Bulk Tissue Research Articles

Investigating fishing strategies and habitat differences in late Holocene Oregon Coast sturgeon (Acipenser spp.) through coupled genetic and isotope analyses

Understanding the habitats people were fishing in the past is central to evaluating the relationship between coastal environmental change and human behavior. Researchers often use zooarchaeological identification of fishes and modern ecological data to infer the habitats people fished in the past. However, these inferences assume stable environmental conditions through time and can be hindered by precision issues in identification of archaeological specimens (species vs. genus or family). Here, we integrate genetic and bulk tissue stable isotope data to investigate a late Holocene sturgeon fishery in northern Oregon. Ancient DNA analysis indicated that people were fishing for both green and white sturgeon (Acipenser medirostris and Acipenser transmontanus) in comparable numbers. Stable isotope analyses of these same bones documented distinct isotope values for each species, correlating with species-specific habitat preferences. These findings highlight the value of paired isotope and genetic data to elucidate human fishing strategies and environmental change and provide baseline ecological data for modern fisheries.

Vascular Dysfunction Is Central to Alzheimer's Disease Pathogenesis in APOE e4 Carriers.

Alzheimer’s disease (AD) is the most common form of dementia and the leading risk factor, after age, is possession of the apolipoprotein E epsilon 4 allele (APOE4). Approximately 50% of AD patients carry one or two copies of APOE4 but the mechanisms by which it confers risk are still unknown. APOE4 carriers are reported to demonstrate changes in brain structure, cognition, and neuropathology, but findings have been inconsistent across studies. In the present study, we used multi-modal data to characterise the effects of APOE4 on the brain, to investigate whether AD pathology manifests differently in APOE4 carriers, and to determine if AD pathomechanisms are different between carriers and non-carriers. Brain structural differences in APOE4 carriers were characterised by applying machine learning to over 2000 brain MRI measurements from 33,384 non-demented UK biobank study participants. APOE4 carriers showed brain changes consistent with vascular dysfunction, such as reduced white matter integrity in posterior brain regions. The relationship between APOE4 and AD pathology was explored among the 1260 individuals from the Religious Orders Study and Memory and Aging Project (ROSMAP). APOE4 status had a greater effect on amyloid than tau load, particularly amyloid in the posterior cortical regions. APOE status was also highly correlated with cerebral amyloid angiopathy (CAA). Bulk tissue brain transcriptomic data from ROSMAP and a similar dataset from the Mount Sinai Brain Bank showed that differentially expressed genes between the dementia and non-dementia groups were enriched for vascular-related processes (e.g., “angiogenesis”) in APOE4 carriers only. Immune-related transcripts were more strongly correlated with AD pathology in APOE4 carriers with some transcripts such as TREM2 and positively correlated with pathology severity in APOE4 carriers, but negatively in non-carriers. Overall, cumulative evidence from the largest neuroimaging, pathology, and transcriptomic studies available suggests that vascular dysfunction is key to the development of AD in APOE4 carriers. However, further studies are required to tease out non-APOE4-specific mechanisms.

Abstract 989: Spatial profiling of androgen receptor splice variant 7 transcriptional activity in prostate cancer metastases

Abstract Introduction: Androgen receptor splice variant 7 (AR-V7) is expressed in metastases from patients with castration resistant prostate cancer (CRPC) and shows a high level of inter- and intra-tumoral variability. However, the downstream activity generated by AR-V7 in tissue has not been shown. Whether AR-V7 is active in tissue or whether AR-V7 is a non-functioning biomarker with full-length AR is not known. To address this question, we constructed a tissue microarray (TMA) of 56 metastases from 27 patients with CRPC to analyze spatial gene expression using the GeoMx Digital Spatial Profiler. Immunostaining was performed to define epithelial, vascular, and stromal compartments. The stained tissues were then hybridized with barcoded tagged oligonucleotides targeting 2093 unique genes, which included those representing AR, AR-V cryptic exons, AR and neuroendocrine activity, and immune cell markers. One 500 um region of interest (ROI) was assessed per tissue core (approximately 1200 cells). A sequential section from the same TMA was then stained with AR-V7 and AR-C-terminal specific antibodies. ROIs for RNA and protein were selected to be similar between slides. In addition to DSP, each metastasis was assessed by RNA-seq on the bulk tissue. Results: The most differentially expressed genes (FDR<0.05) based on association with AR-V7 staining were known downstream AR regulated genes including KLK2 and 3, FKBP5, NKX3.1, TMPRSS2, FASN, and TARP. Additionally, genes associated with proliferation and stemness, e.g., POLB, KRT1, SOX2, were significantly expressed. Since 93% of patients were on ADT at time of tissue collection and over 80% also had been treated with either abiraterone or enzalutamide, the increase in AR downstream genes would not be expected to occur from ligand activation of AR-FL. We also have previously shown that knock-down of AR-V7 in LNCaP95 cells results in loss of AR binding to AREs. In these metastases, then, activation of AR downstream genes would be a result of AR-V7 nuclear transport of AR-FL through AR-V7/AR-FL heterodimers or transcriptional activation by AR-V7 homodimers. Of further note, AR cryptic exons 1, 2, and 5 were also significantly expressed in AR-V7 positive ROIs (p< 0.0001). RNA-seq intron/exon junction reads were used to demonstrate that additional AR-Vs, most commonly AR-V9, were also expressed in tissues positive for AR-V7, suggesting that AR splicing is a common event in CRPC. Finally, expression of neuroendocrine (NE) genes INSM1 and TUBB2 were not expressed in AR-V7 positive ROIs (negatively correlated, p<0.001), indicating that AR-V7 and NE phenotypes cannot co-exist in the same cell. Conclusion: AR-V7 continues to drive prostate cancer through activation of the AR-cistrome. Its expression is heterogenous in metastases along with NE cells, suggesting that in the presence of AR-V7 and NE markers, therapy needs to be directed at the N-terminus of AR and NE components. Citation Format: Cynthia C. Sprenger, Ilsa Coleman, Michelle Kriner, Lauren Brady, Margaret Hoang, Martine Roudier, Mamatha Damodarasamy, Radhika Patel, Lawrence True, Peter Nelson, Michael Haffner, Stephen Plymate. Spatial profiling of androgen receptor splice variant 7 transcriptional activity in prostate cancer metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 989.

Caffeine intake exerts dual genome-wide effects on hippocampal metabolism and learning-dependent transcription.

Caffeine is the most widely consumed psychoactive substance in the world. Strikingly, the molecular pathways engaged by its regular consumption remain unclear. We herein addressed the mechanisms associated with habitual (chronic) caffeine consumption in the mouse hippocampus using untargeted orthogonal omics techniques. Our results revealed that chronic caffeine exerts concerted pleiotropic effects in the hippocampus at the epigenomic, proteomic, and metabolomic levels. Caffeine lowered metabolism-related processes (e.g., at the level of metabolomics and gene expression) in bulk tissue, while it induced neuron-specific epigenetic changes at synaptic transmission/plasticity-related genes and increased experience-driven transcriptional activity. Altogether, these findings suggest that regular caffeine intake improves the signal-to-noise ratio during information encoding, in part through fine-tuning of metabolic genes, while boosting the salience of information processing during learning in neuronal circuits.

Abstract 4013: Functional heterogeneity of cancer-associated stromal subtypes in the prostate cancer microenvironment

Abstract The stromal tumor microenvironment plays a central role in the development, progression and therapy resistance of prostate cancer (PCa), the second leading cause of cancer-related death in males in western nations. Functional and single cell RNA sequencing (scRNA-seq) studies unequivocally demonstrate the coexistence of functionally and spatially distinct fibroblast and mural cell states within the tumor microenvironment of various non-prostate tumors. Stromal cellular heterogeneity in PCa however remains poorly understood. This study therefore aimed to (1) comprehensively analyze stromal cell states within the PCa microenvironment and (2) to identify and characterize onco-supportive fibromuscular entities in respect to their potential clinical exploitation. Thus, we performed bulk tissue scRNA-seq on biopsy cores from benign and cancerous prostate tissue of 4 different patients. Analyses presented here focused on the fibroblast and mural cell clusters, which each delineated further into 2 subclusters. One fibroblast subcluster showed strong similarity to published signatures of inflammatory cancer-associated fibroblasts (iCAF). A closely related but distinct fibroblast subcluster exhibited hallmarks of benign interstitial fibroblasts with enrichment of GO terms such as antigen processing and presentation. Based on expression signatures and spatial localization via immunohistochemistry, the 2 mural cell subclusters (MCAM+) were identified as vascular smooth muscle cells (vSMCs) and dedifferentiated prostate SMCs/myofibroblasts. Notably, the gene signature of this latter subcluster correlated with increasing Gleason score and decreased disease-specific survival. On the basis of scRNA-seq data from this and independent datasets, panels of subcluster-specific markers were selected for validation studies via FACS, multiplex immunohistochemistry and quantitative real time PCR. Thus far, immunohistochemical studies validated not only the in vivo presence of the 4 distinct cellular states but also revealed their distinct spatial localization. We will present molecular and functional data from these ongoing analyses in (i) immortalized fibroblast and smooth muscle cell lines, (ii) heterogeneous ex vivo outgrowth cultures of primary PCa fibroblasts/myofibroblasts and (iii) primary cells from single cell suspensions of PCa biopsies enzymatically digested using an in-house approach optimized for maximal recovery of fibromuscular cells. These studies aim to evaluate the specificity, robustness and suitability of the chosen markers to delineate distinct tumor-relevant stromal cell subtypes enabling their functional contribution to PCa pathophysiology and clinical relevance to be assessed in future experiments. Citation Format: Elisabeth Damisch, Elena Brunner, Sieghart Sopper, Isabel Heidegger, Andreas Pircher, Georgios Fotakis, Zlatko Trajanoski, Sandra Theresa Deichsler, Georg Schäfer, Natalie Sampson. Functional heterogeneity of cancer-associated stromal subtypes in the prostate cancer microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4013.

Abstract 1460: Decoding the tumor biology of the orphan malignancy fibrolamellar carcinoma at single-cell resolution

Abstract The World Health Organization (WHO) recognized fibrolamellar carcinoma (FLC) in 2010 as a rare and aggressive form of liver cancer that predominately afflicts adolescents and young adults. There are currently no effective therapies. Surgical resection remains the only option to date, but it is not viable for patients who present with metastasis. Thus, there is an urgent need to identify therapeutic targets. The hallmark genetic lesion of FLC, occurring in >80% of patients, was recently identified to be a ~400kb heterozygous deletion on chromosome 19, leading to the oncogenic fusion protein DNAJB1-PRKACA (DP). We recently used FLC primary tumors and matched non-malignant liver samples to map the chromatin activity landscape of FLC by chromatin run-on sequencing, or ChRO-seq, which is a state-of-the-art technology for quantifying nascent transcription and defining active regulatory elements across the genome. We identified nearly 7000 FLC-specific enhancers and ~150 “super-enhancers” (SEs) - dense clusters of highly active enhancers that mark nearby critical oncogenes. Despite these advances, a major limitation is the bulk tissue nature of the study - that is, these data reflect an average profile across numerous different cell types (hepatocytes, stellate cells, fibroblasts, macrophages, endothelial cells, etc.), and therefore it is not evident which enhancers and genes are active in which cell types. This represents a major knowledge gap. If we could learn the specific cell types in which FLC enhancers and genes are active, we could then study the functions of these genes in FLC with greater precision and develop more effective targeted therapeutics. I recently conducted single-cell Assay for Transposase Accessible Chromatin ATAC-seq (scATAC-seq) to bridge this knowledge gap. I identified eight clusters from FLC-Primary, FLC-Metastatic, and non-malignant liver (NML) samples. Dimensionality reduction reveals two FLC-Primary, and FLC-Metastatic derived clusters that exhibit an epithelial-like identity most closely related to NML-epithelial cells. Using this scATAC-seq dataset, I have deconvoluted and resolved the bulk resolution limitations of ChRO-seq signal. ScATAC-seq reveals ChRO-seq defined candidate genes are highly accessible in FLC-Primary and FLC-Metastatic transformed Epithelial Cells. I have also dissected ChRO-seq defined SE’s and detailed the proportion of active constituent enhancers within each cell type. Further analysis revealed cell-type-specific transcriptional networks. Together, these studies provide the first single-cell resolution understanding of the transcriptional network in FLC. Citation Format: Alaa R. Farghli, Bo Shui, Seoyeon Lee, Paul R. Munn, Yutong Zhu, Paul Soloway, Praveen Sethupathy. Decoding the tumor biology of the orphan malignancy fibrolamellar carcinoma at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1460.

Abstract 488: A systems biology approach to defining tumor heterogeneity and prognostic and targetable master regulator protein signatures from bulk and single-cell RNAseq in osteosarcoma

Abstract Despite many clinical trials, outcome for osteosarcoma (OS) patients remains poor, especially for those with metastatic or relapsed/refractory disease. We leveraged network-based systems biology approaches to discover Master Regulator (MR) proteins representing pharmacologically accessible, mechanistic determinants of OS cell state, and to dissect tumor transcriptional heterogeneity. MRs were identified by interrogating an OS regulatory network—generated from 87 RNAseq profiles in the TARGET OS cohort—with gene expression signatures from 149 diagnostic OS samples, using the VIPER algorithm. RNAseq profiles were generated in four sarcoma cell lines following perturbation with ~400 oncology drugs, and used to identify drugs capable of inverting MR activity profiles with the OncoTreat algorithm. Unsupervised, protein activity-based clustering of the samples identified two clusters, characterized by a significant overall survival difference (76% vs 38%, log-rank p-val 0.0041). Patients in the high-risk cluster presented aberrant activity of proteins involved in cell cycle (FOXM1, CENPF, TOP2A) and epigenetic remodeling (EZH2, KDM1A), while those in the low-risk cluster had aberrant activity of proteins involved in immune response (VAV1, CD86, CEBPE), interferon gama signaling (IRF5, MNDA), and senescence control (CREG1, TFEC). We further identified patients with metastatic disease and particularly poor outcome (<15% survival) showing high activity in stem cell-related proteins NANOG, ZSCAN4, and LIN28A. To address intra-tumor heterogeneity and immune infiltration (40-60% in the samples) in bulk RNAseq data, we inferred protein activity in previously published single-cell RNAseq profiles from 11 OS patients, using regulatory networks also produced by single-cell analysis. We identified three tumor subpopulations, co-existing in all the samples, with lineage similarity to osteoblasts, chondroblasts, and fibroblasts. The most active MR proteins (p-val < 10E-30) were highly distinct across these subpopulations: NANOG, REL, IGF2, TOP2A (osteoblasts), SSTR3, WNT1, KDM6B, EZH2 (chondroblasts), and NOD1, ERBB3, PRKDC, INSR (fibroblasts). Pharmacologically accessible MRs significantly active across the three subpopulations and in subsets of bulk RNAseq samples included EZH2, CDK2, TOP2A, HDAC5, and PRKDC. OncoTreat analysis predicted sensitivity to camptothecin, seliciclib, galunisertib, and rigosertib in both fibroblast- and chondroblast-like subpopulations. In conclusion, using network-based systems biology approaches in OS, we identified pharmacologically accessible MR subtypes differentiating survival at the bulk tissue level, and defining three distinct tumor subpopulations at the single-cell level with unique predicted drug sensitivities. Citation Format: Somnath Tagore, Jovana Pavisic, Aaron T. Griffin, Katherine Janeway, Andrew L. Kung, Filemon Dela Cruz, Alejandro Sweet-Cordero, Inge Behroozfard, Stanley Leung, Alex Lee, Darrell Yamashiro, Julia Glade Bender, Andrea Califano. A systems biology approach to defining tumor heterogeneity and prognostic and targetable master regulator protein signatures from bulk and single-cell RNAseq in osteosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 488.

Abstract 790: Identification of cell identity pathways that cooperate with oncogenic Kras in pancreatic cancer initiation by single-cell epigenomic analyses

Abstract Introduction: The major genetic driver for pancreatic ductal adenocarcinoma (PDAC) is oncogenic KRAS. However, adult acinar cells, the most probable origin of PDAC, are largely refractory to KrasG12D-mediated oncogenic transformation in conditional mouse models. With the concomitant loss of transcription factors that regulate acinar cell differentiation, such as Pdx1 (Pancreatic and Duodenal Homeobox 1), acinar cells undergo a rapid cell identity switch, the so-called acinar-to-ductal metaplasia (ADM). Consequently, Pdx1 knockout mice present with massively accelerated tumor formation. How loss of cell identity cooperates with oncogenic Kras to induce pancreatic transformation is largely unclear. Methods: To elucidate mechanisms that accelerate the cellular reprogramming after loss of acinar differentiation, conditional Pdx1 knockout animals were analyzed. By performing single-cell ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) from frozen bulk tissue, genome-wide chromatin accessibility states were captured at different stages of carcinogenesis. Changes in the epigenome were correlated to RNA-seq data. Moreover, expression of differentially regulated genes was validated by RNAscope and immunofluorescence staining. Results: While sole expression of KrasG12D in adult acinar cells induces only a few transcriptional and epigenetic changes, loss of the acinar differentiation factor Pdx1 leads to a previously unidentified switch of acinar cell identity. Notably, the chromatin profiles of Pdx1 knockout acinar cells, despite appearing phenotypically normal, show a striking similarity to ADM cells. One of the most differentially regulated genes in acinar cells from wild type versus Pdx1 knockout mice is Ror2. As a mediator of the non-canonical Wnt signaling, Ror2 regulates essential signaling pathways, such as Ras-MAPK signaling. Pdx1 knockout acinar cells exhibit a high accessibility of the gene, while it is repressed in Pdx1 wild type cells. Moreover, gene expression is significantly increased in Pdx1 knockout mice. To test if Ror2 is a potential regulator of pancreatic carcinogenesis, immunostaining of pancreatic cancer tissues from KrasG12D;p53mut (KPC) mice and human PDAC specimens was performed. Staining revealed Ror2 expression in a subset of neoplasms, suggesting a distinct subtype of early lesions. Conclusion: Our data reveal that the loss of the acinar differentiation factor Pdx1 leads to massive alterations in the transcriptome and epigenome of acinar cells, significantly accelerating Kras-dependent pancreatic carcinogenesis. In-depth sequencing and molecular analyses identified de-regulation of the receptor kinase Ror2, an important mediator of multiple intracellular signaling pathways, which we hypothesize cooperates with KrasG12D to induce and promote pancreatic carcinogenesis. Citation Format: Simone Benitz, Ian Loveless, Malak Nasser, Hui-Ju Wen, Daniel Long, Jacee Moore, Erick Davis, Tobias Straub, Ivonne Regel, Filip Bednar, Howard Crawford. Identification of cell identity pathways that cooperate with oncogenic Kras in pancreatic cancer initiation by single-cell epigenomic analyses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 790.

Bulk and Single-Nucleus Transcriptomics Highlight Intra-Telencephalic and Somatostatin Neurons in Alzheimer's Disease.

Cortical neuron loss is a pathological hallmark of late-onset Alzheimer’s disease (AD). However, it remains unclear which neuronal subtypes beyond broad excitatory and inhibitory classes are most vulnerable. Here, we analyzed cell subtype proportion differences in AD compared to non-AD controls using 1037 post-mortem brain samples from six neocortical regions. We identified the strongest associations of AD with fewer somatostatin (SST) inhibitory neurons (β = −0.48, pbonf = 8.98 × 10–9) and intra-telencephalic (IT) excitatory neurons (β = -0.45, pbonf = 4.32 × 10–7). Replication in three AD case-control single-nucleus RNAseq datasets most strongly supported the bulk tissue association of fewer SST neurons in AD. In depth analyses of cell type proportions with specific AD-related neuropathological and cognitive phenotypes revealed fewer SST neurons with greater brain-wide post-mortem tau and beta amyloid, as well as a faster rate of antemortem cognitive decline. In contrast, greater IT neuron proportions were associated with a slower rate of cognitive decline as well as greater residual cognition–a measure of cognitive resilience–but not canonical AD neuropathology. Our findings implicate somatostatin inhibitory and intra-telencephalic excitatory neuron subclasses in the pathogenesis of AD and in cognitive resilience to AD pathology, respectively.

Comparison of fluorescence lifetime and multispectral imaging for quantitative multiplexing in biological tissue.

Fluorescence lifetime (FLT) multiplexing and multispectral imaging (MSI) are both frequently employed for in vitro and ex vivo biological studies. In vivo applications of MSI for deep seated fluorophores require consideration of diffusive light propagation in biological tissue. We have previously shown that a well-known redshift of fluorescence spectra in diffusive medium induces a fluorophore cross-talk, which cannot be accounted for even with known optical properties of the medium. In contrast, FLT measurements remain largely unaffected by light propagation in tissue, enabling zero cross-talk and accurate relative quantification. While a fully quantitative estimation of fluorophore concentrations requires depth resolved tomographic imaging, this is often not possible due to the difficulty of estimating tissue optical properties and modelling light propagation in complex tissue geometries. Here, we experimentally investigate the performance of planar (non-tomographic) MSI and FLT multiplexing for the quantitative recovery of multiple near-infrared fluorophores embedded in 4-8 mm thick tissue. We show that FLT multiplexing provides a superior quantification accuracy (error < 10%) compared to MSI (error = 20-107%) in tissue. The error rates for MSI increased with tissue thickness and can be directly attributed to the spectral redshift induced cross-talk between emission spectra. Our data indicate that planar FLT multiplexing can provide high quantification accuracy in thick biological tissue without a need for optical property estimation, thereby offering an important validation tool for rapid quantification of fluorophore concentrations in bulk tissue.

Bulk and amino acid nitrogen isotopes suggest shifting nitrogen balance of pregnant sharks across gestation.

Nitrogen isotope (δ15N) analysis of bulk tissues and individual amino acids (AA) can be used to assess how consumers maintain nitrogen balance with broad implications for predicting individual fitness. For elasmobranchs, a ureotelic taxa thought to be constantly nitrogen limited, the isotopic effects associated with nitrogen-demanding events such as prolonged gestation remain unknown. Given the linkages between nitrogen isotope variation and consumer nitrogen balance, we used AA δ15N analysis of muscle and liver tissue collected from female bonnethead sharks (Sphyrna tiburo, n = 16) and their embryos (n = 14) to explore how nitrogen balance may vary across gestation. Gestational stage was a strong predictor of bulk tissue and AA δ15N values in pregnant shark tissues, decreasing as individuals neared parturition. This trend was observed in trophic (e.g., Glx, Ala, Val), source (e.g., Lys), and physiological (e.g., Gly) AAs. Several potential mechanisms may explain these results including nitrogen conservation, scavenging, and bacterially mediated breakdown of urea to free ammonia that is used to synthesize AAs. We observed contrasting patterns of isotopic discrimination in embryo tissues, which generally became enriched in 15N throughout development. This was attributed to greater excretion of nitrogenous waste in more developed embryos, and the role of physiologically sensitive AAs (i.e., Gly and Ser) to molecular processes such as nucleotide synthesis. These findings underscore how AA isotopes can quantify shifts in nitrogen balance, providing unequivocal evidence for the role of physiological condition in driving δ15N variation in both bulk tissues and individual AAs.

Dissecting B/Plasma Cells in Periodontitis at Single-Cell/Bulk Resolution

In recent decades, our understanding of periodontitis has evolved from that based on a gross/histologic level to one on a cellular/molecular level. Previous landscape studies have explored molecular subtyping, diagnosis, and gingival tissue cell decomposition in periodontitis, and meaningful results have been obtained at a transcriptomic level. However, current periodontitis transcriptomic studies lack a finer dissection of the intercommunication between immune cells and the biological processes of specific immune cell subtypes. In this study, we classified 15 immune cell types in periodontitis at a single-cell level and conducted a cell communication analysis based on a multicenter integrated single-cell transcriptome profile, in which plasma cell–generated macrophage migration inhibitory factor can communicate with most other immune cells in periodontitis. A pseudotime analysis focusing on B/plasma cell infiltration in periodontitis revealed 2 distinct cell fates (CFs) for B/plasma cells. In addition, at a bulk tissue level, a single-sample gene set enrichment analysis showed a similar immune cell infiltration trend, and a weighted gene coexpression network analysis identified an immune-related gene module. Combined with the above findings, we used machine learning methods to further narrow down potential gene candidates for developing and validating molecular diagnostic models of periodontitis. Multivariable logistic regression of a large public cohort (68 healthy vs. 235 periodontitis) and an independent validation cohort (12 healthy vs. 7 periodontitis) showed the CF1 signature provides a good discrimination and calibration performance with clinical benefits at a proper threshold probability. Furthermore, quantitative real-time polymerase chain reaction validation of the gene candidates was performed in both snap-frozen gingival tissues and gingival crevicular fluids. Our transcriptomic landscape analysis at both single-cell and bulk tissue resolutions thereby illustrates the B/plasma cell infiltration process in periodontitis and reveals a gene signature that may assist in molecular diagnosis of the disease.

Human liver single nucleus and single cell RNA sequencing identify a hepatocellular carcinoma-associated cell-type affecting survival

BackgroundHepatocellular carcinoma (HCC) is a common primary liver cancer with poor overall survival. We hypothesized that there are HCC-associated cell-types that impact patient survival.MethodsWe combined liver single nucleus (snRNA-seq), single cell (scRNA-seq), and bulk RNA-sequencing (RNA-seq) data to search for cell-type differences in HCC. To first identify cell-types in HCC, adjacent non-tumor tissue, and normal liver, we integrated single-cell level data from a healthy liver cohort (n = 9 non-HCC samples) collected in the Strasbourg University Hospital; an HCC cohort (n = 1 non-HCC, n = 14 HCC-tumor, and n = 14 adjacent non-tumor samples) collected in the Singapore General Hospital and National University; and another HCC cohort (n = 3 HCC-tumor and n = 3 adjacent non-tumor samples) collected in the Dumont-UCLA Liver Cancer Center. We then leveraged these single cell level data to decompose the cell-types in liver bulk RNA-seq data from HCC patients’ tumor (n = 361) and adjacent non-tumor tissue (n = 49) from the Cancer Genome Atlas (TCGA) multi-center cohort. For replication, we decomposed 221 HCC and 209 adjacent non-tumor liver microarray samples from the Liver Cancer Institute (LCI) cohort collected by the Liver Cancer Institute and Zhongshan Hospital of Fudan University.ResultsWe discovered a tumor-associated proliferative cell-type, Prol (80.4% tumor cells), enriched for cell cycle and mitosis genes. In the liver bulk tissue from the TCGA cohort, the proportion of the Prol cell-type is significantly increased in HCC and associates with a worse overall survival. Independently from our decomposition analysis, we reciprocally show that Prol nuclei/cells significantly over-express both tumor-elevated and survival-decreasing genes obtained from the bulk tissue. Our replication analysis in the LCI cohort confirmed that an increased estimated proportion of the Prol cell-type in HCC is a significant marker for a shorter overall survival. Finally, we show that somatic mutations in the tumor suppressor genes TP53 and RB1 are linked to an increase of the Prol cell-type in HCC.ConclusionsBy integrating liver single cell, single nucleus, and bulk expression data from multiple cohorts we identified a proliferating cell-type (Prol) enriched in HCC tumors, associated with a decreased overall survival, and linked to TP53 and RB1 somatic mutations.

Shore hardness is a more representative measurement of bulk tissue biomechanics than of skin biomechanics.

To support the effective use of Shore hardness (SH) in research and clinical practice this study investigates whether SH should be interpreted as a measurement of skin or of bulk tissue biomechanics. A 3D finite element model of the heel and a validated model of a Shore-00 durometer were used to simulate testing for different combinations of stiffness and thickness in the skin and subcutaneous tissue. The results of this numerical analysis showed that SH is significantly more sensitive to changes in skin thickness, relatively to subcutaneous tissue, but equally sensitive to changes in the stiffness of either tissue. Indicatively, 25% reduction in skin thickness (0.3 mm thickness change) or in subcutaneous tissue thickness (5.9 mm thickness change), reduced SH by 7% or increased SH by 2% respectively. At the same time, 25% reduction in skin stiffness (10.1 MPa change in initial shear modulus) or of subcutaneous tissue (4.1 MPa change in initial shear modulus) led to 11% or 8% reduction in SH respectively. In the literature, SH is commonly used to study skin biomechanics. However, this analysis indicates that SH quantifies the deformability of bulk tissue, not of skin. Measurements of skin thickness are also necessary for the correct interpretation of SH.

P60. Meta-Analysis of Cell Type-Specific DNA Methylation of Childhood Attention-Deficit/Hyperactivity Disorder Symptoms

The interplay of genetic factors and environmental adversities in ADHD can be reflected by cell type-specific DNA methylation (DNAm). Previous methylome-wide association studies (MWAS) for ADHD have been performed in bulk tissue only, where meaningful DNAm signal could be left undetected. We aim to identify cell type-specific DNAm profiles associated with childhood ADHD symptoms.

Characterizing RNA Modifications in Single Neurons Using Mass Spectrometry.

Post-transcriptional modifications (PTMs) of RNA represent an understudied mechanism involved in the regulation of translation in the central nervous system (CNS). Recent evidence has linked specific neuronal RNA modifications to learning and memory paradigms. Unfortunately, conventional methods for the detection of these epitranscriptomic features are only capable of characterizing highly abundant RNA modifications in bulk tissues, precluding the assessment of unique PTM profiles that may exist for individual neurons within the activated behavioral circuits. In this protocol, an approach is described-single-neuron RNA modification analysis by mass spectrometry (SNRMA-MS)-to simultaneously detect and quantify numerous modified ribonucleosides in single neurons. The approach is validated using individual neurons of the marine mollusk, Aplysia californica, beginning with surgical isolation and enzymatic treatment of major CNS ganglia to expose neuron cell bodies, followed by manual single-neuron isolation using sharp needles and a micropipette. Next, mechanical and thermal treatment of the sample in a small volume of buffer is done to liberate RNA from an individual cell for subsequent RNA digestion. Modified nucleosides are then identified and quantified using an optimized liquid chromatography-mass spectrometry method. SNRMA-MS is employed to establish RNA modification patterns for single, identified neurons from A. californica that have known morphologies and functions. Examples of qualitative and quantitative SNRMA-MS are presented that highlight the heterogeneous distribution of RNA modifications across individual neurons in neuronal networks.

Characterizing RNA Modifications in Single Neurons Using Mass Spectrometry

Post-transcriptional modifications (PTMs) of RNA represent an understudied mechanism involved in the regulation of translation in the central nervous system (CNS). Recent evidence has linked specific neuronal RNA modifications to learning and memory paradigms. Unfortunately, conventional methods for the detection of these epitranscriptomic features are only capable of characterizing highly abundant RNA modifications in bulk tissues, precluding the assessment of unique PTM profiles that may exist for individual neurons within the activated behavioral circuits. In this protocol, an approach is described—single-neuron RNA modification analysis by mass spectrometry (SNRMA-MS)—to simultaneously detect and quantify numerous modified ribonucleosides in single neurons. The approach is validated using individual neurons of the marine mollusk, Aplysia californica, beginning with surgical isolation and enzymatic treatment of major CNS ganglia to expose neuron cell bodies, followed by manual single-neuron isolation using sharp needles and a micropipette. Next, mechanical and thermal treatment of the sample in a small volume of buffer is done to liberate RNA from an individual cell for subsequent RNA digestion. Modified nucleosides are then identified and quantified using an optimized liquid chromatography-mass spectrometry method. SNRMA-MS is employed to establish RNA modification patterns for single, identified neurons from A. californica that have known morphologies and functions. Examples of qualitative and quantitative SNRMA-MS are presented that highlight the heterogeneous distribution of RNA modifications across individual neurons in neuronal networks.

Integrated immunogenomic analysis of single-cell and bulk tissue transcriptome profiling unravels a macrophage activation paradigm associated with immunologically and clinically distinct behaviors in ovarian cancer

IntroductionIncreasing evidence demonstrates that the activation states and diverse spectrum of macrophage subtypes display dynamic heterogeneity in the tumor microenvironment, which plays a critical role in a variety of cancer types. ObjectivesTo investigate the heterogeneity and the homeostasis of different macrophage subtypes, as well as their effect on biological and clinical manifestations of ovarian cancer (OV). MethodIntegrated immunogenomic analysis of single-cell and bulk tissuetranscriptome profiling was performed to systematically investigate the association between macrophage activation and prognostic and therapeutic efficacy. Consensus clustering analysis was used to define novel macrophage subtypes. An artificial neural network was used to simulate the dynamic activation of macrophages. ResultsThe pan-cohort results suggested that high relative infiltration abundance of M0 and M1 macrophages was associated with improved outcome and therapeutic efficacy. However, it was the opposite for M2 macrophages. Unsupervised consensus clustering analysis revealed two OV subgroups characterized by a balance between M0, M1 and M2 macrophages with distinct clinical and immunological behaviors. Finally, a macrophage polarization-derived artificial neural network model was proposed to serve as a robust prognostic factor and predictive biomarker for therapeutic efficacy, which was validated in different independent patient cohorts. ConclusionThe present study provides a new understanding of macrophage heterogeneity and its association with OV prognosis and underlines the future clinical potential of a macrophage activation model for tumor prevention and treatment.

Transcriptional landscape of human microglia implicates age, sex, and APOE-related immunometabolic pathway perturbations.

Microglia have fundamental roles in health and disease; however, effects of age, sex, and genetic factors on human microglia have not been fully explored. We applied bulk and single‐cell approaches to comprehensively characterize human microglia transcriptomes and their associations with age, sex, and APOE. We identified a novel microglial signature, characterized its expression in bulk tissue and single‐cell microglia transcriptomes. We discovered microglial co‐expression network modules associated with age, sex, and APOE‐ε4 that are enriched for lipid and carbohydrate metabolism genes. Integrated analyses of modules with single‐cell transcriptomes revealed significant overlap between age‐associated module genes and both pro‐inflammatory and disease‐associated microglial clusters. These modules and clusters harbor known neurodegenerative disease genes including APOE, PLCG2, and BIN1. Meta‐analyses with published bulk and single‐cell microglial datasets further supported our findings. Thus, these data represent a well‐characterized human microglial transcriptome resource and highlight age, sex, and APOE‐related microglial immunometabolism perturbations with potential relevance in neurodegeneration.

Single-cell proteomics defines the cellular heterogeneity of localized prostate cancer

SummaryLocalized prostate cancer exhibits multiple genomic alterations and heterogeneity at the proteomic level. Single-cell technologies capture important cell-to-cell variability responsible for heterogeneity in biomarker expression that may be overlooked when molecular alterations are based on bulk tissue samples. This study aims to identify prognostic biomarkers and describe the heterogeneity of prostate cancer and the associated microenvironment by simultaneously quantifying 36 proteins using single-cell mass cytometry analysis of over 1.6 million cells from 58 men with localized prostate cancer. We perform this task, using a high-dimensional clustering pipeline named Franken to describe subpopulations of immune, stromal, and prostate cells, including changes occurring in tumor tissues and high-grade disease that provide insights into the coordinated progression of prostate cancer. Our results further indicate that men with localized disease already harbor rare subpopulations that typically occur in castration-resistant and metastatic disease.