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Guerri L, Dobbs LK, da Silva e Silva DA, Meyers A, Ge A, Lecaj L, Djakuduel C, Islek D, Hipolito D, Martinez AB, Shen PH, Marietta CA, Garamszegi SP, Capobianco E, Jiang Z, Schwandt M, Mash DC, Alvarez VA, Goldman D. Low Dopamine D2 Receptor Expression Drives Gene Networks Related to GABA, cAMP, Growth and Neuroinflammation in Striatal Indirect Pathway Neurons. Biol Psychiatry Glob Open Sci 2023; 3:1104-1115. [PMID: 37881572 PMCID: PMC10593893 DOI: 10.1016/j.bpsgos.2022.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 08/06/2022] [Accepted: 08/26/2022] [Indexed: 11/25/2022] Open
Abstract
Background A salient effect of addictive drugs is to hijack the dopamine reward system, an evolutionarily conserved driver of goal-directed behavior and learning. Reduced dopamine type 2 receptor availability in the striatum is an important pathophysiological mechanism for addiction that is both consequential and causal for other molecular, cellular, and neuronal network differences etiologic for this disorder. Here, we sought to identify gene expression changes attributable to innate low expression of the Drd2 gene in the striatum and specific to striatal indirect medium spiny neurons (iMSNs). Methods Cre-conditional, translating ribosome affinity purification (TRAP) was used to purify and analyze the translatome (ribosome-bound messenger RNA) of iMSNs from mice with low/heterozygous or wild-type Drd2 expression in iMSNs. Complementary electrophysiological recordings and gene expression analysis of postmortem brain tissue from human cocaine users were performed. Results Innate low expression of Drd2 in iMSNs led to differential expression of genes involved in GABA (gamma-aminobutyric acid) and cAMP (cyclic adenosine monophosphate) signaling, neural growth, lipid metabolism, neural excitability, and inflammation. Creb1 was identified as a likely upstream regulator, among others. In human brain, expression of FXYD2, a modulatory subunit of the Na/K pump, was negatively correlated with DRD2 messenger RNA expression. In iMSN-TRAP-Drd2HET mice, increased Cartpt and reduced S100a10 (p11) expression recapitulated previous observations in cocaine paradigms. Electrophysiology experiments supported a higher GABA tone in iMSN-Drd2HET mice. Conclusions This study provides strong molecular evidence that, in addiction, inhibition by the indirect pathway is constitutively enhanced through neural growth and increased GABA signaling.
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Affiliation(s)
- Lucia Guerri
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Lauren K. Dobbs
- Laboratory on Neurobiology of Compulsive Behaviors, NIAAA, National Institutes of Health, Bethesda, Maryland
- Department of Neuroscience, University of Texas at Austin, Austin, Texas
- Department of Neurology, University of Texas at Austin, Austin, Texas
| | - Daniel A. da Silva e Silva
- Laboratory on Neurobiology of Compulsive Behaviors, NIAAA, National Institutes of Health, Bethesda, Maryland
| | - Allen Meyers
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Aaron Ge
- University of Maryland, College Park, Maryland
| | - Lea Lecaj
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Caroline Djakuduel
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Damien Islek
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Dionisio Hipolito
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Abdiel Badillo Martinez
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Pei-Hong Shen
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Cheryl A. Marietta
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
| | - Susanna P. Garamszegi
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, Florida
| | - Enrico Capobianco
- Institute for Data Science and Computing, University of Miami, Miami, Florida
| | - Zhijie Jiang
- Institute for Data Science and Computing, University of Miami, Miami, Florida
| | - Melanie Schwandt
- Office of the Clinical Director, NIAAA, National Institutes of Health, Bethesda, Maryland
| | - Deborah C. Mash
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, Florida
- Institute for Data Science and Computing, University of Miami, Miami, Florida
- Department of Molecular and Cellular Pharmacology, Miller School of Medicine, University of Miami, Miami, Florida
| | - Veronica A. Alvarez
- Laboratory on Neurobiology of Compulsive Behaviors, NIAAA, National Institutes of Health, Bethesda, Maryland
- Intramural Research Program, National Institute on Drug Abuse, Baltimore, Maryland
| | - David Goldman
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institutes of Health, Bethesda, Maryland
- Office of the Clinical Director, NIAAA, National Institutes of Health, Bethesda, Maryland
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Staff NP, Hrstka SC, Dasari S, Capobianco E, Rieger S. Skin Extracellular Matrix Breakdown Following Paclitaxel Therapy in Patients with Chemotherapy-Induced Peripheral Neuropathy. Cancers (Basel) 2023; 15:4191. [PMID: 37627219 PMCID: PMC10453667 DOI: 10.3390/cancers15164191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 08/17/2023] [Accepted: 08/17/2023] [Indexed: 08/27/2023] Open
Abstract
The chemotherapeutic agent paclitaxel causes peripheral neuropathy, a dose-limiting side effect, in up to 68% of cancer patients. In this study, we investigated the impact of paclitaxel therapy on the skin of breast cancer patients with chemotherapy-induced peripheral neuropathy (CIPN), building upon previous findings in zebrafish and rodents. Comprehensive assessments, including neurological examinations and quality of life questionnaires, were conducted, followed by intraepidermal nerve fiber (IENF) density evaluations using skin punch biopsies. Additionally, RNA sequencing, immunostaining for Matrix-Metalloproteinase 13 (MMP-13), and transmission electron microscopy provided insights into molecular and ultrastructural changes in this skin. The results showed no significant difference in IENF density between the control and CIPN patients despite the presence of patient-reported CIPN symptoms. Nevertheless, the RNA sequencing and immunostaining on the skin revealed significantly upregulated MMP-13, which is known to play a key role in CIPN caused by paclitaxel therapy. Additionally, various genes involved in the regulation of the extracellular matrix, microtubules, cell cycle, and nervous system were significantly and differentially expressed. An ultrastructural examination of the skin showed changes in collagen and basement membrane structures. These findings highlight the presence of CIPN in the absence of IENF density changes and support the role of skin remodeling as a major contributor to CIPN.
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Affiliation(s)
- Nathan P. Staff
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA; (N.P.S.)
| | - Sybil C. Hrstka
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA; (N.P.S.)
| | - Surendra Dasari
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA; (N.P.S.)
| | | | - Sandra Rieger
- Department of Biology, University of Miami, Coral Gables, FL 33146, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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Capobianco E, Dominietto M. Assessment of brain cancer atlas maps with multimodal imaging features. J Transl Med 2023; 21:385. [PMID: 37308956 DOI: 10.1186/s12967-023-04222-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 05/22/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Glioblastoma Multiforme (GBM) is a fast-growing and highly aggressive brain tumor that invades the nearby brain tissue and presents secondary nodular lesions across the whole brain but generally does not spread to distant organs. Without treatment, GBM can result in death in about 6 months. The challenges are known to depend on multiple factors: brain localization, resistance to conventional therapy, disrupted tumor blood supply inhibiting effective drug delivery, complications from peritumoral edema, intracranial hypertension, seizures, and neurotoxicity. MAIN TEXT Imaging techniques are routinely used to obtain accurate detections of lesions that localize brain tumors. Especially magnetic resonance imaging (MRI) delivers multimodal images both before and after the administration of contrast, which results in displaying enhancement and describing physiological features as hemodynamic processes. This review considers one possible extension of the use of radiomics in GBM studies, one that recalibrates the analysis of targeted segmentations to the whole organ scale. After identifying critical areas of research, the focus is on illustrating the potential utility of an integrated approach with multimodal imaging, radiomic data processing and brain atlases as the main components. The templates associated with the outcome of straightforward analyses represent promising inference tools able to spatio-temporally inform on the GBM evolution while being generalizable also to other cancers. CONCLUSIONS The focus on novel inference strategies applicable to complex cancer systems and based on building radiomic models from multimodal imaging data can be well supported by machine learning and other computational tools potentially able to translate suitably processed information into more accurate patient stratifications and evaluations of treatment efficacy.
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Affiliation(s)
- Enrico Capobianco
- The Jackson Laboratory, 10 Discovery Drive, Farmington, CT, 06032, USA.
| | - Marco Dominietto
- Paul Scherrer Institute (PSI), Forschungsstrasse 111, 5232, Villigen, Switzerland
- Gate To Brain SA, Via Livio 7, 6830, Chiasso, Switzerland
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Capobianco E, McGaughey V, Seraphin G, Heckel J, Rieger S, Lisse TS. Vitamin D inhibits osteosarcoma by reprogramming nonsense-mediated RNA decay and SNAI2-mediated epithelial-to-mesenchymal transition. Front Oncol 2023; 13:1188641. [PMID: 37228489 PMCID: PMC10203545 DOI: 10.3389/fonc.2023.1188641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023] Open
Abstract
Osteosarcomas are immune-resistant and metastatic as a result of elevated nonsense-mediated RNA decay (NMD), reactive oxygen species (ROS), and epithelial-to-mesenchymal transition (EMT). Although vitamin D has anti-cancer effects, its effectiveness and mechanism of action against osteosarcomas are poorly understood. In this study, we assessed the impact of vitamin D and its receptor (VDR) on NMD-ROS-EMT signaling in in vitro and in vivo osteosarcoma animal models. Initiation of VDR signaling facilitated the enrichment of EMT pathway genes, after which 1,25(OH)2D, the active vitamin D derivative, inhibited the EMT pathway in osteosarcoma subtypes. The ligand-bound VDR directly downregulated the EMT inducer SNAI2, differentiating highly metastatic from low metastatic subtypes and 1,25(OH)2D sensitivity. Moreover, epigenome-wide motif and putative target gene analysis revealed the VDR's integration with NMD tumorigenic and immunogenic pathways. In an autoregulatory manner, 1,25(OH)2D inhibited NMD machinery genes and upregulated NMD target genes implicated in anti-oncogenic activity, immunorecognition, and cell-to-cell adhesion. Dicer substrate siRNA knockdown of SNAI2 revealed superoxide dismutase 2 (SOD2)-mediated antioxidative responses and 1,25(OH)2D sensitization via non-canonical SOD2 nuclear-to-mitochondrial translocalization leading to overall ROS suppression. In a mouse xenograft metastasis model, the therapeutically relevant vitamin D derivative calcipotriol inhibited osteosarcoma metastasis and tumor growth shown for the first time. Our results uncover novel osteosarcoma-inhibiting mechanisms for vitamin D and calcipotriol that may be translated to human patients.
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Affiliation(s)
| | - Vanessa McGaughey
- Department of Biology, University of Miami, Coral Gables, FL, United States
| | - Gerbenn Seraphin
- Department of Biology, University of Miami, Coral Gables, FL, United States
| | - John Heckel
- Department of Biology, University of Miami, Coral Gables, FL, United States
| | - Sandra Rieger
- Department of Biology, University of Miami, Coral Gables, FL, United States
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Thomas S. Lisse
- Department of Biology, University of Miami, Coral Gables, FL, United States
- Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
- iCURA DX, Malvern, PA, United States
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Seraphin G, Rieger S, Hewison M, Capobianco E, Lisse TS. The impact of vitamin D on cancer: A Mini Review. J Steroid Biochem Mol Biol 2023; 231:106308. [PMID: 37054849 DOI: 10.1016/j.jsbmb.2023.106308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 04/04/2023] [Accepted: 04/05/2023] [Indexed: 04/15/2023]
Abstract
In this review, we summarize the most recent advances in vitamin D cancer research to provide molecular clarity, as well as its translational trajectory across the cancer landscape. Vitamin D is well known for its role in regulating mineral homeostasis; however, vitamin D deficiency has also been linked to the development and progression of a number of cancer types. Recent epigenomic, transcriptomic, and proteomic studies have revealed novel vitamin D-mediated biological mechanisms that regulate cancer cell self-renewal, differentiation, proliferation, transformation, and death. Tumor microenvironmental studies have also revealed dynamic relationships between the immune system and vitamin D's anti-neoplastic properties. These findings help to explain the large number of population-based studies that show clinicopathological correlations between circulating vitamin D levels and risk of cancer development and death. The majority of evidence suggests that low circulating vitamin D levels are associated with an increased risk of cancers, whereas supplementation alone or in combination with other chemo/immunotherapeutic drugs may improve clinical outcomes even further. These promising results still necessitate further research and development into novel approaches that target vitamin D signaling and metabolic systems to improve cancer outcomes.
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Affiliation(s)
- Gerbenn Seraphin
- University of Miami, Department of Biology, Coral Gables, Florida USA
| | - Sandra Rieger
- University of Miami, Department of Biology, Coral Gables, Florida USA; Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida USA
| | - Martin Hewison
- University of Birmingham, Institute of Metabolism and Systems Research, Birmingham UK
| | | | - Thomas S Lisse
- University of Miami, Department of Biology, Coral Gables, Florida USA; Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, Florida USA; iCURA LLC, Malvern, Pennsylvania USA.
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Trivella MG, Capobianco E, L’Abbate A. Editorial: Physiology in extreme conditions: Adaptations and unexpected reactions, Volume II. Front Physiol 2023; 14:1181010. [PMID: 36998988 PMCID: PMC10043470 DOI: 10.3389/fphys.2023.1181010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 03/08/2023] [Indexed: 03/17/2023] Open
Affiliation(s)
- Maria G. Trivella
- Consiglio Nazionale delle Ricerche, Institute of Clinical Physiology, Pisa, Italy
- *Correspondence: Maria G. Trivella,
| | - Enrico Capobianco
- The Jackson Laboratory, Computational Science, Farmington, CT, United States
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7
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Capobianco E, McGaughey V, Seraphin G, Heckel J, Rieger S, Lisse TS. Vitamin D inhibits osteosarcoma by reprogramming nonsense-mediated RNA decay and SNAI2-mediated epithelial-to-mesenchymal transition. bioRxiv 2023:2023.01.04.522778. [PMID: 36711643 PMCID: PMC9882006 DOI: 10.1101/2023.01.04.522778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Osteosarcomas are immune-resistant and metastatic as a result of elevated nonsense-mediated RNA decay (NMD), reactive oxygen species (ROS), and epithelial-to-mesenchymal transition (EMT). Although vitamin D has anti-cancer effects, its effectiveness and mechanism of action against osteosarcomas are poorly understood. In this study, we assessed the impact of vitamin D and its receptor (VDR) on the NMD-ROS-EMT signaling axis in in vitro and in vivo osteosarcoma animal models. Initiation of VDR signaling facilitated the enrichment of EMT pathway genes, after which 1,25(OH) 2 D, the active vitamin D derivative, inhibited the EMT pathway in osteosarcoma subtypes. The ligand-bound VDR directly downregulated the EMT inducer SNAI2 , differentiating highly metastatic from low metastatic subtypes and 1,25(OH) 2 D sensitivity. Moreover, epigenome-wide motif and putative target gene analysis revealed the VDR’s integration with NMD tumorigenic and immunogenic pathways. In an autoregulatory manner, 1,25(OH) 2 D inhibited NMD machinery genes and upregulated NMD target genes implicated in anti-oncogenic activity, immunorecognition, and cell-to-cell adhesion. Dicer substrate siRNA knockdown of SNAI2 revealed superoxide dismutase 2 (SOD2)-mediated antioxidative responses and 1,25(OH) 2 D sensitization via non-canonical SOD2 nuclear-to-mitochondrial translocalization leading to overall ROS suppression. In a mouse xenograft metastasis model, the therapeutically relevant vitamin D derivative calcipotriol inhibited osteosarcoma metastasis and tumor growth shown for the first time. Our results uncover novel osteosarcoma-inhibiting mechanisms for vitamin D and calcipotriol that may be translated to human patients.
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Mancini A, Capobianco E, Bruno C, Vergani E, Nicolazzi M, Favuzzi AMR, Panocchia N, Meucci E, Mordente A, Silvestrini A. Non-thyroidal illness syndrome in chronic diseases: role of irisin as modulator of antioxidants. Eur Rev Med Pharmacol Sci 2023; 27:1582-1591. [PMID: 36876705 DOI: 10.26355/eurrev_202302_31401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
Abstract
OBJECTIVE Non-thyroidal-illness syndrome (NTIS) refers to condition found in chronic diseases that is an adaptive mechanism. However, oxidative stress is related to NTIS in a vicious circle, due to deiodinases alteration and negative effects of low T3 on antioxidant levels or activity. Muscle is one of the main targets of thyroid hormones and it can secrete a myokine named irisin, which is able to induce the browning of white adipose tissue, energy expenditure and protect against insulin resistance. Inconclusive data have been reported about irisin role in chronic diseases. Moreover, no correlation with antioxidants has been investigated. Therefore, we performed a case-control study with the primary endpoint to evaluate irisin levels in two models of NTIS, such as chronic heart failure (CHF) and chronic kidney disease (CKD) during haemodialytic treatment. The secondary endpoint was the correlation with total antioxidant capacity (TAC) to establish a possible role of irisin in the modulation of antioxidant systems. PATIENTS AND METHODS Three groups of subjects were enrolled. Group A included CHF patients (n=18; aged 70.22 ± 2.78 ys; BMI ± 27.75 ± 1.28 kg/m2); Group B included CKD patients (n=29; aged 67.03 ± 2.64; BMI 24.53 ± 1.01); finally, 11 normal subjects (Group C) have been enrolled as controls. Irisin has been evaluated by ELISA method and Total Antioxidant Capacity (TAC) by spectrophotometric method. RESULTS Irisin was significantly higher in Group B vs. A and C groups (Mean ± SEM: 20.18 ± 0.61 ng/ml vs. 2.77 ± 0.77 and 13.06 ± 0.56, respectively; p<0.05); a significant correlation between irisin and TAC was observed in group B. CONCLUSIONS These preliminary data suggest a possible role of irisin in the modulation of antioxidants in two chronic syndromes with low T3 (i.e., CHF and CKD) with differential pattern in these two models studied. Further insights are needed to confirm this pilot study, which could be the basis for a longitudinal investigation, to assess a prognostic role of irisin with possible therapeutic implications.
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Affiliation(s)
- A Mancini
- Dipartimento di Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy.
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Xu H, Bensalel J, Raju S, Capobianco E, Lu ML, Wei J. Characterization of huntingtin interactomes and their dynamic responses in living cells by proximity proteomics. J Neurochem 2023; 164:512-528. [PMID: 36437609 DOI: 10.1111/jnc.15726] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 10/28/2022] [Accepted: 11/10/2022] [Indexed: 11/29/2022]
Abstract
Huntingtin (Htt) is a large protein without clearly defined molecular functions. Mutation in this protein causes Huntington's disease (HD), a fatal inherited neurodegenerative disorder. Identification of Htt-interacting proteins by the traditional approaches including yeast two-hybrid systems and affinity purifications has greatly facilitated the understanding of Htt function. However, these methods eliminated the intracellular spatial information of the Htt interactome during sample preparations. Moreover, the temporal changes of the Htt interactome in response to acute cellular stresses cannot be easily resolved with these approaches. Ascorbate peroxidase (APEX2)-based proximity labeling has been used to spatiotemporally investigate protein-protein interactions in living cells. In this study, we generated stable human SH-SY5Y cell lines expressing full-length Htt23Q and Htt145Q with N-terminus tagged Flag-APEX2 to quantitatively map the spatiotemporal changes of Htt interactome to a mild acute proteotoxic stress. Our data revealed that normal and mutant Htt (muHtt) are associated with distinct intracellular microenvironments. Specifically, mutant Htt is preferentially associated with intermediate filaments and myosin complexes. Furthermore, the dynamic changes of Htt interactomes in response to stress are different between normal and mutant Htt. Vimentin is identified as one of the most significant proteins that preferentially interacts with muHtt in situ. Further functional studies demonstrated that mutant Htt affects the vimentin's function of regulating proteostasis in healthy and HD human neural stem cells. Taken together, our data offer important insights into the molecular functions of normal and mutant Htt by providing a list of Htt-interacting proteins in their natural cellular context for further studies in different HD models.
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Affiliation(s)
- Hongyuan Xu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, USA
| | - Johanna Bensalel
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, USA
| | - Sunil Raju
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, USA
| | | | - Michael L Lu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, USA
| | - Jianning Wei
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, USA
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Capobianco E, Dominietto M. Translating Data Science Results into Precision Oncology Decisions: A Mini Review. J Clin Med 2023; 12:jcm12020438. [PMID: 36675367 PMCID: PMC9862106 DOI: 10.3390/jcm12020438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 12/29/2022] [Accepted: 01/03/2023] [Indexed: 01/06/2023] Open
Abstract
While reviewing and discussing the potential of data science in oncology, we emphasize medical imaging and radiomics as the leading contextual frameworks to measure the impacts of Artificial Intelligence (AI) and Machine Learning (ML) developments. We envision some domains and research directions in which radiomics should become more significant in view of current barriers and limitations.
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Affiliation(s)
- Enrico Capobianco
- The Jackson Laboratory, 10 Discovery Drive, Farmington, CT 06032, USA
- Correspondence:
| | - Marco Dominietto
- Paul Scherrer Institut, Forschungsstrasse 111, 5232 Villigen, Switzerland
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Capobianco E. Overview of triple negative breast cancer prognostic signatures in the context of data science-driven clinico-genomics research. Ann Transl Med 2022; 10:1300. [PMID: 36660729 PMCID: PMC9843365 DOI: 10.21037/atm-22-5477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 12/15/2022] [Indexed: 01/01/2023]
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Ma W, Wang C, Li R, Han Z, Jiang Y, Zhang X, Divisi D, Capobianco E, Zhang L, Dong W. PTS is activated by ATF4 and promotes lung adenocarcinoma development via the Wnt pathway. Transl Lung Cancer Res 2022; 11:1912-1925. [PMID: 36248333 PMCID: PMC9554678 DOI: 10.21037/tlcr-22-593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 09/16/2022] [Indexed: 11/06/2022]
Abstract
Background The effects and mechanism of 6-pyruvoyl-tetrahydropterin synthase (PTS) on lung adenocarcinoma (LUAD) were studied in LUAD cells and mice with subcutaneously transplanted tumors. Methods PTS level in tissues and cells was tested by immunohistochemistry, western blot, and quantitative real-time polymerase chain reaction (qRT-PCR). The impacts of PTS on cell viability, proliferation, apoptosis, invasion, and migration were determined by Cell Counting Kit-8 (CCK-8), colony formation assay, flow cytometry, transwell assay, and wound healing assay, respectively. The Cancer Genome Atlas (TCGA) analysis and dual luciferase assay were conducted to predict and verify the relationship between PTS and activating transcription factor 4 (ATF4). A mouse model was established by subcutaneous injection with cancer cells. Tumor volume was calculated as V = ab2/2. Ki67 and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining were used to measure cell proliferation and apoptosis in tumors. Results PTS was highly expressed in LUAD. Higher PTS level was correlated with late clinical stages and poor survival of patients. Down-regulation of PTS inhibited the viability and proliferation and induced apoptosis of LUAD cells. PTS was activated by ATF4, and up-regulation of ATF4 reversed the inhibitory effect of PTS silencing on LUAD cells. Silencing of PTS inhibited the Wnt pathway. Down-regulation of PTS inhibited tumor growth in mice. Conclusions PTS was highly expressed in LUAD. PTS was activated by ATF4 and promoted LUAD development via the Wnt pathway.
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Affiliation(s)
- Wei Ma
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Chao Wang
- Department of Respiratory, The First Affiliated Hospital of Shandong First Medical University, Jinan, China
| | - Ruzhen Li
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Zhaohui Han
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yuanzhu Jiang
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Xiangwei Zhang
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Duilio Divisi
- Department of Life, Health and Environmental Sciences, University of L’Aquila, Thoracic Surgery Unit, “Giuseppe Mazzini” Hospital of Teramo, Teramo, Italy
| | | | - Lin Zhang
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Wei Dong
- Department of Thoracic Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
- Department of Thoracic Surgery, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
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Deng J, Hartung T, Capobianco E, Chen JY, Emmert-Streib F. Editorial: Artificial Intelligence for Precision Medicine. Front Artif Intell 2022; 4:834645. [PMID: 35128393 PMCID: PMC8814648 DOI: 10.3389/frai.2021.834645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 12/29/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Jun Deng
- Department of Therapeutic Radiology, Yale University, New Haven, CT, United States
- *Correspondence: Jun Deng
| | - Thomas Hartung
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MA, United States
| | - Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Coral Gables, FL, United States
- National Research Council of Italy (CNR), Institute of Organic Synthesis and Photoreactivity, Bologna, Italy
| | - Jake Y. Chen
- University of Alabama at Birmingham, Birmingham, AL, United States
| | - Frank Emmert-Streib
- Predictive Society and Data Analytics Lab, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland
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14
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Capobianco E, Deng J. Editorial: Big Data Analytics for Precision Health and Prevention. Front Big Data 2022; 4:835353. [PMID: 35098115 PMCID: PMC8790041 DOI: 10.3389/fdata.2021.835353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Coral Gables, FL, United States
- Department of Chemical Sciences and Materials Technologies, Institute of Organic Synthesis and Photoreactivity, National Research Council of Italy (CNR), Bologna, Italy
- *Correspondence: Enrico Capobianco
| | - Jun Deng
- Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT, United States
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15
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Quigley M, Rieger S, Capobianco E, Wang Z, Zhao H, Hewison M, Lisse TS. Vitamin D Modulation of Mitochondrial Oxidative Metabolism and
mTOR
Enforces Stress Adaptations and Anticancer Responses. JBMR Plus 2021; 6:e10572. [PMID: 35079680 PMCID: PMC8771003 DOI: 10.1002/jbm4.10572] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 09/30/2021] [Accepted: 10/08/2021] [Indexed: 01/13/2023] Open
Abstract
The relationship between the active form of vitamin D3 (1,25‐dihydroxyvitamin D, 1,25(OH)2D) and reactive oxygen species (ROS), two integral signaling molecules of the cell, is poorly understood. This is striking, given that both factors are involved in cancer cell regulation and metabolism. Mitochondria (mt) dysfunction is one of the main drivers of cancer, producing more mitochondria, higher cellular energy, and ROS that can enhance oxidative stress and stress tolerance responses. To study the effects of 1,25(OH)2D on metabolic and mt dysfunction, we used the vitamin D receptor (VDR)‐sensitive MG‐63 osteosarcoma cell model. Using biochemical approaches, 1,25(OH)2D decreased mt ROS levels, membrane potential (ΔΨmt), biogenesis, and translation, while enforcing endoplasmic reticulum/mitohormetic stress adaptive responses. Using a mitochondria‐focused transcriptomic approach, gene set enrichment and pathway analyses show that 1,25(OH)2D lowered mt fusion/fission and oxidative phosphorylation (OXPHOS). By contrast, mitophagy, ROS defense, and epigenetic gene regulation were enhanced after 1,25(OH)2D treatment, as well as key metabolic enzymes that regulate fluxes of substrates for cellular architecture and a shift toward non‐oxidative energy metabolism. ATACseq revealed putative oxi‐sensitive and tumor‐suppressing transcription factors that may regulate important mt functional genes such as the mTORC1 inhibitor, DDIT4/REDD1. DDIT4/REDD1 was predominantly localized to the outer mt membrane in untreated MG‐63 cells yet sequestered in the cytoplasm after 1,25(OH)2D and rotenone treatments, suggesting a level of control by membrane depolarization to facilitate its cytoplasmic mTORC1 inhibitory function. The results show that 1,25(OH)2D activates distinct adaptive metabolic responses involving mitochondria to regain redox balance and control the growth of osteosarcoma cells. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
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Affiliation(s)
- Mikayla Quigley
- Biology Department University of Miami Coral Gables FL USA
- Dana Farber Cancer Institute Boston MA USA
| | - Sandra Rieger
- Biology Department University of Miami Coral Gables FL USA
- Sylvester Comprehensive Cancer Center, Miller School of Medicine University of Miami Miami FL USA
| | - Enrico Capobianco
- Institute for Data Science and Computing University of Miami Coral Gables FL USA
| | - Zheng Wang
- Department of Computer Science University of Miami Coral Gables FL USA
| | - Hengguang Zhao
- Department of Dermatology The First Affiliated Hospital of Chongqing Medical University Chongqing China
| | - Martin Hewison
- Institute of Metabolism and Systems Research University of Birmingham Birmingham UK
| | - Thomas S Lisse
- Biology Department University of Miami Coral Gables FL USA
- Sylvester Comprehensive Cancer Center, Miller School of Medicine University of Miami Miami FL USA
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16
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Gialluisi A, Di Castelnuovo A, Costanzo S, Bonaccio M, Persichillo M, Magnacca S, De Curtis A, Cerletti C, Donati MB, de Gaetano G, Capobianco E, Iacoviello L. Exploring domains, clinical implications and environmental associations of a deep learning marker of biological ageing. Eur J Epidemiol 2021; 37:35-48. [PMID: 34453631 DOI: 10.1007/s10654-021-00797-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 08/07/2021] [Indexed: 01/05/2023]
Abstract
Deep Neural Networks (DNN) have been recently developed for the estimation of Biological Age (BA), the hypothetical underlying age of an organism, which can differ from its chronological age (CA). Although promising, these population-specific algorithms warrant further characterization and validation, since their biological, clinical and environmental correlates remain largely unexplored. Here, an accurate DNN was trained to compute BA based on 36 circulating biomarkers in an Italian population (N = 23,858; age ≥ 35 years; 51.7% women). This estimate was heavily influenced by markers of metabolic, heart, kidney and liver function. The resulting Δage (BA-CA) significantly predicted mortality and hospitalization risk for all and specific causes. Slowed biological aging (Δage < 0) was associated with higher physical and mental wellbeing, healthy lifestyles (e.g. adherence to Mediterranean diet) and higher socioeconomic status (educational attainment, household income and occupational status), while accelerated aging (Δage > 0) was associated with smoking and obesity. Together, lifestyles and socioeconomic variables explained ~48% of the total variance in Δage, potentially suggesting the existence of a genetic basis. These findings validate blood-based biological aging as a marker of public health in adult Italians and provide a robust body of knowledge on its biological architecture, clinical implications and potential environmental influences.
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Affiliation(s)
- Alessandro Gialluisi
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy.
| | | | - Simona Costanzo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Marialaura Bonaccio
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Mariarosaria Persichillo
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | | | - Amalia De Curtis
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Chiara Cerletti
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Maria Benedetta Donati
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Giovanni de Gaetano
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
| | - Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Miami, FL, USA
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS Neuromed, Via dell´Elettronica, 86077, Pozzilli, Italy
- Department of Medicine and Surgery, Research Center in Epidemiology and Preventive Medicine (EPIMED), University of Insubria, Varese, Italy
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17
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Xu H, Bensalel J, Capobianco E, Lu ML, Wei J. Impaired Restoration of Global Protein Synthesis Contributes to Increased Vulnerability to Acute ER Stress Recovery in Huntington's Disease. Cell Mol Neurobiol 2021; 42:2757-2771. [PMID: 34347195 DOI: 10.1007/s10571-021-01137-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 07/28/2021] [Indexed: 12/21/2022]
Abstract
Neurons are susceptible to different cellular stresses and this vulnerability has been implicated in the pathogenesis of Huntington's disease (HD). Accumulating evidence suggest that acute or chronic stress, depending on its duration and severity, can cause irreversible cellular damages to HD neurons, which contributes to neurodegeneration. In contrast, how normal and HD neurons respond during the resolution of a cellular stress remain less explored. In this study, we challenged normal and HD cells with a low-level acute ER stress and examined the molecular and cellular responses after stress removal. Using both striatal cell lines and primary neurons, we first showed the temporal activation of p-eIF2α-ATF4-GADD34 pathway in response to the acute ER stress and during recovery between normal and HD cells. HD cells were more vulnerable to cell death during stress recovery and were associated with increased number of apoptotic/necrotic cells and decreased cell proliferation. This is also supported by the Gene Ontology analysis from the RNA-seq data which indicated that "apoptosis-related Biological Processes" were more enriched in HD cells during stress recovery. We further showed that HD cells were defective in restoring global protein synthesis during stress recovery and promoting protein synthesis by an integrated stress response inhibitor, ISRIB, could attenuate cell death in HD cells. Together, these data suggest that normal and HD cells undergo distinct mechanisms of transcriptional reprogramming, leading to different cell fate decisions during the stress recovery.
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Affiliation(s)
- Hongyuan Xu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Johanna Bensalel
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Miami, FL, 33146, USA
| | - Michael L Lu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Jianning Wei
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA.
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18
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Bensalel J, Xu H, Lu ML, Capobianco E, Wei J. RNA-seq analysis reveals significant transcriptome changes in huntingtin-null human neuroblastoma cells. BMC Med Genomics 2021; 14:176. [PMID: 34215255 PMCID: PMC8252266 DOI: 10.1186/s12920-021-01022-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 06/23/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Huntingtin (Htt) protein is the product of the gene mutated in Huntington's disease (HD), a fatal, autosomal dominant, neurodegenerative disorder. Normal Htt is essential for early embryogenesis and the development of the central nervous system. However, the role of Htt in adult tissues is less defined. Following the recent promising clinical trial in which both normal and mutant Htt mRNA were knocked down in HD patients, there is an urgent need to fully understand the molecular consequences of knocking out/down Htt in adult tissues. Htt has been identified as an important transcriptional regulator. Unbiased investigations of transcriptome changes with RNA-sequencing (RNA-Seq) have been done in multiple cell types in HD, further confirming that transcriptional dysregulation is a central pathogenic mechanism in HD. However, there is lack of direct understanding of the transcriptional regulation by normal Htt. METHODS To investigate the transcriptional role of normal Htt, we first knocked out Htt in the human neuroblastoma SH-SY5Y cell line using the CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated protein 9) gene editing approach. We then performed RNA-seq analysis on Htt-null and wild type SH-SY5Y cells to probe the global transcriptome changes induced by Htt deletion. RESULTS In general, Htt has a widespread effect on gene transcription. Functional analysis of the differentially expressed genes (DEGs) using various bioinformatic tools revealed irregularities in pathways related to cell communication and signaling, and more specifically those related to neuron development, neurotransmission and synaptic signaling. We further examined the transcription factors that may regulate these DEGs. Consistent with the disrupted pathways associated with cellular development, we showed that Htt-null cells exhibited slower cell proliferation than wild type cells. We finally validated some of the top DEGS with quantitative RT-PCR. CONCLUSIONS The widespread transcriptome changes in Htt-null cells could be directly caused by the loss of Htt-mediated transcriptional regulation or due to the secondary consequences of disruption in the gene regulatory network. Our study therefore provides valuable information about key genes associated with Htt-mediated transcription and improves our understanding of the molecular mechanisms underlying the cellular functions of normal and mutant Htt.
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Affiliation(s)
- Johanna Bensalel
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Hongyuan Xu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Michael L Lu
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Miami, FL, 33146, USA
| | - Jianning Wei
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, 33431, USA.
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19
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Capobianco E, Meroni PL. Value of digital biomarkers in precision medicine: implications in cancer, autoimmune diseases, and COVID-19. Expert Review of Precision Medicine and Drug Development 2021. [DOI: 10.1080/23808993.2021.1924055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Miami, FL, USA
| | - Pier Luigi Meroni
- Immunorheumatology Research Laboratory, IRCCS Istituto Auxologico Italiano, Milan, Italy
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20
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Buizza R, Capobianco E, Moretti PF, Vineis P. How can we weather a virus storm? Health prediction inspired by meteorology could be the answer. J Transl Med 2021; 19:102. [PMID: 33750382 PMCID: PMC7940861 DOI: 10.1186/s12967-021-02771-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 02/25/2021] [Indexed: 11/10/2022] Open
Affiliation(s)
- Roberto Buizza
- Istituto Scienze Della Vita, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy.
| | - Enrico Capobianco
- University of Miami, Institute of Data Science and Computing, Miami, FL, US
| | - Pier Francesco Moretti
- Italian National Council of Research (CNR), Liaison Office in Brussels, Brussels, Belgium
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21
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Della Gatta L, Guarnieri G, Ambrosanio G, Capobianco E, Muto M. Clinical and imaging selection for CT guided - fluoroscopy 0203 disk treatment. J BIOL REG HOMEOS AG 2020; 34:15-19. SPECIAL ISSUE: OZONE THERAPY. [PMID: 33176413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Low Back Pain (LBP) is the most common spine disease and it is the most common cause of absence from work in developed countries. At lumbar level, the natural history of herniated disc is characterized by a disappearance of clinical symptoms in up to 60% with conservative treatment through simple rest for about 6 weeks and reduction of the disk heniation revealed by CT or MR scans within eight to nine months after the onset of back pain. Surgery is considered the treatment of choice for extruded, migrated and free fragment herniated disk associated to clinical symptomatology of cono-cauda syndrome, progressive foot droop and hyperalgic radiculopathy. patients with a small or contained herniated disk, without any benefit from conservative medical treatment, can be candidates for one of minimally invasive percutaneous techniques, whose outcome, though, depends on the characteristics of hernia itself and on the chosen technique. The aim of this paper is to discuss about O2-O3 treatment for symptomatic not extruded herniated disk at lumbar level, highlighting about indication inclusion exclusion criteria and our results.
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Affiliation(s)
- L Della Gatta
- Neuroradiology Service Cardarelli Hospital, Naples, Italy
| | - G Guarnieri
- Neuroradiology Service Cardarelli Hospital, Naples, Italy
| | - G Ambrosanio
- Neuroradiology Service Cardarelli Hospital, Naples, Italy
| | - E Capobianco
- Neuroradiology Service Cardarelli Hospital, Naples, Italy
| | - M Muto
- Neuroradiology Service Cardarelli Hospital, Naples, Italy
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22
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Affiliation(s)
- Enrico Capobianco
- Institute Data Science and Computing (IDSC), University of Miami, Miami, FL, United States
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.,Department of Medicine and Surgery, University of Insubria, Varese, Italy
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23
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Abstract
The medical field expects from big data essentially two main results: the ability to build predictive models and the possibility of applying them to obtain accurate patient risk profiles and/or health trajectories. Note that the paradigm of precision has determined that similar challenges need to be faced in both population and individualized studies, namely the need of assembling, integrating, modeling, and interpreting data from a variety of information sources and scales potentially influencing disease from onset to progression. In many cases, data require computational treatment through solutions for otherwise intractable problems. However, as precision medicine remains subject to a substantial amount of data imprecision and lack of translational impact, a revision of methodological inference approaches is needed. Both the relevance and the usefulness of such revision crucially deal with the assimilation of data features dynamically interconnected.
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Affiliation(s)
- Enrico Capobianco
- Institute of Data Science and Computing, University of Miami, Miami, FL, United States
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24
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Capobianco E, Dominietto M. From Medical Imaging to Radiomics: Role of Data Science for Advancing Precision Health. J Pers Med 2020; 10:jpm10010015. [PMID: 32121633 PMCID: PMC7151556 DOI: 10.3390/jpm10010015] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Accepted: 02/17/2020] [Indexed: 12/17/2022] Open
Abstract
Treating disease according to precision health requires the individualization of therapeutic solutions as a cardinal step that is part of a process that typically depends on multiple factors. The starting point is the collection and assembly of data over time to assess the patient’s health status and monitor response to therapy. Radiomics is a very important component of this process. Its main goal is implementing a protocol to quantify the image informative contents by first mining and then extracting the most representative features. Further analysis aims to detect potential disease phenotypes through signs and marks of heterogeneity. As multimodal images hinge on various data sources, and these can be integrated with treatment plans and follow-up information, radiomics is naturally centered on dynamically monitoring disease progression and/or the health trajectory of patients. However, radiomics creates critical needs too. A concise list includes: (a) successful harmonization of intra/inter-modality radiomic measurements to facilitate the association with other data domains (genetic, clinical, lifestyle aspects, etc.); (b) ability of data science to revise model strategies and analytics tools to tackle multiple data types and structures (electronic medical records, personal histories, hospitalization data, genomic from various specimens, imaging, etc.) and to offer data-agnostic solutions for patient outcomes prediction; (c) and model validation with independent datasets to ensure generalization of results, clinical value of new risk stratifications, and support to clinical decisions for highly individualized patient management.
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Affiliation(s)
- Enrico Capobianco
- Center for Computational Science, University of Miami, FL 33146, USA
- Correspondence:
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25
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Dominietto M, Pica A, Safai S, Lomax AJ, Weber DC, Capobianco E. Role of Complex Networks for Integrating Medical Images and Radiomic Features of Intracranial Ependymoma Patients in Response to Proton Radiotherapy. Front Med (Lausanne) 2020; 6:333. [PMID: 32010703 PMCID: PMC6978687 DOI: 10.3389/fmed.2019.00333] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 12/23/2019] [Indexed: 12/21/2022] Open
Abstract
Human cancers exhibit phenotypic diversity that medical imaging can precisely and non-invasively detect. Multiple factors underlying innovations and progresses in the medical imaging field exert diagnostic and therapeutic impacts. The emerging field of radiomics has shown unprecedented ability to use imaging information in guiding clinical decisions. To achieve clinical assessment that exploits radiomic knowledge sources, integration between diverse data types is required. A current gap is the accuracy with which radiomics aligns with clinical endpoints. We propose a novel methodological approach that synergizes data volumes (images), tissue-contextualized information breadth, and network-driven resolution depth. Following the Precision Medicine paradigm, disease monitoring and prognostic assessment are tackled at the individual level by examining medical images acquired from two patients affected by intracranial ependymoma (with and without relapse). The challenge of spatially characterizing intratumor heterogeneity is tackled by a network approach that presents two main advantages: (a) Increased detection in the image domain power from high spatial resolution, (b) Superior accuracy in generating hypotheses underlying clinical decisions.
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Affiliation(s)
- Marco Dominietto
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland.,Radiation Oncology Department, University Hospital of Bern, Bern, Switzerland
| | - Alessia Pica
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Sairos Safai
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Antony J Lomax
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland
| | - Damien C Weber
- Center for Proton Therapy, Paul Scherrer Institute, Villigen, Switzerland.,Radiation Oncology Department, University Hospital of Bern, Bern, Switzerland
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Coral Gables, FL, United States
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26
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Abstract
Background: Electronic health records (EHR) play an important role for the redefinition of phenotypes in view of the wealth and heterogeneity of information now available from disparate data sources. A recent cross-sectional retrospective study has described the potential of EHR toward type 2 diabetes mellitus (T2D) screening when ad hoc models are used. About 10,000 US patients have been analyzed through a variety of inference techniques applied to all records with a variable degree of completeness. The analyses conducted in the reference study have indicated that EHR phenotypes significantly improved T2D detection. Methods: With these US patients and the T2D data evidenced in the above study, we propose an integrative inference approach that leverages the prediction power of EHR features selected by two well-known methods, Random Forests and Lasso. The goal is 2-fold: reducing the Big Data redundancies potentially harmful to the predictive learning task and exploiting the interconnectivity of EHR features. A mutual information (MI) network is the inference tool used to identify communities useful to prioritize significant T2D features underlying the similarity between patients. Results: Endowed with a different degree of granularity, the communities detected after the application of both methods were centered especially on T2D comorbidities and risk factors. As such, they appear very relevant for assessment of two main issues, T2D disease burden, and prevention. Conclusions: Our analytical approach offers a solution for managing the EHR scale factor in a complex disease context. EHR are rich sources of phenotypic diversity through which novel stratifications of patients are expected. To enable these results, both pre-screening of variables and calibration of risk prediction methods become necessary steps in EHR analyses. We have presented networks identifying major T2D communities. The specific significance assigned to comorbidities and risk factors in relation to T2D can be inferred with accuracy from just a suitably reduced number of EHR features.
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Affiliation(s)
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, United States
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27
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Capobianco E. Next Generation Networks: Featuring the Potential Role of Emerging Applications in Translational Oncology. J Clin Med 2019; 8:jcm8050664. [PMID: 31083565 PMCID: PMC6572295 DOI: 10.3390/jcm8050664] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 05/06/2019] [Accepted: 05/08/2019] [Indexed: 01/24/2023] Open
Abstract
Nowadays, networks are pervasively used as examples of models suitable to mathematically represent and visualize the complexity of systems associated with many diseases, including cancer. In the cancer context, the concept of network entropy has guided many studies focused on comparing equilibrium to disequilibrium (i.e., perturbed) conditions. Since these conditions reflect both structural and dynamic properties of network interaction maps, the derived topological characterizations offer precious support to conduct cancer inference. Recent innovative directions have emerged in network medicine addressing especially experimental omics approaches integrated with a variety of other data, from molecular to clinical and also electronic records, bioimaging etc. This work considers a few theoretically relevant concepts likely to impact the future of applications in personalized/precision/translational oncology. The focus goes to specific properties of networks that are still not commonly utilized or studied in the oncological domain, and they are: controllability, synchronization and symmetry. The examples here provided take inspiration from the consideration of metastatic processes, especially their progression through stages and their hallmark characteristics. Casting these processes into computational frameworks and identifying network states with specific modular configurations may be extremely useful to interpret or even understand dysregulation patterns underlying cancer, and associated events (onset, progression) and disease phenotypes.
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Affiliation(s)
- Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL 33146, USA.
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28
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Abstract
Changes and transformations enabled by Big Data have direct effects on Translational Medicine. At one end, superior precision is expected from a more data-intensive and individualized medicine, thus accelerating scientific discovery and innovation (in diagnosis, therapy, disease management etc.). At the other end, the scientific method needs to adapt to the increased diversity that data present, and this can be beneficial because potentially revealing greater details of how a disease manifests and progresses. Patient-focused health data provides augmented complexity too, far beyond the simple need of testing hypotheses or validating models. Clinical decision support systems (CDSS) will increasingly deal with such complexity by developing efficient high-performance algorithms and creating a next generation of inferential tools for clinical use. Additionally, new protocols for sharing digital information and effectively integrating patients data will need to be CDSS-embedded features in view of suitable data harmonization aimed at improved diagnosis, therapy assessment and prevention.
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Affiliation(s)
- Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, USA.
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29
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Jiang Z, Cinti C, Taranta M, Mattioli E, Schena E, Singh S, Khurana R, Lattanzi G, Tsinoremas NF, Capobianco E. Network assessment of demethylation treatment in melanoma: Differential transcriptome-methylome and antigen profile signatures. PLoS One 2018; 13:e0206686. [PMID: 30485296 PMCID: PMC6261551 DOI: 10.1371/journal.pone.0206686] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Accepted: 10/17/2018] [Indexed: 02/07/2023] Open
Abstract
Background In melanoma, like in other cancers, both genetic alterations and epigenetic underlie the metastatic process. These effects are usually measured by changes in both methylome and transcriptome profiles, whose cross-correlation remains uncertain. We aimed to assess at systems scale the significance of epigenetic treatment in melanoma cells with different metastatic potential. Methods and findings Treatment by DAC demethylation with 5-Aza-2’-deoxycytidine of two melanoma cell lines endowed with different metastatic potential, SKMEL-2 and HS294T, was performed and high-throughput coupled RNA-Seq and RRBS-Seq experiments delivered differential profiles (DiP) of both transcriptomes and methylomes. Methylation levels measured at both TSS and gene body were studied to inspect correlated patterns with wide-spectrum transcript abundance levels quantified in both protein coding and non-coding RNA (ncRNA) regions. The DiP were then mapped onto standard bio-annotation sources (pathways, biological processes) and network configurations were obtained. The prioritized associations for target identification purposes were expected to elucidate the reprogramming dynamics induced by the epigenetic therapy. The interactomic connectivity maps of each cell line were formed to support the analysis of epigenetically re-activated genes. i.e. those supposedly silenced by melanoma. In particular, modular protein interaction networks (PIN) were used, evidencing a limited number of shared annotations, with an example being MAPK13 (cascade of cellular responses evoked by extracellular stimuli). This gene is also a target associated to the PANDAR ncRNA, therapeutically relevant because of its aberrant expression observed in various cancers. Overall, the non-metastatic SKMEL-2 map reveals post-treatment re-activation of a richer pathway landscape, involving cadherins and integrins as signatures of cell adhesion and proliferation. Relatively more lncRNAs were also annotated, indicating more complex regulation patterns in view of target identification. Finally, the antigen maps matched to DiP display other differential signatures with respect to the metastatic potential of the cell lines. In particular, as demethylated melanomas show connected targets that grow with the increased metastatic potential, also the potential target actionability seems to depend to some degree on the metastatic state. However, caution is required when assessing the direct influence of re-activated genes over the identified targets. In light of the stronger treatment effects observed in non-metastatic conditions, some limitations likely refer to in silico data integration tools and resources available for the analysis of tumor antigens. Conclusion Demethylation treatment strongly affects early melanoma progression by re-activating many genes. This evidence suggests that the efficacy of this type of therapeutic intervention is potentially high at the pre-metastatic stages. The biomarkers that can be assessed through antigens seem informative depending on the metastatic conditions, and networks help to elucidate the assessment of possible targets actionability.
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Affiliation(s)
- Zhijie Jiang
- Center for Computational Science, University of Miami, Miami, FL, United States of America
| | | | | | - Elisabetta Mattioli
- CNR Institute of Molecular Genetics, Bologna, Italy
- IRCCS Rizzoli Orthopedic Institute, Bologna, Italy
| | - Elisa Schena
- CNR Institute of Molecular Genetics, Bologna, Italy
- Endocrinology Unit, Department of Medical & Surgical Sciences, Alma Mater Studiorum University of Bologna, S Orsola-Malpighi Hospital, Bologna, Italy
| | - Sakshi Singh
- Institute of Clinical Physiology, CNR, Siena, Italy
| | - Rimpi Khurana
- Center for Computational Science, University of Miami, Miami, FL, United States of America
| | - Giovanna Lattanzi
- CNR Institute of Molecular Genetics, Bologna, Italy
- IRCCS Rizzoli Orthopedic Institute, Bologna, Italy
| | - Nicholas F. Tsinoremas
- Center for Computational Science, University of Miami, Miami, FL, United States of America
- Department of Medicine, University of Miami, Miami, FL, United States of America
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, United States of America
- * E-mail:
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Capobianco E, Valdes C, Sarti S, Jiang Z, Poliseno L, Tsinoremas NF. Ensemble Modeling Approach Targeting Heterogeneous RNA-Seq data: Application to Melanoma Pseudogenes. Sci Rep 2017; 7:17344. [PMID: 29229974 PMCID: PMC5725464 DOI: 10.1038/s41598-017-17337-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Accepted: 11/23/2017] [Indexed: 01/28/2023] Open
Abstract
We studied the transcriptome landscape of skin cutaneous melanoma (SKCM) using 103 primary tumor samples from TCGA, and measured the expression levels of both protein coding genes and non-coding RNAs (ncRNAs). In particular, we emphasized pseudogenes potentially relevant to this cancer. While cataloguing the profiles based on the known biotypes, all the employed RNA-Seq methods generated just a small consensus of significant biotypes. We thus designed an approach to reconcile the profiles from all methods following a simple strategy: we selected genes that were confirmed as differentially expressed by the ensemble predictions obtained in a regression model. The main advantages of this approach are: 1) Selection of a high-confidence gene set identifying relevant pathways; 2) Use of a regression model whose covariates embed all method-driven outcomes to predict an averaged profile; 3) Method-specific assessment of prediction power and significance. Furthermore, the approach can be generalized to any biological system for which noisy RNA-Seq profiles are computed. As our analyses concerned bio-annotations of both high-quality protein coding genes and ncRNAs, we considered the associations between pseudogenes and parental genes (targets). Among the candidate targets that were validated, we identified PINK1, which is studied in patients with Parkinson and cancer (especially melanoma).
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Affiliation(s)
- Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, USA.
| | - Camilo Valdes
- Center for Computational Science, University of Miami, Miami, FL, USA
| | | | - Zhijie Jiang
- Center for Computational Science, University of Miami, Miami, FL, USA
| | - Laura Poliseno
- Istituto Toscano Tumori Oncogenomics Unit, Institute of Clinical Physiology-National Research Council, Pisa, Italy
| | - Nicolas F Tsinoremas
- Center for Computational Science, University of Miami, Miami, FL, USA
- Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, USA
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31
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Salmasi L, Capobianco E. Predictive Assessment of Cancer Center Catchment Area from Electronic Health Records. Front Public Health 2017; 5:303. [PMID: 29201863 PMCID: PMC5696335 DOI: 10.3389/fpubh.2017.00303] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 10/31/2017] [Indexed: 11/17/2022] Open
Abstract
Healthcare facilities (HF) may identify catchment areas (CA) by selecting criteria that depend on various factors. These refer to hospital activities, geographical definition, patient covariates, and more. The analyses that were traditionally pursued have a limiting factor in the consideration of only static conditions. Instead, some of the CA determinants involve influences occurring at both temporal and spatial scales. The study of CA in the cancer context means choosing between HF, usually divided into general hospitals versus oncological centers (OCs). In the CA context, electronic health records (EHRs) promise to be a valuable source of information, one driving the next-generation patient-driven clinical decision support systems. Among the challenges, digital health requires the re-definition of a role of stochastic modeling to deal with emerging complexities from data heterogeneity. To model CA with cancer EHR, we have chosen a computational framework centered on a logistic model, as a reference, and on a multivariate statistical approach. We also provided a battery of tests for CA assessment. Our results indicate that a more refined CA model’s structure yields superior discrimination power between health facilities. The increased significance was also visualized by comparative evaluations with ad hoc geo-localized maps. Notably, a cancer-specific spatial effect can be noticed, especially for breast cancer and through OCs. To mitigate the data distributional influences, bootstrap analysis was performed, and gains in some cancer-specific and spatially concentrated regions were obtained. Finally, when the temporal dynamics are assessed along a 3-year timeframe, negligible differential effects appear between predicted probabilities observed between standard critical values and bootstrapped values. In conclusion, for interpreting CA in terms of both spatial and temporal dynamics, sophisticated models are required. The one here proposed suggests that bootstrap can improve test accuracy. We recommend that evidences from stochastic modeling are merged with visual analytics, as this combination may be exploited by policy-makers in support to quantitative CA assessment.
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Affiliation(s)
- Luca Salmasi
- Department of Political Science, University of Perugia, Perugia, Italy
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Coral Gables, FL, United States
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Abstract
Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi-faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed. In diabetes, a multidimensional approach to data analysis is needed to better understand the disease conditions, trajectories and the associated comorbidities. Elucidation of multidimensionality comes from the analysis of factors such as disease phenotypes, marker types, and biological motifs while seeking to make use of multiple levels of information including genetics, omics, clinical data, and environmental and lifestyle factors. Examining the synergy between multiple dimensions represents a challenge. In such regard, the role of Big Data fuels the rise of Precision Medicine by allowing an increasing number of descriptions to be captured from individuals. Thus, data curations and analyses should be designed to deliver highly accurate predicted risk profiles and treatment recommendations. It is important to establish linkages between systems and precision medicine in order to translate their principles into clinical practice. Equivalently, to realize their full potential, the involved multiple dimensions must be able to process information ensuring inter-exchange, reducing ambiguities and redundancies, and ultimately improving health care solutions by introducing clinical decision support systems focused on reclassified phenotypes (or digital biomarkers) and community-driven patient stratifications.
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Affiliation(s)
- Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, USA.
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Trivella MG, Capobianco E, L'Abbate A. Editorial: Physiology in Extreme Conditions: Adaptations and Unexpected Reactions. Front Physiol 2017; 8:748. [PMID: 29033848 PMCID: PMC5626853 DOI: 10.3389/fphys.2017.00748] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 09/14/2017] [Indexed: 01/09/2023] Open
Affiliation(s)
- Maria G Trivella
- Consiglio Nazionale delle Ricerche, Istituto di Fisiologia Clinica, Pisa, Italy
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, United States
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Sharma A, Cinti C, Capobianco E. Multitype Network-Guided Target Controllability in Phenotypically Characterized Osteosarcoma: Role of Tumor Microenvironment. Front Immunol 2017; 8:918. [PMID: 28824643 PMCID: PMC5536125 DOI: 10.3389/fimmu.2017.00918] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Accepted: 07/19/2017] [Indexed: 12/13/2022] Open
Abstract
This study highlights the relevance of network-guided controllability analysis as a precision oncology tool. Target controllability through networks is potentially relevant to cancer research for the identification of therapeutic targets. With reference to a recent study on multiple phenotypes from 22 osteosarcoma (OS) cell lines characterized both in vitro and in vivo, we found that a variety of critical proteins in OS regulation circuits were in part phenotype specific and in part shared. To generalize our inference approach and match cancer phenotypic heterogeneity, we employed multitype networks and identified targets in correspondence with protein sub-complexes. Therefore, we established the relevance for diagnostic and therapeutic purposes of inspecting interactive targets, namely those enriched by significant connectivity patterns in protein sub-complexes. Emerging targets appeared with reference to the OS microenvironment, and relatively to small leucine-rich proteoglycan members and D-type cyclins, among other collagen, laminin, and keratin proteins. These described were evidences shared across all phenotypes; instead, specific evidences were provided by critical proteins including IGFBP7 and PDGFRA in the invasive phenotype, and FGFR3 and THBS1 in the colony forming phenotype.
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Affiliation(s)
- Ankush Sharma
- Experimental Oncology Unit, UOS - Institute of Clinical Physiology, CNR, Siena, Italy.,Center for Computational Science, University of Miami, Miami, FL, United States
| | - Caterina Cinti
- Experimental Oncology Unit, UOS - Institute of Clinical Physiology, CNR, Siena, Italy
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, United States.,Miller School of Medicine, University of Miami, Miami, FL, United States
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35
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Sharma A, Capobianco E. Immuno-Oncology Integrative Networks: Elucidating the Influences of Osteosarcoma Phenotypes. Cancer Inform 2017; 16:1176935117721691. [PMID: 28804242 PMCID: PMC5533255 DOI: 10.1177/1176935117721691] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2017] [Accepted: 06/26/2017] [Indexed: 12/22/2022] Open
Abstract
In vivo and in vitro functional phenotyping characterization was recently obtained with reference to an experimental pan-cancer study of 22 osteosarcoma (OS) cell lines. Here, differentially expressed gene (DEG) profiles were recomputed from the publicly available data to conduct network inference on the immune system regulatory activity across the characterized OS phenotypes. Based on such DEG profiles, and for each phenotype that was analyzed, we obtained coexpression networks and bio-annotations for them. Then, we described the immune-modulated influences in phenotype-specific networks' integrating pathway, transcription factor, and microRNA regulations. Overall, this approach seems suitable for representing heterogeneity in OS tumorigenesis.
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Affiliation(s)
- Ankush Sharma
- Center for Computational Science, University of Miami, Miami, FL, USA
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Miami, FL, USA
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36
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Marranci A, Jiang Z, Vitiello M, Guzzolino E, Comelli L, Sarti S, Lubrano S, Franchin C, Echevarría-Vargas I, Tuccoli A, Mercatanti A, Evangelista M, Sportoletti P, Cozza G, Luzi E, Capobianco E, Villanueva J, Arrigoni G, Signore G, Rocchiccioli S, Pitto L, Tsinoremas N, Poliseno L. The landscape of BRAF transcript and protein variants in human cancer. Mol Cancer 2017; 16:85. [PMID: 28454577 PMCID: PMC5410044 DOI: 10.1186/s12943-017-0645-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2016] [Accepted: 04/03/2017] [Indexed: 12/20/2022] Open
Abstract
Background The BRAF protein kinase is widely studied as a cancer driver and therapeutic target. However, the regulation of its expression is not completely understood. Results Taking advantage of the RNA-seq data of more than 4800 patients belonging to 9 different cancer types, we show that BRAF mRNA exists as a pool of 3 isoforms (reference BRAF, BRAF-X1, and BRAF-X2) that differ in the last part of their coding sequences, as well as in the length (BRAF-ref: 76 nt; BRAF-X1 and BRAF-X2: up to 7 kb) and in the sequence of their 3’UTRs. The expression levels of BRAF-ref and BRAF-X1/X2 are inversely correlated, while the most prevalent among the three isoforms varies from cancer type to cancer type. In melanoma cells, the X1 isoform is expressed at the highest level in both therapy-naïve cells and cells with acquired resistance to vemurafenib driven by BRAF gene amplification or expression of the Δ[3–10] splicing variant. In addition to the BRAF-ref protein, the BRAF-X1 protein (the full length as well as the Δ[3–10] variant) is also translated. The expression levels of the BRAF-ref and BRAF-X1 proteins are similar, and together they account for BRAF functional activities. In contrast, the endogenous BRAF-X2 protein is hard to detect because the C-terminal domain is selectively recognized by the ubiquitin-proteasome pathway and targeted for degradation. Conclusions By shedding light on the repertoire of BRAF mRNA and protein variants, and on the complex regulation of their expression, our work paves the way to a deeper understanding of a crucially important player in human cancer and to a more informed development of new therapeutic strategies. Electronic supplementary material The online version of this article (doi:10.1186/s12943-017-0645-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrea Marranci
- Oncogenomics Unit, Core Research Laboratory, Istituto Toscano Tumori (ITT), AOUP, CNR-IFC, Via Moruzzi 1, 56124, Pisa, Italy.,University of Siena, Siena, Italy
| | - Zhijie Jiang
- Center for Computational Science, University of Miami, Gables One Tower, Room 600 N, 1320 S. Dixie Highway, Coral Gables, FL, 33146-2926, USA
| | - Marianna Vitiello
- Oncogenomics Unit, Core Research Laboratory, Istituto Toscano Tumori (ITT), AOUP, CNR-IFC, Via Moruzzi 1, 56124, Pisa, Italy.,Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy
| | | | - Laura Comelli
- Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy
| | - Samanta Sarti
- Oncogenomics Unit, Core Research Laboratory, Istituto Toscano Tumori (ITT), AOUP, CNR-IFC, Via Moruzzi 1, 56124, Pisa, Italy.,University of Siena, Siena, Italy
| | - Simone Lubrano
- Oncogenomics Unit, Core Research Laboratory, Istituto Toscano Tumori (ITT), AOUP, CNR-IFC, Via Moruzzi 1, 56124, Pisa, Italy.,University of Siena, Siena, Italy
| | - Cinzia Franchin
- Department of Biomedical Sciences, University of Padova, Padova, Italy.,Proteomics Center, University of Padova and Azienda Ospedaliera di Padova, Padova, Italy
| | - Ileabett Echevarría-Vargas
- Molecular and Cellular Oncogenesis Program & Melanoma Research Center, The Wistar Institute, Philadelphia, USA
| | - Andrea Tuccoli
- Oncogenomics Unit, Core Research Laboratory, Istituto Toscano Tumori (ITT), AOUP, CNR-IFC, Via Moruzzi 1, 56124, Pisa, Italy
| | - Alberto Mercatanti
- Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy
| | - Monica Evangelista
- Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy
| | | | - Giorgio Cozza
- Department of Molecular Medicine, University of Padova, Padova, Italy
| | - Ettore Luzi
- Department of Surgery and Translational Medicine, University of Firenze, Firenze, Italy
| | - Enrico Capobianco
- Center for Computational Science, University of Miami, Gables One Tower, Room 600 N, 1320 S. Dixie Highway, Coral Gables, FL, 33146-2926, USA
| | - Jessie Villanueva
- Molecular and Cellular Oncogenesis Program & Melanoma Research Center, The Wistar Institute, Philadelphia, USA
| | - Giorgio Arrigoni
- Department of Biomedical Sciences, University of Padova, Padova, Italy.,Proteomics Center, University of Padova and Azienda Ospedaliera di Padova, Padova, Italy
| | | | - Silvia Rocchiccioli
- Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy
| | - Letizia Pitto
- Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy
| | - Nicholas Tsinoremas
- Center for Computational Science, University of Miami, Gables One Tower, Room 600 N, 1320 S. Dixie Highway, Coral Gables, FL, 33146-2926, USA.
| | - Laura Poliseno
- Oncogenomics Unit, Core Research Laboratory, Istituto Toscano Tumori (ITT), AOUP, CNR-IFC, Via Moruzzi 1, 56124, Pisa, Italy. .,Institute of Clinical Physiology (IFC), CNR, Via Moruzzi 1, 56124, Pisa, Italy.
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Capobianco E. Placental mTOR signalling in metabolic diseases. Placenta 2017. [DOI: 10.1016/j.placenta.2017.01.046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Fornes D, White V, Heinecke F, Capobianco E, Jawerbaum A. microRNA-130 and microRNA-122 alteration are related to lipid metabolic impairments in the foetal liver of rats with gestational diabetes mellitus. Placenta 2017. [DOI: 10.1016/j.placenta.2017.01.085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Gherardini L, Sharma A, Capobianco E, Cinti C. Targeting Cancer with Epi-Drugs: A Precision Medicine Perspective. Curr Pharm Biotechnol 2016; 17:856-65. [PMID: 27229488 DOI: 10.2174/1381612822666160527154757] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Revised: 05/06/2016] [Accepted: 05/23/2016] [Indexed: 11/22/2022]
Abstract
Recent pan-cancer studies have shown the importance of coupling DNA methylation patterns with transcriptome profiles to reveal tumor subgroups with clinically relevant distinct characteristics. While the coupling patterns remain in most cases matter for further study and/or interpretation, it is emerging that all associations between epigenetic changes and specific cancer histotypes can facilitate the development of novel epidrugs. In particular, together with chemotherapy and chemoprevention of cancer, these epidrugs will target specific enzymes involved in the complex regulation of gene expression. This perspective surveys recent cancer epigenetic findings on target drugs and therapeutic strategies, and focuses on the epigenetic modifications that can reverse a stable differentiated state of adult cell towards neoplastic phenotypes. The relevance of such developments may thus pave the way for patient's customized personalized therapies.
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Affiliation(s)
| | | | - Enrico Capobianco
- Center for Computational Science (CCS), University of Miami, Miami, FL, USA.
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Affiliation(s)
- Marco D Dominietto
- Department of Biomedical Engineering, Biomaterials Science Center, University of Basel Allschwil, Switzerland
| | - Enrico Capobianco
- Center for Computational Science, University of Miami Miami, FL, USA
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Raju HB, Tsinoremas NF, Capobianco E. Emerging Putative Associations between Non-Coding RNAs and Protein-Coding Genes in Neuropathic Pain: Added Value from Reusing Microarray Data. Front Neurol 2016; 7:168. [PMID: 27803687 PMCID: PMC5067702 DOI: 10.3389/fneur.2016.00168] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2016] [Accepted: 09/20/2016] [Indexed: 12/28/2022] Open
Abstract
Regeneration of injured nerves is likely occurring in the peripheral nervous system, but not in the central nervous system. Although protein-coding gene expression has been assessed during nerve regeneration, little is currently known about the role of non-coding RNAs (ncRNAs). This leaves open questions about the potential effects of ncRNAs at transcriptome level. Due to the limited availability of human neuropathic pain (NP) data, we have identified the most comprehensive time-course gene expression profile referred to sciatic nerve (SN) injury and studied in a rat model using two neuronal tissues, namely dorsal root ganglion (DRG) and SN. We have developed a methodology to identify differentially expressed bioentities starting from microarray probes and repurposing them to annotate ncRNAs, while analyzing the expression profiles of protein-coding genes. The approach is designed to reuse microarray data and perform first profiling and then meta-analysis through three main steps. First, we used contextual analysis to identify what we considered putative or potential protein-coding targets for selected ncRNAs. Relevance was therefore assigned to differential expression of neighbor protein-coding genes, with neighborhood defined by a fixed genomic distance from long or antisense ncRNA loci, and of parental genes associated with pseudogenes. Second, connectivity among putative targets was used to build networks, in turn useful to conduct inference at interactomic scale. Last, network paths were annotated to assess relevance to NP. We found significant differential expression in long-intergenic ncRNAs (32 lincRNAs in SN and 8 in DRG), antisense RNA (31 asRNA in SN and 12 in DRG), and pseudogenes (456 in SN and 56 in DRG). In particular, contextual analysis centered on pseudogenes revealed some targets with known association to neurodegeneration and/or neurogenesis processes. While modules of the olfactory receptors were clearly identified in protein-protein interaction networks, other connectivity paths were identified between proteins already investigated in studies on disorders, such as Parkinson, Down syndrome, Huntington disease, and Alzheimer. Our findings suggest the importance of reusing gene expression data by meta-analysis approaches.
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Affiliation(s)
- Hemalatha B Raju
- Center for Computational Science, University of Miami Miller School of Medicine, Miami, FL, USA; Human Genetics and Genomic Graduate Program, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Nicholas F Tsinoremas
- Center for Computational Science, University of Miami Miller School of Medicine, Miami, FL, USA; Human Genetics and Genomic Graduate Program, University of Miami Miller School of Medicine, Miami, FL, USA; Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Enrico Capobianco
- Center for Computational Science, University of Miami Miller School of Medicine , Miami, FL , USA
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Malusa F, Taranta M, Zaki N, Cinti C, Capobianco E. Time-course gene profiling and networks in demethylated retinoblastoma cell line. Oncotarget 2016; 6:23688-707. [PMID: 26143641 PMCID: PMC4695145 DOI: 10.18632/oncotarget.4644] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 05/31/2015] [Indexed: 02/06/2023] Open
Abstract
Retinoblastoma, a very aggressive cancer of the developing retina, initiatiates by the biallelic loss of RB1 gene, and progresses very quickly following RB1 inactivation. While its genome is stable, multiple pathways are deregulated, also epigenetically. After reviewing the main findings in relation with recently validated markers, we propose an integrative bioinformatics approach to include in the previous group new markers obtained from the analysis of a single cell line subject to epigenetic treatment. In particular, differentially expressed genes are identified from time course microarray experiments on the WERI-RB1 cell line treated with 5-Aza-2′-deoxycytidine (decitabine; DAC). By inducing demethylation of CpG island in promoter genes that are involved in biological processes, for instance apoptosis, we performed the following main integrative analysis steps: i) Gene expression profiling at 48h, 72h and 96h after DAC treatment; ii) Time differential gene co-expression networks and iii) Context-driven marker association (transcriptional factor regulated protein networks, master regulatory paths). The observed DAC-driven temporal profiles and regulatory connectivity patterns are obtained by the application of computational tools, with support from curated literature. It is worth emphasizing the capacity of networks to reconcile multi-type evidences, thus generating testable hypotheses made available by systems scale predictive inference power. Despite our small experimental setting, we propose through such integrations valuable impacts of epigenetic treatment in terms of gene expression measurements, and then validate evidenced apoptotic effects.
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Affiliation(s)
- Federico Malusa
- Laboratory of Integrative Systems Medicine (LISM), Institute of Clinical Physiology, CNR, Pisa, Italy
| | - Monia Taranta
- Experimental Oncology Unit, Institute of Clinical Physiology, CNR, Siena, Italy
| | - Nazar Zaki
- College of Information Technology (CIT), United Arab Emirates University (UAEU), Al Ain, UAE
| | - Caterina Cinti
- Experimental Oncology Unit, Institute of Clinical Physiology, CNR, Siena, Italy
| | - Enrico Capobianco
- Laboratory of Integrative Systems Medicine (LISM), Institute of Clinical Physiology, CNR, Pisa, Italy.,Center for Computational Science (CCS), University of Miami, Miami, FL, USA
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Kleiman E, Salyakina D, De Heusch M, Hoek KL, Llanes JM, Castro I, Wright JA, Clark ES, Dykxhoorn DM, Capobianco E, Takeda A, McCormack RM, Podack ER, Renauld JC, Khan WN. Corrigendum: Distinct Transcriptomic Features Are Associated with Transitional and Mature B-Cell Populations in the Mouse Spleen. Front Immunol 2016; 7:267. [PMID: 27458457 PMCID: PMC4931833 DOI: 10.3389/fimmu.2016.00267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Accepted: 06/22/2016] [Indexed: 11/28/2022] Open
Affiliation(s)
- Eden Kleiman
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Daria Salyakina
- Center for Computational Science, University of Miami , Miami, FL , USA
| | - Magali De Heusch
- Ludwig Institute for Cancer Research, Brussels Branch, Brussels, Belgium; de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Kristen L Hoek
- Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine , Nashville, TN , USA
| | - Joan M Llanes
- Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine , Nashville, TN , USA
| | - Iris Castro
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Jacqueline A Wright
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Emily S Clark
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Derek M Dykxhoorn
- Hussman Institute for Human Genomics, University of Miami , Miami, FL , USA
| | - Enrico Capobianco
- Center for Computational Science, University of Miami , Miami, FL , USA
| | - Akiko Takeda
- Department of Pathology and Immunology, Washington University School of Medicine in St. Louis , St. Louis, MO , USA
| | - Ryan M McCormack
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Eckhard R Podack
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Jean-Christophe Renauld
- Ludwig Institute for Cancer Research, Brussels Branch, Brussels, Belgium; de Duve Institute, Université Catholique de Louvain, Brussels, Belgium
| | - Wasif N Khan
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
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El Baroudi M, Cinti C, Capobianco E. Immunomediated Pan-cancer Regulation Networks are Dominant Fingerprints After Treatment of Cell Lines with Demethylation. Cancer Inform 2016; 15:45-64. [PMID: 27147816 PMCID: PMC4849425 DOI: 10.4137/cin.s31809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2015] [Revised: 02/09/2016] [Accepted: 02/17/2016] [Indexed: 11/11/2022] Open
Abstract
Pan-cancer studies are particularly relevant not only for addressing the complexity of the inherently observed heterogeneity but also for identifying clinically relevant features that may be common to the cancer types. Immune system regulations usually reveal synergistic modulation with other cancer mechanisms and in combination provide insights on possible advances in cancer immunotherapies. Network inference is a powerful approach to decipher pan-cancer systems dynamics. The methodology proposed in this study elucidates the impacts of epigenetic treatment on the drivers of complex pan-cancer regulation circuits involving cell lines of five cancer types. These patterns were observed from differential gene expression measurements following demethylation with 5-azacytidine. Networks were built to establish associations of phenotypes at molecular level with cancer hallmarks through both transcriptional and post-transcriptional regulation mechanisms. The most prominent feature that emerges from our integrative network maps, linking pathway landscapes to disease and drug-target associations, refers primarily to a mosaic of immune-system crosslinked influences. Therefore, characteristics initially evidenced in single cancer maps become motifs well summarized by network cores and fingerprints.
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Affiliation(s)
- Mariama El Baroudi
- Laboratory of Integrative Systems Medicine (LISM), Institute of Clinical Physiology, National Research Council of Italy (CNR), Pisa, Italy.; Medical Oncology Department, MIRO, Institut de Recherche Expérimentale et Clinique (IREC), Université Catholique de Louvain, Brussels, Belgium
| | - Caterina Cinti
- Cancer Therapy UOS, Institute of Clinical Phsyiology, National Research Council of Italy (CNR), Siena, Italy
| | - Enrico Capobianco
- Laboratory of Integrative Systems Medicine (LISM), Institute of Clinical Physiology, National Research Council of Italy (CNR), Pisa, Italy.; Center for Computational Science, Miller School of Medicine, University of Miami, Miami, FL, USA
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Abstract
Precision medicine presents various methodological challenges whose assessment requires the consideration of multiple factors. In particular, the data multitude in the Electronic Health Records poses interoperability issues and requires novel inference strategies. A problem, though apparently a paradox, is that highly specific treatments and a variety of outcomes may hardly match with consistent observations (i.e., large samples). Why is it the case? Owing to the heterogeneity of Electronic Health Records, models for the evaluation of treatment effects need to be selected, and in some cases, the use of instrumental variables might be necessary. We studied the recently defined person-centered treatment effects in cancer and C-section contexts from Electronic Health Record sources and identified as an instrument the distance of patients from hospitals. We present first the rationale for using such instrument and then its model implementation. While for cancer patients consideration of distance turns out to be a penalty, implying a negative effect on the probability of receiving surgery, a positive effect is instead found in C-section due to higher propensity of scheduling delivery. Overall, the estimated person-centered treatment effects reveal a high degree of heterogeneity, whose interpretation remains context-dependent. With regard to the use of instruments in light of our two case studies, our suggestion is that this process requires ad hoc variable selection for both covariates and instruments and additional testing to ensure validity.
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Affiliation(s)
- Luca Salmasi
- 1 Department of Political Science, University of Perugia, Perugia, Italy
| | - Enrico Capobianco
- 2 Center for Computational Science, University of Miami, Coral Gables, Florida, USA.,3 Laboratory of Integrative Systems Medicine, Institute of Clinical Physiology, CNR, Pisa, IT
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Capobianco E. Immuno-regulated common markers but different network signatures in two associated cancers: evidences from epigenetic treatment. Ann Transl Med 2016; 4:86. [PMID: 27047945 DOI: 10.21037/atm.2016.02.14] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Networks are now widely accepted inference tools in translational oncology. Besides providing agnostic model frameworks for complex data-driven clinical problems of diagnostic, therapeutic and prognostic impacts, networks mainly support insights, testable hypotheses and decision processes on the basis of their topological configurations and connectivity patterns. METHODS The purpose of this study is to emphasize the role of both gene and network signatures in two specific cancers. Retinoblastoma (RB) and osteosarcoma are associated to some extent. It is known that patients who carry germline mutations in the RB1 gene, and who survive RB, are typically at an increased risk of early-onset second cancers, including osteosarcomas. Gene signatures are widely used, but also criticized for their partial lack of reproducibility. Network signatures include gene association dynamics by identifying modules or communities in which subsets of genes functionally belong. RESULTS Two cancer cell lines (one per cancer type) were subjected to a similar epigenetic treatment regimen, using a demethylation agent (DAC, and including similar dose and time course administration). A minimal set of shared differentially expressed (DEG) genes was identified in cancer-specific cell lines from microarray analyses. However, the identified immune signatures were observed to translate into much diversified network signatures. CONCLUSIONS Our evidence is relevant to therapeutic developments, indicating that preference should be assigned to the assessment of bio-entities in a connected environment rather than considering single entities alone.
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Affiliation(s)
- Enrico Capobianco
- 1 Center for Computational Science, Miller School of Medicine, University of Miami, Miami, FL 33146, USA ; 2 Laboratory of Integrative Systems Medicine, Institute of Clinical Physiology, National Research Council, Pisa, Italy
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Issac B, Tsinoremas NF, Capobianco E. Abstract B1-04: Co-expression profiling and transcriptional network evidences from RNA-Seq data reveal specific molecular subtype features in breast cancer. Cancer Res 2015. [DOI: 10.1158/1538-7445.compsysbio-b1-04] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Expression profiling is regarded as the gold standard for breast cancer subtypes, but the recent advent of integrative multi-omics is challenging the validity of findings based on clustering approaches, the stability of the identified groups, the overall reproducibility of the molecular subtypes associated to clusters, and the impacts in both diagnostic practice and therapy. The purpose of the study is to elucidate the relevance of method integration, moving from the limitations of co-expression dynamics revealed by clustering to the high potential of transcriptional network analysis aimed to merge gene expression signatures with oncogenic pathway activity, and better define distinct disease features, such as molecular subtypes.
106 solid normal and 124 solid tumor breast cancer paired-end RNA-Seq data were obtained from The Cancer Genome Atlas (TCGA). Tissue type for all samples is infiltrating ductal carcinoma from female patients. Median age of patients is 57 yrs for normal samples and 52.5 yrs for tumor samples. All samples were sequenced on Illumina Hi-Seq 2000 and each sample contains on average ~100 million reads. Only reads with mapping quality (MAQ) score >=20 were used and mapping rate for these reads was above 90% against repeat masked human transcriptome (build hg19). Fragment Per Kilobase per Million reads (FPKM) values were computed using TopHat and Cufflinks software. Comparison between normal and tumor samples generated 2344 significantly differentially expressed genes (DEGs; p-values≤0.05; fold-change≥2).
The data cascade delivered several expression biotype categories, following ENSEMBL classification. Our focus was initially directed to the identification of molecular subtypes associated to clusters. The clusters were treated as seed classes informing on the target phenotypes, but needing refinement. We explored typical associations formed through hierarchical clustering, tested the robustness of the approach, and assessed the accuracy of sample assignment to clusters. Then, we analyzed transcriptional modularity and by constraining the search space of the problem we identified a list of candidate modules to reflect molecular subtype signatures. We annotated such modules and found distinctive features at both functional enrichment and pathway levels by using several software tools and visualization framework (ClueGO, EnrichmentMap, Cytoscape, etc).
We demonstrate that limitations of hierarchical clustering methods for molecular subtyping can in part be bypassed by complementing the expression profiles with transcriptional modules that allow for multiple annotation and useful visualizations. Therefore, it is important to stress a general aspect - that integrative analysis is a key factor relying not just on increasing data dimensionality (i.e., multi-omics into play), but also relying on a refinement of the data cross-fertilization and analysis fusion performed at intra-omic scale, before dealing with inter-omics harmonization.
Citation Format: Biju Issac, Nicholas F. Tsinoremas, Enrico Capobianco. Co-expression profiling and transcriptional network evidences from RNA-Seq data reveal specific molecular subtype features in breast cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B1-04.
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Capobianco E, Ramirez V, Fornes D, Powell T, Jansson T, Jawerbaum A. Activation of mTOR signaling and increased nitric oxide metabolism in the placenta of rats with gestational diabetes. Placenta 2015. [DOI: 10.1016/j.placenta.2015.01.539] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Kleiman E, Salyakina D, De Heusch M, Hoek KL, Llanes JM, Castro I, Wright JA, Clark ES, Dykxhoorn DM, Capobianco E, Takeda A, Renauld JC, Khan WN. Distinct Transcriptomic Features are Associated with Transitional and Mature B-Cell Populations in the Mouse Spleen. Front Immunol 2015; 6:30. [PMID: 25717326 PMCID: PMC4324157 DOI: 10.3389/fimmu.2015.00030] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2014] [Accepted: 01/15/2015] [Indexed: 11/30/2022] Open
Abstract
Splenic transitional B-cells (T1 and T2) are selected to avoid self-reactivity and to safeguard against autoimmunity, then differentiate into mature follicular (FO-I and FO-II) and marginal zone (MZ) subsets. Transcriptomic analysis by RNA-seq of the five B-cell subsets revealed T1 cell signature genes included RAG suggesting a potential for receptor revision. T1 to T2 B-cell differentiation was marked by a switch from Myb to Myc, increased expression of the PI3K adapter DAP10 and MHC class II. FO-II may be an intermediate in FO-I differentiation and may also become MZ B-cells as suggested by principle component analysis. MZ B-cells possessed the most distinct transcriptome including down-regulation of CD45 phosphatase-associated protein (CD45-AP/PTPRC-AP), as well as upregulation of IL-9R and innate molecules TLR3, TLR7, and bactericidal Perforin-2 (MPEG1). Among the endosomal TLRs, stimulation via TLR3 further enhanced Perforin-2 expression exclusively in MZ B-cells. Using gene-deleted and overexpressing transgenic mice we show that IL-9/IL-9R interaction resulted in rapid activation of STAT1, 3, and 5, primarily in MZ B-cells. Importantly, CD45-AP mutant mice had reduced transitional and increased mature MZ and FO B-cells, suggesting that it prevents premature entry of transitional B-cells to the mature B-cell pool or their survival and proliferation. Together, these findings suggest, developmental plasticity among splenic B-cell subsets, potential for receptor revision in peripheral tolerance whereas enhanced metabolism coincides with T2 to mature B-cell differentiation. Further, unique core transcriptional signatures in MZ B-cells may control their innate features.
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Affiliation(s)
- Eden Kleiman
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Daria Salyakina
- Center for Computational Science, University of Miami , Miami, FL , USA
| | - Magali De Heusch
- Ludwig Institute for Cancer Research, Brussels Branch , Brussels , Belgium ; de Duve Institute, Université Catholique de Louvain , Brussels , Belgium
| | - Kristen L Hoek
- Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine , Nashville, TN , USA
| | - Joan M Llanes
- Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine , Nashville, TN , USA
| | - Iris Castro
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Jacqueline A Wright
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Emily S Clark
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
| | - Derek M Dykxhoorn
- Hussman Institute for Human Genomics, University of Miami , Miami, FL , USA
| | - Enrico Capobianco
- Center for Computational Science, University of Miami , Miami, FL , USA
| | - Akiko Takeda
- Department of Pathology and Immunology, Washington University School of Medicine in St. Louis , St. Louis, MO , USA
| | - Jean-Christophe Renauld
- Ludwig Institute for Cancer Research, Brussels Branch , Brussels , Belgium ; de Duve Institute, Université Catholique de Louvain , Brussels , Belgium
| | - Wasif N Khan
- Department of Microbiology and Immunology, Miller School of Medicine, University of Miami , Miami, FL , USA
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