Dose-intensified stereotactic body radiotherapy for painful vertebral metastases: A randomized phase 3 trial.

BACKGROUND: The purpose of this randomised study was to determine whether dose-intensified stereotactic body radiotherapy (SBRT) for painful vertebral metastases results in increased rates of pain improvement compared with conventional external beam radiotherapy (cEBRT) (control) 6 months after treatment. METHODS: This randomized, controlled phase 3 trial was conducted between November 2016 and January 2023, when it was stopped early. Patients were eligible if they were aged 18 years or older; had one or two painful, stable, or potentially unstable vertebral metastases; and had a life expectancy of 1 year or longer according to the investigator's estimates. Patients received 48.5 grays (Gy) in 10 fractions (with epidural involvement) or 40 Gy in five fractions (without epidural involvement) in the SBRT group and 30 Gy in 10 fractions or 20 Gy in five fractions in the cEBRT group, respectively. The primary end point was an improvement in the pain score at the treated site by at least 2 points (on a visual analog scale from 0 to 10 points) at 6-month follow-up. Data were analyzed on an intention-to-treat and per-protocol basis. RESULTS: Of 214 patients who were screened for eligibility, 63 were randomized 1:1 between SBRT (33 patients with 36 metastases) and cEBRT (30 patients with 31 metastases). The median age of all patients was 66 years, and 40 patients were men (63.5%). In the intention-to-treat analysis, the 6-month proportion of patients who had metastases with pain reduction by 2 or more points was significantly higher in the SBRT group versus the control group (69.4% vs. 41.9%, respectively; two-sided p = .02). Changes in opioid medication intake relative to baseline were nonsignificant between the groups. No differences were observed in vertebral compression fracture or adverse event rates between the groups. CONCLUSIONS: Dose-intensified SBRT improved pain score more effectively than cEBRT at 6 months.

Plasma extracellular vesicles in meningioma patients following radiotherapy as liquid biopsy- a prospective explorative biomarker study (ARO 2023-05/AG-NRO-07).

BACKGROUND: While surgical resection remains the primary treatment approach for symptomatic or growing meningiomas, radiotherapy represents an auspicious alternative in patients with meningiomas not safely amenable to surgery. Biopsies are often omitted in light of potential postoperative neurological deficits, resulting in a lack of histological grading and (molecular) risk stratification. In this prospective explorative biomarker study, extracellular vesicles in the bloodstream will be investigated in patients with macroscopic meningiomas to identify a biomarker for molecular risk stratification and disease monitoring. METHODS: In total, 60 patients with meningiomas and an indication of radiotherapy (RT) and macroscopic tumor on the planning MRI will be enrolled. Blood samples will be obtained before the start, during, and after radiotherapy, as well as during clinical follow-up every 6 months. Extracellular vesicles will be isolated from the blood samples, quantified and correlated with the clinical treatment response or progression. Further, nanopore sequencing-based DNA methylation profiles of plasma EV-DNA will be generated for methylation-based meningioma classification. DISCUSSION: This study will explore the dynamic of plasma EVs in meningioma patients under/after radiotherapy, with the objective of identifying potential biomarkers of (early) tumor progression. DNA methylation profiling of plasma EVs in meningioma patients may enable molecular risk stratification, facilitating a molecularly-guided target volume delineation and adjusted dose prescription during RT treatment planning.

The role of the soft palate dose regarding normal tissue toxicities in older adults with head and neck cancer undergoing definitive radiotherapy.

PURPOSE: The number of older adults with head and neck squamous cell carcinoma (HNSCC) is continuously increasing. Older HNSCC patients may be more vulnerable to radiotherapy-related toxicities, so that extrapolation of available normal tissue complication probability (NTCP) models to this population may not be appropriate. Hence, we aimed to investigate the correlation between organ at risk (OAR) doses and chronic toxicities in older patients with HNSCC undergoing definitive radiotherapy. METHODS: Patients treated with definitive radiotherapy, either alone or with concomitant systemic treatment, between 2009 and 2019 in a large tertiary cancer center were eligible for this analysis. OARs were contoured based on international consensus guidelines, and EQD2 doses using α/ß values of 3 Gy for late effects were calculated based on the radiation treatment plans. Treatment-related toxicities were graded according to Common Terminology Criteria for Adverse Events version 5.0. Logistic regression analyses were carried out, and NTCP models were developed and internally validated using the bootstrapping method. RESULTS: A total of 180 patients with a median age of 73 years fulfilled the inclusion criteria and were analyzed. Seventy-three patients developed chronic moderate xerostomia (grade 2), 34 moderate dysgeusia (grade 2), and 59 moderate-to-severe (grade 2-3) dysphagia after definitive radiotherapy. The soft palate dose was significantly associated with all analyzed toxicities (xerostomia: OR = 1.028, dysgeusia: OR = 1.022, dysphagia: OR = 1.027) in the multivariable regression. The superior pharyngeal constrictor muscle was also significantly related to chronic dysphagia (OR = 1.030). Consecutively developed and internally validated NTCP models were predictive for the analyzed toxicities (optimism-corrected AUCs after bootstrapping: AUCxerostomia=0.64, AUCdysgeusia=0.60, AUCdysphagia=0.64). CONCLUSIONS: Our data suggest that the dose to the soft palate is associated with chronic moderate xerostomia, moderate dysgeusia and moderate-to-severe dysphagia in older HNSCC patients undergoing definitive radiotherapy. If validated in external studies, efforts should be undertaken to reduce the soft palate dose in these patients.

After the Infection: A Survey of Pathogens and Non-communicable Human Disease.

There are many well-established relationships between pathogens and human disease, but far fewer when focusing on non-communicable diseases (NCDs). We leverage data from The UK Biobank and TriNetX to perform a systematic survey across 20 pathogens and 426 diseases, focused primarily on NCDs. To this end, we assess the association between disease status and infection history proxies. We identify 206 pathogen-disease pairs that replicate in both cohorts. We replicate many established relationships, including Helicobacter pylori with several gastroenterological diseases, and connections between Epstein-Barr virus with multiple sclerosis and lupus. Overall, our approach identified evidence of association for 15 of the pathogens and 96 distinct diseases, including a currently controversial link between human cytomegalovirus (CMV) and ulcerative colitis (UC). We validate this connection through two orthogonal analyses, revealing increased CMV gene expression in UC patients and enrichment for UC genetic risk signal near human genes that have altered expression upon CMV infection. Collectively, these results form a foundation for future investigations into mechanistic roles played by pathogens in disease.

Population-level single-cell genomics reveals conserved gene programs in systemic juvenile idiopathic arthritis.

Systemic autoimmune and autoinflammatory diseases are characterized by genetic and cellular heterogeneity. While current single-cell genomics methods provide insights into known disease subtypes, these analysis methods do not readily reveal novel cell-type perturbation programs shared among distinct patient subsets. Here, we performed single-cell RNA-Seq of PBMCs of patients with systemic juvenile idiopathic arthritis (SJIA) with diverse clinical manifestations, including macrophage activation syndrome (MAS) and lung disease (LD). We introduced two new computational frameworks called UDON and SATAY-UDON, which define patient subtypes based on their underlying disrupted cellular programs as well as associated biomarkers or clinical features. Among twelve independently identified subtypes, this analysis uncovered what we believe to be a novel complement and interferon activation program identified in SJIA-LD monocytes. Extending these analyses to adult and pediatric lupus patients found new but also shared disease programs with SJIA, including interferon and complement activation. Finally, supervised comparison of these programs in a compiled single-cell pan-immune atlas of over 1,000 healthy donors found a handful of normal healthy donors with evidence of early inflammatory activation in subsets of monocytes and platelets, nominating possible biomarkers for early disease detection. Thus, integrative pan-immune single-cell analysis resolved what we believe to be new conserved gene programs underlying inflammatory disease pathogenesis and associated complications.

Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data.

A large number of genomic and imaging datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While much effort has been devoted to capturing information related to biospecimen information and experimental procedures, the metadata standards that describe data matrices and the analysis workflows that produced them are relatively lacking. Detailed metadata schema related to data analysis are needed to facilitate sharing and interoperability across groups and to promote data provenance for reproducibility. To address this need, we developed the Matrix and Analysis Metadata Standards (MAMS) to serve as a resource for data coordinating centers and tool developers. We first curated several simple and complex "use cases" to characterize the types of feature-observation matrices (FOMs), annotations, and analysis metadata produced in different workflows. Based on these use cases, metadata fields were defined to describe the data contained within each matrix including those related to processing, modality, and subsets. Suggested terms were created for the majority of fields to aid in harmonization of metadata terms across groups. Additional provenance metadata fields were also defined to describe the software and workflows that produced each FOM. Finally, we developed a simple list-like schema that can be used to store MAMS information and implemented in multiple formats. Overall, MAMS can be used as a guide to harmonize analysis-related metadata which will ultimately facilitate integration of datasets across tools and consortia. MAMS specifications, use cases, and examples can be found at https://github.com/single-cell-mams/mams/.

Retinoid X receptor promotes hematopoietic stem cell fitness and quiescence and preserves hematopoietic homeostasis.

Hematopoietic stem cells (HSCs) balance self-renewal and differentiation to maintain hematopoietic fitness throughout life. In steady-state conditions, HSC exhaustion is prevented by the maintenance of most HSCs in a quiescent state, with cells entering the cell cycle only occasionally. HSC quiescence is regulated by retinoid and fatty-acid ligands of transcriptional factors of the nuclear retinoid X receptor (RXR) family. Herein, we show that dual deficiency for hematopoietic RXRα and RXRß induces HSC exhaustion, myeloid cell/megakaryocyte differentiation, and myeloproliferative-like disease. RXRα and RXRß maintain HSC quiescence, survival, and chromatin compaction; moreover, transcriptome changes in RXRα;RXRß-deficient HSCs include premature acquisition of an aging-like HSC signature, MYC pathway upregulation, and RNA intron retention. Fitness loss and associated RNA transcriptome and splicing alterations in RXRα;RXRß-deficient HSCs are prevented by Myc haploinsufficiency. Our study reveals the critical importance of RXRs for the maintenance of HSC fitness and their protection from premature aging.

LungMAP Portal Ecosystem: Systems-Level Exploration of the Lung.

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular, imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multi-omics data and a diverse collection of image data that span mammalian lung development, and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, mouse), to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, re-analysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP and external research efforts.

Fetal maturation revealed by amniotic fluid cell-free transcriptome in rhesus macaques.

Accurate estimate of fetal maturity could provide individualized guidance for delivery of complicated pregnancies. However, current methods are invasive, have low accuracy, and are limited to fetal lung maturation. To identify diagnostic gestational biomarkers, we performed transcriptomic profiling of lung and brain, as well as cell-free RNA from amniotic fluid of preterm and term rhesus macaque fetuses. These data identify potentially new and prior-associated gestational age differences in distinct lung and neuronal cell populations when compared with existing single-cell and bulk RNA-Seq data. Comparative analyses found hundreds of genes coincidently induced in lung and amniotic fluid, along with dozens in brain and amniotic fluid. These data enable creation of computational models that accurately predict lung compliance from amniotic fluid and lung transcriptome of preterm fetuses treated with antenatal corticosteroids. Importantly, antenatal steroids induced off-target gene expression changes in the brain, impinging upon synaptic transmission and neuronal and glial maturation, as this could have long-term consequences on brain development. Cell-free RNA in amniotic fluid may provide a substrate of global fetal maturation markers for personalized management of at-risk pregnancies.

CellDrift: inferring perturbation responses in temporally sampled single-cell data.

Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in the alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns for perturbation analyses, we developed CellDrift (https://github.com/KANG-BIOINFO/CellDrift), a generalized linear model-based functional data analysis method that is capable of identifying covarying temporal patterns of various cell types in response to perturbations. As compared to several other approaches, CellDrift demonstrated superior performance in the identification of temporally varied perturbation patterns and the ability to impute missing time points. We applied CellDrift to multiple longitudinal datasets, including COVID-19 disease progression and gastrointestinal tract development, and demonstrated its ability to identify specific gene programs associated with sequential biological processes, trajectories and outcomes.

Management of Medial Sphenoid Wing Meningioma Involving the Cavernous Sinus: A Single-Center Series of 105 Cases.

OBJECTIVE: Medial sphenoid wing meningiomas are among the three most common intracranial meningiomas. These tumors pose a challenge to neurosurgeons in terms of surgical treatment, as they may involve critical neurovascular structures and invade the cavernous sinus. In case of the latter, a complete resection may not be achievable. The purpose of this study was to investigate prognostic features affecting recurrence and progression-free survival (PFS) of medial sphenoid wing meningiomas involving the cavernous sinus, focusing on the contribution of surgery and postoperative radiotherapy. METHODS: A retrospective analysis was conducted of the database of our institution, and 105 cases of medial sphenoid wing meningioma with invasion of the cavernous sinus, which were treated between 1998 and 2019, were included. Surgical treatment only was performed in 64 cases, and surgical treatment plus postoperative radiotherapy was performed in 41 cases. Kaplan-Meier analysis was conducted to estimate median survival and PFS rates, and Cox regression analysis was applied to determine significant factors that were associated with each therapeutic modality. RESULTS: The risk of recurrence was significantly reduced after near-total resection (NTR) (p-value = 0.0011) compared to subtotal resection. Progression-free survival was also significantly prolonged after postoperative radiotherapy (p-value = 0.0002). CONCLUSIONS: Maximal safe resection and postoperative stereotactic radiotherapy significantly reduced the recurrence rate of medial sphenoid wing meningiomas with infiltration of the cavernous sinus.

A Retrospective Evaluation of the Retrosigmoidal Approach for Petroclival Meningioma Surgery and Prognostic Factors Affecting Clinical Outcome.

Introduction: Petroclival meningioma (PCM) remains a major neurosurgical challenge. There are still controversial strategic treatment concepts about surgical approach, the extent of resection, and postoperative radiotherapy. We aimed to evaluate prognostic factors influencing the progression-free survival (PFS) rates of PCM, with a particular focus on the retrosigmoidal approach, the role of the extent of resection, and postoperative radiotherapy. Methods: Eighty-nine patients with complete follow-up data were included. All patients were operated on via a retrosigmoidal approach, of whom 19 underwent gross total resection (GTR) and 70 underwent subtotal resection (STR). In the subgroups of tumors with infiltration of the cavernous sinus, 41 patients received near total resection (NTR) and 24 STR. Thirty-one patients received postoperative radiotherapy of the residual tumor and 58 were treated with surgery alone. Kaplan-Meier analyses and Cox regression were used to identify significant factors associated with treatment. Results: GTR (p=0.0107) and postoperative radiotherapy (p=0.014) were associated with significantly improved PFS. Even the subgroup analysis of extended PCM with infiltration of the cavernous sinus (CS) showed an advantage for PFS after near total resection (NTR) (p=0.0017). The additional radiotherapy of the residual tumor in the CS in this subgroup also showed a beneficial effect on PFS (p=0.012). Conclusion: The extension of surgical resection remains the most important prognostic factor in relation to oncological outcomes. However, the GTR of extended PCM with infiltration of the CS is associated with significant neurological morbidity and requires additional adjuvant therapy concepts. Postoperative radiotherapy is an important element in the treatment of the residual tumor after surgery.

Progression-Free Survival, Prognostic Factors, and Surgical Outcome of Spheno-Orbital Meningiomas.

OBJECTIVE: Spheno-orbital meningiomas (SOM) are rare intracranial tumors that arise at the sphenoid wing. These tumors can invade important neurovascular structures making radical resection difficult, while residual tumors often lead to recurrence. The purpose of this study was to evaluate prognostic factors influencing the recurrence and progression-free survival (PFS) rates of spheno-orbital meningiomas, with a particular focus on the role of surgery and postoperative radiotherapy. METHODS: Between 2000 and March 2020, 65 cases of spheno-orbital meningioma were included, of which 50 cases underwent surgical treatment alone, and 15 cases underwent resection and radiotherapy. A Kaplan-Meier analysis was performed to provide median point estimates and PFS rates; further, Cox regression analysis was used to identify significant factors associated with treatment. RESULTS: Gross total resection significantly reduced the risk of recurrence (p-value = 0.0062). There was no significant benefit for progression-free survival after postoperative radiotherapy (p-value = 0.42). Additionally, spheno-orbital meningiomas with an invasion of the cavernous sinus and intraconal invasion showed significantly worse PFS compared to other locations (p-value = 0.017). CONCLUSION: The maximal safe resection remains the most important prognostic factor associated with lower recurrence rates and longer PFS in patients with spheno-orbital meningioma. The invasion of the cavernous sinus and intraconal invasion was an independent factor associated with worse PFS. Patients with postoperative high-precision radiotherapy did not show significantly better PFS due to the small number of patients.

Stereotactic cysto-ventricular catheters in craniopharyngiomas: an effective minimally invasive method to improve visual impairment and achieve long-term cyst volume reduction.

Craniopharyngiomas are typically located in the sellar region and frequently contain space-occupying cysts. They usually cause visual impairment and endocrine disorders. Due to the high potential morbidity associated with radical resection, several less invasive surgical approaches have been developed. This study investigated stereotactic-guided implantation of cysto-ventricular catheters (CVC) as a new method to reduce and control cystic components. Twelve patients with cystic craniopharyngiomas were treated with CVC in our hospital between 04/2013 and 05/2017. The clinical and radiological data were retrospectively analysed to evaluate safety aspects as well as ophthalmological and endocrine symptoms. The long-term development of tumour and cyst volumes was assessed by volumetry. The median age of our patients was 69.0 years and the median follow-up period was 41.0 months. Volumetric analyses demonstrated a mean reduction of cyst volume of 64.2% after CVC implantation. At last follow-up assessment, there was a mean reduction of cyst volume of 92.0% and total tumour volume of 85.8% after completion of radiotherapy. Visual acuity improved in 90% of affected patients, and visual field defects improved in 70% of affected patients. No patient showed ophthalmological deterioration after surgery, and endocrine disorders remained stable. Stereotactic implantation of CVC proved to be a safe minimally invasive method for the long-term reduction of cystic components with improved ophthalmological symptoms. The consequential decrease of total tumour volumes optimised conditions for adjuvant radiotherapy. Given the low surgical morbidity and the effective drainage of tumour cysts, this technique should be considered for the treatment of selected cystic craniopharyngiomas.

Monocyte and bone marrow macrophage transcriptional phenotypes in systemic juvenile idiopathic arthritis reveal TRIM8 as a mediator of IFN-γ hyper-responsiveness and risk for macrophage activation syndrome.

OBJECTIVES: Systemic juvenile idiopathic arthritis (SJIA) confers high risk for macrophage activation syndrome (MAS), a life-threatening cytokine storm driven by interferon (IFN)-γ. SJIA monocytes display IFN-γ hyper-responsiveness, but the molecular basis of this remains unclear. The objective of this study is to identify circulating monocyte and bone marrow macrophage (BMM) polarisation phenotypes in SJIA including molecular features contributing to IFN response. METHODS: Bulk RNA-seq was performed on peripheral blood monocytes (n=26 SJIA patients) and single cell (sc) RNA-seq was performed on BMM (n=1). Cultured macrophages were used to define consequences of tripartite motif containing 8 (TRIM8) knockdown on IFN-γ signalling. RESULTS: Bulk RNA-seq of SJIA monocytes revealed marked transcriptional changes in patients with elevated ferritin levels. We identified substantial overlap with multiple polarisation states but little evidence of IFN-induced signature. Interestingly, among the most highly upregulated genes was TRIM8, a positive regulator of IFN-γ signalling. In contrast to PBMC from SJIA patients without MAS, scRNA-seq of BMM from a patient with SJIA and MAS identified distinct subpopulations of BMM with altered transcriptomes, including upregulated IFN-γ response pathways. These BMM also showed significantly increased expression of TRIM8. In vitro knockdown of TRIM8 in macrophages significantly reduced IFN-γ responsiveness. CONCLUSIONS: Macrophages with an 'IFN-γ response' phenotype and TRIM8 overexpression were expanded in the bone marrow from an MAS patient. TRIM8 is also upregulated in SJIA monocytes, and augments macrophage IFN-γ response in vitro, providing both a candidate molecular mechanism and potential therapeutic target for monocyte hyper-responsiveness to IFNγ in cytokine storms including MAS.

Protocol for Identification and Removal of Doublets with DoubletDecon.

Retention of multiplet captures in single-cell RNA sequencing (scRNA-seq) data can hinder identification of discrete or transitional cell populations and associated marker genes. To overcome this challenge, we created DoubletDecon to identify and remove doublets, multiplets of two cells, by using a combination of deconvolution to identify putative doublets and analyses of unique gene expression. Here, we provide the protocol for running DoubletDecon on scRNA-seq data. For complete details on the use and execution of this protocol, please refer to DePasquale et al. (2019).

Resolving single-cell heterogeneity from hundreds of thousands of cells through sequential hybrid clustering and NMF.

MOTIVATION: The rapid proliferation of single-cell RNA-sequencing (scRNA-Seq) technologies has spurred the development of diverse computational approaches to detect transcriptionally coherent populations. While the complexity of the algorithms for detecting heterogeneity has increased, most require significant user-tuning, are heavily reliant on dimension reduction techniques and are not scalable to ultra-large datasets. We previously described a multi-step algorithm, Iterative Clustering and Guide-gene Selection (ICGS), which applies intra-gene correlation and hybrid clustering to uniquely resolve novel transcriptionally coherent cell populations from an intuitive graphical user interface. RESULTS: We describe a new iteration of ICGS that outperforms state-of-the-art scRNA-Seq detection workflows when applied to well-established benchmarks. This approach combines multiple complementary subtype detection methods (HOPACH, sparse non-negative matrix factorization, cluster 'fitness', support vector machine) to resolve rare and common cell-states, while minimizing differences due to donor or batch effects. Using data from multiple cell atlases, we show that the PageRank algorithm effectively downsamples ultra-large scRNA-Seq datasets, without losing extremely rare or transcriptionally similar yet distinct cell types and while recovering novel transcriptionally distinct cell populations. We believe this new approach holds tremendous promise in reproducibly resolving hidden cell populations in complex datasets. AVAILABILITY AND IMPLEMENTATION: ICGS2 is implemented in Python. The source code and documentation are available at http://altanalyze.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DoubletDecon: Deconvoluting Doublets from Single-Cell RNA-Sequencing Data.

Methods for single-cell RNA sequencing (scRNA-seq) have greatly advanced in recent years. While droplet- and well-based methods have increased the capture frequency of cells for scRNA-seq, these technologies readily produce technical artifacts, such as doublet cell captures. Doublets occurring between distinct cell types can appear as hybrid scRNA-seq profiles, but do not have distinct transcriptomes from individual cell states. We introduce DoubletDecon, an approach that detects doublets with a combination of deconvolution analyses and the identification of unique cell-state gene expression. We demonstrate the ability of DoubletDecon to identify synthetic, mixed-species, genetic, and cell-hashing cell doublets from scRNA-seq datasets of varying cellular complexity with a high sensitivity relative to alternative approaches. Importantly, this algorithm prevents the prediction of valid mixed-lineage and transitional cell states as doublets by considering their unique gene expression. DoubletDecon has an easy-to-use graphical user interface and is compatible with diverse species and unsupervised population detection algorithms.

cellHarmony: cell-level matching and holistic comparison of single-cell transcriptomes.

To understand the molecular pathogenesis of human disease, precision analyses to define alterations within and between disease-associated cell populations are desperately needed. Single-cell genomics represents an ideal platform to enable the identification and comparison of normal and diseased transcriptional cell populations. We created cellHarmony, an integrated solution for the unsupervised analysis, classification, and comparison of cell types from diverse single-cell RNA-Seq datasets. cellHarmony efficiently and accurately matches single-cell transcriptomes using a community-clustering and alignment strategy to compute differences in cell-type specific gene expression over potentially dozens of cell populations. Such transcriptional differences are used to automatically identify distinct and shared gene programs among cell-types and identify impacted pathways and transcriptional regulatory networks to understand the impact of perturbations at a systems level. cellHarmony is implemented as a python package and as an integrated workflow within the software AltAnalyze. We demonstrate that cellHarmony has improved or equivalent performance to alternative label projection methods, is able to identify the likely cellular origins of malignant states, stratify patients into clinical disease subtypes from identified gene programs, resolve discrete disease networks impacting specific cell-types, and illuminate therapeutic mechanisms. Thus, this approach holds tremendous promise in revealing the molecular and cellular origins of complex disease.

Integration of transcriptomic and proteomic data identifies biological functions in cell populations from human infant lung.

Systems biology uses computational approaches to integrate diverse data types to understand cell and organ behavior. Data derived from complementary technologies, for example transcriptomic and proteomic analyses, are providing new insights into development and disease. We compared mRNA and protein profiles from purified endothelial, epithelial, immune, and mesenchymal cells from normal human infant lung tissue. Signatures for each cell type were identified and compared at both mRNA and protein levels. Cell-specific biological processes and pathways were predicted by analysis of concordant and discordant RNA-protein pairs. Cell clustering and gene set enrichment comparisons identified shared versus unique processes associated with transcriptomic and/or proteomic data. Clear cell-cell correlations between mRNA and protein data were obtained from each cell type. Approximately 40% of RNA-protein pairs were coherently expressed. While the correlation between RNA and their protein products was relatively low (Spearman rank coefficient rs ~0.4), cell-specific signature genes involved in functional processes characteristic of each cell type were more highly correlated with their protein products. Consistency of cell-specific RNA-protein signatures indicated an essential framework for the function of each cell type. Visualization and reutilization of the protein and RNA profiles are supported by a new web application, "LungProteomics," which is freely accessible to the public.