Category Archives: Transhuman News

Drug development and manufacturing have undergone a seismic shift in the last two decades,1from blockbuster small molecules to highly personalized biologics2and cell and gene therapies. Because these therapies are designed for specific populations, they dont require the kinds of large-scale manufacturing operations that many companies and contract development and manufacturing organizations (CDMOs) have optimized.

While the drugs may offer significant value for patients, smaller batch medicines may not be financially feasible for a larger company to manufacture especially if they have a broader pipeline. Companies are now working to address this disconnect, optimizing their processes for smaller batch biologics.

This article discusses one of the key areas where innovation is needed: downstream processing. Surveys show downstream processing remains a serious bottleneck one that significantly impacts overall production.3Surging demand for treatments and vaccines fueled by the COVID-19 pandemic has only exacerbated these bottlenecks.4,5Many have been exploring alternative processes and products, such as new chromatography columns that better reflect modern manufacturing needs. Biopharmaceutical leaders urgently need these kinds of solutions to improve the productivity, efficiency and flexibility of downstream processing.

As the name suggests, precision medicine is about targeting medical care to each person to improve outcomes and reduce side effects. This field has advanced rapidly over the last two decades, with highly selective biologics and new modalities including bispecifics, trispecifics, antibody-drug conjugates (ADCs), cytokines, and bespoke cell and gene therapies (CGT). Each of these modalities introduces new manufacturing challenges, many related to the potency of the drugs.

ADCs are a validated modality and one that oncology players are increasingly recognizing as important to their discovery and development efforts. We are truly in an ADC renaissance with 11 approved ADCs and more than 100 in development, said Engin Ayturk, PhD, senior director for process engineering and bioconjugation for Mersana Therapeutics. Mersana Therapeutics is advancing a pipeline of novel ADCs, including its lead candidate UpRi (upifitamab rilsodotin), which is being studied in ovarian cancer.

Medicines with greater potency generate increasingly complex regulatory requirements. As a result, the processing of these high-potency molecules including ADCs requires specialized equipment and expertise. Developers must find manufacturing partners that can safely handle high-potency molecules while meeting regulatory requirements.

Technologies such as next-generation sequencing (NGS) provide key insights into the drivers of disease,6,7and how individuals respond to medications. Over the last two decades, this information has helped usher in a new era in precision medicine, targeting unique mutations in cancer or specific pathways in rare or autoimmune diseases (Figure 1). Since these are medications that treat diseases in a target population, these orphan drugs tend to be produced in small batches.

Figure 1: Count of FDA orphan drug/precision medicine designations and approvals by year (1983-2019).8

The rise in disposable single-use technologies has also impacted downstream manufacturing processes and efficiencies. Single-use reactors, membranes and chromatography systems cut down on laborious cleaning processes, giving companies and CDMOs greater flexibility to handle a variety of projects. For smaller-scale manufacturing, they can more readily change out the single-use products and switch to a new therapy. This changeover capability reduces cross-contamination,9provides better bioburden control and ensures companies manufacture high-purity products. Overall, single-use technologies decrease the time and resources spent on clean-up and set-up between different drugs, improving operational efficiency.

You can no longer build a facility that handles just one drug. Your facility must be able to handle more than one drug efficiently, and more and more, were seeing single-use technologies enable that, explained Kasper Mller, PhD, chief technology officer of AGC Biologics. AGC Biologics is a global CDMO offering microbial and mammalian capabilities as well as CGT, fulfilling early-phase through late-phase projects at both small and large scales.

Mller further stated, Disposable single-use technology is rapidly fueling the innovations we see in manufacturing today. As an example, in upstream processing, we developed and implemented the 6-PackTM scale-out concept, which allows us to inoculate and harvest several main bioreactors from one seed train to establish flexible process scaling.

He says this capability is important because manufacturing volume after launch is uncertain for some molecules, even if clinical trial and launch manufacturing is built at a standard 2000L scale. The 6-PackTM scale-out technology allows manufacturers to adjust scale very quickly after launch.

The biopharma experts we interviewed agreed that disposables are now used in every step of the manufacturing process, from buffer preparation, buffer storage and eluate collection all the way to the medication dispensing and weighing rooms. However, some technologies, such as single-use chromatography columns and membranes, have yet to see widespread adoption despite eliminating time consuming packing of columns, qualification, storage and re-validation of oversized columns, and increased throughput. These are expected to become more common in the near future.

A while ago, it became clear that membranes are a great alternative to columns and were becoming more widely used. Weve especially seen great success with flowthrough membranes, Mller explained. Overall, I think were approaching a future in manufacturing where we implement fully disposable processes including all the chromatography steps that support the flexibility that is needed in rare disease and small volume manufacturing.

While not unique to the biopharma industry, the gradual shift from traditional batch processing to continuous processing has also impacted therapeutic manufacturing. Instead of starting and stopping each batch, continuous processing operates as a non-stop cycle. This approach can reduce the cost of manufacturing precision medicines without requiring an increase in scale.10,11

In continuous bioprocessing, continuous chromatography processes are crucial for achieving high purity products. A continuous chromatography process uses several chromatography columns in a concurrent manner: as loading is carried out in the first column, all the other steps washing, elution, regeneration and re-equilibration are carried out in the other columns.12A study that performed a cost analysis of traditional batch processing versus continuous processing for 200 kg of monoclonal antibody (mAb) production found that the latter reduced downstream processing cost of goods by approximately $9/kg.13,14

For smaller biopharmaceutical companies working to produce high-value precision medicines, the new wave of approvals is both exciting and overwhelming. One of those challenges is finding the right facility to handle the manufacturing of each medication.

Facility fit is a big challenge and forward thinking is essential, said Ayturk. Most manufacturing partners are optimized for standard or generic processes that are significantly larger in capacity. There are gaps in finding partners that offer variety in scales of operation and, provide services for drugs that require high-potent handling and/or integrated processes, analytical development and release activities. Finding a manufacturing partner that can handle IND-enabling activities and production needs against aggressive timelines can be challenging.

The COVID-19 pandemic has put pressure on supply chains15and staffing, with many CDMOs and CMOs solidly booked for a year or more. Smaller biotech and biopharma companies without manufacturing abilities that depend on CDMOs can end up deprioritized or paying a premium as they compete for manufacturing capacity alongside larger-scale drugs.

As one engineer at an emerging cancer immunotherapy company puts it: If you have a GMP run that needs to be completed in seven months, but the lead time on the resins and products you need is two years, that is a challenge.

The new wave in precision medicine manufacturing coupled with the COVID-19 pandemic is driving a shortage in new resins and buffers needed for downstream processing. Some market players are quoting lead times of several months to over a year.

To help mitigate these risks, many groups are proactively identifying a second supplier for crucial goods. For example, manufacturers that require a specific resin for removal of a known impurity should find backup products that have a similar resin or membrane. This extra layer of security can help companies meet the deadlines required for clinical trials or for patients who need those therapies the most.

Other backup plans can prove more laborious. In some cases, when weve realized that our columns dedicated to at-scale GMP clinical resupply batches were not going to be delivered on time, weve had to revisit conventional ways of doing work and rebuilt the bridges between single-use and re-use manufacturing approaches, said Ayturk. Weve re-established cycling and resin life-time studies and re-introduced cleaning and storage regimens into our processes to ensure uninterrupted supply to clinic because patients waiting.

The goal for both biopharma companies and CDMOs is to be efficient with drug production in order to ensure their medications reach the populations that need them the most. However, as noted above, this goal can be disrupted by supply chain shortages and a lack of available manufacturing capacity.

Drug developers beginning their manufacturing journey or looking to adapt can learn from these disruptions and plan accordingly. One important step in this direction is evaluating alternative technologies for cleaning up impurities.

Historically, the biopharmaceutical industry has been slow to adopt new technologies for good reason. Regulatory agencies and other stakeholders value proven products and consistency. However, at a certain point, the latest technology must become the status quo to keep up with the evolution in drug modalities and manufacturing processes.

CDMOs sometimes struggle to convince clients that these new technologies will work for their products. Naturally, nobody wants to be the first when it comes to implementing new technology. They want to know how many approved INDs have used that technology, explained Mller. However, we have also seen more development and a strong push for implementing new technology and innovation by the FDA over the last ten years. And so clients do expect that new technologies may be incorporated into their workflows. We routinely make agreements with clients to implement specific technology that solves a unique problem for their product.

There are now both technical and supply chain motivations for adopting new chromatography technologies. As one bioprocessing engineer shared, This is what intrigued us about GOREs membrane technologythe need to have backup or replacement resins that offer speed, efficiency, and long-term cost savings. Ultimately, it is about being able to get the medicines onto the market in order to save lives. GORE had excellent lead times.

GORE Protein Capture Devices with Immobilized Protein A are intended for the affinity purification of precision medicines containing an Fc region in process development to initial GMP clinical applications. The Protein Capture Devices leverage a unique expanded polytetrafluoroethylene (ePTFE) membrane solution that helps to bridge the gap that has long existed between innovations in upstream and downstream processing.

Pre-packed GORE Protein Capture Devices significantly boost productivity with high binding capacity and fast flow rate, enabling a faster path to clinical trials.

As biopharma manufacturers continue to seek alternate solutions in streamlining downstream processes and embrace those with the most viability and efficiency, bottlenecks will be reduced, and productivity will increase. This will have a positive impact as manufacturers shift their focus to precision medicine innovations where ultimately, patients will have access to wider range of therapeutics for a various disease conditions.

References

1. Congressional Budget Office. Research and development in the pharmaceutical industry. Published August 4, 2021. Accessed March 25, 2022. https://www.cbo.gov/publication/57126.

2. Yamamoto Y, Kanayama N, Nakayama Y, Matsushima N. Current status, issues and future prospects of personalized medicine for each disease.J Pers Med. 2022;12(3):444. doi: 10.3390/jpm12030444

3. Bioplan Associates. 13th annual report and survey of biopharmaceutical manufacturing capacity and production. 2016. http://bioplanassociates.com/wp-content/uploads/2016/07/13th-Annual-Biomfg-Report_BioPlan-TABLE-OF-CONTENTS.pdf

4. Challener C. Maximum output starts with optimized upstream processing. BioPharm International. 2021;34(4):10-17. Published April 2, 2021. Accessed August 23, 2022. https://www.biopharminternational.com/view/maximum-output-starts-with-optimized-upstream-processing

5. Barone P, Keumurian F, Wiebe M, et al. The impact of SARS-CoV-2 on biomanufacturing operations. BioPharm International. 2020;33(8):34-38. Accessed February 7, 2022. https://www.biopharminternational.com/view/the-impact-of-sars-cov-2-on-biomanufacturing-operations

6. Gu W, Miller S, Chiu CY. Clinical metagenomic next-generation sequencing for pathogen detection. Annu Rev Pathol Mech Dis. 2019;14(1):319-338. doi: 10.1146/annurev-pathmechdis-012418-012751

7. Adams DR, Eng CM. Next-generation sequencing to diagnose suspected genetic disorders. N Engl J Med. 2018;379(14):1353-1362. doi: 10.1056/NEJMra1711801

8. Miller KL, Fermaglich LJ, Maynard J. Using four decades of FDA orphan drug designations to describe trends in rare disease drug development: substantial growth seen in development of drugs for rare oncologic, neurologic, and pediatric-onset diseases. Orphanet J Rare Dis. 2021;16(1):265. doi: 10.1186/s13023-021-01901-6

9. Sandle T, Saghee MR. Some considerations for the implementation of disposable technology and single-use systems in biopharmaceuticals. J Commer Biotechnol. 2011;17(4):319-329. doi: 10.1057/jcb.2011.21

10. Macdonald GJ. Disrupting downstream bottlenecks. GEN - Genetic Engineering and Biotechnology News. Published June 14, 2018. Accessed February 4, 2022. https://www.genengnews.com/magazine/320/disrupting-downstream-bottlenecks/

11. Tripathi NK, Shrivastava A. Recent developments in bioprocessing of recombinant proteins: expression hosts and process development. Front Bioeng Biotechnol. 2019;7:420. doi: 10.3389/fbioe.2019.00420

12. De Luca C, Felletti S, Lievore G, et al. Modern trends in downstream processing of biotherapeutics through continuous chromatography: The potential of Multicolumn Countercurrent Solvent Gradient Purification. Trends Analyt Chem. 2020;132:116051. doi: 10.1016/j.trac.2020.116051

13. Klutz S, Holtmann L, Lobedann M, Schembecker G. Cost evaluation of antibody production processes in different operation modes. Chem Eng Sci. 2016;141:63-74. doi: 10.1016/j.ces.2015.10.029

14. Somasundaram B, Pleitt K, Shave E, Baker K, Lua LHL. Progression of continuous downstream processing of monoclonal antibodies: Current trends and challenges. Biotechnol Bioeng. 2018;115(12):2893-2907. doi: 10.1002/bit.26812

15. Singh A, et al. Decision-Making Models for Healthcare Supply Chain Disruptions: Review and Insights for Post-Pandemic Era. JGBC. 2022. Singh A, Parida R. Decision-making models for healthcare supply chain disruptions: review and insights for post-pandemic era. JGBC. 2022. doi: 10.1007/s42943-021-00045-5

Originally posted here:
Downstream Processing in the Age of Precision Medicine: Trends and Challenges - Technology Networks

(Boston)Boston University CityLab, a biotechnology learning laboratory for middle and high school teachers and their students, has received a five-year, $1.3 million Science Education Partnership Award (SEPA) grant from the National Institute of General Medical Sciences of the National Institutes of Health (NIH). This grant will allow CityLab to develop, implement and evaluate a new curriculum for high school students that explores genome editing and builds awareness about the importance of diversity, equity, inclusion and social justice in STEM and the biomedical sciences. The grant to Boston University CityLab is the only new SEPA award made to a Massachusetts institution in 2022.

CityLab, a partnership between Boston Universitys School of Medicine and Wheelock College of Education & Human Development, was first funded by the NIH SEPA program in 1991 at the inception of the program and is one of just a few programs that have been continuously operating since that time. The new grant project, "Mystery of the Crooked Cell 2.0: CityLabs Next Generation Socioscientific Approach to Gene Editing," addresses the imperative that NIH's pre-college activities focus on biomedical workforce preparedness, especially for underrepresented minorities (URM).

This project will expand CityLabs Mystery of the Crooked Cell hands-on, inquiry-based curriculum supplement that focuses on the molecular basis of sickle cell disease by incorporating state-of-the-art gene editing content that is immersed with socioscientific reasoning (SSR). This project will reach close to 600 local URM students and, through planned web-based dissemination of the finished curriculum, will reach thousands of students, explained principal investigator Carl Franzblau, PhD, professor of biochemistry at Boston University School of Medicine and the founder of CityLab.

According to principal investigator Donald DeRosa, EdD, clinical associate professor and science education program director at Boston University Wheelock College of Education & Human Development, an SSR approach places science content in a meaningful social context and motivates students to take ownership of their learning. SSR skills include realizing the complexity of the content and context of an issue, analyzing an issue from multiple perspectives, seeking out sources of bias in data and considering how and whether scientific investigations can advance understanding of an issue.

Genome editing is becoming part of the physicians toolkit, so teaching young people about this important and rapidly advancing field will prepare them to be informed patients and, we hope, will position them to enter careers in the biomedical sciences or health professions, highlighted principal investigator Carla Romney, ScD, director of research for CityLab.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

Continue reading here:
BU receives NIH award to increase diversity of STEM and biomedical science workforce - EurekAlert

There is no one-size-fits-all algorithm for AI that enables drug developers to apply it and quickly identify whatever features they seek. Finding an answer to this dilemma has great implications for the field of precision medicine.

Currently, researchers are selecting best-of-breed algorithms in a modular approach to build customized analytics engines that answer specific questions in a way that is both unbiased and reproducible.

We still dont have a gold standard in terms of implementing and applying reproducible AI/ML approaches, said Zeeshan Ahmed, Ph.D., assistant professor of medicine at Robert Wood Johnson Medical School, Rutgers Biomedical and Health Sciences, in an interview with BioSpace.

As yet, there has been very little effort to organize and understand the many computing approaches in this field.

Key AI/ML Objectives for Precision Medicine

A review published in Briefings in Bioinformatics is among the first. Ahmed and colleagues examined five years of literature in whole-genome or whole exome sequencing to identify 32 of the most frequently used AI/ML algorithms and approaches used to deliver precision medicine insights.

The team compared scientific objectives, methodologies, data sources, ethics and gaps for each of those approaches.

For AI/ML to be more useful for drug developers, several things are required. Chief among them, Ahmed said, are:

During cases, when data is of high volume, it is important to ensure the right balance between training and actual datasets to avoid overfitting, Ahmed noted.

For AI/ML to be most useful, the data should be standardized to enable more accurate searches. Ensuring the data uses the same terms to refer to the same elements helps ensure that all the relevant information can be identified and analyzed.

There should be a method to correct errors in the data, too. Data that is entered by hand, for instance, may well have inaccuracies. The study data also should span multiple diseases and distinct populations to reflect the broad way in which diseases, conditions and symptoms present.

The Role of AI/ML in COVID-19 Drug Repurposing

Recent research in Biomedicine & Pharmacotherapy, conducted by Kyung Hyun Choi from the Jeju National University in Korea and colleagues noted the value of ML and deep learning in drug repurposing for COVID-19 therapeutics. Those methods helped them distinguish between drug targets and gene products that affect target activity.

Each type of analysis had its own group of algorithms, Choi explained in the paper. Types of analyses used for machine learning included k-nearest neighbors (a non-supervised learning method), random forest and support vector machine, among others.

Deep learning techniques included artificial neural networks, convolutional neural networks and long short-term memory. AI algorithms were used for link prediction, node prediction or graph prediction and other tasks.

In applying AI/ML to research, Choi and colleagues wrote, The limitationsinclude the inconsistencyin biological networks, as well as challenges associated with various networks that can lead to bias in the outcome. To overcome those issues, he recommended using heterogeneous data from multiple sources to enhance the reliability of analyses.

Another study published in Current Drug Targets last year reviews ML tools used to identify biologically active compounds from among millions of candidates.

It found, among other things, that the support vector machine (SVM) algorithm was more effective than others in indicating the classification model best used for human intestinal absorption predictions. However, the quantitative structure-activity relationship (QSAR) model predicted flavonoid inhibitory effects in specific indications. Clearly, the choice of algorithm matters.

Decoding the Black Box

Until a few years ago, AI often was considered a black box that ingested data and expelled findings without providing researchers with the details needed to understand how those results were derived.

Youre learning how thousands of inputs connect to hundreds or thousands of outputs, David Longo, co-founder and CEO of Ordaos, told BioSpace. Machine learning algorithms learn the intrinsic relationships between for example amino acids and motifs and domainsin a nonlinear, complex way, so theres still a kind of black box element to AL/ML, depending on how you construct it.

Generally, modern AI/ML algorithms allow some degree of insight into how individual algorithms reach their conclusions.

For example, Ordaos, which develops mini-proteins, provides a trace-back of every single amino acid that was changed and how that affected the properties that come out of that protein, Longo said. For researchers, thats a huge benefit.

Innovation in the field of AI/ML today is not necessarily around creating new individual components, but putting them together in interesting ways, Longo continued.

He cited Ordaos multitask learning model as an example.

Traditionally, ML models were developed by training the algorithm in a specific area a structure predictor would just train on structures and, with a few more steps, create a model. Using that model for another, slightly different purpose, required retraining. Ordaos model, in contrast, learns from multiple tasks simultaneously, somewhat countering Ahmeds view of algorithm specificity.

Selecting the Right Algorithms

AI/ML analytic approaches have the potential to help develop enhanced, systems-level understanding of disease mechanisms and treatment impacts, and can replace the homogeneity of existing genetic and statistical approaches with heterogeneity. Realizing that value, however, requires selecting the right algorithms for the job.

It is important to measure and avoid algorithmic bias, Ahmed said. Classifying tasks based on available predictor variables is a key step to correctly address the problem of choosing a suitable AI/ML algorithm.

In my lab, Ahmed said, We practice AI/ML-driven personalized medicine. We are generating AI/ML-ready datasets based on clinical and multi-omics/genomics profiles and are developing automated pipelines to analyze and perform predictive analysis.

Furthermore, we are addressing ethical issues, which involve protecting health information associated with multi-omics/genomic datasets, he continued.

The analytics trend is shifting from generating big data to analyzing and interpreting that data and using it predictively. For those predictions to be accurate, the underlying assumptions also must be accurate, and that requires selecting the right algorithms for the questions.

See the rest here:
Leveraging Best-of-Breed Algorithms for Accuracy in Precision Medicine - BioSpace

Getting from point A to point B has never been easier thanks to digital maps on our smartphones. With the swipe of a finger, we can plan a route to the grocery store, scope out a hiking trail or pick a perfect vacation destination. Soon, biomedical researchers will have a similar tool to easily navigate the vast network of cells in the human body.

The Human BioMolecular Atlas Program, or HuBMAP, is an international consortium of researchers with a shared goal of developing a global atlas of healthy cells in the human body. Once completed, the resource will be made freely available to drug developers and clinical researchers who could use it to shape the development of specialized medical treatments.

The idea behind HuBMAP is akin to the National Institutes of Healths Human Genome Project, which sequenced every single gene in the human body. Completed almost 20 years ago, the massive undertaking kickstarted a renaissance in clinical research and laid the groundwork for innovative approaches to gene-based therapies. But instead of collecting genetic information on the whole organism level, HuBMAP goes deeper with the goal of mapping gene expression, proteins, metabolites and other information in different types of cells across various organs and tissues.

The next step of turning this vast wealth of data into a user-friendly tool is managed by bioinformaticians at the University of Pittsburgh, the Pittsburgh Supercomputing Center (PSC), Carnegie Mellon University and Stanford University. The teams recently received $20 million in renewed funding from the NIH to continue these efforts.

Creating an ecosystem that can connect all the different pieces of data into a single large knowledge resource is a tough job, but thats what this team has special expertise in. We are good at integrating all kinds of various pieces of software and making them run, said co-lead of the Pittsburgh HuBMAP Infrastructure and Engagement Component Jonathan Silverstein, a professor in theDepartment of Biomedical Informaticsat Pitt.

The team, led by Silverstein, who is also a chief research informatics officer at Pitt and UPMCsInstitute for Precision Medicine, and PSCs Scientific Director Phil Blood, will embark on a long journey of annotating vast amounts of molecular-level data from thousands of tissue samples collected in over 60 institutions across the country. A locally maintained and developed hybrid cloud infrastructure for data integration and software development is being used to mold the resulting library of genetic and protein signatures of healthy cells into a comprehensive map.

The HuBMAP Computational Tools Component, led by Matthew Ruffalo of Carnegie Mellons Computational Biology Department, has developed computational pipelines for processing these molecular datasets, allowing for efficient data integration across data types, tissues and more.

The team is also involved in projects aimed at creating an atlas of aging and senescent cells (SenNet) and building a framework for studying molecular markers of breast cancer.

In addition to research, the HuBMAP and SenNet consortia are really helping to shape the ecosystem and the culture around projects that this work will impact, said Kay Metis, SenNet program manager at Pitt. This project has the potential to impact Alzheimers and aging research and make a big difference to the direction of medical research going forward. I love being part of the effort to contribute to the social impact of what a project of this scale can accomplish.

The expertise in molecular biology and clinical data, combined with experience in managing research consortiums and deep knowledge of software integration, along with computing resources provided by the PSC, makes Pittsburgh uniquely capable of handling a complex task such as HuBMAP.

I came to Pitt because it is a place with great depth of interest and scientific expertise and people here are open to building collaborations, not only across Pittsburgh but worldwide. We have created a team that is unbounded not only on the clinical and biological data side, but also on the technology side, Silverstein said.

Ana Gorelova, image by Getty

See original here:
Pitt researchers are leading the way toward a Google Maps of cells - University of Pittsburgh

Nanotechnology, nicknamed "the manufacturing technology of the twenty-first century," allows us to manufacture a vast range of sophisticated molecular devices by manipulating matter on an atomic and molecular scale. These nanomaterials possess the ideal properties of strength, ductility, reactivity, conductance, and capacity at the atomic, molecular, and supramolecular levels to create useable devices and systems in a length range of 1-100 nm. The materials' physical, chemical, and mechanical characteristics differ fundamentally and profoundly at the nanoscale from those of individual atoms, molecules, or bulk material, which enables the most efficient atom alignment in a very tiny space. Nanotechnology allows us to build various intricate nanostructured materials by manipulating matter at the atomic and molecular scale in terms of strength, ductility, reactivity, conductance, and capacity [1,2].

"Nanomedicine" is the science and technology used to diagnose, treat, and prevent diseases. It is also used for pain management and to safeguard and improve people's health through nanosized molecules, biotechnology, genetic engineering, complex mechanical systems, and nanorobots [3]. Nanoscale devices are a thousand times more microscopic than human cells, being comparable to biomolecules like enzymes and their respective receptors in size. Because of this property, nanosized devices can interact with receptors on the cell walls, as well as within the cells. By obtaining entry into different parts of the body, they can help pick up the disease, as well as allow delivery oftreatment to areas of the body that one can never imagine being accessible. Human physiology comprises multiple biological nano-machines. Biological processes that can lead to cancer also occur at the nanoscale. Nanotechnology offers scientists the opportunity to experiment on macromolecules in real time and at the earliest stage of disease, even when very few cells are affected. This helps in the early and accurate detection of cancer.

In a nutshell, the utility of the nanoscale materials for cancer is due to the qualities such as the ability to be functionalized and tailored to human biological systems (compatibility), the ability to offer therapy or act as a therapeutic agent, the ability to act as a diagnostic tool, the capability to penetrate various physiological barriers such as the blood-brain barrier, the capability to accumulate passively in the tumor, and the ability to aggressively target malignant cells.

Nanotechnology in cancer management has yielded various promising outcomes, including drug administration, gene therapy, monitoring and diagnostics, medication carriage, biomarker tracing, medicines, and histopathological imaging. Quantum dots (QDs) and gold nanoparticles are employed at the molecular level to diagnose cancer. Molecular diagnostic techniques based on these nanoparticles, such as biomarker discovery, can properly and quickly diagnose tumors. Nanotechnology therapeutics, such as nanoscale drug delivery, will ensure that malignant tissues are specifically targeted while reducing complications. Because of their biological nature, nanomaterials can cross cell walls with ease. Because of their active and passive targeting, nanomaterials have been used in cancer treatment for many years. This research looks at its applications in cancer diagnosis and therapy, emphasizing the technology's benefits and limitations [3-5]. The various uses of nanotechnology have been enumerated in the Table 1.

Early cancer detection is half the problem solved in the battle against cancer. X-ray, ultrasonography, CT, magnetic resonance imaging (MRI), and PET scan are the imaging techniques routinely used to diagnose cancer. Morphological changes in tissues or cells (histopathology or cytology) help in the final confirmation of cancer. These techniques detect cancer only after visible changes in tissues, by which time the cancer might have proliferated and caused metastasis. Another limitation of conventional imaging techniques is their failure to distinguish benign from malignant tumors. Also, cytology and histopathology cannot be employed as independent, sensitive tests to detect cancer at an early stage. With innovative molecular contrast media and materials, nanotechnology offers quicker and more accurate initial diagnosis, along with an ongoing assessment of cancer patient care [6].

Although nanoparticles are yet to be employed in actual cancer detection, they are currently being used in a range of medical screening tests. Gold nanoparticles are among the most commonly used in home test strips. A significant advantage of using nanoparticles for the detection of cancer is that they have a large surface area to volume ratio in comparison to their larger counterparts. This property ensures antibodies, aptamers, small molecules, fluorescent probes, polyethylene glycol (PEG), and other molecules cover the nanoparticle densely. This presents multiple binding ligands for cancer cells (multivalent effect of nanotools) and therefore increases the specificity and sensitivity of the bioassay [7,8]. Applications of nanotechnology in diagnosis are for the detection of extracellular biomarkers for cancer and for in vivo imaging. A good nanoprobe must have a long circulating time, specificity to the cancer tissue, and no toxicity to nearby tissue [9,10].

Detection of Biomarkers

Nanodevices have been studied to detect blood biomarkers and toxicity to healthy tissues nearby. These biomarkers include cancer-associated circulating tumor cells, associated proteins or cell surface proteins, carbohydrates or circulating tumor nucleic acids, and tumor-shed exosomes. Though it is well known that these biomarkers help to detect cancer at apreliminary stage, they also help to monitor the therapy and recurrence. They have limitations such as low concentrations in body fluids, variations in their levels and timings in different patients, and difficult prospective studies. These hurdles are overcome by nanotechnology, which offers high specificity and sensitivity. High sensitivity, specificity, and multiplexed measurements are all possible with nano-enabled sensors. To further illuminate a problem, next-generation gadgets combine capture with genetic analysis [11-15].

Imaging Using Nanotechnology

Nanotechnology uses nanoprobes that will accumulate selectively in tumor cells by passive or active targeting. The challenges faced are the interaction of nanoparticles with blood proteins, their clearance by the reticuloendothelial system, and targeting of tumors.Passive targeting suggests apreference for collecting the nanoparticles in the solid tumors due to extravasation from the blood vessels. This is made possible by the defective angiogenesis of the tumorwherein the new blood vessels do not have tight junctions in their endothelial cells and allow the leaking out of nanoparticles up to 150 nm in size, leading to a preferential accumulation of nanoparticles in the tumor tissue. This phenomenon is called enhanced permeability and retention (EPR).Active targeting involves the recognition of nanoparticles by the tumor cell surface receptors. This will enhance the sensitivity of in vivo tumor detection. For early detection of cancer, active targeting will give better results than passive targeting [16-18].

This can be classified as delivery of chemotherapy, immunotherapy, radiotherapy, and gene therapy, and delivery of chemotherapy is aimed at improving the pharmacokinetics and reducing drug toxicity by selective targeting and delivery to cancer tissues. This is primarily based on passive targeting, which employs the EPReffect described earlier [16]. Nanocarriers increase the half-life of the drugs. Immunotherapy is a promising new front in cancer treatment based on understanding the tumor-host interaction. Nanotechnology is being investigated to deliver immunostimulatory or immunomodulatory molecules. It can be used as an adjuvant to other therapies [19-21].

Role of Nanotechnology in Radiotherapy

Thistechnology involves targeted delivery of radioisotopes, targeted delivery of radiosensitizer, reduced side effects of radiotherapy by decreasing distribution to healthy tissues, and combining radiotherapy with chemotherapy to achieve synergism but avoid side effects, andadministering image-guided radiotherapy improves precision and accuracy while reducing exposure to surrounding normal tissues[22,23].

Gene Therapy Using Nanotechnology

There is a tremendous interest in the research in gene therapy for cancer, but the results are still falling short of clinical application. Despite a wide array of therapies aimed at gene modulation, such as gene silencing, anti-sense therapy, RNAinterference, and gene and genome editing, finding a way to deliver these effects is challenging. Nanoparticles are used as carriers for gene therapy, with advantages such as easy construction and functionalizing and low immunogenicity and toxicity. Gene-targeted delivery using nanoparticles has great future potential. Gene therapy is still in its infancy but is very promising [24].

Nanodelivery Systems

Quantum dots: Semiconductor nanocrystal quantum dots (QDs) have outstanding physical properties. Probes based on quantum dots have achieved promising cellular and in vivo molecular imaging developments. Increasing research is proving that technology based on quantum dots may become an encouraging approach in cancer research[4]. Biocompatible QDs were launched for mapping cancer cells in vitro in 1998. Scientists used these to create QD-based probes for cancer imaging that were conjugated with cancer-specific ligands, antibodies, or peptides. QD-immunohistochemistry (IHC) has more sensitivity and specificity than traditional immunohistochemistry (IHC) and can accomplish measurements of even low levels, offering considerably higher information for individualized management. Imaging utilizing quantum dots has emerged as a promising technology for early cancer detection[25,26].

Nanoshells and gold nanoparticles/gold nanoshells (AuNSs) are an excellent example of how combining nanoscience and biomedicine can solve a biological problem. They have an adjustable surface plasmon resonance, which can be set to the near-infrared to achieve optimal penetration of tissues. During laser irradiation, AuNSs' highly effective light-to-heat transition induces thermal destruction of the tumor without harming healthy tissues. AuNSs can even be used as a carrier for a wide range of diagnostic and therapeutic substances[27].

Dendrimers: These are novel nanoarchitectures with distinguishing characteristics such as a spherical three-dimensional shape, a monodispersed uni-micellar nature, and a nanometric size range. The biocompatibility of dendrimers has been employed to deliver powerful medications such as doxorubicin. This nanostructure targets malignant cells by attaching ligands to their surfaces. Dendrimers have been intensively investigated for targeting and delivering cancer therapeutics and magnetic resonance imaging contrast agents. The gold coating on its surface significantly reduced their toxicity without significantly affecting their size. It also served as an anchor for attaching high-affinity targeting molecules to tumor cells [28].

Liposomal nanoparticles (Figure 1): These have a role in delivery to a specific target spot, reducing biodistribution toxicity because of the surface-modifiable lipid composition, and have a structure similar to cell membranes. Liposome-based theranostics (particles constructed for the simultaneous delivery of therapeutic and diagnostic moieties) have the advantage of targeting specific cancer cells.Liposomes are more stable in the bloodstream and increase the solubility of the drug. They also act as sustained release preparations and protect the drug from degradation and pH changes, thereby increasing the drug's circulating half-life. Liposomes help to overcome multidrug resistance. Drugs such as doxorubicin, daunorubicin, mitoxantrone, paclitaxel, cytarabine, and irinotecanare used with liposome delivery [29-31].

Polymeric micelles: Micelles are usually spherical particles with a diameter of 10-100 nm, which are self-structured and have a hydrophilic covering shell and a hydrophobic core, suspended in an aqueous medium. Hydrophobic medicines can be contained in the micelle's core. A variety of molecules having the ability to bind to receptors, such as aptamers, peptides, antibodies, polysaccharides, and folic acid, are used to cover the surface of the micelle in active tumor cell targeting. Enzymes, ultrasound, temperature changes, pH gradients, and oxidationare used as stimuli in micelle drug delivery systems. Various physical and chemical triggers are used as stimuli in micelle drug delivery systems. pH-sensitive polymer micelle is released by lowering pH. A co-delivery system transports genetics, as well as anticancer medicines. Although paclitaxel is a powerful microtubule growth inhibitor, it has poor solubility, which causes fast drug aggregation and capillary embolisms. Such medicines' solubility can beraised to 0.0015-2 mg/ml by encapsulating them in micelles. Polymeric micelles are now being tested for use in nanotherapy [32].

Carbon nanotubes (CNTs): Carbon from burned graphite is used to create hollow cylinders known as carbon nanotubes (CNTs). They possess distinct physical and chemical characteristics that make them interesting candidates as carriers of biomolecules and drug delivery transporters. They have a special role in transporting anticancer drugs with a small molecular size. Wu et al. formed amedicine carrier system using multi-walled CNTs (MWCNTs) and the 10-hydroxycamptothecin (HCPT) anticancer compound. As a spacer between MWCNTs and HCPT, they employed hydrophilic diamine trimethylene glycol. In vitro and in vivo, their HCPT-MWCNT conjugates showed significantly increased anticancer efficacy when compared to traditional HCPTformulations. These conjugates were able to circulate in the blood longer and were collected precisely at the tumor site [33,34].

Limitations

Manufacturing costs, extensibility, safety, and the intricacy of nanosystems must all be assessed and balanced against possible benefits. The physicochemical properties of nanoparticles in biological systems determine their biocompatibility and toxicity. As a result, stringent manufacturing and delineation of nanomaterials for delivery of anticancer drugs are essential to reduce nanocarrier toxicity to surrounding cells. Another barrier to medication delivery is ensuring public health safety, as issues with nanoparticles do not have an immediate impact. The use of nanocarriers in cancer treatment may result in unforeseen consequences. Hypothetical possibilities of environmental pollution causing cardiopulmonary morbidity and mortality, production of reactive oxygen species causing inflammation and toxicity, and neuronal or dermal translocations are a few possibilities that worry scientists. Nanotoxicology, a branch of nanomedicine, has arisen as a critical topic of study, paving the way for evaluating nanoparticle toxicity [35-37].

Nanotechnology has been one of the recent advancements of science that not only has revolutionized the engineering field but also is now making its impact in the medical and paramedical field. Scientists have been successful in knowing the properties and characteristics of these nanomaterials and optimizing them for use in the healthcare industry. Although some nanoparticles have failed to convert to the clinic, other new and intriguing nanoparticles are now in research and show great potential, indicating that new treatment options may be available soon. Nanomaterials are highly versatile, with several benefits that can enhance cancer therapies and diagnostics.

These are particularly useful as drug delivery systems due to their tiny size and unique binding properties. Drugs such as doxorubicin, daunorubicin, mitoxantrone, paclitaxel, cytarabine, irinotecan, and amphotericin B are already being conjugated with liposomes for their delivery in current clinical practices. Doxorubicin, cytarabine, vincristine, daunorubicin, mitoxantrone, and paclitaxel, in particular, are key components of cancer chemotherapy. Even in the diagnosis of cancer for imaging and detection of tumor markers, particles such as nanoshells, dendrimers, and gold nanoparticles are currently in use.

Limitations of this novel technology include manufacturing expenses, extensibility, intricacy, health safety, and potential toxicity. These are being overcome adequately by extensive research and clinical trials, and nanomedicine is becoming one of the largest industries in the world. A useful collection of research tools and clinically practical gadgets will be made available in the near future thanks to advancements in nanomedicine. Pharmaceutical companies will use in vivo imaging, novel therapeutics, and enhanced drug delivery technologies in their new commercial applications. In the future, neuro-electronic interfaces and cell healing technology may change medicine and the medical industry when used to treat brain tumors.

Continued here:
The Application of Nanotechnology and Nanomaterials in Cancer Diagnosis and Treatment: A Review - Cureus

Smart Immune Bolsters Management Team with Medical and Technical Appointments

Dr Frederic Lehmann, MD, appointed Chief Medical Officer and Dr Pierre Heimendinger, PharmD, appointed Chief Technical Officer

Dr Pierre Heimendinger and Dr Frederic Lehmann, CTO and CMO of Smart Immune.

PARIS, France, September 13, 2022 Smart Immune SAS, a clinical-stage biotechnology company developing ProTcell, a thymus-empowered T-cell therapy platform to fully and rapidly re-arm the immune system, announced today that it has appointed Dr Frederic Lehmann as Chief Medical Officer and Dr Pierre Heimendinger as Chief Technical Officer. They bring extensive experience and strong industrial track records in the fields of immune-oncology and cell and gene therapy.

Karine Rossignol, PharmD, Co-founder and Chief Executive Officer of Smart Immune, said: "I am thrilled to be expanding our management team with such seasoned and respected executives. Dr Frederic Lehmann and Dr Pierre Heimendinger have both made impressive contributions to the field of allogeneic T-cell medicine, bringing innovation from bench to bedside. Frederics experience in clinical trial design and Pierres in cell therapy process development will be instrumental in getting the Company ready for the registration phase. I am confident that their knowledge and commitment will raise the development of our ProTcell platform to a new level and expedite patient access to our technology. We are excited to welcome them to Smart Immune!"

As the former Head of Clinical Development and Medical Affairs and Vice President of Celyad Oncology, Dr Frederic Lehmann defined the strategic vision and contributed to securing a number of autologous and allogeneic engineered T-cell therapy IND candidates. He also spent 12 years at GSK in several roles including Head of the Early Clinical Development Business Unit for Cancer Immunotherapeutics in the companys Vaccine Division. Frederic takes over as Chief Medical Officer from Smart Immunes Co-founder Marina Cavazzana, MD, PhD, who will transition to the role of Strategic Clinical Development Advisor.

Dr Frederic Lehmann, Chief Medical Officer of Smart Immune, commented: I am honored to be joining such an outstanding organization and its founding team, true pioneers in T-cell progenitors, to give rise to long-lasting cellular therapy fighting cancer and infection. I strongly believe in Smart Immunes potential, and I am very pleased to be appointed Chief Medical Officer at this exciting time. I am fully committed to help enable delivery of this unique therapeutic approach to patients with unmet need.

As Chief Technical Officer, Dr Pierre Heimendinger will oversee the development of Smart Immunes ProTcell platform, most notably ensuring the stability and safety of the ProTcell products as they progress through Phase I/II clinical trials. Pierre brings over 30 years of experience in process automation of allogeneic and autologous CAR-Treg, Treg, viral vectors and vaccines. Prior to joining Smart Immune, he held key managerial roles overseeing production, pharmaceutical development and quality control departments at multiple pharma and biotech companies such as Aventis-Pasteur (Sanofi), Octapharma, Transgene, TxCell, and most recently, Sangamo Therapeutics. Pierre holds a PharmD from the Mrieux Institute in France.

Dr Pierre Heimendinger, Chief Technical Officer of Smart Immune, commented: Smart Immunes developments in T-cell therapy will be completely transformative to the field as we strive to re-arm the immune system for patients fighting cancer and infection, enabling a truly off-the-shelf approach, and making the ProTcell cell therapy accessible for patients when it is needed and wherever it is needed. I am delighted to be working with such a groundbreaking and innovative company at a pivotal time in its growth and development and am thankful to Karine and the rest of the Smart Immune team for such a warm welcome.

Ends

About Smart Immune

Smart Immune is a clinical-stage biotechnology company developing ProTcell, a thymus-empowered T-cell therapy platform to fully and rapidly re-arm the immune system, enabling next-generation allogeneic T-cell therapies for all. The company was founded in 2017 to help patients with life-threatening diseases such as high-risk blood cancers and primary immunodeficiencies.

Smart Immunes ProTcell platform, which is already in Phase I/II clinical trials, enables the recovery of a complete immune repertoire in patients fighting cancer and infection. ProTcell introduces potent, allogeneic T-cell progenitors which are then differentiated by the thymus into fully functional T-cells an off the shelf T-cell medicine.

Smart Immunes partners include Memorial Sloan Kettering in New York and Greater Paris University Hospitals (AP-HP). The company is headquartered at Paris Biotech Sant, 29 rue du Faubourg St Jacques, France.

https://www.smart-immune.com/

LinkedIn | Twitter

Media contact:

Consilium Strategic Communications

smartimmune@consilium-comms.com

Original post:
Smart Immune Bolsters Management Team with Medical and Technical Appointments - GlobeNewswire

Kaaja R, Laivuori H, Laakso M, Tikkanen M, Ylikorkala O. Evidence of a state of increased insulin resistance in preeclampsia. Metabolism. 1999;48(7):8926.

CAS PubMed Article Google Scholar

Bramham K, Villa P, Joslin J, Laivuori H, Hmlinen E, Kajantie E, et al. Predisposition to superimposed preeclampsia in women with chronic hypertension: endothelial, renal, cardiac, and placental factors in a prospective longitudinal cohort. Hypertens Pregnancy. 2020;39(3):32635.

CAS PubMed Article Google Scholar

Leach R, Romero R, Kim Y, Chaiworapongsa T, Kilburn B, Das S, et al. Pre-eclampsia and expression of heparin-binding EGF-like growth factor. Lancet (London). 2002;360(9341):12159.

CAS Article Google Scholar

Ness R, Sibai B. Shared and disparate components of the pathophysiologies of fetal growth restriction and preeclampsia. Am J Obstet Gynecol. 2006;195(1):409.

PubMed Article Google Scholar

Mol BWJ, Roberts CT, Thangaratinam S, Magee LA, de Groot CJM, Hofmeyr GJ. Pre-eclampsia. Lancet. 2016;387(10022):9991011.

PubMed Article Google Scholar

Kolkova Z, Holubekova V, Grendar M, Nachajova M, Zubor P, Pribulova T, et al. Association of circulating miRNA expression with preeclampsia, its onset, and severity. Diagnostics (Basel). 2021;11(3):476.

CAS Article Google Scholar

Poon L, Shennan A, Hyett J, Kapur A, Hadar E, Divakar H, et al. The International Federation of Gynecology and Obstetrics (FIGO) initiative on pre-eclampsia: a pragmatic guide for first-trimester screening and prevention. Int J Gynaecol Obstet. 2019;145(S1):133.

PubMed PubMed Central Article Google Scholar

Karumanchi SA. Angiogenic factors in preeclampsia: from diagnosis to therapy. Hypertension. 2016;67(6):10729.

CAS PubMed Article Google Scholar

Dechend R, Luft FC. Angiogenesis factors and preeclampsia. Nat Med. 2008;14(11):11878.

CAS PubMed Article Google Scholar

Cim N, Kurdoglu M, Ege S, Yoruk I, Yaman G, Yildizhan R. An analysis on the roles of angiogenesis-related factors including serum vitamin D, soluble endoglin (sEng), soluble fms-like tyrosine kinase 1 (sFlt1), and vascular endothelial growth factor (VEGF) in the diagnosis and severity of late-onset preeclampsia. J Matern Fetal Neonatal Med. 2017;30(13):16027.

CAS PubMed Article Google Scholar

Sung KU, Roh JA, Eoh KJ, Kim EH. Maternal serum placental growth factor and pregnancy-associated plasma protein A measured in the first trimester as parameters of subsequent pre-eclampsia and small-for-gestational-age infants: a prospective observational study. Obstet Gynecol Sci. 2017;60(2):15462.

PubMed PubMed Central Article Google Scholar

Saleh L, Tahitu SIM, Danser AHJ, van den Meiracker AH, Visser W. The predictive value of the sFlt-1/PlGF ratio on short-term absence of preeclampsia and maternal and fetal or neonatal complications in twin pregnancies. Pregnancy Hypertens. 2018;14:2227.

PubMed Article Google Scholar

Lou WZ, Jiang F, Hu J, Chen XX, Song YN, Zhou XY, et al. Maternal serum angiogenic factor sFlt-1 to PlGF ratio in preeclampsia: a useful marker for differential diagnosis and prognosis evaluation in Chinese women. Dis Markers. 2019;2019:6270187.

PubMed PubMed Central Article CAS Google Scholar

Bartel D. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):21533.

CAS PubMed PubMed Central Article Google Scholar

Wang X, Qian T, Bao S, Zhao H, Chen H, Xing Z, et al. Circulating exosomal miR-363-5p inhibits lymph node metastasis by downregulating PDGFB and serves as a potential noninvasive biomarker for breast cancer. Mol Oncol. 2021;15(9):246679.

PubMed PubMed Central Article CAS Google Scholar

Bao S, Hu T, Liu J, Su J, Sun J, Ming Y, et al. Genomic instability-derived plasma extracellular vesicle-microRNA signature as a minimally invasive predictor of risk and unfavorable prognosis in breast cancer. J Nanobiotechnology. 2021;19(1):22.

CAS PubMed PubMed Central Article Google Scholar

Gebert LFR, MacRae IJ. Regulation of microRNA function in animals. Nat Rev Mol Cell Biol. 2019;20(1):2137.

CAS PubMed PubMed Central Article Google Scholar

Gantier MP, McCoy CE, Rusinova I, Saulep D, Wang D, Xu D, et al. Analysis of microRNA turnover in mammalian cells following Dicer1 ablation. Nucleic Acids Res. 2011;39(13):5692703.

CAS PubMed PubMed Central Article Google Scholar

Sayed AS, Xia K, Salma U, Yang T, Peng J. Diagnosis, prognosis and therapeutic role of circulating miRNAs in cardiovascular diseases. Heart Lung Circ. 2014;23(6):50310.

PubMed Article Google Scholar

Xu P, Zhao Y, Liu M, Wang Y, Wang H, Li Y, et al. Variations of microRNAs in human placentas and plasma from preeclamptic pregnancy. Hypertension (Dallas, Tex: 1979). 2014;63(6):127684.

CAS Article Google Scholar

Murphy M, Casselman R, Tayade C, Smith G. Differential expression of plasma microRNA in preeclamptic patients at delivery and 1 year postpartum. Am J Obstet Gynecol. 2015;213(3):367.e1-9.

CAS Article Google Scholar

Zheng W, Chen A, Yang H, Hong L. MicroRNA-27a inhibits trophoblast cell migration and invasion by targeting SMAD2: potential role in preeclampsia. Exp Ther Med. 2020;20(3):22629.

CAS PubMed PubMed Central Google Scholar

Cui J, Chen X, Lin S, Li L, Fan J, Hou H, et al. MiR-101-containing extracellular vesicles bind to BRD4 and enhance proliferation and migration of trophoblasts in preeclampsia. Stem Cell Res Ther. 2020;11(1):231.

CAS PubMed PubMed Central Article Google Scholar

Licini C, Avellini C, Picchiassi E, Mensa E, Fantone S, Ramini D, et al. Pre-eclampsia predictive ability of maternal miR-125b: a clinical and experimental study. Transl Res. 2021;228:1327.

CAS PubMed Article Google Scholar

Wang D, Na Q, Song GY, Wang L. Human umbilical cord mesenchymal stem cell-derived exosome-mediated transfer of microRNA-133b boosts trophoblast cell proliferation, migration and invasion in preeclampsia by restricting SGK1. Cell Cycle. 2020;19(15):186983.

CAS PubMed PubMed Central Article Google Scholar

Zhou W, She G, Yang K, Zhang B, Liu J, Yu B. MiR-384 inhibits proliferation and migration of trophoblast cells via targeting PTBP3. Pregnancy Hypertens. 2020;21:1328.

PubMed Article Google Scholar

Awamleh Z, Gloor GB, Han VKM. Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: potential impact on gene expression and pathophysiology. BMC Med Genomics. 2019;12(1):91 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE114349).

PubMed PubMed Central Article CAS Google Scholar

Brookes S, Martin E, Smeester L, Boggess K, Grace M, Fry R. GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84260. 2016.

Wyatt S, Kraus F, Roh C, Elchalal U, Nelson D, Sadovsky Y. The correlation between sampling site and gene expression in the term human placenta. Placenta. 2005;26(5):3729.

CAS PubMed Article Google Scholar

Huang HY, Lin YC, Li J, Huang KY, Shrestha S, Hong HC, et al. miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database. Nucleic Acids Res. 2020;48(D1):D14854.

CAS PubMed Google Scholar

Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.

PubMed PubMed Central Article CAS Google Scholar

Gestational Hypertension and Preeclampsia: ACOG Practice Bulletin. Obstet Gynecol.2020;135(6):e23760.

Magee LA, Nicolaides KH, von Dadelszen P. Preeclampsia. N Engl J Med. 2022;386(19):181732.

CAS PubMed Article Google Scholar

Phipps EA, Thadhani R, Benzing T, Karumanchi SA. Pre-eclampsia: pathogenesis, novel diagnostics and therapies. Nat Rev Nephrol. 2019;15(5):27589.

PubMed PubMed Central Article Google Scholar

Roberge S, Bujold E, Nicolaides KH. Aspirin for the prevention of preterm and term preeclampsia: systematic review and metaanalysis. Am J Obstet Gynecol. 2018;218(3):28793 (e1).

CAS PubMed Article Google Scholar

Fox R, Kitt J, Leeson P, Aye CYL, Lewandowski AJ. Preeclampsia: risk factors, diagnosis, management, and the cardiovascular impact on the offspring. J Clin Med. 2019;8(10):1625.

CAS PubMed Central Article Google Scholar

Rasmussen M, Reddy M, Nolan R, Camunas-Soler J, Khodursky A, Scheller NM, et al. RNA profiles reveal signatures of future health and disease in pregnancy. Nature. 2022;601(7893):4227.

CAS PubMed PubMed Central Article Google Scholar

Rudov A, Balduini W, Carloni S, Perrone S, Buonocore G, Albertini MC. Involvement of miRNAs in placental alterations mediated by oxidative stress. Oxid Med Cell Longev. 2014;2014:103068.

PubMed PubMed Central Article CAS Google Scholar

Mouillet JF, Ouyang Y, Coyne CB, Sadovsky Y. MicroRNAs in placental health and disease. Am J Obstet Gynecol. 2015;213(4 Suppl):S16372.

CAS PubMed PubMed Central Article Google Scholar

Gong S, Gaccioli F, Dopierala J, Sovio U, Cook E, Volders PJ, et al. The RNA landscape of the human placenta in health and disease. Nat Commun. 2021;12(1):2639.

CAS PubMed PubMed Central Article Google Scholar

Fu G, Brkic J, Hayder H, Peng C. MicroRNAs in human placental development and pregnancy complications. Int J Mol Sci. 2013;14(3):551944.

CAS PubMed PubMed Central Article Google Scholar

Luo SS, Ishibashi O, Ishikawa G, Ishikawa T, Katayama A, Mishima T, et al. Human villous trophoblasts express and secrete placenta-specific microRNAs into maternal circulation via exosomes. Biol Reprod. 2009;81(4):71729.

CAS PubMed Article Google Scholar

Makarova JA, Shkurnikov MU, Wicklein D, Lange T, Samatov TR, Turchinovich AA, et al. Intracellular and extracellular microRNA: an update on localization and biological role. Prog Histochem Cytochem. 2016;51(34):3349.

PubMed Article Google Scholar

Hromadnikova I, Dvorakova L, Kotlabova K, Krofta L. The prediction of gestational hypertension, preeclampsia and fetal growth restriction via the first trimester screening of plasma exosomal C19MC microRNAs. Int J Mol Sci. 2019;20(12):2972.

CAS PubMed Central Article Google Scholar

Luizon MR, Conceicao I, Viana-Mattioli S, Caldeira-Dias M, Cavalli RC, Sandrim VC. Circulating microRNAs in the second trimester from pregnant women who subsequently developed preeclampsia: potential candidates as predictive biomarkers and pathway analysis for target genes of miR-204-5p. Front Physiol. 2021;12:678184.

PubMed PubMed Central Article Google Scholar

Niu ZR, Han T, Sun XL, Luan LX, Gou WL, Zhu XM. MicroRNA-30a-3p is overexpressed in the placentas of patients with preeclampsia and affects trophoblast invasion and apoptosis by its effects on IGF-1. Am J Obstet Gynecol. 2018;218(2):249 e1-e12.

Article CAS Google Scholar

Hromadnikova I, Kotlabova K, Ivankova K, Krofta L. First trimester screening of circulating C19MC microRNAs and the evaluation of their potential to predict the onset of preeclampsia and IUGR. PLoS ONE. 2017;12(2):e0171756.

PubMed PubMed Central Article CAS Google Scholar

Mi C, Ye B, Gao Z, Du J, Li R, Huang D. BHLHE40 plays a pathological role in pre-eclampsia through upregulating SNX16 by transcriptional inhibition of miR-196a-5p. Mol Hum Reprod. 2020;26(7):53248.

CAS PubMed Article Google Scholar

Enquobahrie DA, Abetew DF, Sorensen TK, Willoughby D, Chidambaram K, Williams MA. Placental microRNA expression in pregnancies complicated by preeclampsia. Am J Obstet Gynecol. 2011;204(2):178 e12-21.

Article CAS Google Scholar

Bao S, Zhou T, Yan C, Bao J, Yang F, Chao S, et al. GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE206988. 2022.

Read the original here:
A blood-based miRNA signature for early non-invasive diagnosis of preeclampsia - BMC Medicine - BMC Medicine