker panel is composed of a set of 18 antibodies that stratify major immune cell types along with a set three Ebola virus (EBOV)-specific antibodies. We validated these two sets of markers using immunohistochemistry and CODEX in fully inactivated Formalin-Fixed Paraffin-Embedded (FFPE) tissues from mock and EBOV challenged macaques respectively and provide an efficient framework for orthogonal validation of multiple antibody clones using CODEX multiplexed tissue imaging. We also provide the antibody clones and oligonucleotide tag sequences as a valuable resource for other researchers to recreate this reagent set for future studies of tissue immune responses to EBOV infection and other diseases.

Determinants of SARS-CoV-2 entry and replication in airway mucosal tissue and susceptibility in smokers

Understanding viral tropism is an essential step toward reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, decreasing mortality from coronavirus disease 2019 (COVID-19) and limiting opportunities for mutant strains to arise. Currently, little is known about the extent to which distinct tissue sites in the human head and neck region and proximal respiratory tract selectively permit SARS-CoV-2 infection and replication. In this translational study, we discover key variabilities in expression of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), essential SARS-CoV-2 entry factors, among the mucosal tissues of the human proximal airways. We show that SARS-CoV-2 infection is present in all examined head and neck tissues, with a notable tropism for the nasal cavity and tracheal mucosa. Finally, we uncover an association between smoking and higher SARS-CoV-2 viral infection in the human proximal airway, which may explain the increased susceptibility of smokers to developing severe COVID-19. This is at least partially explained by differences in interferon (IFN)-β1 levels between smokers and non-smokers.

Strategies for Accurate Cell Type Identification in CODEX Multiplexed Imaging Data

Multiplexed imaging is a recently developed and powerful single-cell biology research tool. However, it presents new sources of technical noise that are distinct from other types of single-cell data, necessitating new practices for single-cell multiplexed imaging processing and analysis, particularly regarding cell-type identification. Here we created single-cell multiplexed imaging datasets by performing CODEX on four sections of the human colon (ascending, transverse, descending, and sigmoid) using a panel of 47 oligonucleotide-barcoded antibodies. After cell segmentation, we implemented five different normalization techniques crossed with four unsupervised clustering algorithms, resulting in 20 unique cell-type annotations for the same dataset. We generated two standard annotations: hand-gated cell types and cell types produced by over-clustering with spatial verification. We then compared these annotations at four levels of cell-type granularity. First, increasing cell-type granularity led to decreased labeling accuracy; therefore, subtle phenotype annotations should be avoided at the clustering step. Second, accuracy in cell-type identification varied more with normalization choice than with clustering algorithm. Third, unsupervised clustering better accounted for segmentation noise during cell-type annotation than hand-gating. Fourth, Z-score normalization was generally effective in mitigating the effects of noise from single-cell multiplexed imaging. Variation in cell-type identification will lead to significant differential spatial results such as cellular neighborhood analysis; consequently, we also make recommendations for accurately assigning cell-type labels to CODEX multiplexed imaging.

SARS-CoV-2 infects human pancreatic β cells and elicits β cell impairment

Emerging evidence points toward an intricate relationship between the pandemic of coronavirus disease 2019 (COVID-19) and diabetes. While preexisting diabetes is associated with severe COVID-19, it is unclear whether COVID-19 severity is a cause or consequence of diabetes. To mechanistically link COVID-19 to diabetes, we tested whether insulin-producing pancreatic β cells can be infected by SARS-CoV-2 and cause β cell depletion. We found that the SARS-CoV-2 receptor, ACE2, and related entry factors (TMPRSS2, NRP1, and TRFC) are expressed in β cells, with selectively high expression of NRP1. We discovered that SARS-CoV-2 infects human pancreatic β cells in patients who succumbed to COVID-19 and selectively infects human islet β cells in vitro. We demonstrated that SARS-CoV-2 infection attenuates pancreatic insulin levels and secretion and induces β cell apoptosis, each rescued by NRP1 inhibition. Phosphoproteomic pathway analysis of infected islets indicates apoptotic β cell signaling, similar to that observed in type 1 diabetes (T1D). In summary, our study shows SARS-CoV-2 can directly induce β cell killing.

CODEX multiplexed tissue imaging with DNA-conjugated antibodies

Advances in multiplexed imaging technologies have drastically improved our ability to characterize healthy and diseased tissues at the single-cell level. Co-detection by indexing (CODEX) relies on DNA-conjugated antibodies and the cyclic addition and removal of complementary fluorescently labeled DNA probes and has been used so far to simultaneously visualize up to 60 markers in situ. CODEX enables a deep view into the single-cell spatial relationships in tissues and is intended to spur discovery in developmental biology, disease and therapeutic design. Herein, we provide optimized protocols for conjugating purified antibodies to DNA oligonucleotides, validating the conjugation by CODEX staining and executing the CODEX multicycle imaging procedure for both formalin-fixed, paraffin-embedded (FFPE) and fresh-frozen tissues. In addition, we describe basic image processing and data analysis procedures. We apply this approach to an FFPE human tonsil multicycle experiment. The hands-on experimental time for antibody conjugation is ~4.5 h, validation of DNA-conjugated antibodies with CODEX staining takes ~6.5 h and preparation for a CODEX multicycle experiment takes ~8 h. The multicycle imaging and data analysis time depends on the tissue size, number of markers in the panel and computational complexity.

Highly multiplexed tissue imaging using repeated oligonucleotide exchange reaction

Multiparameter tissue imaging enables analysis of cell-cell interactions in situ, the cellular basis for tissue structure, and novel cell types that are spatially restricted, giving clues to biological mechanisms behind tissue homeostasis and disease. Here, we streamlined and simplified the multiplexed imaging method CO-Detection by indEXing (CODEX) by validating 58 unique oligonucleotide barcodes that can be conjugated to antibodies. We showed that barcoded antibodies retained their specificity for staining cognate targets in human tissue. Antibodies were visualized one at a time by adding a fluorescently labeled oligonucleotide complementary to oligonucleotide barcode, imaging, stripping, and repeating this cycle. With this we developed a panel of 46 antibodies that was used to stain five human lymphoid tissues: three tonsils, a spleen, and a LN. To analyze the data produced, an image processing and analysis pipeline was developed that enabled single-cell analysis on the data, including unsupervised clustering, that revealed 31 cell types across all tissues. We compared cell-type compositions within and directly surrounding follicles from the different lymphoid organs and evaluated cell-cell density correlations. This sequential oligonucleotide exchange technique enables a facile imaging of tissues that leverages pre-existing imaging infrastructure to decrease the barriers to broad use of multiplexed imaging.

The Effect of Ethanol Consumption on Composition and Morphology of Femur Cortical Bone in Wild-Type and ALDH2*2-Homozygous Mice

ALDH2 inactivating mutation (ALDH2*2) is the most abundant mutation leading to bone morphological aberration. Osteoporosis has long been associated with changes in bone biomaterial in elderly populations. Such changes can be exacerbated with elevated ethanol consumption and in subjects with impaired ethanol metabolism, such as carriers of aldehyde dehydrogenase 2 (ALDH2)-deficient gene, ALDH2*2. So far, little is known about bone compositional changes besides a decrease in mineralization. Raman spectroscopic imaging has been utilized to study the changes in overall composition of C57BL/6 female femur bone sections, as well as in compound spatial distribution. Raman maps of bone sections were analyzed using multilinear regression with these four isolated components, resulting in maps of their relative distribution. A 15-week treatment of both wild-type (WT) and ALDH2*2/*2 mice with 20% ethanol in the drinking water resulted in a significantly lower mineral content (p < 0.05) in the bones. There was no significant change in mineral and collagen content due to the mutation alone (p > 0.4). Highly localized islets of elongated adipose tissue were observed on most maps. Elevated fat content was found in ALDH2*2 knock-in mice consuming ethanol (p < 0.0001) and this effect appeared cumulative. This work conclusively demonstrates that that osteocytes in femurs of older female mice accumulate fat, as has been previously theorized, and that fat accumulation is likely modulated by levels of acetaldehyde, the ethanol metabolite.

ACE2 localizes to the respiratory cilia and is not increased by ACE inhibitors or ARBs

The coronavirus SARS-CoV-2 is the causative agent of the ongoing severe acute respiratory disease pandemic COVID-19. Tissue and cellular tropism is one key to understanding the pathogenesis of SARS-CoV-2. We investigate the expression and subcellular localization of the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), within the upper (nasal) and lower (pulmonary) respiratory tracts of human donors using a diverse panel of banked tissues. Here, we report our discovery that the ACE2 receptor protein robustly localizes within the motile cilia of airway epithelial cells, which likely represents the initial or early subcellular site of SARS-CoV-2 viral entry during host respiratory transmission. We further determine whether ciliary ACE2 expression in the upper airway is influenced by patient demographics, clinical characteristics, comorbidities, or medication use, and show the first mechanistic evidence that the use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARBs) does not increase susceptibility to SARS-CoV-2 infection through enhancing the expression of ciliary ACE2 receptor. These findings are crucial to our understanding of the transmission of SARS-CoV-2 for prevention and control of this virulent pathogen.

Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front

Antitumoral immunity requires organized, spatially nuanced interactions between components of the immune tumor microenvironment (iTME). Understanding this coordinated behavior in effective versus ineffective tumor control will advance immunotherapies. We re-engineered co-detection by indexing (CODEX) for paraffin-embedded tissue microarrays, enabling simultaneous profiling of 140 tissue regions from 35 advanced-stage colorectal cancer (CRC) patients with 56 protein markers. We identified nine conserved, distinct cellular neighborhoods (CNs)-a collection of components characteristic of the CRC iTME. Enrichment of PD-1+CD4+ T cells only within a granulocyte CN positively correlated with survival in a high-risk patient subset. Coupling of tumor and immune CNs, fragmentation of T cell and macrophage CNs, and disruption of inter-CN communication was associated with inferior outcomes. This study provides a framework for interrogating how complex biological processes, such as antitumoral immunity, occur through concerted actions of cells and spatial domains.

Robust ACE2 protein expression localizes to the motile cilia of the respiratory tract epithelia and is not increased by ACE inhibitors or angiotensin receptor blockers

We investigated the expression and subcellular localization of the SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), within the upper (nasal) and lower (pulmonary) respiratory tracts of healthy human donors. We detected ACE2 protein expression within the cilia organelle of ciliated airway epithelial cells, which likely represents the initial or early subcellular site of SARS-CoV-2 viral entry during respiratory transmission. We further determined whether ACE2 expression in the cilia of upper respiratory cells was influenced by patient demographics, clinical characteristics, co-morbidities, or medication use, and found no evidence that the use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin II receptor blockers (ARBs) increases ACE2 protein expression.

National Cancer Institute Think-Tank Meeting Report on Proteomic Cartography and Biomarkers at the Single-Cell Level: Interrogation of Premalignant Lesions

A Think-Tank Meeting was convened by the National Cancer Institute (NCI) to solicit experts' opinion on the development and application of multiomic single-cell analyses, and especially single-cell proteomics, to improve the development of a new generation of biomarkers for cancer risk, early detection, diagnosis, and prognosis as well as to discuss the discovery of new targets for prevention and therapy. It is anticipated that such markers and targets will be based on cellular, subcellular, molecular, and functional aberrations within the lesion and within individual cells. Single-cell proteomic data will be essential for the establishment of new tools with searchable and scalable features that include spatial and temporal cartographies of premalignant and malignant lesions. Challenges and potential solutions that were discussed included (i) The best way/s to analyze single-cells from fresh and preserved tissue; (ii) Detection and analysis of secreted molecules and from single cells, especially from a tissue slice; (iii) Detection of new, previously undocumented cell type/s in the premalignant and early stage cancer tissue microenvironment; (iv) Multiomic integration of data to support and inform proteomic measurements; (v) Subcellular organelles-identifying abnormal structure, function, distribution, and location within individual premalignant and malignant cells; (vi) How to improve the dynamic range of single-cell proteomic measurements for discovery of differentially expressed proteins and their post-translational modifications (PTM); (vii) The depth of coverage measured concurrently using single-cell techniques; (viii) Quantitation - absolute or semiquantitative? (ix) Single methodology or multiplexed combinations? (x) Application of analytical methods for identification of biologically significant subsets; (xi) Data visualization of N-dimensional data sets; (xii) How to construct intercellular signaling networks in individual cells within premalignant tumor microenvironments (TME); (xiii) Associations between intrinsic cellular processes and extrinsic stimuli; (xiv) How to predict cellular responses to stress-inducing stimuli; (xv) Identification of new markers for prediction of progression from precursor, benign, and localized lesions to invasive cancer, based on spatial and temporal changes within individual cells; (xvi) Identification of new targets for immunoprevention or immunotherapy-identification of neoantigens and surfactome of individual cells within a lesion.

Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging

A highly multiplexed cytometric imaging approach, termed co-detection by indexing (CODEX), is used here to create multiplexed datasets of normal and lupus (MRL/lpr) murine spleens. CODEX iteratively visualizes antibody binding events using DNA barcodes, fluorescent dNTP analogs, and an in situ polymerization-based indexing procedure. An algorithmic pipeline for single-cell antigen quantification in tightly packed tissues was developed and used to overlay well-known morphological features with de novo characterization of lymphoid tissue architecture at a single-cell and cellular neighborhood levels. We observed an unexpected, profound impact of the cellular neighborhood on the expression of protein receptors on immune cells. By comparing normal murine spleen to spleens from animals with systemic autoimmune disease (MRL/lpr), extensive and previously uncharacterized splenic cell-interaction dynamics in the healthy versus diseased state was observed. The fidelity of multiplexed spatial cytometry demonstrated here allows for quantitative systemic characterization of tissue architecture in normal and clinically aberrant samples.

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Autoimmunity analyzed by multiplexed DNA-tagged antibody staining (CODEX)

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CODEX data reveal pairwise interactions and niches changing with disease

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First tier of neighbors significantly impacts marker expression in the index cells

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Changes in splenic morphology correlate with shifts in cell frequencies

Abstract PR14: Automatic identification of cell niches and immune interactions important for clinical outcomes using multiparameter imaging and deep neural networks

Multiparameter cytometry, for example with CyTOF, has enabled the interrogation of immune phenotypes in unprecedented detail in many clinical contexts. But cytometry is incapable of answering a question of critical importance to many tissue context studies, and especially understanding how local interactions between tumor cells and immune cells correlate to clinical outcomes. This becomes especially relevant to understanding the subtleties of how different immunotherapeutic approaches operate in vivo.

We recently developed a multiparameter immunofluorescence technique, termed CODEX, which allows the capture of spatial information for protein and RNA expression in tissue sections. This spatial information enables us to establish not only cell-types according to traditional phenotypic surface marker expression, but also to potentially surmise specific tissue states driving clinical responses. To make sense of the high-dimensional data afforded by CODEX, we apply here state-of-the-art deep neural networks (DNNs). These networks, which have achieved superhuman classification accuracy in many diverse domains, automatically identify cells, cell niches and regions (at multiple scales) that are capable of distinguishing healthy and diseased samples. This is done in an unbiased way, with only ‘healthy’ vs. ‘disease’ labels as additional input alongside the imaging data.

We first train DNNs to successfully classify multiparameter tissue images from independent replicates across conditions. Having achieved a high accuracy of classification, we set the network output to highlight cells and regions deemed to be most relevant to classify each condition. Applying this methodology to healthy and mrl (lupus) spleens stained for 30 markers, our neural network is able to successfully identify a not previously observed enrichment of cell confluences (niches) consisting of CD8 T-cells and conventional dendritic cells enriched in MRL samples, as well as other novel niches completely unpredicted by prior knowledge.

Our DNN enables the systematic and unbiased discovery of specific immune interactions in any tissue type. Applying our technique to the analysis of samples from immunotherapy recipients could enable the discovery of key factors in the tumor microenvironment that distinguish positive responders as well as the subsequent identification of targets for perturbation.

Citation Format: Salil S. Bhate, Nikolay Samusik, Yury Goltsev, Garry P. Nolan. Automatic identification of cell niches and immune interactions important for clinical outcomes using multiparameter imaging and deep neural networks [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr PR14.

Abstract A089: Multiparametric immunofluorescence analysis of the tumor microenvironment using CODEX

The tumor microenvironment plays a critical role in cancer progression and has implications for the efficacy of various cancer immunotherapy treatment options. Immune infiltrates within the tumor microenvironment can correlate with both positive and negative outcomes, depending upon the both the type of cancer as well as infiltrating immune cell(s). These analyses are typically performed using standard immunofluorescence and immunohistochemistry assays where no more than four simultaneous parameters can be visualized on the same tissue. Unfortunately, these tools cannot fully characterize the complexity of the tumor microenvironment due to the inherent limitations of fluorophore spectral overlap. In order to identify each type of immune and tumor cell within a single tissue, at least 40 parameters need to be measured simultaneously. We have developed a multiparametric immunofluorescence technology, entitled CODEX (Co-Detection by IndEXing), which utilizes unique DNA tags as a means of iteratively measuring more than 40 parameters within the same tissue. More than 40 human antibodies have been validated using this approach, including numerous immune markers, checkpoint ligands, tumor markers and cellular activity markers. We are currently analyzing tissue sample from patients with lung cancer. By measuring nearly 50 simultaneous markers within the same tissue, CODEX has the potential to greatly enhance our knowledge of the tumor microenvironment and more accurately define immune infiltrates at the single-cell level.

Citation Format: Julia Kennedy-Darling, Garry P. Nolan, Yury Goltsev, Nikolay Samusik. Multiparametric immunofluorescence analysis of the tumor microenvironment using CODEX [abstract]. In: Proceedings of the Second CRI-CIMT-EATI-AACR International Cancer Immunotherapy Conference: Translating Science into Survival; 2016 Sept 25-28; New York, NY. Philadelphia (PA): AACR; Cancer Immunol Res 2016;4(11 Suppl):Abstract nr A089.

A continuous molecular roadmap to iPSC reprogramming through progression analysis of single-cell mass cytometry

To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4(high)Klf4(high) cells transitioned to a CD73(high)CD104(high)CD54(low) partially reprogrammed state. Ki67(low) cells from this intermediate population reverted to a MEF-like phenotype, but Ki67(high) cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like Nanog(high)Sox2(high)CD54(high) population and a mesendoderm-like Nanog(low)Sox2(low)Lin28(high)CD24(high)PDGFR-α(high) population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.

Unipotent Megakaryopoietic Pathway Bridging Hematopoietic Stem Cells and Mature Megakaryocytes

Recent identification of platelet/megakaryocyte-biased hematopoietic stem/repopulating cells requires revision of the intermediate pathway for megakaryopoiesis. Here, we show a unipotent megakaryopoietic pathway bypassing the bipotent megakaryocyte/erythroid progenitors (biEMPs). Cells purified from mouse bone marrow by CD42b (GPIbα) marking were demonstrated to be unipotent megakaryocytic progenitors (MKPs) by culture and transplantation. A subpopulation of freshly isolated CD41(+) cells in the lineage Sca1(+) cKit(+) (LSK) fraction (subCD41(+) LSK) differentiated only into MKP and mature megakaryocytes in culture. Although CD41(+) LSK cells as a whole were capable of differentiating into all myeloid and lymphoid cells in vivo, they produced unipotent MKP, mature megakaryocytes, and platelets in vitro and in vivo much more efficiently than Flt3(+) CD41(-) LSK cells, especially at the early phase after transplantation. In single cell polymerase chain reaction and thrombopoietin (TPO) signaling analyses, the MKP and a fraction of CD41(+) LSK, but not the biEMP, showed the similarities in mRNA expression profile and visible TPO-mediated phosphorylation. On increased demand of platelet production after 5-FU treatment, a part of CD41(+) LSK population expressed CD42b on the surface, and 90% of them showed unipotent megakaryopoietic capacity in single cell culture and predominantly produced platelets in vivo at the early phase after transplantation. These results suggest that the CD41(+) CD42b(+) LSK are straightforward progenies of megakaryocytes/platelet-biased stem/repopulating cells, but not progenies of biEMP. Consequently, we show a unipotent/highly biased megakaryopoietic pathway interconnecting stem/repopulating cells and mature megakaryocytes, the one that may play physiologic roles especially in emergency megakaryopoiesis.

A robust and sensitive flow cytometric method for multiplex RNA in-situ hybridization analysis of blood cells using oligo probes and branched DNA based signal amplification (P3356)

We present here a novel method for in-situ hybridization (ISH) detection of multiple RNA targets in single cells using standard flow cytometer. This method is based on the use of oligo pairs as probes and bDNA signal amplification for highly sensitive and specific ISH detection of RNA. The oligo pairs are designed to hybridize to specific target sequences and can be readily synthesized. The oligo probes/RNA target complex is detected after signal is generated by bDNA signal amplification. The method is compatible with immunostaining, so simultaneous staining of protein and RNA in single cells is feasible. We demonstrated the co-staining of RNA and surface marker proteins in PBMC, B cells, T cells and leukemic cell lines of U937, K562, Jurkat and M1. In addition, the flow cytometric analysis of cytokine gene induction by lipopolysaccharides/R848 in PBMC was shown by staining with antibody for CD14 protein and probes for RNAs encoding interleukin-1 beta, -6, -8 and tumor necrosis factor-alpha. Taken together, this novel RNA ISH flow cytometry assay offers an invaluable tool for studying immune response, stem cell biology and infectious diseases.

Decoupling of tumor-initiating activity from stable immunophenotype in HoxA9-Meis1-driven AML

Increasing evidence suggests tumors are maintained by cancer stem cells; however, their nature remains controversial. In a HoxA9-Meis1 (H9M) model of acute myeloid leukemia (AML), we found that tumor-initiating activity existed in three, immunophenotypically distinct compartments, corresponding to disparate lineages on the normal hematopoietic hierarchy--stem/progenitor cells (Lin(-)kit(+)) and committed progenitors of the myeloid (Gr1(+)kit(+)) and lymphoid lineages (Lym(+)kit(+)). These distinct tumor-initiating cells (TICs) clonally recapitulated the immunophenotypic spectrum of the original tumor in vivo (including cells with a less-differentiated immunophenotype) and shared signaling networks, such that in vivo pharmacologic targeting of conserved TIC survival pathways (DNA methyltransferase and MEK phosphorylation) significantly increased survival. Collectively, H9M AML is organized as an atypical hierarchy that defies the strict lineage marker boundaries and unidirectional differentiation of normal hematopoiesis. Moreover, this suggests that in certain malignancies tumor-initiation activity (or "cancer stemness") can represent a cellular state that exists independently of distinct immunophenotypic definition.

Abstract 3307: Improved survival in AML by in vivo drug targeting of conserved regulatory pathways in phenotypically distinct tumor-initiating compartments

Increasing evidence suggests tumors are maintained by cancer stem cells, however their nature remains controversial. In a HoxA9-Meis1 (H9M) driven model of acute myeloid leukemia (AML), we found that tumor-initiating activity existed in three, immunophenotypically distinct compartments, corresponding to disparate lineages on the normal hematopoietic hierarchy–stem/progenitor cells (Lin−kit+), and committed progenitors of the myeloid (Gr1+kit+) and lymphoid lineages (Lym+kit+). Each compartment clonally recapitulated the original range of tumor cell immunophenotypes in vivo, including cells with a less-differentiated immunophenotype. These distinct populations largely shared signaling networks, and in vivo pharmacologic targeting of shared pathways (DNA methyltransferase and MEK phosphorylation) significantly increased survival. Collectively, these data show that H9M AML is organized as an atypical hierarchy that defies the strict lineage marker boundaries and unidirectional differentiation of normal hematopoiesis. Moreover, in some malignancies, tumor-initiation ability (or “cancer-stemness”) can represent a targetable, cellular state that can exithat exists independently of distinct immunophenotypic definition.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3307. doi:1538-7445.AM2012-3307

Abstract LB-33: Identification of two unrecognized acute myeloid leukemia (AML) subtypes based on cell by cell analysis of leukemic blasts

Single cell multiparametric flow cytometry studies have previously shown that G-CSF-mediated intracellular signaling responsiveness of blast cell subsets stratified clinical outcomes of AML patients. 13 AML samples were stimulated with G-CSF, fixed, and permeabilized with a technique we developed that preserves mRNA integrity in a manner suitable for microarray-based expression analysis. From the microarray profiles we identified surface markers that could be prospectively used to separately enrich G-CSF Responsive Cells (GRCs) and non-G-CSF Responsive Cells (NGRCs) from each sample. The results demonstrate that two previously unrecognized subtypes of AML could be discerned, as portrayed by the proteomic and molecular characteristics of the GRC and NGRC subsets. First, GRC cells had a higher colony formation capacity as well as being more reactive to cytokines secreted by NGRCs In one discovered AML subtype, patients present with bone marrow that had higher percentages of GRCs (20-50%), with the remainder being NGRCs. The molecular signatures of both the GRCs and NGRCs in this subtype had a hematopoietic progenitors mRNA signature (HPMS). In the second subtype of AML there were lower percentages of GRCs (0.5-10%, which had the HPMS) but in these cases the NGRC mRNA signatures were distinct resembling those of a more differentiated myeloid phenotype. Therefore, in most AML patients tested, two blast cell populations inevitably appear, and each of these blasts represented a distinct level of hematopoietic maturity, or cytokine responsiveness. The common thread between the two subtypes is that the GRCs in each patient were more capable of colony formation, enabled by a potentially more “stem-like” phenotype. Critically, each population would be clinically termed “blast” cells and would therefore be considered malignant and a potential target for chemotherapy. These results lead to two important conclusions. The first is that the blast phenotype can exist independently of the apparent cell maturation stage. This raises the questions of whether each blast subtype is equally susceptible to standard chemotherapy, whether a strategy of defining the molecular players that drive the formation of each of these blast types should be pursued, and finally whether such information can be used to better combat these aspects of the leukemic disease spectrum.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-33. doi:1538-7445.AM2012-LB-33

Clusters of temporal discordances reveal distinct embryonic patterning mechanisms in Drosophila and anopheles

Evolutionary innovations can be driven by spatial and temporal changes in gene expression. Several such differences have been documented in the embryos of lower and higher Diptera. One example is the reduction of the ancient extraembryonic envelope composed of amnion and serosa as seen in mosquitoes to the single amnioserosa of fruit flies. We used transcriptional datasets collected during the embryonic development of the fruit fly, Drosophila melanogaster, and the malaria mosquito, Anopheles gambiae, to search for whole-genome changes in gene expression underlying differences in their respective embryonic morphologies. We found that many orthologous gene pairs could be clustered based on the presence of coincident discordances in their temporal expression profiles. One such cluster contained genes expressed specifically in the mosquito serosa. As shown previously, this cluster is re-deployed later in development at the time of cuticle synthesis. In addition, there is a striking difference in the temporal expression of a subset of maternal genes. Specifically, maternal transcripts that exhibit a sharp reduction at the time of the maternal-zygotic transition in Drosophila display sustained expression in the Anopheles embryo. We propose that gene clustering by local temporal discordance can be used for the de novo identification of the gene batteries underlying morphological diversity.

Abstract B6: Identification of novel mutations in the inhibitory adaptor protein LNK in patients with JAK2 V617F-negative and -positive chronic myeloproliferative neoplasms

Dysregulated JAK-STAT signaling is a hallmark of myeloproliferative neoplasms (MPNs), as evidenced by the identification of activating mutations in JAK2, and the thrombopoietin (TPO) receptor MPL in a subset of MPN patients. Clinical trials with highly specific inhibitors of JAK2 are currently ongoing, and clinical responses have been observed in the majority of MPN patients, validating JAK2 as an important therapeutic target in these patients. In addition, responses have been observed in patients lacking known mutations in JAK2 or MPL, suggesting that other regulatory elements in this pathway are altered. However, the molecular basis for this observation is not well understood.

One regulator of JAK-STAT signaling is LNK (SH2B3), a member of a family of adaptor proteins that share several structural motifs, including a proline-rich N-terminal dimerization domain (Pro/DD), a pleckstrin homology (PH) domain, an SH2 domain, and a conserved C-terminal tyrosine residue. LNK binds to MPL via its SH2 domain and co-localizes to the plasma membrane via its PH domain. Upon cytokine stimulation with TPO, LNK binds strongly to JAK2 and inhibits downstream STAT activation, thereby providing critical negative feedback regulation. LNK-/- mice exhibit an MPN phenotype, including an expanded hematopoietic stem cell compartment, megakaryocyte hyperplasia, splenomegaly, leukocytosis, and thrombocytosis.

We sequenced LNK in a cohort of MPN patients, leading to the identification of novel mutations in 7/159 (4.4%) patients. One patient with JAK2 V617F-negative primary myelofibrosis (PMF) exhibited a 5 base-pair deletion and missense mutation (DEL) leading to a premature stop codon and loss of the PH and SH2 domains. Six additional patients were found to have point mutations affecting conserved residues in the PH domain. Interestingly, a point mutation leading to an E208Q substitution was found in one JAK2 V617F- negative patient with essential thrombocythemia (ET), as well as one JAK2 V617F-positive ET patient. Similarly, a P242S substitution was also found in both a JAK2 V617F-negative ET patient, as well as a JAK2 V617F-positive patient with post-polycythemic myelofibrosis.

These latter findings suggest that even in the presence of the JAK2 V617F mutation, abrogation of LNK function may be a cooperating pathogenetic mutation.

TPO-dependent BaF3-MPL cells transduced with the LNK DEL mutant exhibited augmented and sustained TPO-dependent growth and activation of JAK2-STAT3/5. The E208Q mutation resulted in partial loss of LNK function, suggesting that LNK mutations may confer a spectrum of phenotypes. Primary patient samples from MPN patients bearing the LNK DEL and E208Q mutations exhibited aberrant JAK-STAT activation, and cytokine-responsive CD34+ early progenitors were abnormally abundant. The STAT3/5 activation response was abrogated by JAK inhibition, suggesting that JAK2 inhibitors may be a feasible option for MPN patients bearing LNK mutations.

Our identification of mutations in LNK, the first reported in human disease, demonstrates that loss of JAK-STAT negative feedback control is a novel mechanism of MPN pathogenesis. As each of these LNK mutations localizes to the PH domain and appears to be heterozygous, mislocalized mutant LNK may exert a dominant negative effect by binding and sequestering wild-type LNK. These findings may also partly explain why some MPN patients lacking JAK2 or MPL mutations respond to treatment with JAK2 inhibitors, and highlight the importance of a more complete understanding of the role of inhibitory pathways in MPN pathogenesis.

Citation Information: Clin Cancer Res 2010;16(14 Suppl):B6.

Time warping of evolutionary distant temporal gene expression data based on noise suppression

Background

Comparative analysis of genome wide temporal gene expression data has a broad potential area of application, including evolutionary biology, developmental biology, and medicine. However, at large evolutionary distances, the construction of global alignments and the consequent comparison of the time-series data are difficult. The main reason is the accumulation of variability in expression profiles of orthologous genes, in the course of evolution.

Results

We applied Pearson distance matrices, in combination with other noise-suppression techniques and data filtering to improve alignments. This novel framework enhanced the capacity to capture the similarities between the temporal gene expression datasets separated by large evolutionary distances. We aligned and compared the temporal gene expression data in budding (Saccharomyces cerevisiae) and fission (Schizosaccharomyces pombe) yeast, which are separated by more then ~400 myr of evolution. We found that the global alignment (time warping) properly matched the duration of cell cycle phases in these distant organisms, which was measured in prior studies. At the same time, when applied to individual ortholog pairs, this alignment procedure revealed groups of genes with distinct alignments, different from the global alignment.

Conclusion

Our alignment-based predictions of differences in the cell cycle phases between the two yeast species were in a good agreement with the existing data, thus supporting the computational strategy adopted in this study. We propose that the existence of the alternative alignments, specific to distinct groups of genes, suggests presence of different synchronization modes between the two organisms and possible functional decoupling of particular physiological gene networks in the course of evolution.

Organization of developmental enhancers in the Drosophila embryo

Most cell-specific enhancers are thought to lack an inherent organization, with critical binding sites distributed in a more or less random fashion. However, there are examples of fixed arrangements of binding sites, such as helical phasing, that promote the formation of higher-order protein complexes on the enhancer DNA template. Here, we investigate the regulatory ‘grammar’ of nearly 100 characterized enhancers for developmental control genes active in the early Drosophila embryo. The conservation of grammar is examined in seven divergent Drosophila genomes. Linked binding sites are observed for particular combinations of binding motifs, including Bicoid–Bicoid, Hunchback–Hunchback, Bicoid–Dorsal, Bicoid–Caudal and Dorsal–Twist. Direct evidence is presented for the importance of Bicoid–Dorsal linkage in the integration of the anterior–posterior and dorsal–ventral patterning systems. Hunchback–Hunchback interactions help explain unresolved aspects of segmentation, including the differential regulation of the eve stripe 3 + 7 and stripe 4 + 6 enhancers. We also present evidence that there is an under-representation of nucleosome positioning sequences in many enhancers, raising the possibility for a subtle higher-order structure extending across certain enhancers. We conclude that grammar of gene control regions is pervasively used in the patterning of the Drosophila embryo.

Developmental and evolutionary basis for drought tolerance of the Anopheles gambiae embryo

During the evolution of the Diptera there is a dramatic modification of the embryonic ectoderm, whereby mosquitoes contain separate amnion and serosa lineages while higher flies such as Drosophila melanogaster contain a single amnioserosa. Whole-genome transcriptome assays were performed with isolated serosa from Anopheles gambiae embryos. These assays identified a large number of genes implicated in the production of the larval cuticle. In D. melanogaster, these genes are activated just once during embryogenesis, during late stages where they are used for the production of the larval cuticle. Evidence is presented that the serosal cells secrete a dedicated serosal cuticle, which protects A. gambiae embryos from desiccation. Detailed temporal microarray assays of mosquito gene expression profiles revealed that the cuticular genes display biphasic expression during A. gambiae embryogenesis, first in the serosa of early embryos and then again during late stages as seen in D. melanogaster. We discuss how evolutionary modifications in the well-defined dorsal-ventral patterning network led to the wholesale deployment of the cuticle biosynthesis pathway in early embryos of A. gambiae.

Evolution of the dorsal-ventral patterning network in the mosquito, Anopheles gambiae

The dorsal-ventral patterning of the Drosophila embryo is controlled by a well-defined gene regulation network. We wish to understand how changes in this network produce evolutionary diversity in insect gastrulation. The present study focuses on the dorsal ectoderm in two highly divergent dipterans, the fruitfly Drosophila melanogaster and the mosquito Anopheles gambiae. In D. melanogaster, the dorsal midline of the dorsal ectoderm forms a single extra-embryonic membrane, the amnioserosa. In A. gambiae, an expanded domain forms two distinct extra-embryonic tissues, the amnion and serosa. The analysis of approximately 20 different dorsal-ventral patterning genes suggests that the initial specification of the mesoderm and ventral neurogenic ectoderm is highly conserved in flies and mosquitoes. By contrast, there are numerous differences in the expression profiles of genes active in the dorsal ectoderm. Most notably, the subdivision of the extra-embryonic domain into separate amnion and serosa lineages in A. gambiae correlates with novel patterns of gene expression for several segmentation repressors. Moreover, the expanded amnion and serosa anlage correlates with a broader domain of Dpp signaling as compared with the D. melanogaster embryo. Evidence is presented that this expanded signaling is due to altered expression of the sog gene.

Different combinations of gap repressors for common stripes in Anopheles and Drosophila embryos

Drosophila segmentation is governed by a well-defined gene regulation network. The evolution of this network was investigated by examining the expression profiles of a complete set of segmentation genes in the early embryos of the mosquito, Anopheles gambiae. There are numerous differences in the expression profiles as compared with Drosophila. The germline determinant Oskar is expressed in both the anterior and posterior poles of Anopheles embryos but is strictly localized within the posterior plasm of Drosophila. The gap genes hunchback and giant display inverted patterns of expression in posterior regions of Anopheles embryos, while tailless exhibits an expanded pattern as compared with Drosophila. These observations suggest that the segmentation network has undergone considerable evolutionary change in the dipterans and that similar patterns of pair-rule gene expression can be obtained with different combinations of gap repressors. We discuss the evolution of separate stripe enhancers in the eve loci of different dipterans.

Exploring cell death mechanisms by analyzing signaling cascades of the TNF/NGF receptor family

The ability of ligands of the tumor necrosis factor (TNF) family to induce death of cells independently of new protein synthesis provides a unique approach to molecular analysis of programmed cell death mechanisms. Sequential analysis of the protein-protein interactions by which these receptors signal, allows identification of specific molecules that participate in the cell death process and unequivocal definition of cause-effect relationships between them. Several receptors of this family, with structurally unrelated intracellular domains, have the ability to trigger cell death. some intracellular proteins that bind to the receptors and participate in the induction of their effects have been identified. Association of the Fas/APO1-interacting protein MORT1/FADD with the p55 TNF receptor-interacting protein TRADD, and the association of both MORT1/FADD and TRADD with a third protein, RIP, provide potential cross-talk mechanisms between Fas/APO1 and the p55 TNF receptor. TRAF2, a cytoplasmic protein that binds to the p75 TNF receptor, as well as to several other receptors of the TNF/NGF family, also binds to TRADD, thus further extending the range of receptors of this family that can share common signaling mechanisms. The N-terminal part of MORT1/FADD binds to a protease of the CED3/ICE family, MACH alpha. Activation of MACH alpha by the TNF/NGF receptors appears to be the most upstream enzymatic activity in the cascade of signaling for cell death.