The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of ...Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable to deal with sample sets providing largely uneven coverage of the probability density space. Here, we present a completely new implementation of the algorithm, based on an Adaptive Partitioning strategy (AP) for estimating the Mutual Information. The new AP implementation (ARACNe-AP) achieves a dramatic improvement in computational performance (200× on average) over the previous methodology, while preserving the Mutual Information estimator and the Network inference accuracy of the original algorithm. Given that the previous version of ARACNe is extremely demanding, the new version of the algorithm will allow even researchers with modest computational resources to build complex regulatory networks from hundreds of gene expression profiles.
A JAVA cross-platform command line executable of ARACNe, together with all source code and a detailed usage guide are freely available on Sourceforge (http://sourceforge.net/projects/aracne-ap). JAVA version 8 or higher is required.
califano@c2b2.columbia.edu
Supplementary data are available at Bioinformatics online.
Identifying the multiple dysregulated oncoproteins that contribute to tumorigenesis in a given patient is crucial for developing personalized treatment plans. However, accurate inference of aberrant ...protein activity in biological samples is still challenging as genetic alterations are only partially predictive and direct measurements of protein activity are generally not feasible. To address this problem we introduce and experimentally validate a new algorithm, virtual inference of protein activity by enriched regulon analysis (VIPER), for accurate assessment of protein activity from gene expression data. We used VIPER to evaluate the functional relevance of genetic alterations in regulatory proteins across all samples in The Cancer Genome Atlas (TCGA). In addition to accurately infer aberrant protein activity induced by established mutations, we also identified a fraction of tumors with aberrant activity of druggable oncoproteins despite a lack of mutations, and vice versa. In vitro assays confirmed that VIPER-inferred protein activity outperformed mutational analysis in predicting sensitivity to targeted inhibitors.
Sequencing studies from several model systems have suggested that diverse and abundant small RNAs may be derived from tRNA, but the function of these molecules remains undefined. Here, we demonstrate ...that one such tRNA-derived fragment, cloned from human mature B cells and designated CU1276, in fact possesses the functional characteristics of a microRNA, including a DICER1 -dependent biogenesis, physical association with Argonaute proteins, and the ability to repress mRNA transcripts in a sequence-specific manner. Expression of CU1276 is abundant in normal germinal center B cells but absent in germinal center-derived lymphomas, suggesting a role in the pathogenesis of this disease. Furthermore, CU1276 represses endogenous RPA1 , an essential gene involved in many aspects of DNA dynamics, and consequently, expression of this tRNA-derived microRNA in a lymphoma cell line suppresses proliferation and modulates the molecular response to DNA damage. These results establish that functionally active microRNAs can be derived from tRNA, thus defining a class of genetic entities with potentially important biological roles.
Cancer-associated fibroblasts (CAF) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of ...several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we use single-cell RNA sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human and mouse PDAC tumors. We corroborate the presence of myofibroblastic CAFs and inflammatory CAFs and define their unique gene signatures
. Moreover, we describe a new population of CAFs that express MHC class II and CD74, but do not express classic costimulatory molecules. We term this cell population "antigen-presenting CAFs" and find that they activate CD4
T cells in an antigen-specific fashion in a model system, confirming their putative immune-modulatory capacity. Our cross-species analysis paves the way for investigating distinct functions of CAF subtypes in PDAC immunity and progression. SIGNIFICANCE: Appreciating the full spectrum of fibroblast heterogeneity in pancreatic ductal adenocarcinoma is crucial to developing therapies that specifically target tumor-promoting CAFs. This work identifies MHC class II-expressing CAFs with a capacity to present antigens to CD4
T cells, and potentially to modulate the immune response in pancreatic tumors.
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BACKGROUND:Smooth muscle cells (SMC) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration and transdifferentiation into ...other cell types. Yet, how SMC contribute to pathophysiology of atherosclerosis remains elusive.
METHODS:To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques. We also performed cell biology experiments on isolated SMC-derived cells, conducted integrative human genomics, and employed pharmacological studies targeting SMC-derived cells both in vivo and in vitro.
RESULTS:We found that SMC transitioned to an intermediate cell state during atherosclerosis, which was also found in human atherosclerotic plaques of carotid and coronary arteries. SMC- derived intermediate cells, termed “SEM” cells, were multipotent and could differentiate into macrophage-like and fibrochondrocyte-like cells, as well as return towards SMC phenotype. Retinoic acid (RA) signaling was identified as a regulator of SMC to SEM cell transition and RA signaling was dysregulated in symptomatic human atherosclerosis. Human genomics revealed enrichment of genome wide association study (GWAS) signals for coronary artery disease (CAD) in RA signaling target gene loci and correlation between CAD risk alleles and repressed expression of these genes. Activation of RA signaling by all-trans retinoic acid (ATRA), an anti- cancer drug for acute promyelocytic leukemia, blocked SMC transition to SEM cells, reduced atherosclerotic burden and promoted fibrous cap stability.
CONCLUSIONS:Integration of cell-specific fate mapping, single-cell genomics and human genetics adds novel insights into the complexity of SMC biology and reveals regulatory pathways for therapeutic targeting of SMC transitions in atherosclerotic cardiovascular disease.
Clear cell renal carcinoma (ccRCC) is a heterogeneous disease with a variable post-surgical course. To assemble a comprehensive ccRCC tumor microenvironment (TME) atlas, we performed single-cell RNA ...sequencing (scRNA-seq) of hematopoietic and non-hematopoietic subpopulations from tumor and tumor-adjacent tissue of treatment-naive ccRCC resections. We leveraged the VIPER algorithm to quantitate single-cell protein activity and validated this approach by comparison to flow cytometry. The analysis identified key TME subpopulations, as well as their master regulators and candidate cell-cell interactions, revealing clinically relevant populations, undetectable by gene-expression analysis. Specifically, we uncovered a tumor-specific macrophage subpopulation characterized by upregulation of TREM2/APOE/C1Q, validated by spatially resolved, quantitative multispectral immunofluorescence. In a large clinical validation cohort, these markers were significantly enriched in tumors from patients who recurred following surgery. The study thus identifies TREM2/APOE/C1Q-positive macrophage infiltration as a potential prognostic biomarker for ccRCC recurrence, as well as a candidate therapeutic target.
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•We present a robust pipeline for scRNA-seq analysis by protein activity inference•Our pipeline identifies a C1Q+TREM2+APOE+ macrophage population enriched in ccRCC•Protein activity signature of these cells is prognostic of post-surgical recurrence•C1Q+ Macrophage association with recurrence is validated by immunohistochemistry
Analysis of the tumor microenvironment using tumor and tumor-adjacent tissue of treatment-naive clear cell renal carcinoma resections from patients by combining single-cell sequencing and single-cell protein activity uncovers a tumor-specific infiltrating macrophage subpopulation associated with disease recurrence.
The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. Much of our present knowledge derives from high-throughput ...techniques such as the yeast two-hybrid assay and affinity purification, as well as from manual curation of experiments on individual systems. A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein-protein interactions (PPIs). Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages. Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence. Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human. Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Cancer-associated fibroblasts (CAF) are a poorly characterized cell population in the context of liver cancer. Our study investigates CAF functions in intrahepatic cholangiocarcinoma (ICC), a highly ...desmoplastic liver tumor. Genetic tracing, single-cell RNA sequencing, and ligand-receptor analyses uncovered hepatic stellate cells (HSC) as the main source of CAF and HSC-derived CAF as the dominant population interacting with tumor cells. In mice, CAF promotes ICC progression, as revealed by HSC-selective CAF depletion. In patients, a high panCAF signature is associated with decreased survival and increased recurrence. Single-cell RNA sequencing segregates CAF into inflammatory and growth factor-enriched (iCAF) and myofibroblastic (myCAF) subpopulations, displaying distinct ligand-receptor interactions. myCAF-expressed hyaluronan synthase 2, but not type I collagen, promotes ICC. iCAF-expressed hepatocyte growth factor enhances ICC growth via tumor-expressed MET, thus directly linking CAF to tumor cells. In summary, our data demonstrate promotion of desmoplastic ICC growth by therapeutically targetable CAF subtype-specific mediators, but not by type I collagen.
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•The majority of CAF in ICC are derived from hepatic stellate cells•Inflammatory CAF promote ICC through HGF and its receptor MET•myCAF promote ICC through Has2/hyaluronic acid•CAF-derived type I collagen contributes to stiffness but does not promote ICC growth
Intrahepatic cholangiocarcinoma (ICC) is an extraordinarily stiff liver tumor due to abundant scar-forming cancer-associated fibroblasts (CAF). Here, Affo et al. determine the origin and functions of CAF, and uncover distinct CAF subsets, promoting ICC growth via different therapeutically targetable mediators. Thus, CAF and their mediators may serve as therapeutic targets for ICC.
Current treatments for castration-resistant prostate cancer (CRPC) that target androgen receptor (AR) signaling improve patient survival, yet ultimately fail. Here, we provide novel insights into ...treatment response for the antiandrogen abiraterone by analyses of a genetically engineered mouse (GEM) model with combined inactivation of
and
, which are frequently comutated in human CRPC. These NPp53 mice fail to respond to abiraterone and display accelerated progression to tumors resembling treatment-related CRPC with neuroendocrine differentiation (CRPC-NE) in humans. Cross-species computational analyses identify master regulators of adverse response that are conserved with human CRPC-NE, including the neural differentiation factor
, which promotes neuroendocrine differentiation in cells derived from NPp53 tumors. Furthermore, abiraterone-treated NPp53 prostate tumors contain regions of focal and/or overt neuroendocrine differentiation, distinguished by their proliferative potential. Notably, lineage tracing
provides definitive and quantitative evidence that focal and overt neuroendocrine regions arise by transdifferentiation of luminal adenocarcinoma cells. These findings underscore principal roles for
and
inactivation in abiraterone resistance and progression from adenocarcinoma to CRPC-NE by transdifferentiation.
Understanding adverse treatment response and identifying patients likely to fail treatment represent fundamental clinical challenges. By integrating analyses of GEM models and human clinical data, we provide direct genetic evidence for transdifferentiation as a mechanism of drug resistance as well as for stratifying patients for treatment with antiandrogens.
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By analyzing gene expression data in glioblastoma in combination with matched microRNA profiles, we have uncovered a posttranscriptional regulation layer of surprising magnitude, comprising more than ...248,000 microRNA (miR)-mediated interactions. These include ∼7,000 genes whose transcripts act as miR “sponges” and 148 genes that act through alternative, nonsponge interactions. Biochemical analyses in cell lines confirmed that this network regulates established drivers of tumor initiation and subtype implementation, including PTEN, PDGFRA, RB1, VEGFA, STAT3, and RUNX1, suggesting that these interactions mediate crosstalk between canonical oncogenic pathways. siRNA silencing of 13 miR-mediated PTEN regulators, whose locus deletions are predictive of PTEN expression variability, was sufficient to downregulate PTEN in a 3′UTR-dependent manner and to increase tumor cell growth rates. Thus, miR-mediated interactions provide a mechanistic, experimentally validated rationale for the loss of PTEN expression in a large number of glioma samples with an intact PTEN locus.
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► Computational inference reveals a network of miR-mediated interactions in glioblastoma ► These interactions regulate thousands of genes, including oncogenes and tumor suppressors ► These interactions regulate miR targets without affecting miR expression ► These interactions enable crosstalk between established oncogenic pathways
Computational inference uncovers a massive RNA-RNA interaction network in glioblastoma, which is shown to regulate established tumor drivers, such as PTEN, by modulating microRNA availability.
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