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Archive for the ‘Biological Networks’ Category


Cancer Genomics: Multiomic Analysis of Single Cells and Tumor Heterogeneity

Curator: Stephen J. Williams, PhD

 

scTrio-seq identifies colon cancer lineages

Single-cell multiomics sequencing and analyses of human colorectal cancer. Shuhui Bian et al. Science  30 Nov 2018:Vol. 362, Issue 6418, pp. 1060-1063

To better design treatments for cancer, it is important to understand the heterogeneity in tumors and how this contributes to metastasis. To examine this process, Bian et al. used a single-cell triple omics sequencing (scTrio-seq) technique to examine the mutations, transcriptome, and methylome within colorectal cancer tumors and metastases from 10 individual patients. The analysis provided insights into tumor evolution, linked DNA methylation to genetic lineages, and showed that DNA methylation levels are consistent within lineages but can differ substantially among clones.

Science, this issue p. 1060

Abstract

Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single-cell resolution. Using optimized single-cell multiomics sequencing together with multiregional sampling of the primary tumor and lymphatic and distant metastases, we developed insights beyond intratumoral heterogeneity. Genome-wide DNA methylation levels were relatively consistent within a single genetic sublineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 patients whose DNA we sequenced. The cancer cells’ DNA demethylation degrees clearly correlated with the densities of the heterochromatin-associated histone modification H3K9me3 of normal tissue and those of repetitive element long interspersed nuclear element 1. Our work demonstrates the feasibility of reconstructing genetic lineages and tracing their epigenomic and transcriptomic dynamics with single-cell multiomics sequencing.

Fig. 1 Reconstruction of genetic lineages with scTrio-seq2.

Global SCNA patterns (250-kb resolution) of CRC01. Each row represents an individual cell. The subclonal SCNAs used for identifying genetic sublineages were marked and indexed; for details, see fig. S6B. On the top of the heatmap, the amplification or deletion frequency of each genomic bin (250 kb) of the non-hypermutated CRC samples from the TCGA Project and patient CRC01’s cancer cells are shown.

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Fig. 1 Reconstruction of genetic lineages with scTrio-seq2.

Global SCNA patterns (250-kb resolution) of CRC01. Each row represents an individual cell. The subclonal SCNAs used for identifying genetic sublineages were marked and indexed; for details, see fig. S6B. On the top of the heatmap, the amplification or deletion frequency of each genomic bin (250 kb) of the non-hypermutated CRC samples

 

 

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An Intelligent DNA Nanorobot to Fight Cancer by Targeting HER2 Expression

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

HER2 is an important prognostic biomarker for 20–30% of breast cancers, which is the most common cancer in women. Overexpression of the HER2 receptor stimulates breast cells to proliferate and differentiate uncontrollably, thereby enhancing the malignancy of breast cancer and resulting in a poor prognosis for affected individuals. Current therapies to suppress the overexpression of HER2 in breast cancer mainly involve treatment with HER2-specific monoclonal antibodies. However, these monoclonal anti-HER2 antibodies have severe side effects in clinical trials, such as diarrhea, abnormal liver function, and drug resistance. Removing HER2 from the plasma membrane or inhibiting the gene expression of HER2 is a promising alternative that could limit the malignancy of HER2-positive cancer cells.

 

DNA origami is an emerging field of DNA-based nanotechnology and intelligent DNA nanorobots show great promise in working as a drug delivery system in healthcare. Different DNA-based nanorobots have been developed as affordable and facile therapeutic drugs. In particular, many studies reported that a tetrahedral framework nucleic acid (tFNA) could serve as a promising DNA nanocarrier for many antitumor drugs, owing to its high biocompatibility and biosecurity. For example, tFNA was reported to effectively deliver paclitaxel or doxorubicin to cancer cells for reversing drug resistance, small interfering RNAs (siRNAs) have been modified into tFNA for targeted drug delivery. Moreover, the production and storage of tFNA are not complicated, and they can be quickly degraded in lysosomes by cells. Since both free HApt and tFNA can be diverted into lysosomes, so,  combining the HApt and tFNA as a novel DNA nanorobot (namely, HApt-tFNA) can be an effective strategy to improve its delivery and therapeutic efficacy in treating HER2-positive breast cancer.

 

Researchers reported that a DNA framework-based intelligent DNA nanorobot for selective lysosomal degradation of tumor-specific proteins on cancer cells. An anti-HER2 aptamer (HApt) was site-specifically anchored on a tetrahedral framework nucleic acid (tFNA). This DNA nanorobot (HApt-tFNA) could target HER2-positive breast cancer cells and specifically induce the lysosomal degradation of the membrane protein HER2. An injection of the DNA nanorobot into a mouse model revealed that the presence of tFNA enhanced the stability and prolonged the blood circulation time of HApt, and HApt-tFNA could therefore drive HER2 into lysosomal degradation with a higher efficiency. The formation of the HER2-HApt-tFNA complexes resulted in the HER2-mediated endocytosis and digestion in lysosomes, which effectively reduced the amount of HER2 on the cell surfaces. An increased HER2 digestion through HApt-tFNA further induced cell apoptosis and arrested cell growth. Hence, this novel DNA nanorobot sheds new light on targeted protein degradation for precision breast cancer therapy.

 

It was previously reported that tFNA was degraded by lysosomes and could enhance cell autophagy. Results indicated that free Cy5-HApt and Cy5-HApt-tFNA could enter the lysosomes; thus, tFNA can be regarded as an efficient nanocarrier to transmit HApt into the target organelle. The DNA nanorobot composed of HApt and tFNA showed a higher stability and a more effective performance than free HApt against HER2-positive breast cancer cells. The PI3K/AKT pathway was inhibited when membrane-bound HER2 decreased in SK-BR-3 cells under the action of HApt-tFNA. The research findings suggest that tFNA can enhance the anticancer effects of HApt on SK-BR-3 cells; while HApt-tFNA can bind to HER2 specifically, the compounded HER2-HApt-tFNA complexes can then be transferred and degraded in lysosomes. After these processes, the accumulation of HER2 in the plasma membrane would decrease, which could also influence the downstream PI3K/AKT signaling pathway that is associated with cell growth and death.

 

However, some limitations need to be noted when interpreting the findings: (i) the cytotoxicity of the nanorobot on HER2-positive cancer cells was weak, and the anticancer effects between conventional monoclonal antibodies and HApt-tFNA was not compared; (ii) the differences in delivery efficiency between tFNA and other nanocarriers need to be confirmed; and (iii) the confirmation of anticancer effects of HApt-tFNA on tumors within animals remains challenging. Despite these limitations, the present study provided novel evidence of the biological effects of tFNA when combined with HApt. Although the stability and the anticancer effects of HApt-tFNA may require further improvement before clinical application, this study initiates a promising step toward the development of nanomedicines with novel and intelligent DNA nanorobots for tumor treatment.

 

References:

 

https://pubs.acs.org/doi/10.1021/acs.nanolett.9b01320

 

https://www.ncbi.nlm.nih.gov/pubmed/27939064

 

https://www.ncbi.nlm.nih.gov/pubmed/11694782

 

https://www.ncbi.nlm.nih.gov/pubmed/27082923

 

https://www.ncbi.nlm.nih.gov/pubmed/25365825

 

https://www.ncbi.nlm.nih.gov/pubmed/26840503

 

https://www.ncbi.nlm.nih.gov/pubmed/29802035

 

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Single-cell RNA-seq helps in finding intra-tumoral heterogeneity in pancreatic cancer

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Pancreatic cancer is a significant cause of cancer mortality; therefore, the development of early diagnostic strategies and effective treatment is essential. Improvements in imaging technology, as well as use of biomarkers are changing the way that pancreas cancer is diagnosed and staged. Although progress in treatment for pancreas cancer has been incremental, development of combination therapies involving both chemotherapeutic and biologic agents is ongoing.

 

Cancer is an evolutionary disease, containing the hallmarks of an asexually reproducing unicellular organism subject to evolutionary paradigms. Pancreatic ductal adenocarcinoma (PDAC) is a particularly robust example of this phenomenon. Genomic features indicate that pancreatic cancer cells are selected for fitness advantages when encountering the geographic and resource-depleted constraints of the microenvironment. Phenotypic adaptations to these pressures help disseminated cells to survive in secondary sites, a major clinical problem for patients with this disease.

 

The immune system varies in cell types, states, and locations. The complex networks, interactions, and responses of immune cells produce diverse cellular ecosystems composed of multiple cell types, accompanied by genetic diversity in antigen receptors. Within this ecosystem, innate and adaptive immune cells maintain and protect tissue function, integrity, and homeostasis upon changes in functional demands and diverse insults. Characterizing this inherent complexity requires studies at single-cell resolution. Recent advances such as massively parallel single-cell RNA sequencing and sophisticated computational methods are catalyzing a revolution in our understanding of immunology.

 

PDAC is the most common type of pancreatic cancer featured with high intra-tumoral heterogeneity and poor prognosis. In the present study to comprehensively delineate the PDAC intra-tumoral heterogeneity and the underlying mechanism for PDAC progression, single-cell RNA-seq (scRNA-seq) was employed to acquire the transcriptomic atlas of 57,530 individual pancreatic cells from primary PDAC tumors and control pancreases. The diverse malignant and stromal cell types, including two ductal subtypes with abnormal and malignant gene expression profiles respectively, were identified in PDAC.

 

The researchers found that the heterogenous malignant subtype was composed of several subpopulations with differential proliferative and migratory potentials. Cell trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. Furthermore, it was found a subset of ductal cells with unique proliferative features were associated with an inactivation state in tumor-infiltrating T cells, providing novel markers for the prediction of antitumor immune response. Together, the findings provided a valuable resource for deciphering the intra-tumoral heterogeneity in PDAC and uncover a connection between tumor intrinsic transcriptional state and T cell activation, suggesting potential biomarkers for anticancer treatment such as targeted therapy and immunotherapy.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/31273297

 

https://www.ncbi.nlm.nih.gov/pubmed/21491194

 

https://www.ncbi.nlm.nih.gov/pubmed/27444064

 

https://www.ncbi.nlm.nih.gov/pubmed/28983043

 

https://www.ncbi.nlm.nih.gov/pubmed/24976721

 

https://www.ncbi.nlm.nih.gov/pubmed/27693023

 

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Real Time Coverage @BIOConvention #BIO2019: Machine Learning and Artificial Intelligence: Realizing Precision Medicine One Patient at a Time

Reporter: Stephen J Williams, PhD @StephenJWillia2

The impact of Machine Learning (ML) and Artificial Intelligence (AI) during the last decade has been tremendous. With the rise of infobesity, ML/AI is evolving to an essential capability to help mine the sheer volume of patient genomics, omics, sensor/wearables and real-world data, and unravel the knot of healthcare’s most complex questions.

Despite the advancements in technology, organizations struggle to prioritize and implement ML/AI to achieve the anticipated value, whilst managing the disruption that comes with it. In this session, panelists will discuss ML/AI implementation and adoption strategies that work. Panelists will draw upon their experiences as they share their success stories, discuss how to implement digital diagnostics, track disease progression and treatment, and increase commercial value and ROI compared against traditional approaches.

  • most of trials which are done are still in training AI/ML algorithms with training data sets.  The best results however have been about 80% accuracy in training sets.  Needs to improve
  • All data sets can be biased.  For example a professor was looking at heartrate using a IR detector on a wearable but it wound up that different types of skin would generate a different signal to the detector so training sets maybe population biases (you are getting data from one group)
  • clinical grade equipment actually haven’t been trained on a large set like commercial versions of wearables, Commercial grade is tested on a larger study population.  This can affect the AI/ML algorithms.
  • Regulations:  The regulatory bodies responsible is up to debate.  Whether FDA or FTC is responsible for AI/ML in healtcare and healthcare tech and IT is not fully decided yet.  We don’t have the guidances for these new technologies
  • some rules: never use your own encryption always use industry standards especially when getting personal data from wearables.  One hospital corrupted their system because their computer system was not up to date and could not protect against a virus transmitted by a wearable.
  • pharma companies understand they need to increase value of their products so very interested in how AI/ML can be used.

Please follow LIVE on TWITTER using the following @ handles and # hashtags:

@Handles

@pharma_BI

@AVIVA1950

@BIOConvention

# Hashtags

#BIO2019 (official meeting hashtag)

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The Journey of Antibiotic Discovery

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

The term ‘antibiotic’ was introduced by Selman Waksman as any small molecule, produced by a microbe, with antagonistic properties on the growth of other microbes. An antibiotic interferes with bacterial survival via a specific mode of action but more importantly, at therapeutic concentrations, it is sufficiently potent to be effective against infection and simultaneously presents minimal toxicity. Infectious diseases have been a challenge throughout the ages. From 1347 to 1350, approximately one-third of Europe’s population perished to Bubonic plague. Advances in sanitary and hygienic conditions sufficed to control further plague outbreaks. However, these persisted as a recurrent public health issue. Likewise, infectious diseases in general remained the leading cause of death up to the early 1900s. The mortality rate shrunk after the commercialization of antibiotics, which given their impact on the fate of mankind, were regarded as a ‘medical miracle’. Moreover, the non-therapeutic application of antibiotics has also greatly affected humanity, for instance those used as livestock growth promoters to increase food production after World War II.

 

Currently, more than 2 million North Americans acquire infections associated with antibiotic resistance every year, resulting in 23,000 deaths. In Europe, nearly 700 thousand cases of antibiotic-resistant infections directly develop into over 33,000 deaths yearly, with an estimated cost over €1.5 billion. Despite a 36% increase in human use of antibiotics from 2000 to 2010, approximately 20% of deaths worldwide are related to infectious diseases today. Future perspectives are no brighter, for instance, a government commissioned study in the United Kingdom estimated 10 million deaths per year from antibiotic resistant infections by 2050.

 

The increase in antibiotic-resistant bacteria, alongside the alarmingly low rate of newly approved antibiotics for clinical usage, we are on the verge of not having effective treatments for many common infectious diseases. Historically, antibiotic discovery has been crucial in outpacing resistance and success is closely related to systematic procedures – platforms – that have catalyzed the antibiotic golden age, namely the Waksman platform, followed by the platforms of semi-synthesis and fully synthetic antibiotics. Said platforms resulted in the major antibiotic classes: aminoglycosides, amphenicols, ansamycins, beta-lactams, lipopeptides, diaminopyrimidines, fosfomycins, imidazoles, macrolides, oxazolidinones, streptogramins, polymyxins, sulphonamides, glycopeptides, quinolones and tetracyclines.

 

The increase in drug-resistant pathogens is a consequence of multiple factors, including but not limited to high rates of antimicrobial prescriptions, antibiotic mismanagement in the form of self-medication or interruption of therapy, and large-scale antibiotic use as growth promotors in livestock farming. For example, 60% of the antibiotics sold to the USA food industry are also used as therapeutics in humans. To further complicate matters, it is estimated that $200 million is required for a molecule to reach commercialization, with the risk of antimicrobial resistance rapidly developing, crippling its clinical application, or on the opposing end, a new antibiotic might be so effective it is only used as a last resort therapeutic, thus not widely commercialized.

 

Besides a more efficient management of antibiotic use, there is a pressing need for new platforms capable of consistently and efficiently delivering new lead substances, which should attend their precursors impressively low rates of success, in today’s increasing drug resistance scenario. Antibiotic Discovery Platforms are aiming to screen large libraries, for instance the reservoir of untapped natural products, which is likely the next antibiotic ‘gold mine’. There is a void between phenotanypic screening (high-throughput) and omics-centered assays (high-information), where some mechanistic and molecular information complements antimicrobial activity, without the laborious and extensive application of various omics assays. The increasing need for antibiotics drives the relentless and continuous research on the foreground of antibiotic discovery. This is likely to expand our knowledge on the biological events underlying infectious diseases and, hopefully, result in better therapeutics that can swing the war on infectious diseases back in our favor.

 

During the genomics era came the target-based platform, mostly considered a failure due to limitations in translating drugs to the clinic. Therefore, cell-based platforms were re-instituted, and are still of the utmost importance in the fight against infectious diseases. Although the antibiotic pipeline is still lackluster, especially of new classes and novel mechanisms of action, in the post-genomic era, there is an increasingly large set of information available on microbial metabolism. The translation of such knowledge into novel platforms will hopefully result in the discovery of new and better therapeutics, which can sway the war on infectious diseases back in our favor.

 

References:

 

https://www.mdpi.com/2079-6382/8/2/45/htm

 

https://www.ncbi.nlm.nih.gov/pubmed/19515346

 

https://www.ajicjournal.org/article/S0196-6553(11)00184-2/fulltext

 

https://www.ncbi.nlm.nih.gov/pubmed/21700626

 

http://www.med.or.jp/english/journal/pdf/2009_02/103_108.pdf

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

RNA plays various roles in determining how the information in our genes drives cell behavior. One of its roles is to carry information encoded by our genes from the cell nucleus to the rest of the cell where it can be acted on by other cell components. Rresearchers have now defined how RNA also participates in transmitting information outside cells, known as extracellular RNA or exRNA. This new role of RNA in cell-to-cell communication has led to new discoveries of potential disease biomarkers and therapeutic targets. Cells using RNA to talk to each other is a significant shift in the general thought process about RNA biology.

 

Researchers explored basic exRNA biology, including how exRNA molecules and their transport packages (or carriers) were made, how they were expelled by producer cells and taken up by target cells, and what the exRNA molecules did when they got to their destination. They encountered surprising complexity both in the types of carriers that transport exRNA molecules between cells and in the different types of exRNA molecules associated with the carriers. The researchers had to be exceptionally creative in developing molecular and data-centric tools to begin making sense of the complexity, and found that the type of carrier affected how exRNA messages were sent and received.

 

As couriers of information between cells, exRNA molecules and their carriers give researchers an opportunity to intercept exRNA messages to see if they are associated with disease. If scientists could change or engineer designer exRNA messages, it may be a new way to treat disease. The researchers identified potential exRNA biomarkers for nearly 30 diseases including cardiovascular disease, diseases of the brain and central nervous system, pregnancy complications, glaucoma, diabetes, autoimmune diseases and multiple types of cancer.

 

As for example some researchers found that exRNA in urine showed promise as a biomarker of muscular dystrophy where current studies rely on markers obtained through painful muscle biopsies. Some other researchers laid the groundwork for exRNA as therapeutics with preliminary studies demonstrating how researchers might load exRNA molecules into suitable carriers and target carriers to intended recipient cells, and determining whether engineered carriers could have adverse side effects. Scientists engineered carriers with designer RNA messages to target lab-grown breast cancer cells displaying a certain protein on their surface. In an animal model of breast cancer with the cell surface protein, the researchers showed a reduction in tumor growth after engineered carriers deposited their RNA cargo.

 

Other than the above research work the scientists also created a catalog of exRNA molecules found in human biofluids like plasma, saliva and urine. They analyzed over 50,000 samples from over 2000 donors, generating exRNA profiles for 13 biofluids. This included over 1000 exRNA profiles from healthy volunteers. The researchers found that exRNA profiles varied greatly among healthy individuals depending on characteristics like age and environmental factors like exercise. This means that exRNA profiles can give important and detailed information about health and disease, but careful comparisons need to be made with exRNA data generated from people with similar characteristics.

 

Next the researchers will develop tools to efficiently and reproducibly isolate, identify and analyze different carrier types and their exRNA cargos and allow analysis of one carrier and its cargo at a time. These tools will be shared with the research community to fill gaps in knowledge generated till now and to continue to move this field forward.

 

References:

 

https://www.nih.gov/news-events/news-releases/scientists-explore-new-roles-rna

 

https://www.cell.com/consortium/exRNA

 

https://www.sciencedaily.com/releases/2016/06/160606120230.htm

 

https://www.pasteur.fr/en/multiple-roles-rnas

 

https://www.nature.com/scitable/topicpage/rna-functions-352

 

https://www.umassmed.edu/rti/biology/role-of-rna-in-biology/

 

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Use of 3D Bioprinting for Development of Toxicity Prediction Models

Curator: Stephen J. Williams, PhD

SOT FDA Colloquium on 3D Bioprinted Tissue Models: Tuesday, April 9, 2019

The Society of Toxicology (SOT) and the U.S. Food and Drug Administration (FDA) will hold a workshop on “Alternative Methods for Predictive Safety Testing: 3D Bioprinted Tissue Models” on Tuesday, April 9, at the FDA Center for Food Safety and Applied Nutrition in College Park, Maryland. This workshop is the latest in the series, “SOT FDA Colloquia on Emerging Toxicological Science: Challenges in Food and Ingredient Safety.”

Human 3D bioprinted tissues represent a valuable in vitro approach for chemical, personal care product, cosmetic, and preclinical toxicity/safety testing. Bioprinting of skin, liver, and kidney is already appearing in toxicity testing applications for chemical exposures and disease modeling. The use of 3D bioprinted tissues and organs may provide future alternative approaches for testing that may more closely resemble and simulate intact human tissues to more accurately predict human responses to chemical and drug exposures.

A synopsis of the schedule and related works from the speakers is given below:

 

8:40 AM–9:20 AM Overview and Challenges of Bioprinting
Sharon Presnell, Amnion Foundation, Winston-Salem, NC
9:20 AM–10:00 AM Putting 3D Bioprinting to the Use of Tissue Model Fabrication
Y. Shrike Zhang, Brigham and Women’s Hospital, Harvard Medical School and Harvard-MIT Division of Health Sciences and Technology, Boston, MA
10:00 AM–10:20 AM Break
10:20 AM–11:00 AM Uses of Bioprinted Liver Tissue in Drug Development
Jean-Louis Klein, GlaxoSmithKline, Collegeville, PA
11:00 AM–11:40 AM Biofabrication of 3D Tissue Models for Disease Modeling and Chemical Screening
Marc Ferrer, National Center for Advancing Translational Sciences, NIH, Rockville, MD

Sharon Presnell, Ph.D. President, Amnion Foundation

Dr. Sharon Presnell was most recently the Chief Scientific Officer at Organovo, Inc., and the President of their wholly-owned subsidiary, Samsara Sciences. She received a Ph.D. in Cell & Molecular Pathology from the Medical College of Virginia and completed her undergraduate degree in biology at NC State. In addition to her most recent roles, Presnell has served as the director of cell biology R&D at Becton Dickinson’s corporate research center in RTP, and as the SVP of R&D at Tengion. Her roles have always involved the commercial and clinical translation of basic research and early development in the cell biology space. She serves on the board of the Coulter Foundation at the University of Virginia and is a member of the College of Life Sciences Foundation Board at NC State. In January 2019, Dr. Presnell will begin a new role as President of the Amnion Foundation, a non-profit organization in Winston-Salem.

A few of her relevant publications:

Bioprinted liver provides early insight into the role of Kupffer cells in TGF-β1 and methotrexate-induced fibrogenesis

Integrating Kupffer cells into a 3D bioprinted model of human liver recapitulates fibrotic responses of certain toxicants in a time and context dependent manner.  This work establishes that the presence of Kupffer cells or macrophages are important mediators in fibrotic responses to certain hepatotoxins and both should be incorporated into bioprinted human liver models for toxicology testing.

Bioprinted 3D Primary Liver Tissues Allow Assessment of Organ-Level Response to Clinical Drug Induced Toxicity In Vitro

Abstract: Modeling clinically relevant tissue responses using cell models poses a significant challenge for drug development, in particular for drug induced liver injury (DILI). This is mainly because existing liver models lack longevity and tissue-level complexity which limits their utility in predictive toxicology. In this study, we established and characterized novel bioprinted human liver tissue mimetics comprised of patient-derived hepatocytes and non-parenchymal cells in a defined architecture. Scaffold-free assembly of different cell types in an in vivo-relevant architecture allowed for histologic analysis that revealed distinct intercellular hepatocyte junctions, CD31+ endothelial networks, and desmin positive, smooth muscle actin negative quiescent stellates. Unlike what was seen in 2D hepatocyte cultures, the tissues maintained levels of ATP, Albumin as well as expression and drug-induced enzyme activity of Cytochrome P450s over 4 weeks in culture. To assess the ability of the 3D liver cultures to model tissue-level DILI, dose responses of Trovafloxacin, a drug whose hepatotoxic potential could not be assessed by standard pre-clinical models, were compared to the structurally related non-toxic drug Levofloxacin. Trovafloxacin induced significant, dose-dependent toxicity at clinically relevant doses (≤ 4uM). Interestingly, Trovafloxacin toxicity was observed without lipopolysaccharide stimulation and in the absence of resident macrophages in contrast to earlier reports. Together, these results demonstrate that 3D bioprinted liver tissues can both effectively model DILI and distinguish between highly related compounds with differential profile. Thus, the combination of patient-derived primary cells with bioprinting technology here for the first time demonstrates superior performance in terms of mimicking human drug response in a known target organ at the tissue level.

A great interview with Dr. Presnell and the 3D Models 2017 Symposium is located here:

Please click here for Web based and PDF version of interview

Some highlights of the interview include

  • Exciting advances in field showing we can model complex tissue-level disease-state phenotypes that develop in response to chronic long term injury or exposure
  • Sees the field developing a means to converge both the biology and physiology of tissues, namely modeling the connectivity between tissues such as fluid flow
  • Future work will need to be dedicated to develop comprehensive analytics for 3D tissue analysis. As she states “we are very conditioned to get information in a simple way from biochemical readouts in two dimension, monocellular systems”  however how we address the complexity of various cellular responses in a 3D multicellular environment will be pertinent.
  • Additional challenges include the scalability of such systems and making such system accessible in a larger way
  1. Shrike Zhang, Brigham and Women’s Hospital, Harvard Medical School and Harvard-MIT Division of Health Sciences and Technology

Dr. Zhang currently holds an Assistant Professor position at Harvard Medical School and is an Associate Bioengineer at Brigham and Women’s Hospital. His research interests include organ-on-a-chip, 3D bioprinting, biomaterials, regenerative engineering, biomedical imaging, biosensing, nanomedicine, and developmental biology. His scientific contributions have been recognized by >40 international, national, and regional awards. He has been invited to deliver >70 lectures worldwide, and has served as reviewer for >400 manuscripts for >30 journals. He is serving as Editor-in-Chief for Microphysiological Systems, and Associate Editor for Bio-Design and Manufacturing. He is also on Editorial Board of BioprintingHeliyonBMC Materials, and Essays in Biochemistry, and on Advisory Panel of Nanotechnology.

Some relevant references from Dr. Zhang

Multi-tissue interactions in an integrated three-tissue organ-on-a-chip platform.

Skardal A, Murphy SV, Devarasetty M, Mead I, Kang HW, Seol YJ, Shrike Zhang Y, Shin SR, Zhao L, Aleman J, Hall AR, Shupe TD, Kleensang A, Dokmeci MR, Jin Lee S, Jackson JD, Yoo JJ, Hartung T, Khademhosseini A, Soker S, Bishop CE, Atala A.

Sci Rep. 2017 Aug 18;7(1):8837. doi: 10.1038/s41598-017-08879-x.

 

Reconstruction of Large-scale Defects with a Novel Hybrid Scaffold Made from Poly(L-lactic acid)/Nanohydroxyapatite/Alendronate-loaded Chitosan Microsphere: in vitro and in vivo Studies.

Wu H, Lei P, Liu G, Shrike Zhang Y, Yang J, Zhang L, Xie J, Niu W, Liu H, Ruan J, Hu Y, Zhang C.

Sci Rep. 2017 Mar 23;7(1):359. doi: 10.1038/s41598-017-00506-z.

 

 

A liver-on-a-chip platform with bioprinted hepatic spheroids.

Bhise NS, Manoharan V, Massa S, Tamayol A, Ghaderi M, Miscuglio M, Lang Q, Shrike Zhang Y, Shin SR, Calzone G, Annabi N, Shupe TD, Bishop CE, Atala A, Dokmeci MR, Khademhosseini A.

Biofabrication. 2016 Jan 12;8(1):014101. doi: 10.1088/1758-5090/8/1/014101.

 

Marc Ferrer, National Center for Advancing Translational Sciences, NIH

Marc Ferrer is a team leader in the NCATS Chemical Genomics Center, which was part of the National Human Genome Research Institute when Ferrer began working there in 2010. He has extensive experience in drug discovery, both in the pharmaceutical industry and academic research. Before joining NIH, he was director of assay development and screening at Merck Research Laboratories. For 10 years at Merck, Ferrer led the development of assays for high-throughput screening of small molecules and small interfering RNA (siRNA) to support programs for lead and target identification across all disease areas.

At NCATS, Ferrer leads the implementation of probe development programs, discovery of drug combinations and development of innovative assay paradigms for more effective drug discovery. He advises collaborators on strategies for discovering small molecule therapeutics, including assays for screening and lead identification and optimization. Ferrer has experience implementing high-throughput screens for a broad range of disease areas with a wide array of assay technologies. He has led and managed highly productive teams by setting clear research strategies and goals and by establishing effective collaborations between scientists from diverse disciplines within industry, academia and technology providers.

Ferrer has a Ph.D. in biological chemistry from the University of Minnesota, Twin Cities, and completed postdoctoral training at Harvard University’s Department of Molecular and Cellular Biology. He received a B.Sc. degree in organic chemistry from the University of Barcelona in Spain.

 

Some relevant references for Dr. Ferrer

Fully 3D Bioprinted Skin Equivalent Constructs with Validated Morphology and Barrier Function.

Derr K, Zou J, Luo K, Song MJ, Sittampalam GS, Zhou C, Michael S, Ferrer M, Derr P.

Tissue Eng Part C Methods. 2019 Apr 22. doi: 10.1089/ten.TEC.2018.0318. [Epub ahead of print]

 

Determination of the Elasticity Modulus of 3D-Printed Octet-Truss Structures for Use in Porous Prosthesis Implants.

Bagheri A, Buj-Corral I, Ferrer M, Pastor MM, Roure F.

Materials (Basel). 2018 Nov 29;11(12). pii: E2420. doi: 10.3390/ma11122420.

 

Mutation Profiles in Glioblastoma 3D Oncospheres Modulate Drug Efficacy.

Wilson KM, Mathews-Griner LA, Williamson T, Guha R, Chen L, Shinn P, McKnight C, Michael S, Klumpp-Thomas C, Binder ZA, Ferrer M, Gallia GL, Thomas CJ, Riggins GJ.

SLAS Technol. 2019 Feb;24(1):28-40. doi: 10.1177/2472630318803749. Epub 2018 Oct 5.

 

A high-throughput imaging and nuclear segmentation analysis protocol for cleared 3D culture models.

Boutin ME, Voss TC, Titus SA, Cruz-Gutierrez K, Michael S, Ferrer M.

Sci Rep. 2018 Jul 24;8(1):11135. doi: 10.1038/s41598-018-29169-0.

A High-Throughput Screening Model of the Tumor Microenvironment for Ovarian Cancer Cell Growth.

Lal-Nag M, McGee L, Guha R, Lengyel E, Kenny HA, Ferrer M.

SLAS Discov. 2017 Jun;22(5):494-506. doi: 10.1177/2472555216687082. Epub 2017 Jan 31.

 

Exploring Drug Dosing Regimens In Vitro Using Real-Time 3D Spheroid Tumor Growth Assays.

Lal-Nag M, McGee L, Titus SA, Brimacombe K, Michael S, Sittampalam G, Ferrer M.

SLAS Discov. 2017 Jun;22(5):537-546. doi: 10.1177/2472555217698818. Epub 2017 Mar 15.

 

RNAi High-Throughput Screening of Single- and Multi-Cell-Type Tumor Spheroids: A Comprehensive Analysis in Two and Three Dimensions.

Fu J, Fernandez D, Ferrer M, Titus SA, Buehler E, Lal-Nag MA.

SLAS Discov. 2017 Jun;22(5):525-536. doi: 10.1177/2472555217696796. Epub 2017 Mar 9.

 

Other Articles on 3D Bioprinting on this Open Access Journal include:

Global Technology Conferences on 3D BioPrinting 2015 – 2016

3D Medical BioPrinting Technology Reporting by Irina Robu, PhD – a forthcoming Article in “Medical 3D BioPrinting – The Revolution in Medicine, Technologies for Patient-centered Medicine: From R&D in Biologics to New Medical Devices”

Bio-Inks and 3D BioPrinting

New Scaffold-Free 3D Bioprinting Method Available to Researchers

Gene Editing for Gene Therapies with 3D BioPrinting

 

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