Single Cell Population Research Articles

3D-printed biphasic scaffolds for the simultaneous regeneration of osteochondral tissues

Osteochondral tissue engineering (OCTE) involves the simulation of highly complex tissues with disparate biomechanical properties. OCTE is regarded as the best option for treating osteochondral defects, most of the drawbacks of current treatment methodologies can be addressed by this method. In recent years, the conventional scaffolds used in cartilage and bone regeneration are gradually being replaced by 3D printed scaffolds (3DP). In the present study, we devised the strategy of 3D printing for fabricating biphasic and integrated scaffolds that are loaded with bioactive factors for enhancing the osteochondral tissue regeneration. Polycaprolactone (PCL) and poly(lactic-co-glycolic acid) (PLGA), is used along with bioactive factors (chondroitin sulphate and beta-tricalcium phosphate (βTCP)) for the upper cartilage and lower bone layer respectively. The 3D printed bi-layered scaffolds with varying infill density, to mimic the native tissue, are not previously explored for OCTE. Hence, we tested the simultaneous osteochondrogenic differentiation inducing potential of the aforesaid 3D printed biphasic scaffolds in vitro, using rabbit adipose derived mesenchymal stem cells (ADMSCs). Further, the biphasic scaffolds were highly cytocompatible, with excellent cell adhesion properties and cellular morphology. Most importantly, these biphasic scaffolds directed the simultaneous differentiation of a single stem cell population in to two cell lineages (simultaneous differentiation of rabbit ADMSCs into chondrocytes and osteoblasts). Further, these scaffolds enhanced the production of ECM and induced robust expression of marker genes that is specific for respective cartilage and bone layers. The 3D printed OCTE scaffold of our study hence can simulate the native osteochondral unit and could be potential futuristic biomimetic scaffold for osteochondral defects. Further in vivo studies are warranted.

TMJ regenerative Medicine

AbstractThe temporomandibular joint (TMJ) is an articulation formed between the temporal bone and the mandibular condyle which is commonly affected and course with pain and dysfunctions of the temporomandibular joint. These affections are often so painful during fundamental oral activities that patients have lower quality of life. The treatment of these disorders includes systematically administered drugs (especially non steroid anti-inflammatory drugs and corticoids), physical therapies, and minimally invasive therapies that require intra articular injections. Limitations of therapeutics for severe TMJ diseases have led to increased interest in regenerative strategies combining stem cells, implantable scaffolds and well-targeting bioactive molecules. Recent advances in tissue engineering may provide an alternative to traditional strategies to repair and regenerate the TMJ. To succeed in functional and structural regeneration of TMJ is very challenging. Innovative strategies and biomaterials are absolutely crucial because TMJ can be considered as one of the most difficult tissues to regenerate due to its limited healing capacity, its unique histological and structural properties and the necessity for long-term prevention of its ossified or fibrous adhesions. The ideal approach for TMJ regeneration is a unique scaffold functionalized with an osteochondral molecular gradient containing a single stem cell population able to undergo osteogenic and chondrogenic differentiation such as BMSCs, ADSCs or DPSCs. The key for this complex regeneration is the functionalization with active molecules such as IGF-1, TGF-beta 1 or bFGF. This regeneration can be optimized by nano/micro-assisted functionalization and by spatiotemporal drug delivery systems orchestrating the 3D formation of TMJ tissues. Preceding the current trends in tissue engineering is an analysis of native tissue characterization, toward identifying tissue engineering objectives and validation metrics for restoring healthy and functional structures of the TMJ.

Abstract 446: CRISPRi-SNPs-seq identified regulatory loci conferring prostate cancer

Abstract Introduction: Genome-wide association studies (GWAS) along with expression quantitative trait loci (eQTL) have identified hundreds of genetic variants and target genes in prostate cancer (prCa). Although genetic predisposition has mainly been described in prostate cancer (PrCa), functional characterization of these risk loci remains a challenge. Methods: Low multiplicity of infection creates single lentiviral integrated cell population, which enable us to evaluate biological significance of steric hindrance at certain SNP sites in large scale. To screen for regulatory SNP, we designed a guide RNA library to target 2166 potential functional SNP sites with CRISPOR software. We performed negative screening in dCas9-KRAB stable prostate cell lines and applied RIGOR program to discover the SNPs that are essential for cell proliferation. We further validated regulatory role of selected SNPs using luciferase reporter assay, ChIP-qPCR and CRISPR-based SNP editing in prostate cells. Results: After gRNA interfering for 21 days, we performed RIGOR analysis and identified 153 proliferation-essential SNPs, covered by one or multiple prostate cancer cell lines. Intersection analysis showed that these SNPs tended to reside in 5'-UTR and intron regions. To characterize regulatory role of these SNPs, we performed functional analysis in a SNP rs60 since prostate cells containing guide RNAs targeting rs60 were significantly depleted (FDR<0.05). Pooled GWAS SNP analysis showed that the G allele of this SNP exhibit 10% higher PrCa risk than A allele. eQTL analysis showed that the G allele is associated with an increased expression of RUVBL1 (FDR=3.3E-13). To further characterize the SNP-gene association, we performed CRISPR-based RNA interference analysis that targeted the SNP site. We observed significant inhibition of the RUVBL1 gene expression in prostate cell lines. We also applied xCas9 adenine base editor and successfully converted rs60 A into G allele in multiple clones of BPH1, DU145 and PC3 cell line. Consequently, we observed RUVBL1 expression increase after switching A to G allele at this locus. We performed ChIP-qPCR and confirmed rs60 flanking region was highly H3K4me3 modified, suggesting a transactivation role of this loci in regulating RUVBL1 expression. When stably knocked down RUVBL1 expression by shRNA we found significant proliferation inhibition in multiple prostate cell lines. Gene set enrichment analysis showed an enrichment of MYC target genes with RUVBL1 expression in TCGA prostate cancer cohorts. Furthermore, increased RUVBL1 expression was associated with poor progression-free survival (p<0.01) in TCGA datasets. Conclusion: CRISPRi-SNPs-seq is a powerful screening tool to identify regulatory SNPs essential for cell proliferation. In combination with in-depth functional assays, the technology will facilitate discovery of regulatory variants and their genes responsible for disease risk. Citation Format: Yijun Tian, Jong A. Park, Liang Wang. CRISPRi-SNPs-seq identified regulatory loci conferring prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 446.

Quiescent Human Glioblastoma Stem Cells Mediate Tumor Initiation, Expansion, and Recurrence Following Chemotherapy

We test the hypothesis that human glioblastoma harbors quiescent cancer stem cells that evade anti-proliferative therapies. Functional characterization of spontaneous glioblastomas from genetically engineered mice reveals essential quiescent stem-like cells that can be directly isolated from tumors. A derived novel quiescent cancer stem cell specific gene expression signature is enriched in pre-formed patient xenograft single cell clusters that lack proliferative gene expression. A refined human 118-gene signature is preserved in quiescent single cell populations from primary and recurrent human glioblastomas. The signature conserved F3 cell surface receptor identifies quiescent tumor cells by antibody immunohistochemistry. F3 antibody sorted quiescent glioblastoma cells exhibit stem cell gene expression, enhanced self-renewal in culture, mediate tumor initiation, serial transplantation, and reconstitute tumor heterogeneity. Upon chemotherapy, the spared cancer stem cell pool becomes activated and accelerates transition to proliferation. These results help explain conventional treatment failure and lay a conceptual framework for alternative therapies.

Physiological Diversity Influences Detection of Stimulus Envelope and Fine Structure in Neurons of the Medial Superior Olive.

The neurons of the medial superior olive (MSO) of mammals extract azimuthal information from the delays between sounds reaching the two ears [interaural time differences (ITDs)]. Traditionally, all models of sound localization have assumed that MSO neurons represent a single population of cells with specialized and homogeneous intrinsic and synaptic properties that enable the detection of synaptic coincidence on a timescale of tens to hundreds of microseconds. Here, using patch-clamp recordings from large populations of anatomically labeled neurons in brainstem slices from male and female Mongolian gerbils (Meriones unguiculatus), we show that MSO neurons are far more physiologically diverse than previously appreciated, with properties that depend regionally on cell position along the topographic map of frequency. Despite exhibiting a similar morphology, neurons in the MSO exhibit subthreshold oscillations of differing magnitudes that drive action potentials at rates between 100 and 800 Hz. These oscillations are driven primarily by voltage-gated sodium channels and are distinct from resonant properties derived from other active membrane properties. We show that graded differences in these and other physiological properties across the MSO neuron population enable the MSO to duplex the encoding of ITD information in both fast, submillisecond time-varying signals as well as in slower envelopes.SIGNIFICANCE STATEMENT Neurons in the medial superior olive (MSO) encode sound localization cues by detecting microsecond differences in the arrival times of inputs from the left and right ears, and it has been assumed that this computation is made possible by highly stereotyped structural and physiological specializations. Here we report using a large (>400) sample size in which MSO neurons show a strikingly large continuum of functional properties despite exhibiting similar morphologies. We demonstrate that subthreshold oscillations mediated by voltage-gated Na+ channels play a key role in conferring graded differences in firing properties. This functional diversity likely confers capabilities of processing both fast, submillisecond-scale synaptic activity (acoustic "fine structure"), and slow-rising envelope information that is found in amplitude-modulated sounds and speech patterns.

A Subpopulation of Schwann Cell-Like Cells With Nerve Regeneration Signatures Is Identified Through Single-Cell RNA Sequencing.

Schwann cell-like cells (SCLCs) derived from human amniotic mesenchymal stem cells (hAMSCs) have been shown to promote peripheral nerve regeneration, but the underlying molecular mechanism was still poorly understood. In order to investigate the heterogeneity and potential molecular mechanism of SCLCs in the treatment of peripheral nerve regeneration at a single cell level, single-cell RNA sequencing was applied to profile single cell populations of hAMSCs and SCLCs. We profiled 6,008 and 5,140 single cells from hAMSCs and SCLCs, respectively. Based on bioinformatics analysis, pathways associated with proliferation, ECM organization, and tissue repair were enriched within both populations. Cell cycle analysis indicated that single cells within these two populations remained mostly in the G0/G1 phase. The transformation of single cells from hAMSCs to SCLCs was characterized by pseudotime analysis. Furthermore, we identified a subpopulation of SCLCs that highly expressed genes associated with Schwann cell proliferation, migration, and survival, such as JUN, JUND, and NRG1., Genes such as PTGS2, PITX1, VEGFA, and FGF2 that promote nerve regeneration were also highly expressed in single cells within this subpopulation, and terms associated with inflammatory and tissue repair were enriched in this subpopulation by pathway enrichment analysis. Our results indicate that a subpopulation of SCLCs with nerve regeneration signatures may be the key populations that promote nerve regeneration.

Immu-Mela: An open resource for exploring immunotherapy-related multidimensional genomic profiles in melanoma

There are increasing studies aimed to reveal genomic hallmarks predictive of immune checkpoint blockade (ICB) treatment response, which generated a large number of data and provided an unprecedented opportunity to identify response-related features and evaluate their robustness across cohorts. However, those valuable data sets are not easily accessible to the research community. To take full advantage of existing large-scale immuno-genomic profiles, we developed Immu-Mela (http://bioinfo.vanderbilt.edu/database/Immu-Mela/), a multidimensional immuno-genomic portal that provides interactive exploration of associations between ICB responsiveness and multi-omics features in melanoma, including genetic, transcriptomics, immune cells, and single-cell populations. Immu-Mela also enables integrative analysis of any two genomic features. We demonstrated the value of Immu-Mela by identifying known and novel genomic features associated with ICB response. In addition, Immu-Mela allows users to upload their data sets (unrestricted to any cancer types) and co-analyze with existing data to identify and validate signatures of interest. Immu-Mela reduces barriers between researchers and complex genomic data, facilitating discoveries in cancer immunotherapy.

Methods for analysing lineage tracing datasets.

A single population of progenitor cells maintains many epithelial tissues. Transgenic mouse cell tracking has frequently been used to study the growth dynamics of competing clones in these tissues. A mathematical model (the ‘single-progenitor model’) has been argued to reproduce the observed progenitor dynamics accurately. This requires three parameters to describe the growth dynamics observed in transgenic mouse cell tracking—a division rate, a stratification rate and the probability of dividing symmetrically. Deriving these parameters is a time intensive and complex process. We compare the alternative strategies for analysing this source of experimental data, identifying an approximate Bayesian computation-based approach as the best in terms of efficiency and appropriate error estimation. We support our findings by explicitly modelling biological variation and consider the impact of different sampling regimes. All tested solutions are made available to allow new datasets to be analysed following our workflows. Based on our findings, we make recommendations for future experimental design.

Single cell plasticity and population coding stability in auditory thalamus upon associative learning

Cortical and limbic brain areas are regarded as centres for learning. However, how thalamic sensory relays participate in plasticity upon associative learning, yet support stable long-term sensory coding remains unknown. Using a miniature microscope imaging approach, we monitor the activity of populations of auditory thalamus (medial geniculate body) neurons in freely moving mice upon fear conditioning. We find that single cells exhibit mixed selectivity and heterogeneous plasticity patterns to auditory and aversive stimuli upon learning, which is conserved in amygdala-projecting medial geniculate body neurons. Activity in auditory thalamus to amygdala-projecting neurons stabilizes single cell plasticity in the total medial geniculate body population and is necessary for fear memory consolidation. In contrast to individual cells, population level encoding of auditory stimuli remained stable across days. Our data identifies auditory thalamus as a site for complex neuronal plasticity in fear learning upstream of the amygdala that is in an ideal position to drive plasticity in cortical and limbic brain areas. These findings suggest that medial geniculate body’s role goes beyond a sole relay function by balancing experience-dependent, diverse single cell plasticity with consistent ensemble level representations of the sensory environment to support stable auditory perception with minimal affective bias.

070 Comprehensive single-cell analysis of Sézary syndrome reveals novel expression and therapeutic biomarkers

Cutaneous T cell lymphomas (CTCL) are a group of malignancies thought to derive from a clonal proliferation of skin-tropic T cells. Diagnosis is often delayed several years due to variations in presentation and lack of definitive biomarkers, which result in missed early intervention opportunities that may prevent disease progression. In the setting of more aggressive forms of CTCL, most treatments can initially decrease the tumor burden, but often ultimately fail to prevent the selective outgrowth of a resistant population. The lack of effective therapies is due in part to an incomplete understanding of tumor biology. Using single-cell mRNA and adaptive immune receptor sequencing of peripheral blood immune cells in SS, transcriptomic variations were quantified of almost 50,000 malignant and nonmalignant T cells across six SS patients. Within the population of single cells, we identified both quiescent and proliferative populations across multiple patients, and were able to newly identify a large number of genes associated with malignancy. Furthermore, in a single patient, we characterized differences in cell populations comparing malignant T cells after disease progression in the setting of treatment with histone deacetylase inhibition (HDACi) and photopheresis. HDACi therapy led to new transcriptional profiles in a subset of SS cells, characterized by the increased expression of the transcriptional factor FOXP3. These data are critical in defining a compendium of gene expression profiles and intratumoral heterogeneity in SS and CTCL, which are pivotal in our understanding of CTCL biology and in the development of targeted treatments.

FGF-MAPK signaling regulates human deep-layer corticogenesis.

SummaryDespite heterogeneity across the six layers of the mammalian cortex, all excitatory neurons are generated from a single founder population of neuroepithelial stem cells. However, how these progenitors alter their layer competence over time remains unknown. Here, we used human embryonic stem cell-derived cortical progenitors to examine the role of fibroblast growth factor (FGF) and Notch signaling in influencing cell fate, assessing their impact on progenitor phenotype, cell-cycle kinetics, and layer specificity. Forced early cell-cycle exit, via Notch inhibition, caused rapid, near-exclusive generation of deep-layer VI neurons. In contrast, prolonged FGF2 promoted proliferation and maintained progenitor identity, delaying laminar progression via MAPK-dependent mechanisms. Inhibiting MAPK extended cell-cycle length and led to generation of layer-V CTIP2+ neurons by repressing alternative laminar fates. Taken together, FGF/MAPK regulates the proliferative/neurogenic balance in deep-layer corticogenesis and provides a resource for generating layer-specific neurons for studying development and disease.

Simple Fluorogenic Cellular Assay for Histone Deacetylase Inhibitors Based on Split-Yellow Fluorescent Protein and Intrabodies.

Histone deacetylase (HDAC) inhibitors that regulate the posttranslational modifications of histone tails are therapeutic drugs for many diseases such as cancers, neurodegenerative diseases, and asthma; however, convenient and sensitive methods to measure the effect of HDAC inhibitors in cultured mammalian cells remain limited. In this study, a fluorogenic assay was developed to detect the acetylation of lysine 9 on histone H3 (H3K9ac), which is involved in several cancers, Alzheimer’s disease, and autism spectrum disorder. To monitor the changes in H3K9ac levels, an H3K9ac-specific intrabody fused with a small fragment FP11 of the split-yellow fluorescent protein (YFP) (scFv-FP11) was expressed in mammalian cells, together with a larger YFP fragment FP1-10 fused with a nuclear localization signal. When the intranuclear level of H3K9ac is increased, the scFv-FP11 is more enriched in the nucleus via passive diffusion through the nuclear pores from the cytoplasm, which increases the chance of forming a fluorescent complex with the nuclear YFP1-10. The results showed that the YFP fluorescence increased when the cells were treated with HDAC inhibitors. Moreover, the sensitivity of the split YFP reporter system to three HDAC inhibitors was higher than that of a conventional cell viability test. The assay system will be a simple and sensitive detection method to evaluate HDAC inhibitor activities at the levels of both single cells and cell populations.

An interplay of resource availability, population size and mutation rate potentiates the evolution of metabolic signaling

BackgroundAsexually reproducing populations of single cells evolve through mutation, natural selection, and genetic drift. Environmental conditions in which the evolution takes place define the emergent fitness landscapes. In this work, we used Avida—a digital evolution framework—to uncover a hitherto unexplored interaction between mutation rates, population size, and the relative abundance of metabolizable resources, and its effect on evolutionary outcomes in small populations of digital organisms.ResultsOver each simulation, the population evolved to one of several states, each associated with a single dominant phenotype with its associated fitness and genotype. For a low mutation rate, acquisition of fitness by organisms was accompanied with, and dependent on, an increase in rate of genomic replication. At an increased mutation rate, phenotypes with high fitness values were similarly achieved through enhanced genome replication rates. In addition, we also observed the frequent emergence of suboptimal fitness phenotype, wherein neighboring organisms signaled to each other information relevant to performing metabolic tasks. This metabolic signaling was vital to fitness acquisition and was correlated with greater genotypic and phenotypic heterogeneity in the population. The frequency of appearance of signaling populations increased with population size and with resource abundance.ConclusionsOur results reveal a minimal set of environment–genotype interactions that lead to the emergence of metabolic signaling within evolving populations.

Quantitative Approach for Protein Analysis in Small Cell Ensembles by an Integrated Microfluidic Chip with MALDI Mass Spectrometry.

Increasing evidence has demonstrated that cells are individually heterogeneous. Advancing the technologies for single-cell analysis will improve our ability to characterize cells, study cell biology, design and screen drugs, and aid cancer diagnosis and treatment. Most current single-cell protein analysis approaches are based on fluorescent antibody-binding technology. However, this technology is limited by high background and cross-talk of multiple tags introduced by fluorescent labels. Stable isotope labels used in mass cytometry can overcome the spectral overlap of fluorophores. Nevertheless, the specificity of each antibody and heavy-metal-tagged antibody combination must be carefully validated to ensure detection of the intended target. Thus, novel single-cell protein analysis methods without using labels are urgently needed. Moreover, the labeling approach targets already known motifs, hampering the discovery of new biomarkers relevant to single-cell population variation. Here, we report a combined microfluidic and matrix-assisted laser desorption and ionization (MALDI) mass spectrometric approach for the analysis of protein biomarkers suitable for small cell ensembles. All necessary steps for cell analysis including cell lysis, protein capture, and digestion as well as MALDI matrix deposition are integrated on a microfluidic chip prior to the downstream MALDI-time-of-flight (TOF) detection. For proof of principle, this combined method is used to assess the amount of Bcl-2, an apoptosis regulator, in metastatic breast cancer cells (MCF-7) by using an isotope-labeled peptide as an internal standard. The proposed approach will eventually provide a new means for proteome studies in small cell ensembles with the potential for single-cell analysis and improve our ability in disease diagnosis, drug discovery, and personalized therapy.

Microdroplet-based one-step RT-PCR for ultrahigh throughput single-cell multiplex gene expression analysis and rare cell detection

Gene expression analysis of individual cells enables characterization of heterogeneous and rare cell populations, yet widespread implementation of existing single-cell gene analysis techniques has been hindered due to limitations in scale, ease, and cost. Here, we present a novel microdroplet-based, one-step reverse-transcriptase polymerase chain reaction (RT-PCR) platform and demonstrate the detection of three targets simultaneously in over 100,000 single cells in a single experiment with a rapid read-out. Our customized reagent cocktail incorporates the bacteriophage T7 gene 2.5 protein to overcome cell lysate-mediated inhibition and allows for one-step RT-PCR of single cells encapsulated in nanoliter droplets. Fluorescent signals indicative of gene expressions are analyzed using a probabilistic deconvolution method to account for ambient RNA and cell doublets and produce single-cell gene signature profiles, as well as predict cell frequencies within heterogeneous samples. We also developed a simulation model to guide experimental design and optimize the accuracy and precision of the assay. Using mixtures of in vitro transcripts and murine cell lines, we demonstrated the detection of single RNA molecules and rare cell populations at a frequency of 0.1%. This low cost, sensitive, and adaptable technique will provide an accessible platform for high throughput single-cell analysis and enable a wide range of research and clinical applications.

Transcriptional bursts explain autosomal random monoallelic expression and affect allelic imbalance.

Transcriptional bursts render substantial biological noise in cellular transcriptomes. Here, we investigated the theoretical extent of allelic expression resulting from transcriptional bursting and how it compared to the amount biallelic, monoallelic and allele-biased expression observed in single-cell RNA-sequencing (scRNA-seq) data. We found that transcriptional bursting can explain the allelic expression patterns observed in single cells, including the frequent observations of autosomal monoallelic gene expression. Importantly, we identified that the burst frequency largely determined the fraction of cells with monoallelic expression, whereas the burst size had little effect on monoallelic observations. The high consistency between the bursting model predictions and scRNA-seq observations made it possible to assess the heterogeneity of a group of cells as their deviation in allelic observations from the expected. Finally, both burst frequency and size contributed to allelic imbalance observations and reinforced that studies of allelic imbalance can be confounded from the inherent noise in transcriptional bursting. Altogether, we demonstrate that allele-level transcriptional bursting renders widespread, although predictable, amounts of monoallelic and biallelic expression in single cells and cell populations.

Single cell eQTL analysis identifies cell type-specific genetic control of gene expression in fibroblasts and reprogrammed induced pluripotent stem cells

BackgroundThe discovery that somatic cells can be reprogrammed to induced pluripotent stem cells (iPSCs) has provided a foundation for in vitro human disease modelling, drug development and population genetics studies. Gene expression plays a critical role in complex disease risk and therapeutic response. However, while the genetic background of reprogrammed cell lines has been shown to strongly influence gene expression, the effect has not been evaluated at the level of individual cells which would provide significant resolution. By integrating single cell RNA-sequencing (scRNA-seq) and population genetics, we apply a framework in which to evaluate cell type-specific effects of genetic variation on gene expression.ResultsHere, we perform scRNA-seq on 64,018 fibroblasts from 79 donors and map expression quantitative trait loci (eQTLs) at the level of individual cell types. We demonstrate that the majority of eQTLs detected in fibroblasts are specific to an individual cell subtype. To address if the allelic effects on gene expression are maintained following cell reprogramming, we generate scRNA-seq data in 19,967 iPSCs from 31 reprogramed donor lines. We again identify highly cell type-specific eQTLs in iPSCs and show that the eQTLs in fibroblasts almost entirely disappear during reprogramming.ConclusionsThis work provides an atlas of how genetic variation influences gene expression across cell subtypes and provides evidence for patterns of genetic architecture that lead to cell type-specific eQTL effects.

Abstract PO009: Single-cell protein activity inference identifies tumor-enriched macrophages associated with early post-surgical disease recurrence

Abstract Primary Clear Cell Renal Carcinoma (ccRCC) is a highly heterogenous disease with a variable disease course post-surgery. To elucidate the cellular and transcriptional mechanisms driving disease recurrence, we aimed in this study to transcriptionally profile single-cell populations enriched in the Tumor Micro-Environment (TME) and assess their key regulatory proteins as biomarkers of recurrence. We performed scRNASeq on immune and non-immune populations from tumor compared to tumor-adjacent tissue in primary resections of treatment-naïve ccRCC patients (n=11), thus producing a complete atlas of the ccRCC tumor microenvironment. In order to mitigate gene dropout inherent to scRNASeq and commonly preventing detection of >80% of genes, we leveraged the VIPER algorithm to infer proteomic regulators of cell state. This approach relies on construction of lineage-specific gene regulatory networks with ARACNe, the Algorithm for Reconstruction of Accurate Cellular Networks, and infers protein activity from expression of hundreds of downstream transcriptional targets. By VIPER, we recover key regulatory proteins not significantly detected by gene expression alone, and improve resolution of cell subtypes. VIPER-inferred protein activity systematically abrogated gene dropout effects on a repertoire of >6,000 regulatory proteins, comparing favorably with antibody-based measurements for a subset of proteins profiled by spectral flow cytometry. This helped comprehensively characterize the individual cellular sub-populations comprising the ccRCC tumor and peri-tumor microenvironment, as well as their specific master regulators and candidate cell-cell interactions, revealing several populations undetectable by gene expression analysis. Specifically, we uncovered a novel tumor-specific macrophage subpopulation characterized by significant upregulation of TREM2, APOE, and C1Q, further validated by spatially-resolved quantitative multispectral immunofluorescence (qmIF). These tumor-specific macrophages were significantly over-represented in an exploratory cohort of patients who recurred following surgery compared to patients who did not recur (n=8), predictive of time-to-recurrence with a p-value of 0.0067. In a larger validation cohort (n=157), enrichment of tumor-specific macrophage population markers was associated with early post-surgical recurrence with a p-value of 0.0029. This study highlights the substantial increase in resolution of scRNASeq analysis afforded by VIPER and identifies TREM2/APOE/C1Q-positive macrophage infiltration as a potential biomarker for ccRCC recurrence and a candidate target for intervention to reduce post-surgical recurrence rates. Citation Format: Aleksandar Obradovic, Nivedita Chowdhury, Casey Ager, Vinson Wang, Lukas Vlahos, Xinzheng Guo, David Aggen, Andrea Califano, Charles Drake. Single-cell protein activity inference identifies tumor-enriched macrophages associated with early post-surgical disease recurrence [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO009.

Abstract SP112: Spatial variance signatures/Intra-tumor zonation in TNBC

Abstract It is increasingly clear that triple negative breast cancer (TNBC) is a heterogeneous disease with variable clinical presentation, histological features and response to therapy. While these differences have been partially explained by inter- and intra-tumoral heterogeneity, spatial heterogeneity represented by the tumor architecture plays a critical role in clonal evolution and displays a landscape for different compartment-specific processes and cell-to-cell specific interactions. To better understand the impact of spatial heterogeneity on gene-expression-defined cell populations, we have coupled single-cell RNA sequencing with multiplex immunofluorescence (IF). Multiplex immunofluorescence using specific markers for each cell cluster, integrated with computational image analyses and neighborhood maps, has revealed spatial zonation of single cell subpopulations. Zonation of single cell populations was coupled to hypoxia and overlayed distinct metabolic tumor zones and defined areas of differential stress and cell plasticity that give rise to tumor cells with enhanced fitness and aggressivity. Citation Format: M Park, C Martínez Ramirez, Y Yang, A Blanchet-Cohen, H Kuasne, A Fortier, J Ragoussis, P Savage, A Omeroglou, S Meterissian, S Costantino, C Kleinman. Spatial variance signatures/Intra-tumor zonation in TNBC [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SP112.

Dissociation Constant of Integrin-RGD Binding in Live Cells from Automated Micropipette and Label-Free Optical Data.

The binding of integrin proteins to peptide sequences such as arginine-glycine-aspartic acid (RGD) is a crucial step in the adhesion process of mammalian cells. While these bonds can be examined between purified proteins and their ligands, live-cell assays are better suited to gain biologically relevant information. Here we apply a computer-controlled micropipette (CCMP) to measure the dissociation constant (Kd) of integrin-RGD-binding. Surface coatings with varying RGD densities were prepared, and the detachment of single cells from these surfaces was measured by applying a local flow inducing hydrodynamic lifting force on the targeted cells in discrete steps. The average behavior of the populations was then fit according to the chemical law of mass action. To verify the resulting value of Kd2d = (4503 ± 1673) 1/µm2, a resonant waveguide grating based biosensor was used, characterizing and fitting the adhesion kinetics of the cell populations. Both methods yielded a Kd within the same range. Furthermore, an analysis of subpopulations was presented, confirming the ability of CCMP to characterize cell adhesion both on single cell and whole population levels. The introduced methodologies offer convenient and automated routes to quantify the adhesivity of living cells before their further processing.